From e8c9493dcd414805c54b15ef32056e33b7bd4e80 Mon Sep 17 00:00:00 2001
From: Neehar Duvvuri <40341266+needuv@users.noreply.github.com>
Date: Thu, 16 Mar 2023 11:28:50 -0400
Subject: [PATCH] update april preview client with latest swagger from master
---
.../_azure_machine_learning_workspaces.py | 10 +-
.../v2023_04_01_preview/_metadata.json | 144 -
.../aio/_azure_machine_learning_workspaces.py | 10 +-
.../aio/operations/__init__.py | 4 -
.../operations/_code_versions_operations.py | 89 +-
.../_component_versions_operations.py | 5 +
.../operations/_data_versions_operations.py | 5 +
.../_featureset_containers_operations.py | 22 +-
.../_featureset_versions_operations.py | 60 +-
...aturestore_entity_containers_operations.py | 22 +-
...featurestore_entity_versions_operations.py | 32 +-
.../aio/operations/_jobs_operations.py | 74 +-
.../operations/_model_versions_operations.py | 5 +
.../_online_endpoints_operations.py | 4 +-
.../_registry_code_versions_operations.py | 78 +-
..._registry_component_versions_operations.py | 5 +
.../_registry_data_containers_operations.py | 468 -
.../_registry_data_versions_operations.py | 508 -
.../_registry_model_versions_operations.py | 78 +-
.../v2023_04_01_preview/models/__init__.py | 229 +-
...azure_machine_learning_workspaces_enums.py | 235 +-
.../v2023_04_01_preview/models/_models.py | 3868 +-
.../v2023_04_01_preview/models/_models_py3.py | 4232 +-
.../operations/__init__.py | 4 -
.../operations/_code_versions_operations.py | 138 +
.../_component_versions_operations.py | 8 +
.../operations/_data_versions_operations.py | 8 +
.../_featureset_containers_operations.py | 34 +-
.../_featureset_versions_operations.py | 85 +-
...aturestore_entity_containers_operations.py | 34 +-
...featurestore_entity_versions_operations.py | 50 +-
.../operations/_jobs_operations.py | 115 +
.../operations/_model_versions_operations.py | 8 +
.../_online_endpoints_operations.py | 4 +-
.../_registry_code_versions_operations.py | 121 +
..._registry_component_versions_operations.py | 8 +
.../_registry_data_containers_operations.py | 644 -
.../_registry_data_versions_operations.py | 702 -
.../_registry_model_versions_operations.py | 121 +
.../preview/2023-04-01-preview/mfe.json | 43709 ++++++++--------
40 files changed, 31765 insertions(+), 24215 deletions(-)
delete mode 100644 sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_metadata.json
delete mode 100644 sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_containers_operations.py
delete mode 100644 sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_versions_operations.py
delete mode 100644 sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_containers_operations.py
delete mode 100644 sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_versions_operations.py
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_azure_machine_learning_workspaces.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_azure_machine_learning_workspaces.py
index a4b522758c10..9dcb6cd69738 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_azure_machine_learning_workspaces.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_azure_machine_learning_workspaces.py
@@ -15,7 +15,7 @@
from . import models
from ._configuration import AzureMachineLearningWorkspacesConfiguration
-from .operations import BatchDeploymentsOperations, BatchEndpointsOperations, CodeContainersOperations, CodeVersionsOperations, ComponentContainersOperations, ComponentVersionsOperations, ComputeOperations, DataContainersOperations, DataVersionsOperations, DatastoresOperations, EnvironmentContainersOperations, EnvironmentVersionsOperations, FeaturesetContainersOperations, FeaturesetVersionsOperations, FeaturestoreEntityContainersOperations, FeaturestoreEntityVersionsOperations, JobsOperations, LabelingJobsOperations, ModelContainersOperations, ModelVersionsOperations, OnlineDeploymentsOperations, OnlineEndpointsOperations, Operations, PrivateEndpointConnectionsOperations, PrivateLinkResourcesOperations, QuotasOperations, RegistriesOperations, RegistryCodeContainersOperations, RegistryCodeVersionsOperations, RegistryComponentContainersOperations, RegistryComponentVersionsOperations, RegistryDataContainersOperations, RegistryDataVersionsOperations, RegistryEnvironmentContainersOperations, RegistryEnvironmentVersionsOperations, RegistryModelContainersOperations, RegistryModelVersionsOperations, SchedulesOperations, UsagesOperations, VirtualMachineSizesOperations, WorkspaceConnectionsOperations, WorkspaceFeaturesOperations, WorkspacesOperations
+from .operations import BatchDeploymentsOperations, BatchEndpointsOperations, CodeContainersOperations, CodeVersionsOperations, ComponentContainersOperations, ComponentVersionsOperations, ComputeOperations, DataContainersOperations, DataVersionsOperations, DatastoresOperations, EnvironmentContainersOperations, EnvironmentVersionsOperations, FeaturesetContainersOperations, FeaturesetVersionsOperations, FeaturestoreEntityContainersOperations, FeaturestoreEntityVersionsOperations, JobsOperations, LabelingJobsOperations, ModelContainersOperations, ModelVersionsOperations, OnlineDeploymentsOperations, OnlineEndpointsOperations, Operations, PrivateEndpointConnectionsOperations, PrivateLinkResourcesOperations, QuotasOperations, RegistriesOperations, RegistryCodeContainersOperations, RegistryCodeVersionsOperations, RegistryComponentContainersOperations, RegistryComponentVersionsOperations, RegistryEnvironmentContainersOperations, RegistryEnvironmentVersionsOperations, RegistryModelContainersOperations, RegistryModelVersionsOperations, SchedulesOperations, UsagesOperations, VirtualMachineSizesOperations, WorkspaceConnectionsOperations, WorkspaceFeaturesOperations, WorkspacesOperations
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
@@ -66,12 +66,6 @@ class AzureMachineLearningWorkspaces(object): # pylint: disable=too-many-inst
:ivar registry_component_versions: RegistryComponentVersionsOperations operations
:vartype registry_component_versions:
azure.mgmt.machinelearningservices.operations.RegistryComponentVersionsOperations
- :ivar registry_data_containers: RegistryDataContainersOperations operations
- :vartype registry_data_containers:
- azure.mgmt.machinelearningservices.operations.RegistryDataContainersOperations
- :ivar registry_data_versions: RegistryDataVersionsOperations operations
- :vartype registry_data_versions:
- azure.mgmt.machinelearningservices.operations.RegistryDataVersionsOperations
:ivar registry_environment_containers: RegistryEnvironmentContainersOperations operations
:vartype registry_environment_containers:
azure.mgmt.machinelearningservices.operations.RegistryEnvironmentContainersOperations
@@ -186,8 +180,6 @@ def __init__(
self.registry_code_versions = RegistryCodeVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_component_containers = RegistryComponentContainersOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_component_versions = RegistryComponentVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
- self.registry_data_containers = RegistryDataContainersOperations(self._client, self._config, self._serialize, self._deserialize)
- self.registry_data_versions = RegistryDataVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_environment_containers = RegistryEnvironmentContainersOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_environment_versions = RegistryEnvironmentVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_model_containers = RegistryModelContainersOperations(self._client, self._config, self._serialize, self._deserialize)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_metadata.json b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_metadata.json
deleted file mode 100644
index e68db97fabd0..000000000000
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/_metadata.json
+++ /dev/null
@@ -1,144 +0,0 @@
-{
- "chosen_version": "2023-04-01-preview",
- "total_api_version_list": ["2023-04-01-preview"],
- "client": {
- "name": "AzureMachineLearningWorkspaces",
- "filename": "_azure_machine_learning_workspaces",
- "description": "These APIs allow end users to operate on Azure Machine Learning Workspace resources.",
- "host_value": "\"https://management.azure.com\"",
- "parameterized_host_template": null,
- "azure_arm": true,
- "has_lro_operations": true,
- "client_side_validation": false,
- "sync_imports": "{\"typing\": {\"azurecore\": {\"azure.core.credentials\": [\"TokenCredential\"]}}, \"regular\": {\"azurecore\": {\"azure.profiles\": [\"KnownProfiles\", \"ProfileDefinition\"], \"azure.profiles.multiapiclient\": [\"MultiApiClientMixin\"], \"azure.mgmt.core\": [\"ARMPipelineClient\"]}, \"local\": {\"._configuration\": [\"AzureMachineLearningWorkspacesConfiguration\"]}, \"thirdparty\": {\"msrest\": [\"Deserializer\", \"Serializer\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Optional\"]}}}",
- "async_imports": "{\"typing\": {\"azurecore\": {\"azure.core.credentials_async\": [\"AsyncTokenCredential\"], \"azure.core.credentials\": [\"TokenCredential\"]}}, \"regular\": {\"azurecore\": {\"azure.profiles\": [\"KnownProfiles\", \"ProfileDefinition\"], \"azure.profiles.multiapiclient\": [\"MultiApiClientMixin\"], \"azure.mgmt.core\": [\"AsyncARMPipelineClient\"]}, \"local\": {\"._configuration\": [\"AzureMachineLearningWorkspacesConfiguration\"]}, \"thirdparty\": {\"msrest\": [\"Deserializer\", \"Serializer\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Optional\"]}}}"
- },
- "global_parameters": {
- "sync": {
- "credential": {
- "signature": "credential, # type: \"TokenCredential\"",
- "description": "Credential needed for the client to connect to Azure.",
- "docstring_type": "~azure.core.credentials.TokenCredential",
- "required": true
- },
- "subscription_id": {
- "signature": "subscription_id, # type: str",
- "description": "The ID of the target subscription.",
- "docstring_type": "str",
- "required": true
- }
- },
- "async": {
- "credential": {
- "signature": "credential: \"AsyncTokenCredential\",",
- "description": "Credential needed for the client to connect to Azure.",
- "docstring_type": "~azure.core.credentials_async.AsyncTokenCredential",
- "required": true
- },
- "subscription_id": {
- "signature": "subscription_id: str,",
- "description": "The ID of the target subscription.",
- "docstring_type": "str",
- "required": true
- }
- },
- "constant": {
- },
- "call": "credential, subscription_id",
- "service_client_specific": {
- "sync": {
- "api_version": {
- "signature": "api_version=None, # type: Optional[str]",
- "description": "API version to use if no profile is provided, or if missing in profile.",
- "docstring_type": "str",
- "required": false
- },
- "base_url": {
- "signature": "base_url=\"https://management.azure.com\", # type: str",
- "description": "Service URL",
- "docstring_type": "str",
- "required": false
- },
- "profile": {
- "signature": "profile=KnownProfiles.default, # type: KnownProfiles",
- "description": "A profile definition, from KnownProfiles to dict.",
- "docstring_type": "azure.profiles.KnownProfiles",
- "required": false
- }
- },
- "async": {
- "api_version": {
- "signature": "api_version: Optional[str] = None,",
- "description": "API version to use if no profile is provided, or if missing in profile.",
- "docstring_type": "str",
- "required": false
- },
- "base_url": {
- "signature": "base_url: str = \"https://management.azure.com\",",
- "description": "Service URL",
- "docstring_type": "str",
- "required": false
- },
- "profile": {
- "signature": "profile: KnownProfiles = KnownProfiles.default,",
- "description": "A profile definition, from KnownProfiles to dict.",
- "docstring_type": "azure.profiles.KnownProfiles",
- "required": false
- }
- }
- }
- },
- "config": {
- "credential": true,
- "credential_scopes": ["https://management.azure.com/.default"],
- "credential_call_sync": "ARMChallengeAuthenticationPolicy(self.credential, *self.credential_scopes, **kwargs)",
- "credential_call_async": "AsyncARMChallengeAuthenticationPolicy(self.credential, *self.credential_scopes, **kwargs)",
- "sync_imports": "{\"regular\": {\"azurecore\": {\"azure.core.configuration\": [\"Configuration\"], \"azure.core.pipeline\": [\"policies\"], \"azure.mgmt.core.policies\": [\"ARMChallengeAuthenticationPolicy\", \"ARMHttpLoggingPolicy\"]}, \"local\": {\"._version\": [\"VERSION\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\"]}}, \"typing\": {\"azurecore\": {\"azure.core.credentials\": [\"TokenCredential\"]}}}",
- "async_imports": "{\"regular\": {\"azurecore\": {\"azure.core.configuration\": [\"Configuration\"], \"azure.core.pipeline\": [\"policies\"], \"azure.mgmt.core.policies\": [\"ARMHttpLoggingPolicy\", \"AsyncARMChallengeAuthenticationPolicy\"]}, \"local\": {\".._version\": [\"VERSION\"]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\"]}}, \"typing\": {\"azurecore\": {\"azure.core.credentials_async\": [\"AsyncTokenCredential\"]}}}"
- },
- "operation_groups": {
- "operations": "Operations",
- "workspaces": "WorkspacesOperations",
- "usages": "UsagesOperations",
- "virtual_machine_sizes": "VirtualMachineSizesOperations",
- "quotas": "QuotasOperations",
- "compute": "ComputeOperations",
- "private_endpoint_connections": "PrivateEndpointConnectionsOperations",
- "private_link_resources": "PrivateLinkResourcesOperations",
- "workspace_connections": "WorkspaceConnectionsOperations",
- "registries": "RegistriesOperations",
- "workspace_features": "WorkspaceFeaturesOperations",
- "registry_code_containers": "RegistryCodeContainersOperations",
- "registry_code_versions": "RegistryCodeVersionsOperations",
- "registry_component_containers": "RegistryComponentContainersOperations",
- "registry_component_versions": "RegistryComponentVersionsOperations",
- "registry_data_containers": "RegistryDataContainersOperations",
- "registry_data_versions": "RegistryDataVersionsOperations",
- "registry_environment_containers": "RegistryEnvironmentContainersOperations",
- "registry_environment_versions": "RegistryEnvironmentVersionsOperations",
- "registry_model_containers": "RegistryModelContainersOperations",
- "registry_model_versions": "RegistryModelVersionsOperations",
- "batch_endpoints": "BatchEndpointsOperations",
- "batch_deployments": "BatchDeploymentsOperations",
- "code_containers": "CodeContainersOperations",
- "code_versions": "CodeVersionsOperations",
- "component_containers": "ComponentContainersOperations",
- "component_versions": "ComponentVersionsOperations",
- "data_containers": "DataContainersOperations",
- "data_versions": "DataVersionsOperations",
- "datastores": "DatastoresOperations",
- "environment_containers": "EnvironmentContainersOperations",
- "environment_versions": "EnvironmentVersionsOperations",
- "featureset_containers": "FeaturesetContainersOperations",
- "featureset_versions": "FeaturesetVersionsOperations",
- "featurestore_entity_containers": "FeaturestoreEntityContainersOperations",
- "featurestore_entity_versions": "FeaturestoreEntityVersionsOperations",
- "jobs": "JobsOperations",
- "labeling_jobs": "LabelingJobsOperations",
- "model_containers": "ModelContainersOperations",
- "model_versions": "ModelVersionsOperations",
- "online_endpoints": "OnlineEndpointsOperations",
- "online_deployments": "OnlineDeploymentsOperations",
- "schedules": "SchedulesOperations"
- }
-}
\ No newline at end of file
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/_azure_machine_learning_workspaces.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/_azure_machine_learning_workspaces.py
index 94f280ae99a1..600ad6da25c9 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/_azure_machine_learning_workspaces.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/_azure_machine_learning_workspaces.py
@@ -16,7 +16,7 @@
from .. import models
from ._configuration import AzureMachineLearningWorkspacesConfiguration
-from .operations import BatchDeploymentsOperations, BatchEndpointsOperations, CodeContainersOperations, CodeVersionsOperations, ComponentContainersOperations, ComponentVersionsOperations, ComputeOperations, DataContainersOperations, DataVersionsOperations, DatastoresOperations, EnvironmentContainersOperations, EnvironmentVersionsOperations, FeaturesetContainersOperations, FeaturesetVersionsOperations, FeaturestoreEntityContainersOperations, FeaturestoreEntityVersionsOperations, JobsOperations, LabelingJobsOperations, ModelContainersOperations, ModelVersionsOperations, OnlineDeploymentsOperations, OnlineEndpointsOperations, Operations, PrivateEndpointConnectionsOperations, PrivateLinkResourcesOperations, QuotasOperations, RegistriesOperations, RegistryCodeContainersOperations, RegistryCodeVersionsOperations, RegistryComponentContainersOperations, RegistryComponentVersionsOperations, RegistryDataContainersOperations, RegistryDataVersionsOperations, RegistryEnvironmentContainersOperations, RegistryEnvironmentVersionsOperations, RegistryModelContainersOperations, RegistryModelVersionsOperations, SchedulesOperations, UsagesOperations, VirtualMachineSizesOperations, WorkspaceConnectionsOperations, WorkspaceFeaturesOperations, WorkspacesOperations
+from .operations import BatchDeploymentsOperations, BatchEndpointsOperations, CodeContainersOperations, CodeVersionsOperations, ComponentContainersOperations, ComponentVersionsOperations, ComputeOperations, DataContainersOperations, DataVersionsOperations, DatastoresOperations, EnvironmentContainersOperations, EnvironmentVersionsOperations, FeaturesetContainersOperations, FeaturesetVersionsOperations, FeaturestoreEntityContainersOperations, FeaturestoreEntityVersionsOperations, JobsOperations, LabelingJobsOperations, ModelContainersOperations, ModelVersionsOperations, OnlineDeploymentsOperations, OnlineEndpointsOperations, Operations, PrivateEndpointConnectionsOperations, PrivateLinkResourcesOperations, QuotasOperations, RegistriesOperations, RegistryCodeContainersOperations, RegistryCodeVersionsOperations, RegistryComponentContainersOperations, RegistryComponentVersionsOperations, RegistryEnvironmentContainersOperations, RegistryEnvironmentVersionsOperations, RegistryModelContainersOperations, RegistryModelVersionsOperations, SchedulesOperations, UsagesOperations, VirtualMachineSizesOperations, WorkspaceConnectionsOperations, WorkspaceFeaturesOperations, WorkspacesOperations
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
@@ -64,12 +64,6 @@ class AzureMachineLearningWorkspaces: # pylint: disable=too-many-instance-att
:ivar registry_component_versions: RegistryComponentVersionsOperations operations
:vartype registry_component_versions:
azure.mgmt.machinelearningservices.aio.operations.RegistryComponentVersionsOperations
- :ivar registry_data_containers: RegistryDataContainersOperations operations
- :vartype registry_data_containers:
- azure.mgmt.machinelearningservices.aio.operations.RegistryDataContainersOperations
- :ivar registry_data_versions: RegistryDataVersionsOperations operations
- :vartype registry_data_versions:
- azure.mgmt.machinelearningservices.aio.operations.RegistryDataVersionsOperations
:ivar registry_environment_containers: RegistryEnvironmentContainersOperations operations
:vartype registry_environment_containers:
azure.mgmt.machinelearningservices.aio.operations.RegistryEnvironmentContainersOperations
@@ -187,8 +181,6 @@ def __init__(
self.registry_code_versions = RegistryCodeVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_component_containers = RegistryComponentContainersOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_component_versions = RegistryComponentVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
- self.registry_data_containers = RegistryDataContainersOperations(self._client, self._config, self._serialize, self._deserialize)
- self.registry_data_versions = RegistryDataVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_environment_containers = RegistryEnvironmentContainersOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_environment_versions = RegistryEnvironmentVersionsOperations(self._client, self._config, self._serialize, self._deserialize)
self.registry_model_containers = RegistryModelContainersOperations(self._client, self._config, self._serialize, self._deserialize)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/__init__.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/__init__.py
index 0eb66403ac68..0b1b8b50da59 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/__init__.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/__init__.py
@@ -21,8 +21,6 @@
from ._registry_code_versions_operations import RegistryCodeVersionsOperations
from ._registry_component_containers_operations import RegistryComponentContainersOperations
from ._registry_component_versions_operations import RegistryComponentVersionsOperations
-from ._registry_data_containers_operations import RegistryDataContainersOperations
-from ._registry_data_versions_operations import RegistryDataVersionsOperations
from ._registry_environment_containers_operations import RegistryEnvironmentContainersOperations
from ._registry_environment_versions_operations import RegistryEnvironmentVersionsOperations
from ._registry_model_containers_operations import RegistryModelContainersOperations
@@ -66,8 +64,6 @@
'RegistryCodeVersionsOperations',
'RegistryComponentContainersOperations',
'RegistryComponentVersionsOperations',
- 'RegistryDataContainersOperations',
- 'RegistryDataVersionsOperations',
'RegistryEnvironmentContainersOperations',
'RegistryEnvironmentVersionsOperations',
'RegistryModelContainersOperations',
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_code_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_code_versions_operations.py
index e38288b386ed..6b74c9325e77 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_code_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_code_versions_operations.py
@@ -19,7 +19,7 @@
from ... import models as _models
from ..._vendor import _convert_request
-from ...operations._code_versions_operations import build_create_or_update_request, build_delete_request, build_get_request, build_list_request
+from ...operations._code_versions_operations import build_create_or_get_pending_upload_request, build_create_or_update_request, build_delete_request, build_get_request, build_list_request
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -54,6 +54,8 @@ def list(
order_by: Optional[str] = None,
top: Optional[int] = None,
skip: Optional[str] = None,
+ hash: Optional[str] = None,
+ hash_version: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.CodeVersionResourceArmPaginatedResult"]:
"""List versions.
@@ -72,6 +74,11 @@ def list(
:type top: int
:param skip: Continuation token for pagination.
:type skip: str
+ :param hash: If specified, return CodeVersion assets with specified content hash value,
+ regardless of name.
+ :type hash: str
+ :param hash_version: Hash algorithm version when listing by hash.
+ :type hash_version: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CodeVersionResourceArmPaginatedResult or the
result of cls(response)
@@ -98,6 +105,8 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ hash=hash,
+ hash_version=hash_version,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -114,6 +123,8 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ hash=hash,
+ hash_version=hash_version,
template_url=next_link,
)
request = _convert_request(request)
@@ -364,3 +375,79 @@ async def create_or_update(
create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}"} # type: ignore
+
+ @distributed_trace_async
+ async def create_or_get_pending_upload(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ name: str,
+ version: str,
+ body: "_models.PendingUploadRequestDto",
+ **kwargs: Any
+ ) -> "_models.PendingUploadResponseDto":
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive.
+ :type version: str
+ :param body: Pending upload request object.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.PendingUploadResponseDto"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PendingUploadRequestDto')
+
+ request = build_create_or_get_pending_upload_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ workspace_name=workspace_name,
+ name=name,
+ version=version,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.create_or_get_pending_upload.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('PendingUploadResponseDto', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_pending_upload.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/pendingUpload/{version}"} # type: ignore
+
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_component_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_component_versions_operations.py
index 9da0ba08f70a..b1e49bfdca00 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_component_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_component_versions_operations.py
@@ -54,6 +54,7 @@ def list(
order_by: Optional[str] = None,
top: Optional[int] = None,
skip: Optional[str] = None,
+ stage: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
**kwargs: Any
) -> AsyncIterable["_models.ComponentVersionResourceArmPaginatedResult"]:
@@ -73,6 +74,8 @@ def list(
:type top: int
:param skip: Continuation token for pagination.
:type skip: str
+ :param stage: Component stage.
+ :type stage: str
:param list_view_type: View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
:keyword callable cls: A custom type or function that will be passed the direct response
@@ -101,6 +104,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
list_view_type=list_view_type,
template_url=self.list.metadata['url'],
)
@@ -118,6 +122,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
list_view_type=list_view_type,
template_url=next_link,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_data_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_data_versions_operations.py
index d0c94106486b..f8f3819f2163 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_data_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_data_versions_operations.py
@@ -55,6 +55,7 @@ def list(
top: Optional[int] = None,
skip: Optional[str] = None,
tags: Optional[str] = None,
+ stage: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
**kwargs: Any
) -> AsyncIterable["_models.DataVersionBaseResourceArmPaginatedResult"]:
@@ -79,6 +80,8 @@ def list(
:param tags: Comma-separated list of tag names (and optionally values). Example:
tag1,tag2=value2.
:type tags: str
+ :param stage: data stage.
+ :type stage: str
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
@@ -109,6 +112,7 @@ def prepare_request(next_link=None):
top=top,
skip=skip,
tags=tags,
+ stage=stage,
list_view_type=list_view_type,
template_url=self.list.metadata['url'],
)
@@ -127,6 +131,7 @@ def prepare_request(next_link=None):
top=top,
skip=skip,
tags=tags,
+ stage=stage,
list_view_type=list_view_type,
template_url=next_link,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_containers_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_containers_operations.py
index cde6e4074afb..7e0e06becbc2 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_containers_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_containers_operations.py
@@ -55,6 +55,10 @@ def list(
skip: Optional[str] = None,
tags: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
+ page_size: Optional[int] = 20,
+ name: Optional[str] = None,
+ description: Optional[str] = None,
+ created_by: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.FeaturesetContainerResourceArmPaginatedResult"]:
"""List featurestore entity containers.
@@ -73,6 +77,14 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param name: name for the featureset.
+ :type name: str
+ :param description: description for the feature set.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FeaturesetContainerResourceArmPaginatedResult or
the result of cls(response)
@@ -98,6 +110,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -113,6 +129,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=next_link,
)
request = _convert_request(request)
@@ -460,7 +480,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = AsyncNoPolling()
else: polling_method = polling
if cont_token:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_versions_operations.py
index 769657b84968..818a113068a0 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featureset_versions_operations.py
@@ -56,6 +56,12 @@ def list(
skip: Optional[str] = None,
tags: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
+ page_size: Optional[int] = 20,
+ version_name: Optional[str] = None,
+ version: Optional[str] = None,
+ description: Optional[str] = None,
+ created_by: Optional[str] = None,
+ stage: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.FeaturesetVersionResourceArmPaginatedResult"]:
"""List versions.
@@ -76,6 +82,18 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param version_name: name for the featureset version.
+ :type version_name: str
+ :param version: featureset version.
+ :type version: str
+ :param description: description for the feature set version.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
+ :param stage: stage.
+ :type stage: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FeaturesetVersionResourceArmPaginatedResult or the
result of cls(response)
@@ -102,6 +120,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -118,6 +142,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=next_link,
)
request = _convert_request(request)
@@ -481,7 +511,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = AsyncNoPolling()
else: polling_method = polling
if cont_token:
@@ -503,8 +533,8 @@ async def _backfill_initial(
version: str,
body: "_models.FeaturesetVersionBackfillRequest",
**kwargs: Any
- ) -> Optional["_models.FeaturesetVersionBackfillResponse"]:
- cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.FeaturesetVersionBackfillResponse"]]
+ ) -> Optional["_models.FeaturesetJob"]:
+ cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.FeaturesetJob"]]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
@@ -543,7 +573,7 @@ async def _backfill_initial(
deserialized = None
response_headers = {}
if response.status_code == 200:
- deserialized = self._deserialize('FeaturesetVersionBackfillResponse', pipeline_response)
+ deserialized = self._deserialize('FeaturesetJob', pipeline_response)
if response.status_code == 202:
response_headers['Location']=self._deserialize('str', response.headers.get('Location'))
@@ -567,7 +597,7 @@ async def begin_backfill(
version: str,
body: "_models.FeaturesetVersionBackfillRequest",
**kwargs: Any
- ) -> AsyncLROPoller["_models.FeaturesetVersionBackfillResponse"]:
+ ) -> AsyncLROPoller["_models.FeaturesetJob"]:
"""Backfill.
Backfill.
@@ -590,16 +620,16 @@ async def begin_backfill(
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
- :return: An instance of AsyncLROPoller that returns either FeaturesetVersionBackfillResponse or
- the result of cls(response)
+ :return: An instance of AsyncLROPoller that returns either FeaturesetJob or the result of
+ cls(response)
:rtype:
- ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.FeaturesetVersionBackfillResponse]
+ ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.FeaturesetJob]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType["_models.FeaturesetVersionBackfillResponse"]
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.FeaturesetJob"]
lro_delay = kwargs.pop(
'polling_interval',
self._config.polling_interval
@@ -621,7 +651,7 @@ async def begin_backfill(
def get_long_running_output(pipeline_response):
response = pipeline_response.http_response
- deserialized = self._deserialize('FeaturesetVersionBackfillResponse', pipeline_response)
+ deserialized = self._deserialize('FeaturesetJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@@ -726,6 +756,8 @@ def list_features(
version: str,
skip: Optional[str] = None,
tags: Optional[str] = None,
+ feature_name: Optional[str] = None,
+ description: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.FeatureArmPaginatedResult"]:
"""List Features.
@@ -745,6 +777,10 @@ def list_features(
:param tags: Comma-separated list of tag names (and optionally values). Example:
tag1,tag2=value2.
:type tags: str
+ :param feature_name: feature name.
+ :type feature_name: str
+ :param description: description.
+ :type description: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FeatureArmPaginatedResult or the result of
cls(response)
@@ -771,6 +807,8 @@ def prepare_request(next_link=None):
api_version=api_version,
skip=skip,
tags=tags,
+ feature_name=feature_name,
+ description=description,
template_url=self.list_features.metadata['url'],
)
request = _convert_request(request)
@@ -787,6 +825,8 @@ def prepare_request(next_link=None):
api_version=api_version,
skip=skip,
tags=tags,
+ feature_name=feature_name,
+ description=description,
template_url=next_link,
)
request = _convert_request(request)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_containers_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_containers_operations.py
index 9a7496c9f0b5..488e7d21fc4e 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_containers_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_containers_operations.py
@@ -55,6 +55,10 @@ def list(
skip: Optional[str] = None,
tags: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
+ page_size: Optional[int] = 20,
+ name: Optional[str] = None,
+ description: Optional[str] = None,
+ created_by: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.FeaturestoreEntityContainerResourceArmPaginatedResult"]:
"""List featurestore entity containers.
@@ -73,6 +77,14 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param name: name for the featurestore entity.
+ :type name: str
+ :param description: description for the featurestore entity.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either
FeaturestoreEntityContainerResourceArmPaginatedResult or the result of cls(response)
@@ -98,6 +110,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -113,6 +129,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=next_link,
)
request = _convert_request(request)
@@ -460,7 +480,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = AsyncNoPolling()
else: polling_method = polling
if cont_token:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_versions_operations.py
index fa747dc85c8b..3e9fd8a6a184 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_featurestore_entity_versions_operations.py
@@ -56,6 +56,12 @@ def list(
skip: Optional[str] = None,
tags: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
+ page_size: Optional[int] = 20,
+ version_name: Optional[str] = None,
+ version: Optional[str] = None,
+ description: Optional[str] = None,
+ created_by: Optional[str] = None,
+ stage: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.FeaturestoreEntityVersionResourceArmPaginatedResult"]:
"""List versions.
@@ -76,6 +82,18 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param version_name: name for the featurestore entity version.
+ :type version_name: str
+ :param version: featurestore entity version.
+ :type version: str
+ :param description: description for the feature entity version.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
+ :param stage: stage.
+ :type stage: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either
FeaturestoreEntityVersionResourceArmPaginatedResult or the result of cls(response)
@@ -102,6 +120,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -118,6 +142,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=next_link,
)
request = _convert_request(request)
@@ -481,7 +511,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = AsyncNoPolling()
else: polling_method = polling
if cont_token:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_jobs_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_jobs_operations.py
index 5ada11773b44..0d202f357c9e 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_jobs_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_jobs_operations.py
@@ -21,7 +21,7 @@
from ... import models as _models
from ..._vendor import _convert_request
-from ...operations._jobs_operations import build_cancel_request_initial, build_create_or_update_request, build_delete_request_initial, build_get_request, build_list_request
+from ...operations._jobs_operations import build_cancel_request_initial, build_create_or_update_request, build_delete_request_initial, build_get_request, build_list_request, build_update_request
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -352,6 +352,78 @@ async def get(
get.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}"} # type: ignore
+ @distributed_trace_async
+ async def update(
+ self,
+ resource_group_name: str,
+ workspace_name: str,
+ id: str,
+ body: "_models.PartialJobBasePartialResource",
+ **kwargs: Any
+ ) -> "_models.JobBase":
+ """Updates a Job.
+
+ Updates a Job.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace.
+ :type workspace_name: str
+ :param id: The name and identifier for the Job. This is case-sensitive.
+ :type id: str
+ :param body: Job definition to apply during the operation.
+ :type body: ~azure.mgmt.machinelearningservices.models.PartialJobBasePartialResource
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: JobBase, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.JobBase
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.JobBase"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PartialJobBasePartialResource')
+
+ request = build_update_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ workspace_name=workspace_name,
+ id=id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.update.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('JobBase', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}"} # type: ignore
+
+
@distributed_trace_async
async def create_or_update(
self,
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_model_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_model_versions_operations.py
index 483f4cbf7507..f877bd06931c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_model_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_model_versions_operations.py
@@ -62,6 +62,7 @@ def list(
tags: Optional[str] = None,
properties: Optional[str] = None,
feed: Optional[str] = None,
+ stage: Optional[str] = None,
list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
**kwargs: Any
) -> AsyncIterable["_models.ModelVersionResourceArmPaginatedResult"]:
@@ -95,6 +96,8 @@ def list(
:type properties: str
:param feed: Name of the feed.
:type feed: str
+ :param stage: Model stage.
+ :type stage: str
:param list_view_type: View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
:keyword callable cls: A custom type or function that will be passed the direct response
@@ -129,6 +132,7 @@ def prepare_request(next_link=None):
tags=tags,
properties=properties,
feed=feed,
+ stage=stage,
list_view_type=list_view_type,
template_url=self.list.metadata['url'],
)
@@ -152,6 +156,7 @@ def prepare_request(next_link=None):
tags=tags,
properties=properties,
feed=feed,
+ stage=stage,
list_view_type=list_view_type,
template_url=next_link,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_online_endpoints_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_online_endpoints_operations.py
index e0e465d53a95..7ccf92cb9791 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_online_endpoints_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_online_endpoints_operations.py
@@ -839,9 +839,9 @@ async def get_token(
endpoint_name: str,
**kwargs: Any
) -> "_models.EndpointAuthToken":
- """Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ """Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
- Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_code_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_code_versions_operations.py
index 296870248a4b..fe64aed04ff8 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_code_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_code_versions_operations.py
@@ -21,7 +21,7 @@
from ... import models as _models
from ..._vendor import _convert_request
-from ...operations._registry_code_versions_operations import build_create_or_update_request_initial, build_delete_request_initial, build_get_request, build_list_request
+from ...operations._registry_code_versions_operations import build_create_or_get_pending_upload_request, build_create_or_update_request_initial, build_delete_request_initial, build_get_request, build_list_request
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -492,3 +492,79 @@ def get_long_running_output(pipeline_response):
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"} # type: ignore
+
+ @distributed_trace_async
+ async def create_or_get_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ code_name: str,
+ version: str,
+ body: "_models.PendingUploadRequestDto",
+ **kwargs: Any
+ ) -> "_models.PendingUploadResponseDto":
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive.
+ :type version: str
+ :param body: Pending upload request object.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.PendingUploadResponseDto"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PendingUploadRequestDto')
+
+ request = build_create_or_get_pending_upload_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.create_or_get_pending_upload.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('PendingUploadResponseDto', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_pending_upload.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/pendingUpload/{version}"} # type: ignore
+
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_component_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_component_versions_operations.py
index 3d3f1ea76626..d951a75080cf 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_component_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_component_versions_operations.py
@@ -56,6 +56,7 @@ def list(
order_by: Optional[str] = None,
top: Optional[int] = None,
skip: Optional[str] = None,
+ stage: Optional[str] = None,
**kwargs: Any
) -> AsyncIterable["_models.ComponentVersionResourceArmPaginatedResult"]:
"""List versions.
@@ -74,6 +75,8 @@ def list(
:type top: int
:param skip: Continuation token for pagination.
:type skip: str
+ :param stage: Component stage.
+ :type stage: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either ComponentVersionResourceArmPaginatedResult or the
result of cls(response)
@@ -100,6 +103,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -116,6 +120,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
template_url=next_link,
)
request = _convert_request(request)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_containers_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_containers_operations.py
deleted file mode 100644
index f6badc052c6c..000000000000
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_containers_operations.py
+++ /dev/null
@@ -1,468 +0,0 @@
-# pylint: disable=too-many-lines
-# coding=utf-8
-# --------------------------------------------------------------------------
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License. See License.txt in the project root for license information.
-# Code generated by Microsoft (R) AutoRest Code Generator.
-# Changes may cause incorrect behavior and will be lost if the code is regenerated.
-# --------------------------------------------------------------------------
-from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar, Union
-
-from azure.core.async_paging import AsyncItemPaged, AsyncList
-from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
-from azure.core.pipeline import PipelineResponse
-from azure.core.pipeline.transport import AsyncHttpResponse
-from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
-from azure.core.rest import HttpRequest
-from azure.core.tracing.decorator import distributed_trace
-from azure.core.tracing.decorator_async import distributed_trace_async
-from azure.mgmt.core.exceptions import ARMErrorFormat
-from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
-
-from ... import models as _models
-from ..._vendor import _convert_request
-from ...operations._registry_data_containers_operations import build_create_or_update_request_initial, build_delete_request_initial, build_get_request, build_list_request
-T = TypeVar('T')
-ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
-
-class RegistryDataContainersOperations:
- """RegistryDataContainersOperations async operations.
-
- You should not instantiate this class directly. Instead, you should create a Client instance that
- instantiates it for you and attaches it as an attribute.
-
- :ivar models: Alias to model classes used in this operation group.
- :type models: ~azure.mgmt.machinelearningservices.models
- :param client: Client for service requests.
- :param config: Configuration of service client.
- :param serializer: An object model serializer.
- :param deserializer: An object model deserializer.
- """
-
- models = _models
-
- def __init__(self, client, config, serializer, deserializer) -> None:
- self._client = client
- self._serialize = serializer
- self._deserialize = deserializer
- self._config = config
-
- @distributed_trace
- def list(
- self,
- resource_group_name: str,
- registry_name: str,
- skip: Optional[str] = None,
- list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
- **kwargs: Any
- ) -> AsyncIterable["_models.DataContainerResourceArmPaginatedResult"]:
- """List containers.
-
- List containers.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param skip: Continuation token for pagination.
- :type skip: str
- :param list_view_type: View type for including/excluding (for example) archived entities.
- :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: An iterator like instance of either DataContainerResourceArmPaginatedResult or the
- result of cls(response)
- :rtype:
- ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.DataContainerResourceArmPaginatedResult]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainerResourceArmPaginatedResult"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
- def prepare_request(next_link=None):
- if not next_link:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- api_version=api_version,
- skip=skip,
- list_view_type=list_view_type,
- template_url=self.list.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- else:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- api_version=api_version,
- skip=skip,
- list_view_type=list_view_type,
- template_url=next_link,
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
- request.method = "GET"
- return request
-
- async def extract_data(pipeline_response):
- deserialized = self._deserialize("DataContainerResourceArmPaginatedResult", pipeline_response)
- list_of_elem = deserialized.value
- if cls:
- list_of_elem = cls(list_of_elem)
- return deserialized.next_link or None, AsyncList(list_of_elem)
-
- async def get_next(next_link=None):
- request = prepare_request(next_link)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- return pipeline_response
-
-
- return AsyncItemPaged(
- get_next, extract_data
- )
- list.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data"} # type: ignore
-
- async def _delete_initial( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- **kwargs: Any
- ) -> None:
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_delete_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- template_url=self._delete_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 202, 204]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 202:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Location']=self._deserialize('str', response.headers.get('Location'))
- response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After'))
-
-
- if cls:
- return cls(pipeline_response, None, response_headers)
-
- _delete_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
-
- @distributed_trace_async
- async def begin_delete( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- **kwargs: Any
- ) -> AsyncLROPoller[None]:
- """Delete container.
-
- Delete container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
- this operation to not poll, or pass in your own initialized polling object for a personal
- polling strategy.
- :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
- :rtype: ~azure.core.polling.AsyncLROPoller[None]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = await self._delete_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- if cls:
- return cls(pipeline_response, None, {})
-
-
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
- elif polling is False: polling_method = AsyncNoPolling()
- else: polling_method = polling
- if cont_token:
- return AsyncLROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_delete.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
- @distributed_trace_async
- async def get(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- **kwargs: Any
- ) -> "_models.DataContainer":
- """Get container.
-
- Get container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: DataContainer, or the result of cls(response)
- :rtype: ~azure.mgmt.machinelearningservices.models.DataContainer
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainer"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_get_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- template_url=self.get.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- deserialized = self._deserialize('DataContainer', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, {})
-
- return deserialized
-
- get.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
-
- async def _create_or_update_initial(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- body: "_models.DataContainer",
- **kwargs: Any
- ) -> "_models.DataContainer":
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainer"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
-
- _json = self._serialize.body(body, 'DataContainer')
-
- request = build_create_or_update_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- content_type=content_type,
- json=_json,
- template_url=self._create_or_update_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 201]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 200:
- deserialized = self._deserialize('DataContainer', pipeline_response)
-
- if response.status_code == 201:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation'))
-
- deserialized = self._deserialize('DataContainer', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, response_headers)
-
- return deserialized
-
- _create_or_update_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
-
- @distributed_trace_async
- async def begin_create_or_update(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- body: "_models.DataContainer",
- **kwargs: Any
- ) -> AsyncLROPoller["_models.DataContainer"]:
- """Create or update container.
-
- Create or update container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param body: Container entity to create or update.
- :type body: ~azure.mgmt.machinelearningservices.models.DataContainer
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
- this operation to not poll, or pass in your own initialized polling object for a personal
- polling strategy.
- :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of AsyncLROPoller that returns either DataContainer or the result of
- cls(response)
- :rtype:
- ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
- polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainer"]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = await self._create_or_update_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- body=body,
- api_version=api_version,
- content_type=content_type,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- response = pipeline_response.http_response
- deserialized = self._deserialize('DataContainer', pipeline_response)
- if cls:
- return cls(pipeline_response, deserialized, {})
- return deserialized
-
-
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
- elif polling is False: polling_method = AsyncNoPolling()
- else: polling_method = polling
- if cont_token:
- return AsyncLROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_versions_operations.py
deleted file mode 100644
index 8641d7a7fafe..000000000000
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_data_versions_operations.py
+++ /dev/null
@@ -1,508 +0,0 @@
-# pylint: disable=too-many-lines
-# coding=utf-8
-# --------------------------------------------------------------------------
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License. See License.txt in the project root for license information.
-# Code generated by Microsoft (R) AutoRest Code Generator.
-# Changes may cause incorrect behavior and will be lost if the code is regenerated.
-# --------------------------------------------------------------------------
-from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar, Union
-
-from azure.core.async_paging import AsyncItemPaged, AsyncList
-from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
-from azure.core.pipeline import PipelineResponse
-from azure.core.pipeline.transport import AsyncHttpResponse
-from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
-from azure.core.rest import HttpRequest
-from azure.core.tracing.decorator import distributed_trace
-from azure.core.tracing.decorator_async import distributed_trace_async
-from azure.mgmt.core.exceptions import ARMErrorFormat
-from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling
-
-from ... import models as _models
-from ..._vendor import _convert_request
-from ...operations._registry_data_versions_operations import build_create_or_update_request_initial, build_delete_request_initial, build_get_request, build_list_request
-T = TypeVar('T')
-ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
-
-class RegistryDataVersionsOperations:
- """RegistryDataVersionsOperations async operations.
-
- You should not instantiate this class directly. Instead, you should create a Client instance that
- instantiates it for you and attaches it as an attribute.
-
- :ivar models: Alias to model classes used in this operation group.
- :type models: ~azure.mgmt.machinelearningservices.models
- :param client: Client for service requests.
- :param config: Configuration of service client.
- :param serializer: An object model serializer.
- :param deserializer: An object model deserializer.
- """
-
- models = _models
-
- def __init__(self, client, config, serializer, deserializer) -> None:
- self._client = client
- self._serialize = serializer
- self._deserialize = deserializer
- self._config = config
-
- @distributed_trace
- def list(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- order_by: Optional[str] = None,
- top: Optional[int] = None,
- skip: Optional[str] = None,
- tags: Optional[str] = None,
- list_view_type: Optional[Union[str, "_models.ListViewType"]] = None,
- **kwargs: Any
- ) -> AsyncIterable["_models.DataVersionBaseResourceArmPaginatedResult"]:
- """List data versions in the data container.
-
- List data versions in the data container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Data container's name.
- :type name: str
- :param order_by: Please choose OrderBy value from ['createdtime', 'modifiedtime'].
- :type order_by: str
- :param top: Top count of results, top count cannot be greater than the page size.
- If topCount > page size, results with be default page size count
- will be returned.
- :type top: int
- :param skip: Continuation token for pagination.
- :type skip: str
- :param tags: Comma-separated list of tag names (and optionally values). Example:
- tag1,tag2=value2.
- :type tags: str
- :param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
- ListViewType.All]View type for including/excluding (for example) archived entities.
- :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: An iterator like instance of either DataVersionBaseResourceArmPaginatedResult or the
- result of cls(response)
- :rtype:
- ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.machinelearningservices.models.DataVersionBaseResourceArmPaginatedResult]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBaseResourceArmPaginatedResult"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
- def prepare_request(next_link=None):
- if not next_link:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- order_by=order_by,
- top=top,
- skip=skip,
- tags=tags,
- list_view_type=list_view_type,
- template_url=self.list.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- else:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- order_by=order_by,
- top=top,
- skip=skip,
- tags=tags,
- list_view_type=list_view_type,
- template_url=next_link,
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
- request.method = "GET"
- return request
-
- async def extract_data(pipeline_response):
- deserialized = self._deserialize("DataVersionBaseResourceArmPaginatedResult", pipeline_response)
- list_of_elem = deserialized.value
- if cls:
- list_of_elem = cls(list_of_elem)
- return deserialized.next_link or None, AsyncList(list_of_elem)
-
- async def get_next(next_link=None):
- request = prepare_request(next_link)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- return pipeline_response
-
-
- return AsyncItemPaged(
- get_next, extract_data
- )
- list.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions"} # type: ignore
-
- async def _delete_initial( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- version: str,
- **kwargs: Any
- ) -> None:
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_delete_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- template_url=self._delete_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 202, 204]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 202:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Location']=self._deserialize('str', response.headers.get('Location'))
- response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After'))
-
-
- if cls:
- return cls(pipeline_response, None, response_headers)
-
- _delete_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
-
- @distributed_trace_async
- async def begin_delete( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- version: str,
- **kwargs: Any
- ) -> AsyncLROPoller[None]:
- """Delete version.
-
- Delete version.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param version: Version identifier.
- :type version: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
- this operation to not poll, or pass in your own initialized polling object for a personal
- polling strategy.
- :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of AsyncLROPoller that returns either None or the result of cls(response)
- :rtype: ~azure.core.polling.AsyncLROPoller[None]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = await self._delete_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- if cls:
- return cls(pipeline_response, None, {})
-
-
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
- elif polling is False: polling_method = AsyncNoPolling()
- else: polling_method = polling
- if cont_token:
- return AsyncLROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_delete.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
- @distributed_trace_async
- async def get(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- version: str,
- **kwargs: Any
- ) -> "_models.DataVersionBase":
- """Get version.
-
- Get version.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param version: Version identifier.
- :type version: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: DataVersionBase, or the result of cls(response)
- :rtype: ~azure.mgmt.machinelearningservices.models.DataVersionBase
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBase"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_get_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- template_url=self.get.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, {})
-
- return deserialized
-
- get.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
-
- async def _create_or_update_initial(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- version: str,
- body: "_models.DataVersionBase",
- **kwargs: Any
- ) -> "_models.DataVersionBase":
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBase"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
-
- _json = self._serialize.body(body, 'DataVersionBase')
-
- request = build_create_or_update_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- content_type=content_type,
- json=_json,
- template_url=self._create_or_update_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 201]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 200:
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
-
- if response.status_code == 201:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation'))
-
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, response_headers)
-
- return deserialized
-
- _create_or_update_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
-
- @distributed_trace_async
- async def begin_create_or_update(
- self,
- resource_group_name: str,
- registry_name: str,
- name: str,
- version: str,
- body: "_models.DataVersionBase",
- **kwargs: Any
- ) -> AsyncLROPoller["_models.DataVersionBase"]:
- """Create or update version.
-
- Create or update version.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param version: Version identifier.
- :type version: str
- :param body: Version entity to create or update.
- :type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be AsyncARMPolling. Pass in False for
- this operation to not poll, or pass in your own initialized polling object for a personal
- polling strategy.
- :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of AsyncLROPoller that returns either DataVersionBase or the result of
- cls(response)
- :rtype:
- ~azure.core.polling.AsyncLROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
- polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBase"]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = await self._create_or_update_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- body=body,
- api_version=api_version,
- content_type=content_type,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- response = pipeline_response.http_response
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
- if cls:
- return cls(pipeline_response, deserialized, {})
- return deserialized
-
-
- if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
- elif polling is False: polling_method = AsyncNoPolling()
- else: polling_method = polling
- if cont_token:
- return AsyncLROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_model_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_model_versions_operations.py
index 85a029571033..c14a71fa00ed 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_model_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/aio/operations/_registry_model_versions_operations.py
@@ -21,7 +21,7 @@
from ... import models as _models
from ..._vendor import _convert_request
-from ...operations._registry_model_versions_operations import build_create_or_update_request_initial, build_delete_request_initial, build_get_request, build_list_request
+from ...operations._registry_model_versions_operations import build_create_or_get_pending_upload_request, build_create_or_update_request_initial, build_delete_request_initial, build_get_request, build_list_request
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
@@ -519,3 +519,79 @@ def get_long_running_output(pipeline_response):
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"} # type: ignore
+
+ @distributed_trace_async
+ async def create_or_get_pending_upload(
+ self,
+ resource_group_name: str,
+ registry_name: str,
+ model_name: str,
+ version: str,
+ body: "_models.PendingUploadRequestDto",
+ **kwargs: Any
+ ) -> "_models.PendingUploadResponseDto":
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive.
+ :type version: str
+ :param body: Pending upload request object.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.PendingUploadResponseDto"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PendingUploadRequestDto')
+
+ request = build_create_or_get_pending_upload_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.create_or_get_pending_upload.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = await self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('PendingUploadResponseDto', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_pending_upload.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/pendingUpload/{version}"} # type: ignore
+
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/__init__.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/__init__.py
index 957807463a36..f46a4be52762 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/__init__.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/__init__.py
@@ -17,6 +17,7 @@
from ._models_py3 import AksComputeSecrets
from ._models_py3 import AksComputeSecretsProperties
from ._models_py3 import AksNetworkingConfiguration
+ from ._models_py3 import AllFeatures
from ._models_py3 import AllNodes
from ._models_py3 import AmlCompute
from ._models_py3 import AmlComputeNodeInformation
@@ -35,6 +36,7 @@
from ._models_py3 import AssetJobOutput
from ._models_py3 import AssetReferenceBase
from ._models_py3 import AssignedUser
+ from ._models_py3 import AutoDeleteSetting
from ._models_py3 import AutoForecastHorizon
from ._models_py3 import AutoMLJob
from ._models_py3 import AutoMLVertical
@@ -49,6 +51,7 @@
from ._models_py3 import AzureDataLakeGen1Datastore
from ._models_py3 import AzureDataLakeGen2Datastore
from ._models_py3 import AzureDatastore
+ from ._models_py3 import AzureDevOpsWebhook
from ._models_py3 import AzureFileDatastore
from ._models_py3 import AzureMLBatchInferencingServer
from ._models_py3 import AzureMLOnlineInferencingServer
@@ -67,10 +70,15 @@
from ._models_py3 import BatchRetrySettings
from ._models_py3 import BayesianSamplingAlgorithm
from ._models_py3 import BindOptions
+ from ._models_py3 import BlobReferenceForConsumptionDto
from ._models_py3 import BuildContext
+ from ._models_py3 import CategoricalDataDriftMetricThreshold
+ from ._models_py3 import CategoricalDataQualityMetricThreshold
+ from ._models_py3 import CategoricalPredictionDriftMetricThreshold
from ._models_py3 import CertificateDatastoreCredentials
from ._models_py3 import CertificateDatastoreSecrets
from ._models_py3 import Classification
+ from ._models_py3 import ClassificationModelPerformanceMetricThreshold
from ._models_py3 import ClassificationTrainingSettings
from ._models_py3 import ClusterUpdateParameters
from ._models_py3 import CocoExportSummary
@@ -81,6 +89,7 @@
from ._models_py3 import CodeVersion
from ._models_py3 import CodeVersionProperties
from ._models_py3 import CodeVersionResourceArmPaginatedResult
+ from ._models_py3 import Collection
from ._models_py3 import ColumnTransformer
from ._models_py3 import CommandJob
from ._models_py3 import CommandJobLimits
@@ -114,28 +123,39 @@
from ._models_py3 import ContainerResourceRequirements
from ._models_py3 import ContainerResourceSettings
from ._models_py3 import CosmosDbSettings
+ from ._models_py3 import CreateMonitorAction
from ._models_py3 import CronTrigger
from ._models_py3 import CsvExportSummary
from ._models_py3 import CustomForecastHorizon
from ._models_py3 import CustomInferencingServer
+ from ._models_py3 import CustomMetricThreshold
from ._models_py3 import CustomModelJobInput
from ._models_py3 import CustomModelJobOutput
+ from ._models_py3 import CustomMonitoringSignal
from ._models_py3 import CustomNCrossValidations
from ._models_py3 import CustomSeasonality
from ._models_py3 import CustomService
from ._models_py3 import CustomTargetLags
from ._models_py3 import CustomTargetRollingWindowSize
+ from ._models_py3 import DataCollector
from ._models_py3 import DataContainer
from ._models_py3 import DataContainerProperties
from ._models_py3 import DataContainerResourceArmPaginatedResult
+ from ._models_py3 import DataDriftMetricThresholdBase
+ from ._models_py3 import DataDriftMonitoringSignal
from ._models_py3 import DataFactory
+ from ._models_py3 import DataImport
+ from ._models_py3 import DataImportSource
from ._models_py3 import DataLakeAnalytics
from ._models_py3 import DataLakeAnalyticsSchema
from ._models_py3 import DataLakeAnalyticsSchemaProperties
from ._models_py3 import DataPathAssetReference
+ from ._models_py3 import DataQualityMetricThresholdBase
+ from ._models_py3 import DataQualityMonitoringSignal
from ._models_py3 import DataVersionBase
from ._models_py3 import DataVersionBaseProperties
from ._models_py3 import DataVersionBaseResourceArmPaginatedResult
+ from ._models_py3 import DatabaseSource
from ._models_py3 import Databricks
from ._models_py3 import DatabricksComputeSecrets
from ._models_py3 import DatabricksComputeSecretsProperties
@@ -189,7 +209,10 @@
from ._models_py3 import FQDNEndpointsProperties
from ._models_py3 import Feature
from ._models_py3 import FeatureArmPaginatedResult
+ from ._models_py3 import FeatureAttributionDriftMonitoringSignal
+ from ._models_py3 import FeatureAttributionMetricThreshold
from ._models_py3 import FeatureStoreSettings
+ from ._models_py3 import FeatureSubset
from ._models_py3 import FeatureWindow
from ._models_py3 import FeaturesetContainer
from ._models_py3 import FeaturesetContainerProperties
@@ -199,7 +222,6 @@
from ._models_py3 import FeaturesetSpecification
from ._models_py3 import FeaturesetVersion
from ._models_py3 import FeaturesetVersionBackfillRequest
- from ._models_py3 import FeaturesetVersionBackfillResponse
from ._models_py3 import FeaturesetVersionProperties
from ._models_py3 import FeaturesetVersionResourceArmPaginatedResult
from ._models_py3 import FeaturestoreEntityContainer
@@ -209,6 +231,7 @@
from ._models_py3 import FeaturestoreEntityVersionProperties
from ._models_py3 import FeaturestoreEntityVersionResourceArmPaginatedResult
from ._models_py3 import FeaturizationSettings
+ from ._models_py3 import FileSystemSource
from ._models_py3 import FlavorData
from ._models_py3 import ForecastHorizon
from ._models_py3 import Forecasting
@@ -241,11 +264,13 @@
from ._models_py3 import ImageObjectDetectionBase
from ._models_py3 import ImageSweepSettings
from ._models_py3 import ImageVertical
+ from ._models_py3 import ImportDataAction
from ._models_py3 import IndexColumn
from ._models_py3 import InferenceContainerProperties
from ._models_py3 import InferencingServer
from ._models_py3 import InstanceTypeSchema
from ._models_py3 import InstanceTypeSchemaResources
+ from ._models_py3 import IntellectualProperty
from ._models_py3 import JobBase
from ._models_py3 import JobBaseProperties
from ._models_py3 import JobBaseResourceArmPaginatedResult
@@ -274,6 +299,7 @@
from ._models_py3 import LabelingJobProperties
from ._models_py3 import LabelingJobResourceArmPaginatedResult
from ._models_py3 import LabelingJobTextProperties
+ from ._models_py3 import LakehouseArtifact
from ._models_py3 import ListAmlUserFeatureResult
from ._models_py3 import ListNotebookKeysResult
from ._models_py3 import ListStorageAccountKeysResult
@@ -301,9 +327,17 @@
from ._models_py3 import ModelContainerProperties
from ._models_py3 import ModelContainerResourceArmPaginatedResult
from ._models_py3 import ModelPackageInput
+ from ._models_py3 import ModelPerformanceMetricThresholdBase
+ from ._models_py3 import ModelPerformanceSignalBase
from ._models_py3 import ModelVersion
from ._models_py3 import ModelVersionProperties
from ._models_py3 import ModelVersionResourceArmPaginatedResult
+ from ._models_py3 import MonitorDefinition
+ from ._models_py3 import MonitoringDataSegment
+ from ._models_py3 import MonitoringFeatureFilterBase
+ from ._models_py3 import MonitoringInputData
+ from ._models_py3 import MonitoringSignalBase
+ from ._models_py3 import MonitoringThreshold
from ._models_py3 import Mpi
from ._models_py3 import NCrossValidations
from ._models_py3 import NlpFixedParameters
@@ -320,7 +354,12 @@
from ._models_py3 import NotebookPreparationError
from ._models_py3 import NotebookResourceInfo
from ._models_py3 import NotificationSetting
+ from ._models_py3 import NumericalDataDriftMetricThreshold
+ from ._models_py3 import NumericalDataQualityMetricThreshold
+ from ._models_py3 import NumericalPredictionDriftMetricThreshold
from ._models_py3 import Objective
+ from ._models_py3 import OneLakeArtifact
+ from ._models_py3 import OneLakeDatastore
from ._models_py3 import OnlineDeployment
from ._models_py3 import OnlineDeploymentProperties
from ._models_py3 import OnlineDeploymentTrackedResourceArmPaginatedResult
@@ -341,15 +380,23 @@
from ._models_py3 import PaginatedComputeResourcesList
from ._models_py3 import PartialBatchDeployment
from ._models_py3 import PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties
+ from ._models_py3 import PartialJobBase
+ from ._models_py3 import PartialJobBasePartialResource
from ._models_py3 import PartialManagedServiceIdentity
from ._models_py3 import PartialMinimalTrackedResource
from ._models_py3 import PartialMinimalTrackedResourceWithIdentity
from ._models_py3 import PartialMinimalTrackedResourceWithSku
+ from ._models_py3 import PartialNotificationSetting
from ._models_py3 import PartialRegistryPartialTrackedResource
from ._models_py3 import PartialSku
from ._models_py3 import Password
+ from ._models_py3 import PendingUploadCredentialDto
+ from ._models_py3 import PendingUploadRequestDto
+ from ._models_py3 import PendingUploadResponseDto
from ._models_py3 import PersonalComputeInstanceSettings
from ._models_py3 import PipelineJob
+ from ._models_py3 import PredictionDriftMetricThresholdBase
+ from ._models_py3 import PredictionDriftMonitoringSignal
from ._models_py3 import PrivateEndpoint
from ._models_py3 import PrivateEndpointConnection
from ._models_py3 import PrivateEndpointConnectionListResult
@@ -363,6 +410,7 @@
from ._models_py3 import QuotaBaseProperties
from ._models_py3 import QuotaUpdateParameters
from ._models_py3 import RandomSamplingAlgorithm
+ from ._models_py3 import Ray
from ._models_py3 import RecurrenceSchedule
from ._models_py3 import RecurrenceTrigger
from ._models_py3 import RegenerateEndpointKeysRequest
@@ -372,7 +420,9 @@
from ._models_py3 import RegistryRegionArmDetails
from ._models_py3 import RegistryTrackedResourceArmPaginatedResult
from ._models_py3 import Regression
+ from ._models_py3 import RegressionModelPerformanceMetricThreshold
from ._models_py3 import RegressionTrainingSettings
+ from ._models_py3 import RequestLogging
from ._models_py3 import Resource
from ._models_py3 import ResourceBase
from ._models_py3 import ResourceConfiguration
@@ -381,6 +431,7 @@
from ._models_py3 import ResourceQuota
from ._models_py3 import Route
from ._models_py3 import SASAuthTypeWorkspaceConnectionProperties
+ from ._models_py3 import SASCredentialDto
from ._models_py3 import SamplingAlgorithm
from ._models_py3 import SasDatastoreCredentials
from ._models_py3 import SasDatastoreSecrets
@@ -394,6 +445,7 @@
from ._models_py3 import ScriptReference
from ._models_py3 import ScriptsToExecute
from ._models_py3 import Seasonality
+ from ._models_py3 import SecretConfiguration
from ._models_py3 import ServiceManagedResourcesSettings
from ._models_py3 import ServicePrincipalAuthTypeWorkspaceConnectionProperties
from ._models_py3 import ServicePrincipalDatastoreCredentials
@@ -404,7 +456,10 @@
from ._models_py3 import SkuCapacity
from ._models_py3 import SkuResource
from ._models_py3 import SkuResourceArmPaginatedResult
+ from ._models_py3 import SkuResourceArmPaginatedResultAutoGenerated
+ from ._models_py3 import SkuResourceAutoGenerated
from ._models_py3 import SkuSetting
+ from ._models_py3 import SkuSettingAutoGenerated
from ._models_py3 import SparkJob
from ._models_py3 import SparkJobEntry
from ._models_py3 import SparkJobPythonEntry
@@ -436,6 +491,7 @@
from ._models_py3 import TextClassificationMultilabel
from ._models_py3 import TextNer
from ._models_py3 import TmpfsOptions
+ from ._models_py3 import TopNFeaturesByAttribution
from ._models_py3 import TrackedResource
from ._models_py3 import TrainingSettings
from ._models_py3 import TrialComponent
@@ -471,6 +527,7 @@
from ._models_py3 import VirtualMachineSshCredentials
from ._models_py3 import VolumeDefinition
from ._models_py3 import VolumeOptions
+ from ._models_py3 import Webhook
from ._models_py3 import Workspace
from ._models_py3 import WorkspaceConnectionAccessKey
from ._models_py3 import WorkspaceConnectionManagedIdentity
@@ -494,6 +551,7 @@
from ._models import AksComputeSecrets # type: ignore
from ._models import AksComputeSecretsProperties # type: ignore
from ._models import AksNetworkingConfiguration # type: ignore
+ from ._models import AllFeatures # type: ignore
from ._models import AllNodes # type: ignore
from ._models import AmlCompute # type: ignore
from ._models import AmlComputeNodeInformation # type: ignore
@@ -512,6 +570,7 @@
from ._models import AssetJobOutput # type: ignore
from ._models import AssetReferenceBase # type: ignore
from ._models import AssignedUser # type: ignore
+ from ._models import AutoDeleteSetting # type: ignore
from ._models import AutoForecastHorizon # type: ignore
from ._models import AutoMLJob # type: ignore
from ._models import AutoMLVertical # type: ignore
@@ -526,6 +585,7 @@
from ._models import AzureDataLakeGen1Datastore # type: ignore
from ._models import AzureDataLakeGen2Datastore # type: ignore
from ._models import AzureDatastore # type: ignore
+ from ._models import AzureDevOpsWebhook # type: ignore
from ._models import AzureFileDatastore # type: ignore
from ._models import AzureMLBatchInferencingServer # type: ignore
from ._models import AzureMLOnlineInferencingServer # type: ignore
@@ -544,10 +604,15 @@
from ._models import BatchRetrySettings # type: ignore
from ._models import BayesianSamplingAlgorithm # type: ignore
from ._models import BindOptions # type: ignore
+ from ._models import BlobReferenceForConsumptionDto # type: ignore
from ._models import BuildContext # type: ignore
+ from ._models import CategoricalDataDriftMetricThreshold # type: ignore
+ from ._models import CategoricalDataQualityMetricThreshold # type: ignore
+ from ._models import CategoricalPredictionDriftMetricThreshold # type: ignore
from ._models import CertificateDatastoreCredentials # type: ignore
from ._models import CertificateDatastoreSecrets # type: ignore
from ._models import Classification # type: ignore
+ from ._models import ClassificationModelPerformanceMetricThreshold # type: ignore
from ._models import ClassificationTrainingSettings # type: ignore
from ._models import ClusterUpdateParameters # type: ignore
from ._models import CocoExportSummary # type: ignore
@@ -558,6 +623,7 @@
from ._models import CodeVersion # type: ignore
from ._models import CodeVersionProperties # type: ignore
from ._models import CodeVersionResourceArmPaginatedResult # type: ignore
+ from ._models import Collection # type: ignore
from ._models import ColumnTransformer # type: ignore
from ._models import CommandJob # type: ignore
from ._models import CommandJobLimits # type: ignore
@@ -591,28 +657,39 @@
from ._models import ContainerResourceRequirements # type: ignore
from ._models import ContainerResourceSettings # type: ignore
from ._models import CosmosDbSettings # type: ignore
+ from ._models import CreateMonitorAction # type: ignore
from ._models import CronTrigger # type: ignore
from ._models import CsvExportSummary # type: ignore
from ._models import CustomForecastHorizon # type: ignore
from ._models import CustomInferencingServer # type: ignore
+ from ._models import CustomMetricThreshold # type: ignore
from ._models import CustomModelJobInput # type: ignore
from ._models import CustomModelJobOutput # type: ignore
+ from ._models import CustomMonitoringSignal # type: ignore
from ._models import CustomNCrossValidations # type: ignore
from ._models import CustomSeasonality # type: ignore
from ._models import CustomService # type: ignore
from ._models import CustomTargetLags # type: ignore
from ._models import CustomTargetRollingWindowSize # type: ignore
+ from ._models import DataCollector # type: ignore
from ._models import DataContainer # type: ignore
from ._models import DataContainerProperties # type: ignore
from ._models import DataContainerResourceArmPaginatedResult # type: ignore
+ from ._models import DataDriftMetricThresholdBase # type: ignore
+ from ._models import DataDriftMonitoringSignal # type: ignore
from ._models import DataFactory # type: ignore
+ from ._models import DataImport # type: ignore
+ from ._models import DataImportSource # type: ignore
from ._models import DataLakeAnalytics # type: ignore
from ._models import DataLakeAnalyticsSchema # type: ignore
from ._models import DataLakeAnalyticsSchemaProperties # type: ignore
from ._models import DataPathAssetReference # type: ignore
+ from ._models import DataQualityMetricThresholdBase # type: ignore
+ from ._models import DataQualityMonitoringSignal # type: ignore
from ._models import DataVersionBase # type: ignore
from ._models import DataVersionBaseProperties # type: ignore
from ._models import DataVersionBaseResourceArmPaginatedResult # type: ignore
+ from ._models import DatabaseSource # type: ignore
from ._models import Databricks # type: ignore
from ._models import DatabricksComputeSecrets # type: ignore
from ._models import DatabricksComputeSecretsProperties # type: ignore
@@ -666,7 +743,10 @@
from ._models import FQDNEndpointsProperties # type: ignore
from ._models import Feature # type: ignore
from ._models import FeatureArmPaginatedResult # type: ignore
+ from ._models import FeatureAttributionDriftMonitoringSignal # type: ignore
+ from ._models import FeatureAttributionMetricThreshold # type: ignore
from ._models import FeatureStoreSettings # type: ignore
+ from ._models import FeatureSubset # type: ignore
from ._models import FeatureWindow # type: ignore
from ._models import FeaturesetContainer # type: ignore
from ._models import FeaturesetContainerProperties # type: ignore
@@ -676,7 +756,6 @@
from ._models import FeaturesetSpecification # type: ignore
from ._models import FeaturesetVersion # type: ignore
from ._models import FeaturesetVersionBackfillRequest # type: ignore
- from ._models import FeaturesetVersionBackfillResponse # type: ignore
from ._models import FeaturesetVersionProperties # type: ignore
from ._models import FeaturesetVersionResourceArmPaginatedResult # type: ignore
from ._models import FeaturestoreEntityContainer # type: ignore
@@ -686,6 +765,7 @@
from ._models import FeaturestoreEntityVersionProperties # type: ignore
from ._models import FeaturestoreEntityVersionResourceArmPaginatedResult # type: ignore
from ._models import FeaturizationSettings # type: ignore
+ from ._models import FileSystemSource # type: ignore
from ._models import FlavorData # type: ignore
from ._models import ForecastHorizon # type: ignore
from ._models import Forecasting # type: ignore
@@ -718,11 +798,13 @@
from ._models import ImageObjectDetectionBase # type: ignore
from ._models import ImageSweepSettings # type: ignore
from ._models import ImageVertical # type: ignore
+ from ._models import ImportDataAction # type: ignore
from ._models import IndexColumn # type: ignore
from ._models import InferenceContainerProperties # type: ignore
from ._models import InferencingServer # type: ignore
from ._models import InstanceTypeSchema # type: ignore
from ._models import InstanceTypeSchemaResources # type: ignore
+ from ._models import IntellectualProperty # type: ignore
from ._models import JobBase # type: ignore
from ._models import JobBaseProperties # type: ignore
from ._models import JobBaseResourceArmPaginatedResult # type: ignore
@@ -751,6 +833,7 @@
from ._models import LabelingJobProperties # type: ignore
from ._models import LabelingJobResourceArmPaginatedResult # type: ignore
from ._models import LabelingJobTextProperties # type: ignore
+ from ._models import LakehouseArtifact # type: ignore
from ._models import ListAmlUserFeatureResult # type: ignore
from ._models import ListNotebookKeysResult # type: ignore
from ._models import ListStorageAccountKeysResult # type: ignore
@@ -778,9 +861,17 @@
from ._models import ModelContainerProperties # type: ignore
from ._models import ModelContainerResourceArmPaginatedResult # type: ignore
from ._models import ModelPackageInput # type: ignore
+ from ._models import ModelPerformanceMetricThresholdBase # type: ignore
+ from ._models import ModelPerformanceSignalBase # type: ignore
from ._models import ModelVersion # type: ignore
from ._models import ModelVersionProperties # type: ignore
from ._models import ModelVersionResourceArmPaginatedResult # type: ignore
+ from ._models import MonitorDefinition # type: ignore
+ from ._models import MonitoringDataSegment # type: ignore
+ from ._models import MonitoringFeatureFilterBase # type: ignore
+ from ._models import MonitoringInputData # type: ignore
+ from ._models import MonitoringSignalBase # type: ignore
+ from ._models import MonitoringThreshold # type: ignore
from ._models import Mpi # type: ignore
from ._models import NCrossValidations # type: ignore
from ._models import NlpFixedParameters # type: ignore
@@ -797,7 +888,12 @@
from ._models import NotebookPreparationError # type: ignore
from ._models import NotebookResourceInfo # type: ignore
from ._models import NotificationSetting # type: ignore
+ from ._models import NumericalDataDriftMetricThreshold # type: ignore
+ from ._models import NumericalDataQualityMetricThreshold # type: ignore
+ from ._models import NumericalPredictionDriftMetricThreshold # type: ignore
from ._models import Objective # type: ignore
+ from ._models import OneLakeArtifact # type: ignore
+ from ._models import OneLakeDatastore # type: ignore
from ._models import OnlineDeployment # type: ignore
from ._models import OnlineDeploymentProperties # type: ignore
from ._models import OnlineDeploymentTrackedResourceArmPaginatedResult # type: ignore
@@ -818,15 +914,23 @@
from ._models import PaginatedComputeResourcesList # type: ignore
from ._models import PartialBatchDeployment # type: ignore
from ._models import PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties # type: ignore
+ from ._models import PartialJobBase # type: ignore
+ from ._models import PartialJobBasePartialResource # type: ignore
from ._models import PartialManagedServiceIdentity # type: ignore
from ._models import PartialMinimalTrackedResource # type: ignore
from ._models import PartialMinimalTrackedResourceWithIdentity # type: ignore
from ._models import PartialMinimalTrackedResourceWithSku # type: ignore
+ from ._models import PartialNotificationSetting # type: ignore
from ._models import PartialRegistryPartialTrackedResource # type: ignore
from ._models import PartialSku # type: ignore
from ._models import Password # type: ignore
+ from ._models import PendingUploadCredentialDto # type: ignore
+ from ._models import PendingUploadRequestDto # type: ignore
+ from ._models import PendingUploadResponseDto # type: ignore
from ._models import PersonalComputeInstanceSettings # type: ignore
from ._models import PipelineJob # type: ignore
+ from ._models import PredictionDriftMetricThresholdBase # type: ignore
+ from ._models import PredictionDriftMonitoringSignal # type: ignore
from ._models import PrivateEndpoint # type: ignore
from ._models import PrivateEndpointConnection # type: ignore
from ._models import PrivateEndpointConnectionListResult # type: ignore
@@ -840,6 +944,7 @@
from ._models import QuotaBaseProperties # type: ignore
from ._models import QuotaUpdateParameters # type: ignore
from ._models import RandomSamplingAlgorithm # type: ignore
+ from ._models import Ray # type: ignore
from ._models import RecurrenceSchedule # type: ignore
from ._models import RecurrenceTrigger # type: ignore
from ._models import RegenerateEndpointKeysRequest # type: ignore
@@ -849,7 +954,9 @@
from ._models import RegistryRegionArmDetails # type: ignore
from ._models import RegistryTrackedResourceArmPaginatedResult # type: ignore
from ._models import Regression # type: ignore
+ from ._models import RegressionModelPerformanceMetricThreshold # type: ignore
from ._models import RegressionTrainingSettings # type: ignore
+ from ._models import RequestLogging # type: ignore
from ._models import Resource # type: ignore
from ._models import ResourceBase # type: ignore
from ._models import ResourceConfiguration # type: ignore
@@ -858,6 +965,7 @@
from ._models import ResourceQuota # type: ignore
from ._models import Route # type: ignore
from ._models import SASAuthTypeWorkspaceConnectionProperties # type: ignore
+ from ._models import SASCredentialDto # type: ignore
from ._models import SamplingAlgorithm # type: ignore
from ._models import SasDatastoreCredentials # type: ignore
from ._models import SasDatastoreSecrets # type: ignore
@@ -871,6 +979,7 @@
from ._models import ScriptReference # type: ignore
from ._models import ScriptsToExecute # type: ignore
from ._models import Seasonality # type: ignore
+ from ._models import SecretConfiguration # type: ignore
from ._models import ServiceManagedResourcesSettings # type: ignore
from ._models import ServicePrincipalAuthTypeWorkspaceConnectionProperties # type: ignore
from ._models import ServicePrincipalDatastoreCredentials # type: ignore
@@ -881,7 +990,10 @@
from ._models import SkuCapacity # type: ignore
from ._models import SkuResource # type: ignore
from ._models import SkuResourceArmPaginatedResult # type: ignore
+ from ._models import SkuResourceArmPaginatedResultAutoGenerated # type: ignore
+ from ._models import SkuResourceAutoGenerated # type: ignore
from ._models import SkuSetting # type: ignore
+ from ._models import SkuSettingAutoGenerated # type: ignore
from ._models import SparkJob # type: ignore
from ._models import SparkJobEntry # type: ignore
from ._models import SparkJobPythonEntry # type: ignore
@@ -913,6 +1025,7 @@
from ._models import TextClassificationMultilabel # type: ignore
from ._models import TextNer # type: ignore
from ._models import TmpfsOptions # type: ignore
+ from ._models import TopNFeaturesByAttribution # type: ignore
from ._models import TrackedResource # type: ignore
from ._models import TrainingSettings # type: ignore
from ._models import TrialComponent # type: ignore
@@ -948,6 +1061,7 @@
from ._models import VirtualMachineSshCredentials # type: ignore
from ._models import VolumeDefinition # type: ignore
from ._models import VolumeOptions # type: ignore
+ from ._models import Webhook # type: ignore
from ._models import Workspace # type: ignore
from ._models import WorkspaceConnectionAccessKey # type: ignore
from ._models import WorkspaceConnectionManagedIdentity # type: ignore
@@ -965,6 +1079,7 @@
AllocationState,
ApplicationSharingPolicy,
AssetProvisioningState,
+ AutoDeleteCondition,
AutoRebuildSetting,
Autosave,
BaseEnvironmentSourceType,
@@ -974,6 +1089,10 @@
BillingCurrency,
BlockedTransformers,
Caching,
+ CategoricalDataDriftMetric,
+ CategoricalDataQualityMetric,
+ CategoricalPredictionDriftMetric,
+ ClassificationModelPerformanceMetric,
ClassificationModels,
ClassificationMultilabelPrimaryMetrics,
ClassificationPrimaryMetrics,
@@ -987,6 +1106,8 @@
ContainerType,
CreatedByType,
CredentialsType,
+ DataCollectionMode,
+ DataImportSourceType,
DataType,
DatastoreType,
DeploymentProvisioningState,
@@ -1002,6 +1123,7 @@
EnvironmentType,
EnvironmentVariableType,
ExportFormatType,
+ FeatureAttributionMetric,
FeatureDataType,
FeatureLags,
FeaturestoreJobType,
@@ -1029,6 +1151,8 @@
LearningRateScheduler,
ListViewType,
LoadBalancerType,
+ LogTrainingMetrics,
+ LogValidationLoss,
LogVerbosity,
MLAssistConfigurationType,
MLFlowAutologgerState,
@@ -1037,6 +1161,12 @@
MediaType,
MlflowAutologger,
ModelSize,
+ MonitoringFeatureDataType,
+ MonitoringFeatureFilterType,
+ MonitoringInputDataContext,
+ MonitoringModelType,
+ MonitoringNotificationMode,
+ MonitoringSignalType,
MountAction,
MountState,
MultiSelect,
@@ -1045,7 +1175,11 @@
NlpLearningRateScheduler,
NodeState,
NodesValueType,
+ NumericalDataDriftMetric,
+ NumericalDataQualityMetric,
+ NumericalPredictionDriftMetric,
ObjectDetectionPrimaryMetrics,
+ OneLakeArtifactType,
OperatingSystemType,
OperationName,
OperationStatus,
@@ -1056,8 +1190,11 @@
PackageBuildState,
PackageInputDeliveryMode,
PackageInputType,
+ PendingUploadCredentialType,
+ PendingUploadType,
PrivateEndpointConnectionProvisioningState,
PrivateEndpointServiceConnectionStatus,
+ ProtectionLevel,
Protocol,
ProvisioningState,
ProvisioningStatus,
@@ -1067,9 +1204,11 @@
RandomSamplingAlgorithmRule,
RecurrenceFrequency,
ReferenceType,
+ RegressionModelPerformanceMetric,
RegressionModels,
RegressionPrimaryMetrics,
RemoteLoginPortPublicAccess,
+ RollingRateType,
SamplingAlgorithmType,
ScaleType,
ScheduleActionType,
@@ -1109,6 +1248,7 @@
ValueFormat,
VmPriority,
VolumeDefinitionType,
+ WebhookType,
WeekDay,
)
@@ -1123,6 +1263,7 @@
'AksComputeSecrets',
'AksComputeSecretsProperties',
'AksNetworkingConfiguration',
+ 'AllFeatures',
'AllNodes',
'AmlCompute',
'AmlComputeNodeInformation',
@@ -1141,6 +1282,7 @@
'AssetJobOutput',
'AssetReferenceBase',
'AssignedUser',
+ 'AutoDeleteSetting',
'AutoForecastHorizon',
'AutoMLJob',
'AutoMLVertical',
@@ -1155,6 +1297,7 @@
'AzureDataLakeGen1Datastore',
'AzureDataLakeGen2Datastore',
'AzureDatastore',
+ 'AzureDevOpsWebhook',
'AzureFileDatastore',
'AzureMLBatchInferencingServer',
'AzureMLOnlineInferencingServer',
@@ -1173,10 +1316,15 @@
'BatchRetrySettings',
'BayesianSamplingAlgorithm',
'BindOptions',
+ 'BlobReferenceForConsumptionDto',
'BuildContext',
+ 'CategoricalDataDriftMetricThreshold',
+ 'CategoricalDataQualityMetricThreshold',
+ 'CategoricalPredictionDriftMetricThreshold',
'CertificateDatastoreCredentials',
'CertificateDatastoreSecrets',
'Classification',
+ 'ClassificationModelPerformanceMetricThreshold',
'ClassificationTrainingSettings',
'ClusterUpdateParameters',
'CocoExportSummary',
@@ -1187,6 +1335,7 @@
'CodeVersion',
'CodeVersionProperties',
'CodeVersionResourceArmPaginatedResult',
+ 'Collection',
'ColumnTransformer',
'CommandJob',
'CommandJobLimits',
@@ -1220,28 +1369,39 @@
'ContainerResourceRequirements',
'ContainerResourceSettings',
'CosmosDbSettings',
+ 'CreateMonitorAction',
'CronTrigger',
'CsvExportSummary',
'CustomForecastHorizon',
'CustomInferencingServer',
+ 'CustomMetricThreshold',
'CustomModelJobInput',
'CustomModelJobOutput',
+ 'CustomMonitoringSignal',
'CustomNCrossValidations',
'CustomSeasonality',
'CustomService',
'CustomTargetLags',
'CustomTargetRollingWindowSize',
+ 'DataCollector',
'DataContainer',
'DataContainerProperties',
'DataContainerResourceArmPaginatedResult',
+ 'DataDriftMetricThresholdBase',
+ 'DataDriftMonitoringSignal',
'DataFactory',
+ 'DataImport',
+ 'DataImportSource',
'DataLakeAnalytics',
'DataLakeAnalyticsSchema',
'DataLakeAnalyticsSchemaProperties',
'DataPathAssetReference',
+ 'DataQualityMetricThresholdBase',
+ 'DataQualityMonitoringSignal',
'DataVersionBase',
'DataVersionBaseProperties',
'DataVersionBaseResourceArmPaginatedResult',
+ 'DatabaseSource',
'Databricks',
'DatabricksComputeSecrets',
'DatabricksComputeSecretsProperties',
@@ -1295,7 +1455,10 @@
'FQDNEndpointsProperties',
'Feature',
'FeatureArmPaginatedResult',
+ 'FeatureAttributionDriftMonitoringSignal',
+ 'FeatureAttributionMetricThreshold',
'FeatureStoreSettings',
+ 'FeatureSubset',
'FeatureWindow',
'FeaturesetContainer',
'FeaturesetContainerProperties',
@@ -1305,7 +1468,6 @@
'FeaturesetSpecification',
'FeaturesetVersion',
'FeaturesetVersionBackfillRequest',
- 'FeaturesetVersionBackfillResponse',
'FeaturesetVersionProperties',
'FeaturesetVersionResourceArmPaginatedResult',
'FeaturestoreEntityContainer',
@@ -1315,6 +1477,7 @@
'FeaturestoreEntityVersionProperties',
'FeaturestoreEntityVersionResourceArmPaginatedResult',
'FeaturizationSettings',
+ 'FileSystemSource',
'FlavorData',
'ForecastHorizon',
'Forecasting',
@@ -1347,11 +1510,13 @@
'ImageObjectDetectionBase',
'ImageSweepSettings',
'ImageVertical',
+ 'ImportDataAction',
'IndexColumn',
'InferenceContainerProperties',
'InferencingServer',
'InstanceTypeSchema',
'InstanceTypeSchemaResources',
+ 'IntellectualProperty',
'JobBase',
'JobBaseProperties',
'JobBaseResourceArmPaginatedResult',
@@ -1380,6 +1545,7 @@
'LabelingJobProperties',
'LabelingJobResourceArmPaginatedResult',
'LabelingJobTextProperties',
+ 'LakehouseArtifact',
'ListAmlUserFeatureResult',
'ListNotebookKeysResult',
'ListStorageAccountKeysResult',
@@ -1407,9 +1573,17 @@
'ModelContainerProperties',
'ModelContainerResourceArmPaginatedResult',
'ModelPackageInput',
+ 'ModelPerformanceMetricThresholdBase',
+ 'ModelPerformanceSignalBase',
'ModelVersion',
'ModelVersionProperties',
'ModelVersionResourceArmPaginatedResult',
+ 'MonitorDefinition',
+ 'MonitoringDataSegment',
+ 'MonitoringFeatureFilterBase',
+ 'MonitoringInputData',
+ 'MonitoringSignalBase',
+ 'MonitoringThreshold',
'Mpi',
'NCrossValidations',
'NlpFixedParameters',
@@ -1426,7 +1600,12 @@
'NotebookPreparationError',
'NotebookResourceInfo',
'NotificationSetting',
+ 'NumericalDataDriftMetricThreshold',
+ 'NumericalDataQualityMetricThreshold',
+ 'NumericalPredictionDriftMetricThreshold',
'Objective',
+ 'OneLakeArtifact',
+ 'OneLakeDatastore',
'OnlineDeployment',
'OnlineDeploymentProperties',
'OnlineDeploymentTrackedResourceArmPaginatedResult',
@@ -1447,15 +1626,23 @@
'PaginatedComputeResourcesList',
'PartialBatchDeployment',
'PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties',
+ 'PartialJobBase',
+ 'PartialJobBasePartialResource',
'PartialManagedServiceIdentity',
'PartialMinimalTrackedResource',
'PartialMinimalTrackedResourceWithIdentity',
'PartialMinimalTrackedResourceWithSku',
+ 'PartialNotificationSetting',
'PartialRegistryPartialTrackedResource',
'PartialSku',
'Password',
+ 'PendingUploadCredentialDto',
+ 'PendingUploadRequestDto',
+ 'PendingUploadResponseDto',
'PersonalComputeInstanceSettings',
'PipelineJob',
+ 'PredictionDriftMetricThresholdBase',
+ 'PredictionDriftMonitoringSignal',
'PrivateEndpoint',
'PrivateEndpointConnection',
'PrivateEndpointConnectionListResult',
@@ -1469,6 +1656,7 @@
'QuotaBaseProperties',
'QuotaUpdateParameters',
'RandomSamplingAlgorithm',
+ 'Ray',
'RecurrenceSchedule',
'RecurrenceTrigger',
'RegenerateEndpointKeysRequest',
@@ -1478,7 +1666,9 @@
'RegistryRegionArmDetails',
'RegistryTrackedResourceArmPaginatedResult',
'Regression',
+ 'RegressionModelPerformanceMetricThreshold',
'RegressionTrainingSettings',
+ 'RequestLogging',
'Resource',
'ResourceBase',
'ResourceConfiguration',
@@ -1487,6 +1677,7 @@
'ResourceQuota',
'Route',
'SASAuthTypeWorkspaceConnectionProperties',
+ 'SASCredentialDto',
'SamplingAlgorithm',
'SasDatastoreCredentials',
'SasDatastoreSecrets',
@@ -1500,6 +1691,7 @@
'ScriptReference',
'ScriptsToExecute',
'Seasonality',
+ 'SecretConfiguration',
'ServiceManagedResourcesSettings',
'ServicePrincipalAuthTypeWorkspaceConnectionProperties',
'ServicePrincipalDatastoreCredentials',
@@ -1510,7 +1702,10 @@
'SkuCapacity',
'SkuResource',
'SkuResourceArmPaginatedResult',
+ 'SkuResourceArmPaginatedResultAutoGenerated',
+ 'SkuResourceAutoGenerated',
'SkuSetting',
+ 'SkuSettingAutoGenerated',
'SparkJob',
'SparkJobEntry',
'SparkJobPythonEntry',
@@ -1542,6 +1737,7 @@
'TextClassificationMultilabel',
'TextNer',
'TmpfsOptions',
+ 'TopNFeaturesByAttribution',
'TrackedResource',
'TrainingSettings',
'TrialComponent',
@@ -1577,6 +1773,7 @@
'VirtualMachineSshCredentials',
'VolumeDefinition',
'VolumeOptions',
+ 'Webhook',
'Workspace',
'WorkspaceConnectionAccessKey',
'WorkspaceConnectionManagedIdentity',
@@ -1592,6 +1789,7 @@
'AllocationState',
'ApplicationSharingPolicy',
'AssetProvisioningState',
+ 'AutoDeleteCondition',
'AutoRebuildSetting',
'Autosave',
'BaseEnvironmentSourceType',
@@ -1601,6 +1799,10 @@
'BillingCurrency',
'BlockedTransformers',
'Caching',
+ 'CategoricalDataDriftMetric',
+ 'CategoricalDataQualityMetric',
+ 'CategoricalPredictionDriftMetric',
+ 'ClassificationModelPerformanceMetric',
'ClassificationModels',
'ClassificationMultilabelPrimaryMetrics',
'ClassificationPrimaryMetrics',
@@ -1614,6 +1816,8 @@
'ContainerType',
'CreatedByType',
'CredentialsType',
+ 'DataCollectionMode',
+ 'DataImportSourceType',
'DataType',
'DatastoreType',
'DeploymentProvisioningState',
@@ -1629,6 +1833,7 @@
'EnvironmentType',
'EnvironmentVariableType',
'ExportFormatType',
+ 'FeatureAttributionMetric',
'FeatureDataType',
'FeatureLags',
'FeaturestoreJobType',
@@ -1656,6 +1861,8 @@
'LearningRateScheduler',
'ListViewType',
'LoadBalancerType',
+ 'LogTrainingMetrics',
+ 'LogValidationLoss',
'LogVerbosity',
'MLAssistConfigurationType',
'MLFlowAutologgerState',
@@ -1664,6 +1871,12 @@
'MediaType',
'MlflowAutologger',
'ModelSize',
+ 'MonitoringFeatureDataType',
+ 'MonitoringFeatureFilterType',
+ 'MonitoringInputDataContext',
+ 'MonitoringModelType',
+ 'MonitoringNotificationMode',
+ 'MonitoringSignalType',
'MountAction',
'MountState',
'MultiSelect',
@@ -1672,7 +1885,11 @@
'NlpLearningRateScheduler',
'NodeState',
'NodesValueType',
+ 'NumericalDataDriftMetric',
+ 'NumericalDataQualityMetric',
+ 'NumericalPredictionDriftMetric',
'ObjectDetectionPrimaryMetrics',
+ 'OneLakeArtifactType',
'OperatingSystemType',
'OperationName',
'OperationStatus',
@@ -1683,8 +1900,11 @@
'PackageBuildState',
'PackageInputDeliveryMode',
'PackageInputType',
+ 'PendingUploadCredentialType',
+ 'PendingUploadType',
'PrivateEndpointConnectionProvisioningState',
'PrivateEndpointServiceConnectionStatus',
+ 'ProtectionLevel',
'Protocol',
'ProvisioningState',
'ProvisioningStatus',
@@ -1694,9 +1914,11 @@
'RandomSamplingAlgorithmRule',
'RecurrenceFrequency',
'ReferenceType',
+ 'RegressionModelPerformanceMetric',
'RegressionModels',
'RegressionPrimaryMetrics',
'RemoteLoginPortPublicAccess',
+ 'RollingRateType',
'SamplingAlgorithmType',
'ScaleType',
'ScheduleActionType',
@@ -1736,5 +1958,6 @@
'ValueFormat',
'VmPriority',
'VolumeDefinitionType',
+ 'WebhookType',
'WeekDay',
]
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_azure_machine_learning_workspaces_enums.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_azure_machine_learning_workspaces_enums.py
index 00c5d0d3794f..a00a1d6bc380 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_azure_machine_learning_workspaces_enums.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_azure_machine_learning_workspaces_enums.py
@@ -42,6 +42,11 @@ class AssetProvisioningState(with_metaclass(CaseInsensitiveEnumMeta, str, Enum))
UPDATING = "Updating"
DELETING = "Deleting"
+class AutoDeleteCondition(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ CREATED_GREATER_THAN = "CreatedGreaterThan"
+ LAST_ACCESSED_GREATER_THAN = "LastAccessedGreaterThan"
+
class AutoRebuildSetting(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""AutoRebuild setting for the derived image
"""
@@ -130,6 +135,44 @@ class Caching(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
READ_ONLY = "ReadOnly"
READ_WRITE = "ReadWrite"
+class CategoricalDataDriftMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: The Jensen Shannon Distance (JSD) metric.
+ JENSEN_SHANNON_DISTANCE = "JensenShannonDistance"
+ #: The Population Stability Index (PSI) metric.
+ POPULATION_STABILITY_INDEX = "PopulationStabilityIndex"
+ #: The Pearsons Chi Squared Test metric.
+ PEARSONS_CHI_SQUARED_TEST = "PearsonsChiSquaredTest"
+
+class CategoricalDataQualityMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Calculates the rate of null values.
+ NULL_VALUE_RATE = "NullValueRate"
+ #: Calculates the rate of data type errors.
+ DATA_TYPE_ERROR_RATE = "DataTypeErrorRate"
+ #: Calculates the rate values are out of bounds.
+ OUT_OF_BOUNDS_RATE = "OutOfBoundsRate"
+
+class CategoricalPredictionDriftMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: The Jensen Shannon Distance (JSD) metric.
+ JENSEN_SHANNON_DISTANCE = "JensenShannonDistance"
+ #: The Population Stability Index (PSI) metric.
+ POPULATION_STABILITY_INDEX = "PopulationStabilityIndex"
+ #: The Pearsons Chi Squared Test metric.
+ PEARSONS_CHI_SQUARED_TEST = "PearsonsChiSquaredTest"
+
+class ClassificationModelPerformanceMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Calculates the accuracy of the model predictions.
+ ACCURACY = "Accuracy"
+ #: Calculates the precision of the model predictions.
+ PRECISION = "Precision"
+ #: Calculates the recall of the model predictions.
+ RECALL = "Recall"
+ #: Calculates the F1 score of the model predictions.
+ F1_SCORE = "F1Score"
+
class ClassificationModels(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Enum for all classification models supported by AutoML.
"""
@@ -177,8 +220,8 @@ class ClassificationModels(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
#: decision rules inferred from the data features.
DECISION_TREE = "DecisionTree"
#: Random forest is a supervised learning algorithm.
- #: The "forest" it builds, is an ensemble of decision trees, usually trained with the 'bagging'
- #: method.
+ #: The "forest" it builds, is an ensemble of decision trees, usually trained with the
+ #: “bagging†method.
#: The general idea of the bagging method is that a combination of learning models increases the
#: overall result.
RANDOM_FOREST = "RandomForest"
@@ -353,6 +396,18 @@ class CredentialsType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
KERBEROS_KEYTAB = "KerberosKeytab"
KERBEROS_PASSWORD = "KerberosPassword"
+class DataCollectionMode(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ ENABLED = "Enabled"
+ DISABLED = "Disabled"
+
+class DataImportSourceType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+ """Enum to determine the type of data.
+ """
+
+ DATABASE = "database"
+ FILE_SYSTEM = "file_system"
+
class DatastoreType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Enum to determine the datastore contents type.
"""
@@ -362,6 +417,7 @@ class DatastoreType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
AZURE_DATA_LAKE_GEN2 = "AzureDataLakeGen2"
AZURE_FILE = "AzureFile"
HDFS = "Hdfs"
+ ONE_LAKE = "OneLake"
class DataType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Enum to determine the type of data.
@@ -398,6 +454,7 @@ class DistributionType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
PY_TORCH = "PyTorch"
TENSOR_FLOW = "TensorFlow"
MPI = "Mpi"
+ RAY = "Ray"
class EarlyTerminationPolicyType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
@@ -476,6 +533,11 @@ class ExportFormatType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
COCO = "Coco"
CSV = "CSV"
+class FeatureAttributionMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: The Normalized Discounted Cumulative Gain metric.
+ NORMALIZED_DISCOUNTED_CUMULATIVE_GAIN = "NormalizedDiscountedCumulativeGain"
+
class FeatureDataType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
STRING = "String"
@@ -586,8 +648,8 @@ class ForecastingModels(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
#: It's an inexact but powerful technique.
SGD = "SGD"
#: Random forest is a supervised learning algorithm.
- #: The "forest" it builds, is an ensemble of decision trees, usually trained with the 'bagging'
- #: method.
+ #: The "forest" it builds, is an ensemble of decision trees, usually trained with the
+ #: “bagging†method.
#: The general idea of the bagging method is that a combination of learning models increases the
#: overall result.
RANDOM_FOREST = "RandomForest"
@@ -816,6 +878,20 @@ class LoadBalancerType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
PUBLIC_IP = "PublicIp"
INTERNAL_LOAD_BALANCER = "InternalLoadBalancer"
+class LogTrainingMetrics(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Enable compute and log training metrics.
+ ENABLE = "Enable"
+ #: Disable compute and log training metrics.
+ DISABLE = "Disable"
+
+class LogValidationLoss(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Enable compute and log validation metrics.
+ ENABLE = "Enable"
+ #: Disable compute and log validation metrics.
+ DISABLE = "Disable"
+
class LogVerbosity(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Enum for setting log verbosity.
"""
@@ -891,6 +967,69 @@ class ModelSize(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
#: Extra large size.
EXTRA_LARGE = "ExtraLarge"
+class MonitoringFeatureDataType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Used for features of numerical data type.
+ NUMERICAL = "Numerical"
+ #: Used for features of categorical data type.
+ CATEGORICAL = "Categorical"
+
+class MonitoringFeatureFilterType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Includes all features.
+ ALL_FEATURES = "AllFeatures"
+ #: Only includes the top contributing features, measured by feature attribution.
+ TOP_N_BY_ATTRIBUTION = "TopNByAttribution"
+ #: Includes a user-defined subset of features.
+ FEATURE_SUBSET = "FeatureSubset"
+
+class MonitoringInputDataContext(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: A dataset containing the feature input to the model.
+ MODEL_INPUTS = "ModelInputs"
+ #: A dataset containing the infered results of the model.
+ MODEL_OUTPUTS = "ModelOutputs"
+ #: A dataset containing the data used for training the model.
+ TRAINING = "Training"
+ #: A dataset leveraged to test the model.
+ TEST = "Test"
+ #: A dataset leveraged for model validation.
+ VALIDATION = "Validation"
+ #: A dataset containing the ground truth data.
+ GROUND_TRUTH = "GroundTruth"
+
+class MonitoringModelType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: A model trained for classification tasks.
+ CLASSIFICATION = "Classification"
+ #: A model trained for regressions tasks.
+ REGRESSION = "Regression"
+
+class MonitoringNotificationMode(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Disabled notifications will not produce emails/metrics leveraged for alerting.
+ DISABLED = "Disabled"
+ #: Enabled notification will produce emails/metrics leveraged for alerting.
+ ENABLED = "Enabled"
+
+class MonitoringSignalType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Tracks model input data distribution change, comparing against training data or past production
+ #: data.
+ DATA_DRIFT = "DataDrift"
+ #: Tracks prediction result data distribution change, comparing against validation/test label data
+ #: or past production data.
+ PREDICTION_DRIFT = "PredictionDrift"
+ #: Tracks model input data integrity.
+ DATA_QUALITY = "DataQuality"
+ #: Tracks feature importance change in production, comparing against feature importance at
+ #: training time.
+ FEATURE_ATTRIBUTION_DRIFT = "FeatureAttributionDrift"
+ #: Tracks a custom signal provided by users.
+ CUSTOM = "Custom"
+ #: Tracks model perforance based on ground truth data.
+ MODEL_PERFORMANCE = "ModelPerformance"
+
class MountAction(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Mount Action.
"""
@@ -971,6 +1110,37 @@ class NodesValueType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
ALL = "All"
CUSTOM = "Custom"
+class NumericalDataDriftMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: The Jensen Shannon Distance (JSD) metric.
+ JENSEN_SHANNON_DISTANCE = "JensenShannonDistance"
+ #: The Population Stability Index (PSI) metric.
+ POPULATION_STABILITY_INDEX = "PopulationStabilityIndex"
+ #: The Normalized Wasserstein Distance metric.
+ NORMALIZED_WASSERSTEIN_DISTANCE = "NormalizedWassersteinDistance"
+ #: The Two Sample Kolmogorov-Smirnov Test (two-sample K–S) metric.
+ TWO_SAMPLE_KOLMOGOROV_SMIRNOV_TEST = "TwoSampleKolmogorovSmirnovTest"
+
+class NumericalDataQualityMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: Calculates the rate of null values.
+ NULL_VALUE_RATE = "NullValueRate"
+ #: Calculates the rate of data type errors.
+ DATA_TYPE_ERROR_RATE = "DataTypeErrorRate"
+ #: Calculates the rate values are out of bounds.
+ OUT_OF_BOUNDS_RATE = "OutOfBoundsRate"
+
+class NumericalPredictionDriftMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: The Jensen Shannon Distance (JSD) metric.
+ JENSEN_SHANNON_DISTANCE = "JensenShannonDistance"
+ #: The Population Stability Index (PSI) metric.
+ POPULATION_STABILITY_INDEX = "PopulationStabilityIndex"
+ #: The Normalized Wasserstein Distance metric.
+ NORMALIZED_WASSERSTEIN_DISTANCE = "NormalizedWassersteinDistance"
+ #: The Two Sample Kolmogorov-Smirnov Test (two-sample K–S) metric.
+ TWO_SAMPLE_KOLMOGOROV_SMIRNOV_TEST = "TwoSampleKolmogorovSmirnovTest"
+
class ObjectDetectionPrimaryMetrics(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Primary metrics for Image ObjectDetection task.
"""
@@ -979,6 +1149,12 @@ class ObjectDetectionPrimaryMetrics(with_metaclass(CaseInsensitiveEnumMeta, str,
#: AP is calculated for each class and averaged to get the MAP.
MEAN_AVERAGE_PRECISION = "MeanAveragePrecision"
+class OneLakeArtifactType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+ """Enum to determine OneLake artifact type.
+ """
+
+ LAKEHOUSE = "Lakehouse"
+
class OperatingSystemType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""The type of operating system.
"""
@@ -1063,6 +1239,19 @@ class PackageInputType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
URI_FILE = "UriFile"
URI_FOLDER = "UriFolder"
+class PendingUploadCredentialType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+ """Enum to determine the PendingUpload credentials type.
+ """
+
+ SAS = "SAS"
+
+class PendingUploadType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+ """Type of storage to use for the pending upload location
+ """
+
+ NONE = "None"
+ TEMPORARY_BLOB_REFERENCE = "TemporaryBlobReference"
+
class PrivateEndpointConnectionProvisioningState(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""The current provisioning state.
"""
@@ -1082,6 +1271,15 @@ class PrivateEndpointServiceConnectionStatus(with_metaclass(CaseInsensitiveEnumM
DISCONNECTED = "Disconnected"
TIMEOUT = "Timeout"
+class ProtectionLevel(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+ """Protection level associated with the Intellectual Property.
+ """
+
+ #: All means Intellectual Property is fully protected.
+ ALL = "All"
+ #: None means it is not an Intellectual Property.
+ NONE = "None"
+
class Protocol(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Protocol over which communication will happen over this endpoint
"""
@@ -1162,6 +1360,15 @@ class ReferenceType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
DATA_PATH = "DataPath"
OUTPUT_PATH = "OutputPath"
+class RegressionModelPerformanceMetric(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ #: The Mean Absolute Error (MAE) metric.
+ MEAN_ABSOLUTE_ERROR = "MeanAbsoluteError"
+ #: The Root Mean Squared Error (RMSE) metric.
+ ROOT_MEAN_SQUARED_ERROR = "RootMeanSquaredError"
+ #: The Mean Squared Error (MSE) metric.
+ MEAN_SQUARED_ERROR = "MeanSquaredError"
+
class RegressionModels(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Enum for all Regression models supported by AutoML.
"""
@@ -1192,8 +1399,8 @@ class RegressionModels(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
#: It's an inexact but powerful technique.
SGD = "SGD"
#: Random forest is a supervised learning algorithm.
- #: The "forest" it builds, is an ensemble of decision trees, usually trained with the 'bagging'
- #: method.
+ #: The "forest" it builds, is an ensemble of decision trees, usually trained with the
+ #: “bagging†method.
#: The general idea of the bagging method is that a combination of learning models increases the
#: overall result.
RANDOM_FOREST = "RandomForest"
@@ -1235,6 +1442,14 @@ class RemoteLoginPortPublicAccess(with_metaclass(CaseInsensitiveEnumMeta, str, E
DISABLED = "Disabled"
NOT_SPECIFIED = "NotSpecified"
+class RollingRateType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+
+ YEAR = "Year"
+ MONTH = "Month"
+ DAY = "Day"
+ HOUR = "Hour"
+ MINUTE = "Minute"
+
class SamplingAlgorithmType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
GRID = "Grid"
@@ -1250,6 +1465,8 @@ class ScheduleActionType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
CREATE_JOB = "CreateJob"
INVOKE_BATCH_ENDPOINT = "InvokeBatchEndpoint"
+ IMPORT_DATA = "ImportData"
+ CREATE_MONITOR = "CreateMonitor"
class ScheduleListViewType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
@@ -1608,6 +1825,12 @@ class VolumeDefinitionType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
TMPFS = "tmpfs"
NPIPE = "npipe"
+class WebhookType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
+ """Enum to determine the webhook callback service type.
+ """
+
+ AZURE_DEV_OPS = "AzureDevOps"
+
class WeekDay(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Enum of weekday
"""
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py
index ada60246f098..cbb107504068 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py
@@ -781,6 +781,73 @@ def __init__(
self.load_balancer_subnet = kwargs.get('load_balancer_subnet', None)
+class MonitoringFeatureFilterBase(msrest.serialization.Model):
+ """MonitoringFeatureFilterBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: AllFeatures, FeatureSubset, TopNFeaturesByAttribution.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'filter_type': {'AllFeatures': 'AllFeatures', 'FeatureSubset': 'FeatureSubset', 'TopNByAttribution': 'TopNFeaturesByAttribution'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(MonitoringFeatureFilterBase, self).__init__(**kwargs)
+ self.filter_type = None # type: Optional[str]
+
+
+class AllFeatures(MonitoringFeatureFilterBase):
+ """AllFeatures.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(AllFeatures, self).__init__(**kwargs)
+ self.filter_type = 'AllFeatures' # type: str
+
+
class Nodes(msrest.serialization.Model):
"""Abstract Nodes definition.
@@ -1473,9 +1540,13 @@ class AssetBase(ResourceBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
"""
@@ -1483,6 +1554,7 @@ class AssetBase(ResourceBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
}
@@ -1498,12 +1570,17 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
"""
super(AssetBase, self).__init__(**kwargs)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.is_anonymous = kwargs.get('is_anonymous', False)
self.is_archived = kwargs.get('is_archived', False)
@@ -1574,7 +1651,7 @@ class AssetJobInput(msrest.serialization.Model):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -1605,6 +1682,8 @@ class AssetJobOutput(msrest.serialization.Model):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -1615,6 +1694,7 @@ class AssetJobOutput(msrest.serialization.Model):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
}
@@ -1628,6 +1708,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -1637,6 +1719,7 @@ def __init__(
super(AssetJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
@@ -1712,6 +1795,37 @@ def __init__(
self.tenant_id = kwargs['tenant_id']
+class AutoDeleteSetting(msrest.serialization.Model):
+ """AutoDeleteSetting.
+
+ :ivar condition: When to check if an asset is expired. Possible values include:
+ "CreatedGreaterThan", "LastAccessedGreaterThan".
+ :vartype condition: str or ~azure.mgmt.machinelearningservices.models.AutoDeleteCondition
+ :ivar value: Expiration condition value.
+ :vartype value: str
+ """
+
+ _attribute_map = {
+ 'condition': {'key': 'condition', 'type': 'str'},
+ 'value': {'key': 'value', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword condition: When to check if an asset is expired. Possible values include:
+ "CreatedGreaterThan", "LastAccessedGreaterThan".
+ :paramtype condition: str or ~azure.mgmt.machinelearningservices.models.AutoDeleteCondition
+ :keyword value: Expiration condition value.
+ :paramtype value: str
+ """
+ super(AutoDeleteSetting, self).__init__(**kwargs)
+ self.condition = kwargs.get('condition', None)
+ self.value = kwargs.get('value', None)
+
+
class ForecastHorizon(msrest.serialization.Model):
"""The desired maximum forecast horizon in units of time-series frequency.
@@ -1844,6 +1958,9 @@ class JobBaseProperties(ResourceBase):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -1870,6 +1987,7 @@ class JobBaseProperties(ResourceBase):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
}
@@ -1906,6 +2024,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -1919,6 +2040,7 @@ def __init__(
self.is_archived = kwargs.get('is_archived', False)
self.job_type = 'JobBaseProperties' # type: str
self.notification_setting = kwargs.get('notification_setting', None)
+ self.secrets_configuration = kwargs.get('secrets_configuration', None)
self.services = kwargs.get('services', None)
self.status = None
@@ -1958,6 +2080,9 @@ class AutoMLJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -2000,6 +2125,7 @@ class AutoMLJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'environment_id': {'key': 'environmentId', 'type': 'str'},
@@ -2038,6 +2164,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -2477,7 +2606,7 @@ class DatastoreProperties(ResourceBase):
"""Base definition for datastore contents configuration.
You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: AzureBlobDatastore, AzureDataLakeGen1Datastore, AzureDataLakeGen2Datastore, AzureFileDatastore, HdfsDatastore.
+ sub-classes are: AzureBlobDatastore, AzureDataLakeGen1Datastore, AzureDataLakeGen2Datastore, AzureFileDatastore, HdfsDatastore, OneLakeDatastore.
Variables are only populated by the server, and will be ignored when sending a request.
@@ -2493,8 +2622,10 @@ class DatastoreProperties(ResourceBase):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2512,11 +2643,12 @@ class DatastoreProperties(ResourceBase):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
}
_subtype_map = {
- 'datastore_type': {'AzureBlob': 'AzureBlobDatastore', 'AzureDataLakeGen1': 'AzureDataLakeGen1Datastore', 'AzureDataLakeGen2': 'AzureDataLakeGen2Datastore', 'AzureFile': 'AzureFileDatastore', 'Hdfs': 'HdfsDatastore'}
+ 'datastore_type': {'AzureBlob': 'AzureBlobDatastore', 'AzureDataLakeGen1': 'AzureDataLakeGen1Datastore', 'AzureDataLakeGen2': 'AzureDataLakeGen2Datastore', 'AzureFile': 'AzureFileDatastore', 'Hdfs': 'HdfsDatastore', 'OneLake': 'OneLakeDatastore'}
}
def __init__(
@@ -2532,10 +2664,14 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
"""
super(DatastoreProperties, self).__init__(**kwargs)
self.credentials = kwargs['credentials']
self.datastore_type = 'DatastoreProperties' # type: str
+ self.intellectual_property = kwargs.get('intellectual_property', None)
self.is_default = None
@@ -2560,8 +2696,10 @@ class AzureBlobDatastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2594,6 +2732,7 @@ class AzureBlobDatastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'account_name': {'key': 'accountName', 'type': 'str'},
'container_name': {'key': 'containerName', 'type': 'str'},
@@ -2619,6 +2758,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword account_name: Storage account name.
:paramtype account_name: str
:keyword container_name: Storage account container name.
@@ -2646,6 +2788,7 @@ def __init__(
self.properties = kwargs.get('properties', None)
self.tags = kwargs.get('tags', None)
self.credentials = kwargs['credentials']
+ self.intellectual_property = kwargs.get('intellectual_property', None)
self.is_default = None
@@ -2670,8 +2813,10 @@ class AzureDataLakeGen1Datastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2688,7 +2833,7 @@ class AzureDataLakeGen1Datastore(DatastoreProperties, AzureDatastore):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'store_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'store_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -2699,6 +2844,7 @@ class AzureDataLakeGen1Datastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'service_data_access_auth_identity': {'key': 'serviceDataAccessAuthIdentity', 'type': 'str'},
'store_name': {'key': 'storeName', 'type': 'str'},
@@ -2721,6 +2867,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword service_data_access_auth_identity: Indicates which identity to use to authenticate
service data access to customer's storage. Possible values include: "None",
"WorkspaceSystemAssignedIdentity", "WorkspaceUserAssignedIdentity".
@@ -2739,6 +2888,7 @@ def __init__(
self.properties = kwargs.get('properties', None)
self.tags = kwargs.get('tags', None)
self.credentials = kwargs['credentials']
+ self.intellectual_property = kwargs.get('intellectual_property', None)
self.is_default = None
@@ -2763,8 +2913,10 @@ class AzureDataLakeGen2Datastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2787,8 +2939,8 @@ class AzureDataLakeGen2Datastore(DatastoreProperties, AzureDatastore):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'account_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'filesystem': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'account_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'filesystem': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -2799,6 +2951,7 @@ class AzureDataLakeGen2Datastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'account_name': {'key': 'accountName', 'type': 'str'},
'endpoint': {'key': 'endpoint', 'type': 'str'},
@@ -2824,6 +2977,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword account_name: Required. [Required] Storage account name.
:paramtype account_name: str
:keyword endpoint: Azure cloud endpoint for the storage account.
@@ -2851,9 +3007,84 @@ def __init__(
self.properties = kwargs.get('properties', None)
self.tags = kwargs.get('tags', None)
self.credentials = kwargs['credentials']
+ self.intellectual_property = kwargs.get('intellectual_property', None)
self.is_default = None
+class Webhook(msrest.serialization.Model):
+ """Webhook base.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: AzureDevOpsWebhook.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar event_type: Send callback on a specified notification event.
+ :vartype event_type: str
+ :ivar webhook_type: Required. [Required] Specifies the type of service to send a
+ callback.Constant filled by server. Possible values include: "AzureDevOps".
+ :vartype webhook_type: str or ~azure.mgmt.machinelearningservices.models.WebhookType
+ """
+
+ _validation = {
+ 'webhook_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'event_type': {'key': 'eventType', 'type': 'str'},
+ 'webhook_type': {'key': 'webhookType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'webhook_type': {'AzureDevOps': 'AzureDevOpsWebhook'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword event_type: Send callback on a specified notification event.
+ :paramtype event_type: str
+ """
+ super(Webhook, self).__init__(**kwargs)
+ self.event_type = kwargs.get('event_type', None)
+ self.webhook_type = None # type: Optional[str]
+
+
+class AzureDevOpsWebhook(Webhook):
+ """Webhook details specific for Azure DevOps.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar event_type: Send callback on a specified notification event.
+ :vartype event_type: str
+ :ivar webhook_type: Required. [Required] Specifies the type of service to send a
+ callback.Constant filled by server. Possible values include: "AzureDevOps".
+ :vartype webhook_type: str or ~azure.mgmt.machinelearningservices.models.WebhookType
+ """
+
+ _validation = {
+ 'webhook_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'event_type': {'key': 'eventType', 'type': 'str'},
+ 'webhook_type': {'key': 'webhookType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword event_type: Send callback on a specified notification event.
+ :paramtype event_type: str
+ """
+ super(AzureDevOpsWebhook, self).__init__(**kwargs)
+ self.webhook_type = 'AzureDevOps' # type: str
+
+
class AzureFileDatastore(DatastoreProperties, AzureDatastore):
"""Azure File datastore configuration.
@@ -2875,8 +3106,10 @@ class AzureFileDatastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2900,8 +3133,8 @@ class AzureFileDatastore(DatastoreProperties, AzureDatastore):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'account_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'file_share_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'account_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'file_share_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -2912,6 +3145,7 @@ class AzureFileDatastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'account_name': {'key': 'accountName', 'type': 'str'},
'endpoint': {'key': 'endpoint', 'type': 'str'},
@@ -2937,6 +3171,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword account_name: Required. [Required] Storage account name.
:paramtype account_name: str
:keyword endpoint: Azure cloud endpoint for the storage account.
@@ -2965,6 +3202,7 @@ def __init__(
self.properties = kwargs.get('properties', None)
self.tags = kwargs.get('tags', None)
self.credentials = kwargs['credentials']
+ self.intellectual_property = kwargs.get('intellectual_property', None)
self.is_default = None
@@ -3221,7 +3459,7 @@ class BaseEnvironmentId(BaseEnvironmentSource):
_validation = {
'base_environment_source_type': {'required': True},
- 'resource_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'resource_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -4150,6 +4388,43 @@ def __init__(
self.selinux = kwargs.get('selinux', None)
+class BlobReferenceForConsumptionDto(msrest.serialization.Model):
+ """BlobReferenceForConsumptionDto.
+
+ :ivar blob_uri: Blob URI path for client to upload data.
+ Example: https://blob.windows.core.net/Container/Path.
+ :vartype blob_uri: str
+ :ivar credential: Credential info to access storage account.
+ :vartype credential: ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialDto
+ :ivar storage_account_arm_id: Arm ID of the storage account to use.
+ :vartype storage_account_arm_id: str
+ """
+
+ _attribute_map = {
+ 'blob_uri': {'key': 'blobUri', 'type': 'str'},
+ 'credential': {'key': 'credential', 'type': 'PendingUploadCredentialDto'},
+ 'storage_account_arm_id': {'key': 'storageAccountArmId', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword blob_uri: Blob URI path for client to upload data.
+ Example: https://blob.windows.core.net/Container/Path.
+ :paramtype blob_uri: str
+ :keyword credential: Credential info to access storage account.
+ :paramtype credential: ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialDto
+ :keyword storage_account_arm_id: Arm ID of the storage account to use.
+ :paramtype storage_account_arm_id: str
+ """
+ super(BlobReferenceForConsumptionDto, self).__init__(**kwargs)
+ self.blob_uri = kwargs.get('blob_uri', None)
+ self.credential = kwargs.get('credential', None)
+ self.storage_account_arm_id = kwargs.get('storage_account_arm_id', None)
+
+
class BuildContext(msrest.serialization.Model):
"""Configuration settings for Docker build context.
@@ -4174,7 +4449,7 @@ class BuildContext(msrest.serialization.Model):
"""
_validation = {
- 'context_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'context_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -4209,45 +4484,33 @@ def __init__(
self.dockerfile_path = kwargs.get('dockerfile_path', "Dockerfile")
-class CertificateDatastoreCredentials(DatastoreCredentials):
- """Certificate datastore credentials configuration.
+class DataDriftMetricThresholdBase(msrest.serialization.Model):
+ """DataDriftMetricThresholdBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CategoricalDataDriftMetricThreshold, NumericalDataDriftMetricThreshold.
All required parameters must be populated in order to send to Azure.
- :ivar credentials_type: Required. [Required] Credential type used to authentication with
- storage.Constant filled by server. Possible values include: "AccountKey", "Certificate",
- "None", "Sas", "ServicePrincipal", "KerberosKeytab", "KerberosPassword".
- :vartype credentials_type: str or ~azure.mgmt.machinelearningservices.models.CredentialsType
- :ivar authority_url: Authority URL used for authentication.
- :vartype authority_url: str
- :ivar client_id: Required. [Required] Service principal client ID.
- :vartype client_id: str
- :ivar resource_url: Resource the service principal has access to.
- :vartype resource_url: str
- :ivar secrets: Required. [Required] Service principal secrets.
- :vartype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
- :ivar tenant_id: Required. [Required] ID of the tenant to which the service principal belongs.
- :vartype tenant_id: str
- :ivar thumbprint: Required. [Required] Thumbprint of the certificate used for authentication.
- :vartype thumbprint: str
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
"""
_validation = {
- 'credentials_type': {'required': True},
- 'client_id': {'required': True},
- 'secrets': {'required': True},
- 'tenant_id': {'required': True},
- 'thumbprint': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_type': {'required': True},
}
_attribute_map = {
- 'credentials_type': {'key': 'credentialsType', 'type': 'str'},
- 'authority_url': {'key': 'authorityUrl', 'type': 'str'},
- 'client_id': {'key': 'clientId', 'type': 'str'},
- 'resource_url': {'key': 'resourceUrl', 'type': 'str'},
- 'secrets': {'key': 'secrets', 'type': 'CertificateDatastoreSecrets'},
- 'tenant_id': {'key': 'tenantId', 'type': 'str'},
- 'thumbprint': {'key': 'thumbprint', 'type': 'str'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'Categorical': 'CategoricalDataDriftMetricThreshold', 'Numerical': 'NumericalDataDriftMetricThreshold'}
}
def __init__(
@@ -4255,51 +4518,40 @@ def __init__(
**kwargs
):
"""
- :keyword authority_url: Authority URL used for authentication.
- :paramtype authority_url: str
- :keyword client_id: Required. [Required] Service principal client ID.
- :paramtype client_id: str
- :keyword resource_url: Resource the service principal has access to.
- :paramtype resource_url: str
- :keyword secrets: Required. [Required] Service principal secrets.
- :paramtype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
- :keyword tenant_id: Required. [Required] ID of the tenant to which the service principal
- belongs.
- :paramtype tenant_id: str
- :keyword thumbprint: Required. [Required] Thumbprint of the certificate used for
- authentication.
- :paramtype thumbprint: str
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
"""
- super(CertificateDatastoreCredentials, self).__init__(**kwargs)
- self.credentials_type = 'Certificate' # type: str
- self.authority_url = kwargs.get('authority_url', None)
- self.client_id = kwargs['client_id']
- self.resource_url = kwargs.get('resource_url', None)
- self.secrets = kwargs['secrets']
- self.tenant_id = kwargs['tenant_id']
- self.thumbprint = kwargs['thumbprint']
+ super(DataDriftMetricThresholdBase, self).__init__(**kwargs)
+ self.data_type = None # type: Optional[str]
+ self.threshold = kwargs.get('threshold', None)
-class CertificateDatastoreSecrets(DatastoreSecrets):
- """Datastore certificate secrets.
+class CategoricalDataDriftMetricThreshold(DataDriftMetricThresholdBase):
+ """CategoricalDataDriftMetricThreshold.
All required parameters must be populated in order to send to Azure.
- :ivar secrets_type: Required. [Required] Credential type used to authentication with
- storage.Constant filled by server. Possible values include: "AccountKey", "Certificate", "Sas",
- "ServicePrincipal", "KerberosPassword", "KerberosKeytab".
- :vartype secrets_type: str or ~azure.mgmt.machinelearningservices.models.SecretsType
- :ivar certificate: Service principal certificate.
- :vartype certificate: str
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The categorical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex", "PearsonsChiSquaredTest".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.CategoricalDataDriftMetric
"""
_validation = {
- 'secrets_type': {'required': True},
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
}
_attribute_map = {
- 'secrets_type': {'key': 'secretsType', 'type': 'str'},
- 'certificate': {'key': 'certificate', 'type': 'str'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
}
def __init__(
@@ -4307,71 +4559,360 @@ def __init__(
**kwargs
):
"""
- :keyword certificate: Service principal certificate.
- :paramtype certificate: str
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The categorical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex", "PearsonsChiSquaredTest".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.CategoricalDataDriftMetric
"""
- super(CertificateDatastoreSecrets, self).__init__(**kwargs)
- self.secrets_type = 'Certificate' # type: str
- self.certificate = kwargs.get('certificate', None)
+ super(CategoricalDataDriftMetricThreshold, self).__init__(**kwargs)
+ self.data_type = 'Categorical' # type: str
+ self.metric = kwargs['metric']
-class TableVertical(msrest.serialization.Model):
- """Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.
+class DataQualityMetricThresholdBase(msrest.serialization.Model):
+ """DataQualityMetricThresholdBase.
- :ivar cv_split_column_names: Columns to use for CVSplit data.
- :vartype cv_split_column_names: list[str]
- :ivar featurization_settings: Featurization inputs needed for AutoML job.
- :vartype featurization_settings:
- ~azure.mgmt.machinelearningservices.models.TableVerticalFeaturizationSettings
- :ivar fixed_parameters: Model/training parameters that will remain constant throughout
- training.
- :vartype fixed_parameters: ~azure.mgmt.machinelearningservices.models.TableFixedParameters
- :ivar limit_settings: Execution constraints for AutoMLJob.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.TableVerticalLimitSettings
- :ivar n_cross_validations: Number of cross validation folds to be applied on training dataset
- when validation dataset is not provided.
- :vartype n_cross_validations: ~azure.mgmt.machinelearningservices.models.NCrossValidations
- :ivar search_space: Search space for sampling different combinations of models and their
- hyperparameters.
- :vartype search_space: list[~azure.mgmt.machinelearningservices.models.TableParameterSubspace]
- :ivar sweep_settings: Settings for model sweeping and hyperparameter tuning.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.TableSweepSettings
- :ivar test_data: Test data input.
- :vartype test_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar test_data_size: The fraction of test dataset that needs to be set aside for validation
- purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype test_data_size: float
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
- :ivar weight_column_name: The name of the sample weight column. Automated ML supports a
- weighted column as an input, causing rows in the data to be weighted up or down.
- :vartype weight_column_name: str
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CategoricalDataQualityMetricThreshold, NumericalDataQualityMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
"""
+ _validation = {
+ 'data_type': {'required': True},
+ }
+
_attribute_map = {
- 'cv_split_column_names': {'key': 'cvSplitColumnNames', 'type': '[str]'},
- 'featurization_settings': {'key': 'featurizationSettings', 'type': 'TableVerticalFeaturizationSettings'},
- 'fixed_parameters': {'key': 'fixedParameters', 'type': 'TableFixedParameters'},
- 'limit_settings': {'key': 'limitSettings', 'type': 'TableVerticalLimitSettings'},
- 'n_cross_validations': {'key': 'nCrossValidations', 'type': 'NCrossValidations'},
- 'search_space': {'key': 'searchSpace', 'type': '[TableParameterSubspace]'},
- 'sweep_settings': {'key': 'sweepSettings', 'type': 'TableSweepSettings'},
- 'test_data': {'key': 'testData', 'type': 'MLTableJobInput'},
- 'test_data_size': {'key': 'testDataSize', 'type': 'float'},
- 'validation_data': {'key': 'validationData', 'type': 'MLTableJobInput'},
- 'validation_data_size': {'key': 'validationDataSize', 'type': 'float'},
- 'weight_column_name': {'key': 'weightColumnName', 'type': 'str'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
}
- def __init__(
- self,
+ _subtype_map = {
+ 'data_type': {'Categorical': 'CategoricalDataQualityMetricThreshold', 'Numerical': 'NumericalDataQualityMetricThreshold'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(DataQualityMetricThresholdBase, self).__init__(**kwargs)
+ self.data_type = None # type: Optional[str]
+ self.threshold = kwargs.get('threshold', None)
+
+
+class CategoricalDataQualityMetricThreshold(DataQualityMetricThresholdBase):
+ """CategoricalDataQualityMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The categorical data quality metric to calculate. Possible
+ values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.CategoricalDataQualityMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The categorical data quality metric to calculate.
+ Possible values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.CategoricalDataQualityMetric
+ """
+ super(CategoricalDataQualityMetricThreshold, self).__init__(**kwargs)
+ self.data_type = 'Categorical' # type: str
+ self.metric = kwargs['metric']
+
+
+class PredictionDriftMetricThresholdBase(msrest.serialization.Model):
+ """PredictionDriftMetricThresholdBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CategoricalPredictionDriftMetricThreshold, NumericalPredictionDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'Categorical': 'CategoricalPredictionDriftMetricThreshold', 'Numerical': 'NumericalPredictionDriftMetricThreshold'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(PredictionDriftMetricThresholdBase, self).__init__(**kwargs)
+ self.data_type = None # type: Optional[str]
+ self.threshold = kwargs.get('threshold', None)
+
+
+class CategoricalPredictionDriftMetricThreshold(PredictionDriftMetricThresholdBase):
+ """CategoricalPredictionDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The categorical prediction drift metric to calculate.
+ Possible values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "PearsonsChiSquaredTest".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.CategoricalPredictionDriftMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The categorical prediction drift metric to calculate.
+ Possible values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "PearsonsChiSquaredTest".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.CategoricalPredictionDriftMetric
+ """
+ super(CategoricalPredictionDriftMetricThreshold, self).__init__(**kwargs)
+ self.data_type = 'Categorical' # type: str
+ self.metric = kwargs['metric']
+
+
+class CertificateDatastoreCredentials(DatastoreCredentials):
+ """Certificate datastore credentials configuration.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credentials_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "AccountKey", "Certificate",
+ "None", "Sas", "ServicePrincipal", "KerberosKeytab", "KerberosPassword".
+ :vartype credentials_type: str or ~azure.mgmt.machinelearningservices.models.CredentialsType
+ :ivar authority_url: Authority URL used for authentication.
+ :vartype authority_url: str
+ :ivar client_id: Required. [Required] Service principal client ID.
+ :vartype client_id: str
+ :ivar resource_url: Resource the service principal has access to.
+ :vartype resource_url: str
+ :ivar secrets: Required. [Required] Service principal secrets.
+ :vartype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
+ :ivar tenant_id: Required. [Required] ID of the tenant to which the service principal belongs.
+ :vartype tenant_id: str
+ :ivar thumbprint: Required. [Required] Thumbprint of the certificate used for authentication.
+ :vartype thumbprint: str
+ """
+
+ _validation = {
+ 'credentials_type': {'required': True},
+ 'client_id': {'required': True},
+ 'secrets': {'required': True},
+ 'tenant_id': {'required': True},
+ 'thumbprint': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'credentials_type': {'key': 'credentialsType', 'type': 'str'},
+ 'authority_url': {'key': 'authorityUrl', 'type': 'str'},
+ 'client_id': {'key': 'clientId', 'type': 'str'},
+ 'resource_url': {'key': 'resourceUrl', 'type': 'str'},
+ 'secrets': {'key': 'secrets', 'type': 'CertificateDatastoreSecrets'},
+ 'tenant_id': {'key': 'tenantId', 'type': 'str'},
+ 'thumbprint': {'key': 'thumbprint', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword authority_url: Authority URL used for authentication.
+ :paramtype authority_url: str
+ :keyword client_id: Required. [Required] Service principal client ID.
+ :paramtype client_id: str
+ :keyword resource_url: Resource the service principal has access to.
+ :paramtype resource_url: str
+ :keyword secrets: Required. [Required] Service principal secrets.
+ :paramtype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
+ :keyword tenant_id: Required. [Required] ID of the tenant to which the service principal
+ belongs.
+ :paramtype tenant_id: str
+ :keyword thumbprint: Required. [Required] Thumbprint of the certificate used for
+ authentication.
+ :paramtype thumbprint: str
+ """
+ super(CertificateDatastoreCredentials, self).__init__(**kwargs)
+ self.credentials_type = 'Certificate' # type: str
+ self.authority_url = kwargs.get('authority_url', None)
+ self.client_id = kwargs['client_id']
+ self.resource_url = kwargs.get('resource_url', None)
+ self.secrets = kwargs['secrets']
+ self.tenant_id = kwargs['tenant_id']
+ self.thumbprint = kwargs['thumbprint']
+
+
+class CertificateDatastoreSecrets(DatastoreSecrets):
+ """Datastore certificate secrets.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar secrets_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "AccountKey", "Certificate", "Sas",
+ "ServicePrincipal", "KerberosPassword", "KerberosKeytab".
+ :vartype secrets_type: str or ~azure.mgmt.machinelearningservices.models.SecretsType
+ :ivar certificate: Service principal certificate.
+ :vartype certificate: str
+ """
+
+ _validation = {
+ 'secrets_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'secrets_type': {'key': 'secretsType', 'type': 'str'},
+ 'certificate': {'key': 'certificate', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword certificate: Service principal certificate.
+ :paramtype certificate: str
+ """
+ super(CertificateDatastoreSecrets, self).__init__(**kwargs)
+ self.secrets_type = 'Certificate' # type: str
+ self.certificate = kwargs.get('certificate', None)
+
+
+class TableVertical(msrest.serialization.Model):
+ """Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.
+
+ :ivar cv_split_column_names: Columns to use for CVSplit data.
+ :vartype cv_split_column_names: list[str]
+ :ivar featurization_settings: Featurization inputs needed for AutoML job.
+ :vartype featurization_settings:
+ ~azure.mgmt.machinelearningservices.models.TableVerticalFeaturizationSettings
+ :ivar fixed_parameters: Model/training parameters that will remain constant throughout
+ training.
+ :vartype fixed_parameters: ~azure.mgmt.machinelearningservices.models.TableFixedParameters
+ :ivar limit_settings: Execution constraints for AutoMLJob.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.TableVerticalLimitSettings
+ :ivar n_cross_validations: Number of cross validation folds to be applied on training dataset
+ when validation dataset is not provided.
+ :vartype n_cross_validations: ~azure.mgmt.machinelearningservices.models.NCrossValidations
+ :ivar search_space: Search space for sampling different combinations of models and their
+ hyperparameters.
+ :vartype search_space: list[~azure.mgmt.machinelearningservices.models.TableParameterSubspace]
+ :ivar sweep_settings: Settings for model sweeping and hyperparameter tuning.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.TableSweepSettings
+ :ivar test_data: Test data input.
+ :vartype test_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar test_data_size: The fraction of test dataset that needs to be set aside for validation
+ purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype test_data_size: float
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
+ :ivar weight_column_name: The name of the sample weight column. Automated ML supports a
+ weighted column as an input, causing rows in the data to be weighted up or down.
+ :vartype weight_column_name: str
+ """
+
+ _attribute_map = {
+ 'cv_split_column_names': {'key': 'cvSplitColumnNames', 'type': '[str]'},
+ 'featurization_settings': {'key': 'featurizationSettings', 'type': 'TableVerticalFeaturizationSettings'},
+ 'fixed_parameters': {'key': 'fixedParameters', 'type': 'TableFixedParameters'},
+ 'limit_settings': {'key': 'limitSettings', 'type': 'TableVerticalLimitSettings'},
+ 'n_cross_validations': {'key': 'nCrossValidations', 'type': 'NCrossValidations'},
+ 'search_space': {'key': 'searchSpace', 'type': '[TableParameterSubspace]'},
+ 'sweep_settings': {'key': 'sweepSettings', 'type': 'TableSweepSettings'},
+ 'test_data': {'key': 'testData', 'type': 'MLTableJobInput'},
+ 'test_data_size': {'key': 'testDataSize', 'type': 'float'},
+ 'validation_data': {'key': 'validationData', 'type': 'MLTableJobInput'},
+ 'validation_data_size': {'key': 'validationDataSize', 'type': 'float'},
+ 'weight_column_name': {'key': 'weightColumnName', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
**kwargs
):
"""
@@ -4603,6 +5144,95 @@ def __init__(
self.training_data = kwargs['training_data']
+class ModelPerformanceMetricThresholdBase(msrest.serialization.Model):
+ """ModelPerformanceMetricThresholdBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: ClassificationModelPerformanceMetricThreshold, RegressionModelPerformanceMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar model_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'model_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'model_type': {'Classification': 'ClassificationModelPerformanceMetricThreshold', 'Regression': 'RegressionModelPerformanceMetricThreshold'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(ModelPerformanceMetricThresholdBase, self).__init__(**kwargs)
+ self.model_type = None # type: Optional[str]
+ self.threshold = kwargs.get('threshold', None)
+
+
+class ClassificationModelPerformanceMetricThreshold(ModelPerformanceMetricThresholdBase):
+ """ClassificationModelPerformanceMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar model_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The classification model performance to calculate. Possible
+ values include: "Accuracy", "Precision", "Recall", "F1Score".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationModelPerformanceMetric
+ """
+
+ _validation = {
+ 'model_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The classification model performance to calculate.
+ Possible values include: "Accuracy", "Precision", "Recall", "F1Score".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationModelPerformanceMetric
+ """
+ super(ClassificationModelPerformanceMetricThreshold, self).__init__(**kwargs)
+ self.model_type = 'Classification' # type: str
+ self.metric = kwargs['metric']
+
+
class TrainingSettings(msrest.serialization.Model):
"""Training related configuration.
@@ -5147,9 +5777,13 @@ class CodeVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar code_uri: Uri where code is located.
:vartype code_uri: str
@@ -5167,6 +5801,7 @@ class CodeVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'code_uri': {'key': 'codeUri', 'type': 'str'},
@@ -5184,9 +5819,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword code_uri: Uri where code is located.
:paramtype code_uri: str
@@ -5227,6 +5866,57 @@ def __init__(
self.value = kwargs.get('value', None)
+class Collection(msrest.serialization.Model):
+ """Collection.
+
+ :ivar client_id: The msi client id used to collect logging to blob storage. If it's
+ null,backend will pick a registered endpoint identity to auth.
+ :vartype client_id: str
+ :ivar data_collection_mode: Enable or disable data collection. Possible values include:
+ "Enabled", "Disabled".
+ :vartype data_collection_mode: str or
+ ~azure.mgmt.machinelearningservices.models.DataCollectionMode
+ :ivar data_id: The data asset arm resource id. Client side will ensure data asset is pointing
+ to the blob storage, and backend will collect data to the blob storage.
+ :vartype data_id: str
+ :ivar sampling_rate: The sampling rate for collection. Sampling rate 1.0 means we collect 100%
+ of data by default.
+ :vartype sampling_rate: float
+ """
+
+ _attribute_map = {
+ 'client_id': {'key': 'clientId', 'type': 'str'},
+ 'data_collection_mode': {'key': 'dataCollectionMode', 'type': 'str'},
+ 'data_id': {'key': 'dataId', 'type': 'str'},
+ 'sampling_rate': {'key': 'samplingRate', 'type': 'float'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword client_id: The msi client id used to collect logging to blob storage. If it's
+ null,backend will pick a registered endpoint identity to auth.
+ :paramtype client_id: str
+ :keyword data_collection_mode: Enable or disable data collection. Possible values include:
+ "Enabled", "Disabled".
+ :paramtype data_collection_mode: str or
+ ~azure.mgmt.machinelearningservices.models.DataCollectionMode
+ :keyword data_id: The data asset arm resource id. Client side will ensure data asset is
+ pointing to the blob storage, and backend will collect data to the blob storage.
+ :paramtype data_id: str
+ :keyword sampling_rate: The sampling rate for collection. Sampling rate 1.0 means we collect
+ 100% of data by default.
+ :paramtype sampling_rate: float
+ """
+ super(Collection, self).__init__(**kwargs)
+ self.client_id = kwargs.get('client_id', None)
+ self.data_collection_mode = kwargs.get('data_collection_mode', None)
+ self.data_id = kwargs.get('data_id', None)
+ self.sampling_rate = kwargs.get('sampling_rate', 1)
+
+
class ColumnTransformer(msrest.serialization.Model):
"""Column transformer parameters.
@@ -5291,6 +5981,9 @@ class CommandJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -5307,7 +6000,7 @@ class CommandJob(JobBaseProperties):
train.py".
:vartype command: str
:ivar distribution: Distribution configuration of the job. If set, this should be one of Mpi,
- Tensorflow, PyTorch, or null.
+ Tensorflow, PyTorch, Ray, or null.
:vartype distribution: ~azure.mgmt.machinelearningservices.models.DistributionConfiguration
:ivar environment_id: Required. [Required] The ARM resource ID of the Environment specification
for the job.
@@ -5332,7 +6025,7 @@ class CommandJob(JobBaseProperties):
'job_type': {'required': True},
'status': {'readonly': True},
'command': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
- 'environment_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'environment_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'parameters': {'readonly': True},
}
@@ -5348,6 +6041,7 @@ class CommandJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'autologger_settings': {'key': 'autologgerSettings', 'type': 'AutologgerSettings'},
@@ -5392,6 +6086,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -5404,7 +6101,7 @@ def __init__(
"python train.py".
:paramtype command: str
:keyword distribution: Distribution configuration of the job. If set, this should be one of
- Mpi, Tensorflow, PyTorch, or null.
+ Mpi, Tensorflow, PyTorch, Ray, or null.
:paramtype distribution: ~azure.mgmt.machinelearningservices.models.DistributionConfiguration
:keyword environment_id: Required. [Required] The ARM resource ID of the Environment
specification for the job.
@@ -5720,9 +6417,13 @@ class ComponentVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar component_spec: Defines Component definition details.
@@ -5737,6 +6438,8 @@ class ComponentVersionProperties(AssetBase):
include: "Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the component lifecycle.
+ :vartype stage: str
"""
_validation = {
@@ -5747,10 +6450,12 @@ class ComponentVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'component_spec': {'key': 'componentSpec', 'type': 'object'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -5764,9 +6469,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword component_spec: Defines Component definition details.
@@ -5777,10 +6486,13 @@ def __init__(
href="https://docs.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-command"
/>.
:paramtype component_spec: any
+ :keyword stage: Stage in the component lifecycle.
+ :paramtype stage: str
"""
super(ComponentVersionProperties, self).__init__(**kwargs)
self.component_spec = kwargs.get('component_spec', None)
self.provisioning_state = None
+ self.stage = kwargs.get('stage', None)
class ComponentVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -6873,7 +7585,78 @@ class CosmosDbSettings(msrest.serialization.Model):
"""
_attribute_map = {
- 'collections_throughput': {'key': 'collectionsThroughput', 'type': 'int'},
+ 'collections_throughput': {'key': 'collectionsThroughput', 'type': 'int'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword collections_throughput: The throughput of the collections in cosmosdb database.
+ :paramtype collections_throughput: int
+ """
+ super(CosmosDbSettings, self).__init__(**kwargs)
+ self.collections_throughput = kwargs.get('collections_throughput', None)
+
+
+class ScheduleActionBase(msrest.serialization.Model):
+ """ScheduleActionBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: JobScheduleAction, CreateMonitorAction, ImportDataAction, EndpointScheduleAction.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
+ :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
+ """
+
+ _validation = {
+ 'action_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'action_type': {'key': 'actionType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'action_type': {'CreateJob': 'JobScheduleAction', 'CreateMonitor': 'CreateMonitorAction', 'ImportData': 'ImportDataAction', 'InvokeBatchEndpoint': 'EndpointScheduleAction'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(ScheduleActionBase, self).__init__(**kwargs)
+ self.action_type = None # type: Optional[str]
+
+
+class CreateMonitorAction(ScheduleActionBase):
+ """CreateMonitorAction.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
+ :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
+ :ivar monitor_definition: Required. [Required] Defines the monitor.
+ :vartype monitor_definition: ~azure.mgmt.machinelearningservices.models.MonitorDefinition
+ """
+
+ _validation = {
+ 'action_type': {'required': True},
+ 'monitor_definition': {'required': True},
+ }
+
+ _attribute_map = {
+ 'action_type': {'key': 'actionType', 'type': 'str'},
+ 'monitor_definition': {'key': 'monitorDefinition', 'type': 'MonitorDefinition'},
}
def __init__(
@@ -6881,11 +7664,12 @@ def __init__(
**kwargs
):
"""
- :keyword collections_throughput: The throughput of the collections in cosmosdb database.
- :paramtype collections_throughput: int
+ :keyword monitor_definition: Required. [Required] Defines the monitor.
+ :paramtype monitor_definition: ~azure.mgmt.machinelearningservices.models.MonitorDefinition
"""
- super(CosmosDbSettings, self).__init__(**kwargs)
- self.collections_throughput = kwargs.get('collections_throughput', None)
+ super(CreateMonitorAction, self).__init__(**kwargs)
+ self.action_type = 'CreateMonitor' # type: str
+ self.monitor_definition = kwargs['monitor_definition']
class TriggerBase(msrest.serialization.Model):
@@ -6980,7 +7764,7 @@ class CronTrigger(TriggerBase):
_validation = {
'trigger_type': {'required': True},
- 'expression': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'expression': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -7144,6 +7928,43 @@ def __init__(
self.inference_configuration = kwargs.get('inference_configuration', None)
+class CustomMetricThreshold(msrest.serialization.Model):
+ """CustomMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar metric: Required. [Required] The user-defined metric to calculate.
+ :vartype metric: str
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'metric': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'metric': {'key': 'metric', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword metric: Required. [Required] The user-defined metric to calculate.
+ :paramtype metric: str
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(CustomMetricThreshold, self).__init__(**kwargs)
+ self.metric = kwargs['metric']
+ self.threshold = kwargs.get('threshold', None)
+
+
class JobInput(msrest.serialization.Model):
"""Command job definition.
@@ -7205,7 +8026,7 @@ class CustomModelJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -7287,6 +8108,8 @@ class CustomModelJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -7307,6 +8130,7 @@ class CustomModelJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -7322,6 +8146,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -7333,12 +8159,138 @@ def __init__(
super(CustomModelJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
self.job_output_type = 'custom_model' # type: str
self.description = kwargs.get('description', None)
+class MonitoringSignalBase(msrest.serialization.Model):
+ """MonitoringSignalBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CustomMonitoringSignal, DataDriftMonitoringSignal, DataQualityMonitoringSignal, FeatureAttributionDriftMonitoringSignal, ModelPerformanceSignalBase, PredictionDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'signal_type': {'Custom': 'CustomMonitoringSignal', 'DataDrift': 'DataDriftMonitoringSignal', 'DataQuality': 'DataQualityMonitoringSignal', 'FeatureAttributionDrift': 'FeatureAttributionDriftMonitoringSignal', 'ModelPerformanceSignalBase': 'ModelPerformanceSignalBase', 'PredictionDrift': 'PredictionDriftMonitoringSignal'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ """
+ super(MonitoringSignalBase, self).__init__(**kwargs)
+ self.lookback_period = kwargs.get('lookback_period', None)
+ self.mode = kwargs.get('mode', None)
+ self.signal_type = None # type: Optional[str]
+
+
+class CustomMonitoringSignal(MonitoringSignalBase):
+ """CustomMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar component_id: Required. [Required] ARM resource ID of the component resource used to
+ calculate the custom metrics.
+ :vartype component_id: str
+ :ivar input_assets: Monitoring assets to take as input. Key is the component input port name,
+ value is the data asset.
+ :vartype input_assets: dict[str,
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputData]
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.CustomMetricThreshold]
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'component_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'metric_thresholds': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'component_id': {'key': 'componentId', 'type': 'str'},
+ 'input_assets': {'key': 'inputAssets', 'type': '{MonitoringInputData}'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[CustomMetricThreshold]'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword component_id: Required. [Required] ARM resource ID of the component resource used to
+ calculate the custom metrics.
+ :paramtype component_id: str
+ :keyword input_assets: Monitoring assets to take as input. Key is the component input port
+ name, value is the data asset.
+ :paramtype input_assets: dict[str,
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputData]
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.CustomMetricThreshold]
+ """
+ super(CustomMonitoringSignal, self).__init__(**kwargs)
+ self.signal_type = 'Custom' # type: str
+ self.component_id = kwargs['component_id']
+ self.input_assets = kwargs.get('input_assets', None)
+ self.metric_thresholds = kwargs['metric_thresholds']
+
+
class CustomNCrossValidations(NCrossValidations):
"""N-Cross validations are specified by user.
@@ -7542,6 +8494,104 @@ def __init__(
self.value = kwargs['value']
+class DataImportSource(msrest.serialization.Model):
+ """DataImportSource.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: DatabaseSource, FileSystemSource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar connection: Workspace connection for data import source storage.
+ :vartype connection: str
+ :ivar source_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "database", "file_system".
+ :vartype source_type: str or ~azure.mgmt.machinelearningservices.models.DataImportSourceType
+ """
+
+ _validation = {
+ 'source_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'connection': {'key': 'connection', 'type': 'str'},
+ 'source_type': {'key': 'sourceType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'source_type': {'database': 'DatabaseSource', 'file_system': 'FileSystemSource'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword connection: Workspace connection for data import source storage.
+ :paramtype connection: str
+ """
+ super(DataImportSource, self).__init__(**kwargs)
+ self.connection = kwargs.get('connection', None)
+ self.source_type = None # type: Optional[str]
+
+
+class DatabaseSource(DataImportSource):
+ """DatabaseSource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar connection: Workspace connection for data import source storage.
+ :vartype connection: str
+ :ivar source_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "database", "file_system".
+ :vartype source_type: str or ~azure.mgmt.machinelearningservices.models.DataImportSourceType
+ :ivar query: SQL Query statement for data import Database source.
+ :vartype query: str
+ :ivar stored_procedure: SQL StoredProcedure on data import Database source.
+ :vartype stored_procedure: str
+ :ivar stored_procedure_params: SQL StoredProcedure parameters.
+ :vartype stored_procedure_params: list[dict[str, str]]
+ :ivar table_name: Name of the table on data import Database source.
+ :vartype table_name: str
+ """
+
+ _validation = {
+ 'source_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'connection': {'key': 'connection', 'type': 'str'},
+ 'source_type': {'key': 'sourceType', 'type': 'str'},
+ 'query': {'key': 'query', 'type': 'str'},
+ 'stored_procedure': {'key': 'storedProcedure', 'type': 'str'},
+ 'stored_procedure_params': {'key': 'storedProcedureParams', 'type': '[{str}]'},
+ 'table_name': {'key': 'tableName', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword connection: Workspace connection for data import source storage.
+ :paramtype connection: str
+ :keyword query: SQL Query statement for data import Database source.
+ :paramtype query: str
+ :keyword stored_procedure: SQL StoredProcedure on data import Database source.
+ :paramtype stored_procedure: str
+ :keyword stored_procedure_params: SQL StoredProcedure parameters.
+ :paramtype stored_procedure_params: list[dict[str, str]]
+ :keyword table_name: Name of the table on data import Database source.
+ :paramtype table_name: str
+ """
+ super(DatabaseSource, self).__init__(**kwargs)
+ self.source_type = 'database' # type: str
+ self.query = kwargs.get('query', None)
+ self.stored_procedure = kwargs.get('stored_procedure', None)
+ self.stored_procedure_params = kwargs.get('stored_procedure_params', None)
+ self.table_name = kwargs.get('table_name', None)
+
+
class DatabricksSchema(msrest.serialization.Model):
"""DatabricksSchema.
@@ -7744,6 +8794,67 @@ def __init__(
self.workspace_url = kwargs.get('workspace_url', None)
+class DataCollector(msrest.serialization.Model):
+ """DataCollector.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar collections: Required. [Required] The collection configuration. Each collection has it
+ own configuration to collect model data and the name of collection can be arbitrary string.
+ Model data collector can be used for either payload logging or custom logging or both of them.
+ Collection request and response are reserved for payload logging, others are for custom
+ logging.
+ :vartype collections: dict[str, ~azure.mgmt.machinelearningservices.models.Collection]
+ :ivar request_logging: The request logging configuration for mdc, it includes advanced logging
+ settings for all collections. It's optional.
+ :vartype request_logging: ~azure.mgmt.machinelearningservices.models.RequestLogging
+ :ivar rolling_rate: When model data is collected to blob storage, we need to roll the data to
+ different path to avoid logging all of them in a single blob file.
+ If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/.
+ If it's day, all data will be collected in blob path /yyyy/MM/dd/.
+ The other benefit of rolling path is that model monitoring ui is able to select a time range
+ of data very quickly. Possible values include: "Year", "Month", "Day", "Hour", "Minute".
+ :vartype rolling_rate: str or ~azure.mgmt.machinelearningservices.models.RollingRateType
+ """
+
+ _validation = {
+ 'collections': {'required': True},
+ }
+
+ _attribute_map = {
+ 'collections': {'key': 'collections', 'type': '{Collection}'},
+ 'request_logging': {'key': 'requestLogging', 'type': 'RequestLogging'},
+ 'rolling_rate': {'key': 'rollingRate', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword collections: Required. [Required] The collection configuration. Each collection has it
+ own configuration to collect model data and the name of collection can be arbitrary string.
+ Model data collector can be used for either payload logging or custom logging or both of them.
+ Collection request and response are reserved for payload logging, others are for custom
+ logging.
+ :paramtype collections: dict[str, ~azure.mgmt.machinelearningservices.models.Collection]
+ :keyword request_logging: The request logging configuration for mdc, it includes advanced
+ logging settings for all collections. It's optional.
+ :paramtype request_logging: ~azure.mgmt.machinelearningservices.models.RequestLogging
+ :keyword rolling_rate: When model data is collected to blob storage, we need to roll the data
+ to different path to avoid logging all of them in a single blob file.
+ If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/.
+ If it's day, all data will be collected in blob path /yyyy/MM/dd/.
+ The other benefit of rolling path is that model monitoring ui is able to select a time range
+ of data very quickly. Possible values include: "Year", "Month", "Day", "Hour", "Minute".
+ :paramtype rolling_rate: str or ~azure.mgmt.machinelearningservices.models.RollingRateType
+ """
+ super(DataCollector, self).__init__(**kwargs)
+ self.collections = kwargs['collections']
+ self.request_logging = kwargs.get('request_logging', None)
+ self.rolling_rate = kwargs.get('rolling_rate', None)
+
+
class DataContainer(Resource):
"""Azure Resource Manager resource envelope.
@@ -7886,6 +8997,86 @@ def __init__(
self.value = kwargs.get('value', None)
+class DataDriftMonitoringSignal(MonitoringSignalBase):
+ """DataDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar data_segment: The data segment used for scoping on a subset of the data population.
+ :vartype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :ivar features: The feature filter which identifies which feature to calculate drift over.
+ :vartype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataDriftMetricThresholdBase]
+ :ivar target_data: Required. [Required] The data which drift will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_thresholds': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'data_segment': {'key': 'dataSegment', 'type': 'MonitoringDataSegment'},
+ 'features': {'key': 'features', 'type': 'MonitoringFeatureFilterBase'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[DataDriftMetricThresholdBase]'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword data_segment: The data segment used for scoping on a subset of the data population.
+ :paramtype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :keyword features: The feature filter which identifies which feature to calculate drift over.
+ :paramtype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataDriftMetricThresholdBase]
+ :keyword target_data: Required. [Required] The data which drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(DataDriftMonitoringSignal, self).__init__(**kwargs)
+ self.signal_type = 'DataDrift' # type: str
+ self.baseline_data = kwargs['baseline_data']
+ self.data_segment = kwargs.get('data_segment', None)
+ self.features = kwargs.get('features', None)
+ self.metric_thresholds = kwargs['metric_thresholds']
+ self.target_data = kwargs['target_data']
+
+
class DataFactory(Compute):
"""A DataFactory compute.
@@ -7923,25 +9114,193 @@ class DataFactory(Compute):
"""
_validation = {
- 'compute_type': {'required': True},
- 'provisioning_state': {'readonly': True},
- 'created_on': {'readonly': True},
- 'modified_on': {'readonly': True},
- 'provisioning_errors': {'readonly': True},
- 'is_attached_compute': {'readonly': True},
+ 'compute_type': {'required': True},
+ 'provisioning_state': {'readonly': True},
+ 'created_on': {'readonly': True},
+ 'modified_on': {'readonly': True},
+ 'provisioning_errors': {'readonly': True},
+ 'is_attached_compute': {'readonly': True},
+ }
+
+ _attribute_map = {
+ 'compute_type': {'key': 'computeType', 'type': 'str'},
+ 'compute_location': {'key': 'computeLocation', 'type': 'str'},
+ 'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'description': {'key': 'description', 'type': 'str'},
+ 'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
+ 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'},
+ 'resource_id': {'key': 'resourceId', 'type': 'str'},
+ 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[ErrorResponse]'},
+ 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'},
+ 'disable_local_auth': {'key': 'disableLocalAuth', 'type': 'bool'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword compute_location: Location for the underlying compute.
+ :paramtype compute_location: str
+ :keyword description: The description of the Machine Learning compute.
+ :paramtype description: str
+ :keyword resource_id: ARM resource id of the underlying compute.
+ :paramtype resource_id: str
+ :keyword disable_local_auth: Opt-out of local authentication and ensure customers can use only
+ MSI and AAD exclusively for authentication.
+ :paramtype disable_local_auth: bool
+ """
+ super(DataFactory, self).__init__(**kwargs)
+ self.compute_type = 'DataFactory' # type: str
+
+
+class DataVersionBaseProperties(AssetBase):
+ """Data version base definition.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: MLTableData, UriFileDataVersion, UriFolderDataVersion.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :vartype is_anonymous: bool
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :vartype is_archived: bool
+ :ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "uri_file", "uri_folder", "mltable".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
+ :ivar data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'description': {'key': 'description', 'type': 'str'},
+ 'properties': {'key': 'properties', 'type': '{str}'},
+ 'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
+ 'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
+ 'is_archived': {'key': 'isArchived', 'type': 'bool'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'mltable': 'MLTableData', 'uri_file': 'UriFileDataVersion', 'uri_folder': 'UriFolderDataVersion'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword description: The asset description text.
+ :paramtype description: str
+ :keyword properties: The asset property dictionary.
+ :paramtype properties: dict[str, str]
+ :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :paramtype tags: dict[str, str]
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :paramtype is_anonymous: bool
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :paramtype is_archived: bool
+ :keyword data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
+ """
+ super(DataVersionBaseProperties, self).__init__(**kwargs)
+ self.data_type = 'DataVersionBaseProperties' # type: str
+ self.data_uri = kwargs['data_uri']
+ self.intellectual_property = kwargs.get('intellectual_property', None)
+ self.stage = kwargs.get('stage', None)
+
+
+class DataImport(DataVersionBaseProperties):
+ """DataImport.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :vartype is_anonymous: bool
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :vartype is_archived: bool
+ :ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "uri_file", "uri_folder", "mltable".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
+ :ivar data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
+ :ivar asset_name: Name of the asset for data import job to create.
+ :vartype asset_name: str
+ :ivar source: Source data of the asset to import from.
+ :vartype source: ~azure.mgmt.machinelearningservices.models.DataImportSource
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
- 'compute_type': {'key': 'computeType', 'type': 'str'},
- 'compute_location': {'key': 'computeLocation', 'type': 'str'},
- 'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
- 'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
- 'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'},
- 'resource_id': {'key': 'resourceId', 'type': 'str'},
- 'provisioning_errors': {'key': 'provisioningErrors', 'type': '[ErrorResponse]'},
- 'is_attached_compute': {'key': 'isAttachedCompute', 'type': 'bool'},
- 'disable_local_auth': {'key': 'disableLocalAuth', 'type': 'bool'},
+ 'properties': {'key': 'properties', 'type': '{str}'},
+ 'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
+ 'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
+ 'is_archived': {'key': 'isArchived', 'type': 'bool'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
+ 'asset_name': {'key': 'assetName', 'type': 'str'},
+ 'source': {'key': 'source', 'type': 'DataImportSource'},
}
def __init__(
@@ -7949,18 +9308,38 @@ def __init__(
**kwargs
):
"""
- :keyword compute_location: Location for the underlying compute.
- :paramtype compute_location: str
- :keyword description: The description of the Machine Learning compute.
+ :keyword description: The asset description text.
:paramtype description: str
- :keyword resource_id: ARM resource id of the underlying compute.
- :paramtype resource_id: str
- :keyword disable_local_auth: Opt-out of local authentication and ensure customers can use only
- MSI and AAD exclusively for authentication.
- :paramtype disable_local_auth: bool
+ :keyword properties: The asset property dictionary.
+ :paramtype properties: dict[str, str]
+ :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :paramtype tags: dict[str, str]
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :paramtype is_anonymous: bool
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :paramtype is_archived: bool
+ :keyword data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
+ :keyword asset_name: Name of the asset for data import job to create.
+ :paramtype asset_name: str
+ :keyword source: Source data of the asset to import from.
+ :paramtype source: ~azure.mgmt.machinelearningservices.models.DataImportSource
"""
- super(DataFactory, self).__init__(**kwargs)
- self.compute_type = 'DataFactory' # type: str
+ super(DataImport, self).__init__(**kwargs)
+ self.data_type = 'uri_folder' # type: str
+ self.asset_name = kwargs.get('asset_name', None)
+ self.source = kwargs.get('source', None)
class DataLakeAnalyticsSchema(msrest.serialization.Model):
@@ -8145,6 +9524,82 @@ def __init__(
self.path = kwargs.get('path', None)
+class DataQualityMonitoringSignal(MonitoringSignalBase):
+ """DataQualityMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar features: The features to calculate drift over.
+ :vartype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataQualityMetricThresholdBase]
+ :ivar target_data: Required. [Required] The data produced by the production service which drift
+ will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_thresholds': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'features': {'key': 'features', 'type': 'MonitoringFeatureFilterBase'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[DataQualityMetricThresholdBase]'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword features: The features to calculate drift over.
+ :paramtype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataQualityMetricThresholdBase]
+ :keyword target_data: Required. [Required] The data produced by the production service which
+ drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(DataQualityMonitoringSignal, self).__init__(**kwargs)
+ self.signal_type = 'DataQuality' # type: str
+ self.baseline_data = kwargs['baseline_data']
+ self.features = kwargs.get('features', None)
+ self.metric_thresholds = kwargs['metric_thresholds']
+ self.target_data = kwargs['target_data']
+
+
class DatasetExportSummary(ExportSummary):
"""DatasetExportSummary.
@@ -8327,75 +9782,6 @@ def __init__(
self.properties = kwargs['properties']
-class DataVersionBaseProperties(AssetBase):
- """Data version base definition.
-
- You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: MLTableData, UriFileDataVersion, UriFolderDataVersion.
-
- All required parameters must be populated in order to send to Azure.
-
- :ivar description: The asset description text.
- :vartype description: str
- :ivar properties: The asset property dictionary.
- :vartype properties: dict[str, str]
- :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
- :vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
- :vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
- :vartype is_archived: bool
- :ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
- Possible values include: "uri_file", "uri_folder", "mltable".
- :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
- :ivar data_uri: Required. [Required] Uri of the data. Example:
- https://go.microsoft.com/fwlink/?linkid=2202330.
- :vartype data_uri: str
- """
-
- _validation = {
- 'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- }
-
- _attribute_map = {
- 'description': {'key': 'description', 'type': 'str'},
- 'properties': {'key': 'properties', 'type': '{str}'},
- 'tags': {'key': 'tags', 'type': '{str}'},
- 'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
- 'is_archived': {'key': 'isArchived', 'type': 'bool'},
- 'data_type': {'key': 'dataType', 'type': 'str'},
- 'data_uri': {'key': 'dataUri', 'type': 'str'},
- }
-
- _subtype_map = {
- 'data_type': {'mltable': 'MLTableData', 'uri_file': 'UriFileDataVersion', 'uri_folder': 'UriFolderDataVersion'}
- }
-
- def __init__(
- self,
- **kwargs
- ):
- """
- :keyword description: The asset description text.
- :paramtype description: str
- :keyword properties: The asset property dictionary.
- :paramtype properties: dict[str, str]
- :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
- :paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
- :paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
- :paramtype is_archived: bool
- :keyword data_uri: Required. [Required] Uri of the data. Example:
- https://go.microsoft.com/fwlink/?linkid=2202330.
- :paramtype data_uri: str
- """
- super(DataVersionBaseProperties, self).__init__(**kwargs)
- self.data_type = 'DataVersionBaseProperties' # type: str
- self.data_uri = kwargs['data_uri']
-
-
class DataVersionBaseResourceArmPaginatedResult(msrest.serialization.Model):
"""A paginated list of DataVersionBase entities.
@@ -8553,6 +9939,10 @@ class ResourceConfiguration(msrest.serialization.Model):
:vartype instance_type: str
:ivar locations: Locations where the job can run.
:vartype locations: list[str]
+ :ivar max_instance_count: Optional max allowed number of instances or nodes to be used by the
+ compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :vartype max_instance_count: int
:ivar properties: Additional properties bag.
:vartype properties: dict[str, any]
"""
@@ -8561,6 +9951,7 @@ class ResourceConfiguration(msrest.serialization.Model):
'instance_count': {'key': 'instanceCount', 'type': 'int'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
'locations': {'key': 'locations', 'type': '[str]'},
+ 'max_instance_count': {'key': 'maxInstanceCount', 'type': 'int'},
'properties': {'key': 'properties', 'type': '{object}'},
}
@@ -8575,6 +9966,10 @@ def __init__(
:paramtype instance_type: str
:keyword locations: Locations where the job can run.
:paramtype locations: list[str]
+ :keyword max_instance_count: Optional max allowed number of instances or nodes to be used by
+ the compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :paramtype max_instance_count: int
:keyword properties: Additional properties bag.
:paramtype properties: dict[str, any]
"""
@@ -8582,6 +9977,7 @@ def __init__(
self.instance_count = kwargs.get('instance_count', 1)
self.instance_type = kwargs.get('instance_type', None)
self.locations = kwargs.get('locations', None)
+ self.max_instance_count = kwargs.get('max_instance_count', None)
self.properties = kwargs.get('properties', None)
@@ -8594,6 +9990,10 @@ class DeploymentResourceConfiguration(ResourceConfiguration):
:vartype instance_type: str
:ivar locations: Locations where the job can run.
:vartype locations: list[str]
+ :ivar max_instance_count: Optional max allowed number of instances or nodes to be used by the
+ compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :vartype max_instance_count: int
:ivar properties: Additional properties bag.
:vartype properties: dict[str, any]
"""
@@ -8602,6 +10002,7 @@ class DeploymentResourceConfiguration(ResourceConfiguration):
'instance_count': {'key': 'instanceCount', 'type': 'int'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
'locations': {'key': 'locations', 'type': '[str]'},
+ 'max_instance_count': {'key': 'maxInstanceCount', 'type': 'int'},
'properties': {'key': 'properties', 'type': '{object}'},
}
@@ -8616,6 +10017,10 @@ def __init__(
:paramtype instance_type: str
:keyword locations: Locations where the job can run.
:paramtype locations: list[str]
+ :keyword max_instance_count: Optional max allowed number of instances or nodes to be used by
+ the compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :paramtype max_instance_count: int
:keyword properties: Additional properties bag.
:paramtype properties: dict[str, any]
"""
@@ -8865,12 +10270,13 @@ class DistributionConfiguration(msrest.serialization.Model):
"""Base definition for job distribution configuration.
You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: Mpi, PyTorch, TensorFlow.
+ sub-classes are: Mpi, PyTorch, Ray, TensorFlow.
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
"""
@@ -8883,7 +10289,7 @@ class DistributionConfiguration(msrest.serialization.Model):
}
_subtype_map = {
- 'distribution_type': {'Mpi': 'Mpi', 'PyTorch': 'PyTorch', 'TensorFlow': 'TensorFlow'}
+ 'distribution_type': {'Mpi': 'Mpi', 'PyTorch': 'PyTorch', 'Ray': 'Ray', 'TensorFlow': 'TensorFlow'}
}
def __init__(
@@ -9199,48 +10605,14 @@ def __init__(
self.token_type = kwargs.get('token_type', None)
-class ScheduleActionBase(msrest.serialization.Model):
- """ScheduleActionBase.
-
- You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: JobScheduleAction, EndpointScheduleAction.
-
- All required parameters must be populated in order to send to Azure.
-
- :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
- filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint".
- :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
- """
-
- _validation = {
- 'action_type': {'required': True},
- }
-
- _attribute_map = {
- 'action_type': {'key': 'actionType', 'type': 'str'},
- }
-
- _subtype_map = {
- 'action_type': {'CreateJob': 'JobScheduleAction', 'InvokeBatchEndpoint': 'EndpointScheduleAction'}
- }
-
- def __init__(
- self,
- **kwargs
- ):
- """
- """
- super(ScheduleActionBase, self).__init__(**kwargs)
- self.action_type = None # type: Optional[str]
-
-
class EndpointScheduleAction(ScheduleActionBase):
"""EndpointScheduleAction.
All required parameters must be populated in order to send to Azure.
:ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
- filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint".
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
:vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
:ivar endpoint_invocation_definition: Required. [Required] Defines Schedule action definition
details.
@@ -9520,9 +10892,13 @@ class EnvironmentVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar auto_rebuild: Defines if image needs to be rebuilt based on base image changes. Possible
values include: "Disabled", "OnBaseImageUpdate".
@@ -9561,12 +10937,17 @@ class EnvironmentVersionProperties(AssetBase):
:ivar inference_config: Defines configuration specific to inference.
:vartype inference_config:
~azure.mgmt.machinelearningservices.models.InferenceContainerProperties
+ :ivar intellectual_property: Intellectual Property details. Used if environment is an
+ Intellectual Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar os_type: The OS type of the environment. Possible values include: "Linux", "Windows".
:vartype os_type: str or ~azure.mgmt.machinelearningservices.models.OperatingSystemType
:ivar provisioning_state: Provisioning state for the environment version. Possible values
include: "Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the environment lifecycle assigned to this environment.
+ :vartype stage: str
"""
_validation = {
@@ -9578,6 +10959,7 @@ class EnvironmentVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'auto_rebuild': {'key': 'autoRebuild', 'type': 'str'},
@@ -9586,8 +10968,10 @@ class EnvironmentVersionProperties(AssetBase):
'environment_type': {'key': 'environmentType', 'type': 'str'},
'image': {'key': 'image', 'type': 'str'},
'inference_config': {'key': 'inferenceConfig', 'type': 'InferenceContainerProperties'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'os_type': {'key': 'osType', 'type': 'str'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -9601,9 +10985,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword auto_rebuild: Defines if image needs to be rebuilt based on base image changes.
Possible values include: "Disabled", "OnBaseImageUpdate".
@@ -9632,8 +11020,14 @@ def __init__(
:keyword inference_config: Defines configuration specific to inference.
:paramtype inference_config:
~azure.mgmt.machinelearningservices.models.InferenceContainerProperties
+ :keyword intellectual_property: Intellectual Property details. Used if environment is an
+ Intellectual Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword os_type: The OS type of the environment. Possible values include: "Linux", "Windows".
:paramtype os_type: str or ~azure.mgmt.machinelearningservices.models.OperatingSystemType
+ :keyword stage: Stage in the environment lifecycle assigned to this environment.
+ :paramtype stage: str
"""
super(EnvironmentVersionProperties, self).__init__(**kwargs)
self.auto_rebuild = kwargs.get('auto_rebuild', None)
@@ -9642,8 +11036,10 @@ def __init__(
self.environment_type = None
self.image = kwargs.get('image', None)
self.inference_config = kwargs.get('inference_config', None)
+ self.intellectual_property = kwargs.get('intellectual_property', None)
self.os_type = kwargs.get('os_type', None)
self.provisioning_state = None
+ self.stage = kwargs.get('stage', None)
class EnvironmentVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -9972,6 +11368,113 @@ def __init__(
self.value = kwargs.get('value', None)
+class FeatureAttributionDriftMonitoringSignal(MonitoringSignalBase):
+ """FeatureAttributionDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetricThreshold
+ :ivar target_data: Required. [Required] The data which drift will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_threshold': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'metric_threshold': {'key': 'metricThreshold', 'type': 'FeatureAttributionMetricThreshold'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetricThreshold
+ :keyword target_data: Required. [Required] The data which drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(FeatureAttributionDriftMonitoringSignal, self).__init__(**kwargs)
+ self.signal_type = 'FeatureAttributionDrift' # type: str
+ self.baseline_data = kwargs['baseline_data']
+ self.metric_threshold = kwargs['metric_threshold']
+ self.target_data = kwargs['target_data']
+
+
+class FeatureAttributionMetricThreshold(msrest.serialization.Model):
+ """FeatureAttributionMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar metric: Required. [Required] The feature attribution metric to calculate. Possible values
+ include: "NormalizedDiscountedCumulativeGain".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetric
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'metric': {'key': 'metric', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword metric: Required. [Required] The feature attribution metric to calculate. Possible
+ values include: "NormalizedDiscountedCumulativeGain".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetric
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(FeatureAttributionMetricThreshold, self).__init__(**kwargs)
+ self.metric = kwargs['metric']
+ self.threshold = kwargs.get('threshold', None)
+
+
class FeaturesetContainer(Resource):
"""Azure Resource Manager resource envelope.
@@ -10335,36 +11838,13 @@ def __init__(
:keyword tags: A set of tags. Specifies the tags.
:paramtype tags: dict[str, str]
"""
- super(FeaturesetVersionBackfillRequest, self).__init__(**kwargs)
- self.description = kwargs.get('description', None)
- self.display_name = kwargs.get('display_name', None)
- self.feature_window = kwargs.get('feature_window', None)
- self.resource = kwargs.get('resource', None)
- self.spark_configuration = kwargs.get('spark_configuration', None)
- self.tags = kwargs.get('tags', None)
-
-
-class FeaturesetVersionBackfillResponse(msrest.serialization.Model):
- """Response payload for creating a backfill request for a given feature set version.
-
- :ivar job_id: Job id created as part of request.
- :vartype job_id: str
- """
-
- _attribute_map = {
- 'job_id': {'key': 'jobId', 'type': 'str'},
- }
-
- def __init__(
- self,
- **kwargs
- ):
- """
- :keyword job_id: Job id created as part of request.
- :paramtype job_id: str
- """
- super(FeaturesetVersionBackfillResponse, self).__init__(**kwargs)
- self.job_id = kwargs.get('job_id', None)
+ super(FeaturesetVersionBackfillRequest, self).__init__(**kwargs)
+ self.description = kwargs.get('description', None)
+ self.display_name = kwargs.get('display_name', None)
+ self.feature_window = kwargs.get('feature_window', None)
+ self.resource = kwargs.get('resource', None)
+ self.spark_configuration = kwargs.get('spark_configuration', None)
+ self.tags = kwargs.get('tags', None)
class FeaturesetVersionProperties(AssetBase):
@@ -10378,9 +11858,13 @@ class FeaturesetVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar entities: Specifies list of entities.
:vartype entities: list[str]
@@ -10405,6 +11889,7 @@ class FeaturesetVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'entities': {'key': 'entities', 'type': '[str]'},
@@ -10425,9 +11910,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword entities: Specifies list of entities.
:paramtype entities: list[str]
@@ -10681,9 +12170,13 @@ class FeaturestoreEntityVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar index_columns: Specifies index columns.
:vartype index_columns: list[~azure.mgmt.machinelearningservices.models.IndexColumn]
@@ -10691,6 +12184,8 @@ class FeaturestoreEntityVersionProperties(AssetBase):
values include: "Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Specifies the asset stage.
+ :vartype stage: str
"""
_validation = {
@@ -10701,10 +12196,12 @@ class FeaturestoreEntityVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'index_columns': {'key': 'indexColumns', 'type': '[IndexColumn]'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -10718,16 +12215,23 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword index_columns: Specifies index columns.
:paramtype index_columns: list[~azure.mgmt.machinelearningservices.models.IndexColumn]
+ :keyword stage: Specifies the asset stage.
+ :paramtype stage: str
"""
super(FeaturestoreEntityVersionProperties, self).__init__(**kwargs)
self.index_columns = kwargs.get('index_columns', None)
self.provisioning_state = None
+ self.stage = kwargs.get('stage', None)
class FeaturestoreEntityVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -10796,6 +12300,43 @@ def __init__(
self.online_store_connection_name = kwargs.get('online_store_connection_name', None)
+class FeatureSubset(MonitoringFeatureFilterBase):
+ """FeatureSubset.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ :ivar features: Required. [Required] The list of features to include.
+ :vartype features: list[str]
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ 'features': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ 'features': {'key': 'features', 'type': '[str]'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword features: Required. [Required] The list of features to include.
+ :paramtype features: list[str]
+ """
+ super(FeatureSubset, self).__init__(**kwargs)
+ self.filter_type = 'FeatureSubset' # type: str
+ self.features = kwargs['features']
+
+
class FeatureWindow(msrest.serialization.Model):
"""Specifies the feature window.
@@ -10848,6 +12389,45 @@ def __init__(
self.dataset_language = kwargs.get('dataset_language', None)
+class FileSystemSource(DataImportSource):
+ """FileSystemSource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar connection: Workspace connection for data import source storage.
+ :vartype connection: str
+ :ivar source_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "database", "file_system".
+ :vartype source_type: str or ~azure.mgmt.machinelearningservices.models.DataImportSourceType
+ :ivar path: Path on data import FileSystem source.
+ :vartype path: str
+ """
+
+ _validation = {
+ 'source_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'connection': {'key': 'connection', 'type': 'str'},
+ 'source_type': {'key': 'sourceType', 'type': 'str'},
+ 'path': {'key': 'path', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword connection: Workspace connection for data import source storage.
+ :paramtype connection: str
+ :keyword path: Path on data import FileSystem source.
+ :paramtype path: str
+ """
+ super(FileSystemSource, self).__init__(**kwargs)
+ self.source_type = 'file_system' # type: str
+ self.path = kwargs.get('path', None)
+
+
class FlavorData(msrest.serialization.Model):
"""FlavorData.
@@ -11061,6 +12641,11 @@ class ForecastingSettings(msrest.serialization.Model):
:ivar feature_lags: Flag for generating lags for the numeric features with 'auto' or null.
Possible values include: "None", "Auto".
:vartype feature_lags: str or ~azure.mgmt.machinelearningservices.models.FeatureLags
+ :ivar features_unknown_at_forecast_time: The feature columns that are available for training
+ but unknown at the time of forecast/inference.
+ If features_unknown_at_forecast_time is not set, it is assumed that all the feature columns in
+ the dataset are known at inference time.
+ :vartype features_unknown_at_forecast_time: list[str]
:ivar forecast_horizon: The desired maximum forecast horizon in units of time-series frequency.
:vartype forecast_horizon: ~azure.mgmt.machinelearningservices.models.ForecastHorizon
:ivar frequency: When forecasting, this parameter represents the period with which the forecast
@@ -11105,6 +12690,7 @@ class ForecastingSettings(msrest.serialization.Model):
'country_or_region_for_holidays': {'key': 'countryOrRegionForHolidays', 'type': 'str'},
'cv_step_size': {'key': 'cvStepSize', 'type': 'int'},
'feature_lags': {'key': 'featureLags', 'type': 'str'},
+ 'features_unknown_at_forecast_time': {'key': 'featuresUnknownAtForecastTime', 'type': '[str]'},
'forecast_horizon': {'key': 'forecastHorizon', 'type': 'ForecastHorizon'},
'frequency': {'key': 'frequency', 'type': 'str'},
'seasonality': {'key': 'seasonality', 'type': 'Seasonality'},
@@ -11133,6 +12719,11 @@ def __init__(
:keyword feature_lags: Flag for generating lags for the numeric features with 'auto' or null.
Possible values include: "None", "Auto".
:paramtype feature_lags: str or ~azure.mgmt.machinelearningservices.models.FeatureLags
+ :keyword features_unknown_at_forecast_time: The feature columns that are available for training
+ but unknown at the time of forecast/inference.
+ If features_unknown_at_forecast_time is not set, it is assumed that all the feature columns in
+ the dataset are known at inference time.
+ :paramtype features_unknown_at_forecast_time: list[str]
:keyword forecast_horizon: The desired maximum forecast horizon in units of time-series
frequency.
:paramtype forecast_horizon: ~azure.mgmt.machinelearningservices.models.ForecastHorizon
@@ -11178,6 +12769,7 @@ def __init__(
self.country_or_region_for_holidays = kwargs.get('country_or_region_for_holidays', None)
self.cv_step_size = kwargs.get('cv_step_size', None)
self.feature_lags = kwargs.get('feature_lags', None)
+ self.features_unknown_at_forecast_time = kwargs.get('features_unknown_at_forecast_time', None)
self.forecast_horizon = kwargs.get('forecast_horizon', None)
self.frequency = kwargs.get('frequency', None)
self.seasonality = kwargs.get('seasonality', None)
@@ -11456,8 +13048,10 @@ class HdfsDatastore(DatastoreProperties):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -11474,7 +13068,7 @@ class HdfsDatastore(DatastoreProperties):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'name_node_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'name_node_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -11483,6 +13077,7 @@ class HdfsDatastore(DatastoreProperties):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'hdfs_server_certificate': {'key': 'hdfsServerCertificate', 'type': 'str'},
'name_node_address': {'key': 'nameNodeAddress', 'type': 'str'},
@@ -11502,6 +13097,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword hdfs_server_certificate: The TLS cert of the HDFS server. Needs to be a base64 encoded
string. Required if "Https" protocol is selected.
:paramtype hdfs_server_certificate: str
@@ -11683,7 +13281,7 @@ class IdAssetReference(AssetReferenceBase):
_validation = {
'reference_type': {'required': True},
- 'asset_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'asset_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -12403,11 +14001,11 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:code:`
Some examples are:
-
+```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
-`
+````
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
@@ -12648,11 +14246,11 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:code:`
Some examples are:
-
+```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
-`
+````
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
@@ -12897,11 +14495,11 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:code:`
Some examples are:
-
+```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
-`
+````
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
@@ -13868,6 +15466,14 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
Note: The training run may get into CUDA OOM if the size is too big.
Note: This settings is only supported for the 'yolov5' algorithm.
:vartype image_size: int
+ :ivar log_training_metrics: Enable computing and logging training metrics. Possible values
+ include: "Enable", "Disable".
+ :vartype log_training_metrics: str or
+ ~azure.mgmt.machinelearningservices.models.LogTrainingMetrics
+ :ivar log_validation_loss: Enable computing and logging validation loss. Possible values
+ include: "Enable", "Disable".
+ :vartype log_validation_loss: str or
+ ~azure.mgmt.machinelearningservices.models.LogValidationLoss
:ivar max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
Note: This settings is not supported for the 'yolov5' algorithm.
@@ -13947,6 +15553,8 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
'box_detections_per_image': {'key': 'boxDetectionsPerImage', 'type': 'int'},
'box_score_threshold': {'key': 'boxScoreThreshold', 'type': 'float'},
'image_size': {'key': 'imageSize', 'type': 'int'},
+ 'log_training_metrics': {'key': 'logTrainingMetrics', 'type': 'str'},
+ 'log_validation_loss': {'key': 'logValidationLoss', 'type': 'str'},
'max_size': {'key': 'maxSize', 'type': 'int'},
'min_size': {'key': 'minSize', 'type': 'int'},
'model_size': {'key': 'modelSize', 'type': 'str'},
@@ -14067,6 +15675,14 @@ def __init__(
Note: The training run may get into CUDA OOM if the size is too big.
Note: This settings is only supported for the 'yolov5' algorithm.
:paramtype image_size: int
+ :keyword log_training_metrics: Enable computing and logging training metrics. Possible values
+ include: "Enable", "Disable".
+ :paramtype log_training_metrics: str or
+ ~azure.mgmt.machinelearningservices.models.LogTrainingMetrics
+ :keyword log_validation_loss: Enable computing and logging validation loss. Possible values
+ include: "Enable", "Disable".
+ :paramtype log_validation_loss: str or
+ ~azure.mgmt.machinelearningservices.models.LogValidationLoss
:keyword max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
Note: This settings is not supported for the 'yolov5' algorithm.
@@ -14113,6 +15729,8 @@ def __init__(
self.box_detections_per_image = kwargs.get('box_detections_per_image', None)
self.box_score_threshold = kwargs.get('box_score_threshold', None)
self.image_size = kwargs.get('image_size', None)
+ self.log_training_metrics = kwargs.get('log_training_metrics', None)
+ self.log_validation_loss = kwargs.get('log_validation_loss', None)
self.max_size = kwargs.get('max_size', None)
self.min_size = kwargs.get('min_size', None)
self.model_size = kwargs.get('model_size', None)
@@ -14277,6 +15895,43 @@ def __init__(
self.sampling_algorithm = kwargs['sampling_algorithm']
+class ImportDataAction(ScheduleActionBase):
+ """ImportDataAction.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
+ :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
+ :ivar data_import_definition: Required. [Required] Defines Schedule action definition details.
+ :vartype data_import_definition: ~azure.mgmt.machinelearningservices.models.DataImport
+ """
+
+ _validation = {
+ 'action_type': {'required': True},
+ 'data_import_definition': {'required': True},
+ }
+
+ _attribute_map = {
+ 'action_type': {'key': 'actionType', 'type': 'str'},
+ 'data_import_definition': {'key': 'dataImportDefinition', 'type': 'DataImport'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword data_import_definition: Required. [Required] Defines Schedule action definition
+ details.
+ :paramtype data_import_definition: ~azure.mgmt.machinelearningservices.models.DataImport
+ """
+ super(ImportDataAction, self).__init__(**kwargs)
+ self.action_type = 'ImportData' # type: str
+ self.data_import_definition = kwargs['data_import_definition']
+
+
class IndexColumn(msrest.serialization.Model):
"""Dto object representing index column.
@@ -14403,6 +16058,45 @@ def __init__(
self.limits = kwargs.get('limits', None)
+class IntellectualProperty(msrest.serialization.Model):
+ """Intellectual Property details for a resource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar protection_level: Protection level of the Intellectual Property. Possible values include:
+ "All", "None".
+ :vartype protection_level: str or ~azure.mgmt.machinelearningservices.models.ProtectionLevel
+ :ivar publisher: Required. [Required] Publisher of the Intellectual Property. Must be the same
+ as Registry publisher name.
+ :vartype publisher: str
+ """
+
+ _validation = {
+ 'publisher': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'protection_level': {'key': 'protectionLevel', 'type': 'str'},
+ 'publisher': {'key': 'publisher', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword protection_level: Protection level of the Intellectual Property. Possible values
+ include: "All", "None".
+ :paramtype protection_level: str or ~azure.mgmt.machinelearningservices.models.ProtectionLevel
+ :keyword publisher: Required. [Required] Publisher of the Intellectual Property. Must be the
+ same as Registry publisher name.
+ :paramtype publisher: str
+ """
+ super(IntellectualProperty, self).__init__(**kwargs)
+ self.protection_level = kwargs.get('protection_level', None)
+ self.publisher = kwargs['publisher']
+
+
class JobBase(Resource):
"""Azure Resource Manager resource envelope.
@@ -14493,6 +16187,10 @@ class JobResourceConfiguration(ResourceConfiguration):
:vartype instance_type: str
:ivar locations: Locations where the job can run.
:vartype locations: list[str]
+ :ivar max_instance_count: Optional max allowed number of instances or nodes to be used by the
+ compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :vartype max_instance_count: int
:ivar properties: Additional properties bag.
:vartype properties: dict[str, any]
:ivar docker_args: Extra arguments to pass to the Docker run command. This would override any
@@ -14513,6 +16211,7 @@ class JobResourceConfiguration(ResourceConfiguration):
'instance_count': {'key': 'instanceCount', 'type': 'int'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
'locations': {'key': 'locations', 'type': '[str]'},
+ 'max_instance_count': {'key': 'maxInstanceCount', 'type': 'int'},
'properties': {'key': 'properties', 'type': '{object}'},
'docker_args': {'key': 'dockerArgs', 'type': 'str'},
'shm_size': {'key': 'shmSize', 'type': 'str'},
@@ -14529,6 +16228,10 @@ def __init__(
:paramtype instance_type: str
:keyword locations: Locations where the job can run.
:paramtype locations: list[str]
+ :keyword max_instance_count: Optional max allowed number of instances or nodes to be used by
+ the compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :paramtype max_instance_count: int
:keyword properties: Additional properties bag.
:paramtype properties: dict[str, any]
:keyword docker_args: Extra arguments to pass to the Docker run command. This would override
@@ -14551,7 +16254,8 @@ class JobScheduleAction(ScheduleActionBase):
All required parameters must be populated in order to send to Azure.
:ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
- filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint".
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
:vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
:ivar job_definition: Required. [Required] Defines Schedule action definition details.
:vartype job_definition: ~azure.mgmt.machinelearningservices.models.JobBaseProperties
@@ -14659,9 +16363,9 @@ class KerberosCredentials(msrest.serialization.Model):
"""
_validation = {
- 'kerberos_kdc_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_principal': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_realm': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_kdc_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_principal': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_realm': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -14710,9 +16414,9 @@ class KerberosKeytabCredentials(DatastoreCredentials, KerberosCredentials):
"""
_validation = {
- 'kerberos_kdc_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_principal': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_realm': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_kdc_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_principal': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_realm': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'credentials_type': {'required': True},
'secrets': {'required': True},
}
@@ -14804,9 +16508,9 @@ class KerberosPasswordCredentials(DatastoreCredentials, KerberosCredentials):
"""
_validation = {
- 'kerberos_kdc_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_principal': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_realm': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_kdc_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_principal': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_realm': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'credentials_type': {'required': True},
'secrets': {'required': True},
}
@@ -15015,6 +16719,8 @@ class OnlineDeploymentProperties(EndpointDeploymentPropertiesBase):
:vartype properties: dict[str, str]
:ivar app_insights_enabled: If true, enables Application Insights logging.
:vartype app_insights_enabled: bool
+ :ivar data_collector: The mdc configuration, we disable mdc when it's null.
+ :vartype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:ivar egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -15060,6 +16766,7 @@ class OnlineDeploymentProperties(EndpointDeploymentPropertiesBase):
'environment_variables': {'key': 'environmentVariables', 'type': '{str}'},
'properties': {'key': 'properties', 'type': '{str}'},
'app_insights_enabled': {'key': 'appInsightsEnabled', 'type': 'bool'},
+ 'data_collector': {'key': 'dataCollector', 'type': 'DataCollector'},
'egress_public_network_access': {'key': 'egressPublicNetworkAccess', 'type': 'str'},
'endpoint_compute_type': {'key': 'endpointComputeType', 'type': 'str'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
@@ -15094,6 +16801,8 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword app_insights_enabled: If true, enables Application Insights logging.
:paramtype app_insights_enabled: bool
+ :keyword data_collector: The mdc configuration, we disable mdc when it's null.
+ :paramtype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:keyword egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -15120,6 +16829,7 @@ def __init__(
"""
super(OnlineDeploymentProperties, self).__init__(**kwargs)
self.app_insights_enabled = kwargs.get('app_insights_enabled', False)
+ self.data_collector = kwargs.get('data_collector', None)
self.egress_public_network_access = kwargs.get('egress_public_network_access', None)
self.endpoint_compute_type = 'OnlineDeploymentProperties' # type: str
self.instance_type = kwargs.get('instance_type', None)
@@ -15152,6 +16862,8 @@ class KubernetesOnlineDeployment(OnlineDeploymentProperties):
:vartype properties: dict[str, str]
:ivar app_insights_enabled: If true, enables Application Insights logging.
:vartype app_insights_enabled: bool
+ :ivar data_collector: The mdc configuration, we disable mdc when it's null.
+ :vartype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:ivar egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -15201,6 +16913,7 @@ class KubernetesOnlineDeployment(OnlineDeploymentProperties):
'environment_variables': {'key': 'environmentVariables', 'type': '{str}'},
'properties': {'key': 'properties', 'type': '{str}'},
'app_insights_enabled': {'key': 'appInsightsEnabled', 'type': 'bool'},
+ 'data_collector': {'key': 'dataCollector', 'type': 'DataCollector'},
'egress_public_network_access': {'key': 'egressPublicNetworkAccess', 'type': 'str'},
'endpoint_compute_type': {'key': 'endpointComputeType', 'type': 'str'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
@@ -15232,6 +16945,8 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword app_insights_enabled: If true, enables Application Insights logging.
:paramtype app_insights_enabled: bool
+ :keyword data_collector: The mdc configuration, we disable mdc when it's null.
+ :paramtype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:keyword egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -15609,6 +17324,9 @@ class LabelingJobProperties(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -15665,6 +17383,7 @@ class LabelingJobProperties(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'created_date_time': {'key': 'createdDateTime', 'type': 'iso-8601'},
@@ -15707,6 +17426,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -15807,6 +17529,82 @@ def __init__(
self.annotation_type = kwargs.get('annotation_type', None)
+class OneLakeArtifact(msrest.serialization.Model):
+ """OneLake artifact (data source) configuration.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: LakehouseArtifact.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar artifact_name: Required. [Required] OneLake artifact name.
+ :vartype artifact_name: str
+ :ivar artifact_type: Required. [Required] OneLake artifact type.Constant filled by server.
+ Possible values include: "Lakehouse".
+ :vartype artifact_type: str or ~azure.mgmt.machinelearningservices.models.OneLakeArtifactType
+ """
+
+ _validation = {
+ 'artifact_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'artifact_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'artifact_name': {'key': 'artifactName', 'type': 'str'},
+ 'artifact_type': {'key': 'artifactType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'artifact_type': {'Lakehouse': 'LakehouseArtifact'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword artifact_name: Required. [Required] OneLake artifact name.
+ :paramtype artifact_name: str
+ """
+ super(OneLakeArtifact, self).__init__(**kwargs)
+ self.artifact_name = kwargs['artifact_name']
+ self.artifact_type = None # type: Optional[str]
+
+
+class LakehouseArtifact(OneLakeArtifact):
+ """LakehouseArtifact.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar artifact_name: Required. [Required] OneLake artifact name.
+ :vartype artifact_name: str
+ :ivar artifact_type: Required. [Required] OneLake artifact type.Constant filled by server.
+ Possible values include: "Lakehouse".
+ :vartype artifact_type: str or ~azure.mgmt.machinelearningservices.models.OneLakeArtifactType
+ """
+
+ _validation = {
+ 'artifact_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'artifact_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'artifact_name': {'key': 'artifactName', 'type': 'str'},
+ 'artifact_type': {'key': 'artifactType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword artifact_name: Required. [Required] OneLake artifact name.
+ :paramtype artifact_name: str
+ """
+ super(LakehouseArtifact, self).__init__(**kwargs)
+ self.artifact_type = 'Lakehouse' # type: str
+
+
class ListAmlUserFeatureResult(msrest.serialization.Model):
"""The List Aml user feature operation response.
@@ -16031,7 +17829,7 @@ class LiteralJobInput(JobInput):
_validation = {
'job_input_type': {'required': True},
- 'value': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'value': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -16190,6 +17988,8 @@ class ManagedOnlineDeployment(OnlineDeploymentProperties):
:vartype properties: dict[str, str]
:ivar app_insights_enabled: If true, enables Application Insights logging.
:vartype app_insights_enabled: bool
+ :ivar data_collector: The mdc configuration, we disable mdc when it's null.
+ :vartype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:ivar egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -16235,6 +18035,7 @@ class ManagedOnlineDeployment(OnlineDeploymentProperties):
'environment_variables': {'key': 'environmentVariables', 'type': '{str}'},
'properties': {'key': 'properties', 'type': '{str}'},
'app_insights_enabled': {'key': 'appInsightsEnabled', 'type': 'bool'},
+ 'data_collector': {'key': 'dataCollector', 'type': 'DataCollector'},
'egress_public_network_access': {'key': 'egressPublicNetworkAccess', 'type': 'str'},
'endpoint_compute_type': {'key': 'endpointComputeType', 'type': 'str'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
@@ -16265,6 +18066,8 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword app_insights_enabled: If true, enables Application Insights logging.
:paramtype app_insights_enabled: bool
+ :keyword data_collector: The mdc configuration, we disable mdc when it's null.
+ :paramtype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:keyword egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -16546,8 +18349,8 @@ class MLAssistConfigurationEnabled(MLAssistConfiguration):
_validation = {
'ml_assist': {'required': True},
- 'inferencing_compute_binding': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'training_compute_binding': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'inferencing_compute_binding': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'training_compute_binding': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -16592,7 +18395,7 @@ class MLFlowModelJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -16632,6 +18435,8 @@ class MLFlowModelJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -16652,6 +18457,7 @@ class MLFlowModelJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -16667,6 +18473,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -16678,6 +18486,7 @@ def __init__(
super(MLFlowModelJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
self.job_output_type = 'mlflow_model' # type: str
@@ -16695,9 +18504,13 @@ class MLTableData(DataVersionBaseProperties):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
Possible values include: "uri_file", "uri_folder", "mltable".
@@ -16705,23 +18518,31 @@ class MLTableData(DataVersionBaseProperties):
:ivar data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
:ivar referenced_uris: Uris referenced in the MLTable definition (required for lineage).
:vartype referenced_uris: list[str]
"""
_validation = {
'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'data_type': {'key': 'dataType', 'type': 'str'},
'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
'referenced_uris': {'key': 'referencedUris', 'type': '[str]'},
}
@@ -16736,13 +18557,23 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
:keyword referenced_uris: Uris referenced in the MLTable definition (required for lineage).
:paramtype referenced_uris: list[str]
"""
@@ -16770,7 +18601,7 @@ class MLTableJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -16810,6 +18641,8 @@ class MLTableJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -16830,6 +18663,7 @@ class MLTableJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -16845,6 +18679,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -16856,6 +18692,7 @@ def __init__(
super(MLTableJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
self.job_output_type = 'mltable' # type: str
@@ -17083,6 +18920,82 @@ def __init__(
self.path = kwargs['path']
+class ModelPerformanceSignalBase(MonitoringSignalBase):
+ """ModelPerformanceSignalBase.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar data_segment: The data segment.
+ :vartype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :ivar metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.ModelPerformanceMetricThresholdBase
+ :ivar target_data: Required. [Required] The data produced by the production service which drift
+ will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_threshold': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'data_segment': {'key': 'dataSegment', 'type': 'MonitoringDataSegment'},
+ 'metric_threshold': {'key': 'metricThreshold', 'type': 'ModelPerformanceMetricThresholdBase'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword data_segment: The data segment.
+ :paramtype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :keyword metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.ModelPerformanceMetricThresholdBase
+ :keyword target_data: Required. [Required] The data produced by the production service which
+ drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(ModelPerformanceSignalBase, self).__init__(**kwargs)
+ self.signal_type = 'ModelPerformanceSignalBase' # type: str
+ self.baseline_data = kwargs['baseline_data']
+ self.data_segment = kwargs.get('data_segment', None)
+ self.metric_threshold = kwargs['metric_threshold']
+ self.target_data = kwargs['target_data']
+
+
class ModelVersion(Resource):
"""Azure Resource Manager resource envelope.
@@ -17144,12 +19057,19 @@ class ModelVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar flavors: Mapping of model flavors to their properties.
:vartype flavors: dict[str, ~azure.mgmt.machinelearningservices.models.FlavorData]
+ :ivar intellectual_property: Intellectual Property details. Used if model is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar job_name: Name of the training job which produced this model.
:vartype job_name: str
:ivar model_type: The storage format for this entity. Used for NCD.
@@ -17160,6 +19080,8 @@ class ModelVersionProperties(AssetBase):
"Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the model lifecycle assigned to this model.
+ :vartype stage: str
"""
_validation = {
@@ -17170,13 +19092,16 @@ class ModelVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'flavors': {'key': 'flavors', 'type': '{FlavorData}'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'job_name': {'key': 'jobName', 'type': 'str'},
'model_type': {'key': 'modelType', 'type': 'str'},
'model_uri': {'key': 'modelUri', 'type': 'str'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -17190,40 +19115,207 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword flavors: Mapping of model flavors to their properties.
:paramtype flavors: dict[str, ~azure.mgmt.machinelearningservices.models.FlavorData]
+ :keyword intellectual_property: Intellectual Property details. Used if model is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword job_name: Name of the training job which produced this model.
:paramtype job_name: str
:keyword model_type: The storage format for this entity. Used for NCD.
:paramtype model_type: str
:keyword model_uri: The URI path to the model contents.
:paramtype model_uri: str
+ :keyword stage: Stage in the model lifecycle assigned to this model.
+ :paramtype stage: str
+ """
+ super(ModelVersionProperties, self).__init__(**kwargs)
+ self.flavors = kwargs.get('flavors', None)
+ self.intellectual_property = kwargs.get('intellectual_property', None)
+ self.job_name = kwargs.get('job_name', None)
+ self.model_type = kwargs.get('model_type', None)
+ self.model_uri = kwargs.get('model_uri', None)
+ self.provisioning_state = None
+ self.stage = kwargs.get('stage', None)
+
+
+class ModelVersionResourceArmPaginatedResult(msrest.serialization.Model):
+ """A paginated list of ModelVersion entities.
+
+ :ivar next_link: The link to the next page of ModelVersion objects. If null, there are no
+ additional pages.
+ :vartype next_link: str
+ :ivar value: An array of objects of type ModelVersion.
+ :vartype value: list[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ """
+
+ _attribute_map = {
+ 'next_link': {'key': 'nextLink', 'type': 'str'},
+ 'value': {'key': 'value', 'type': '[ModelVersion]'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword next_link: The link to the next page of ModelVersion objects. If null, there are no
+ additional pages.
+ :paramtype next_link: str
+ :keyword value: An array of objects of type ModelVersion.
+ :paramtype value: list[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ """
+ super(ModelVersionResourceArmPaginatedResult, self).__init__(**kwargs)
+ self.next_link = kwargs.get('next_link', None)
+ self.value = kwargs.get('value', None)
+
+
+class MonitorDefinition(msrest.serialization.Model):
+ """MonitorDefinition.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar compute_id: Required. [Required] The ARM resource ID of the compute resource to run the
+ monitoring job on.
+ :vartype compute_id: str
+ :ivar monitoring_target: The ARM resource ID of either the model or deployment targeted by this
+ monitor.
+ :vartype monitoring_target: str
+ :ivar notification_setting: The monitor's notification settings.
+ :vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar signals: Required. [Required] The signals to monitor.
+ :vartype signals: dict[str, ~azure.mgmt.machinelearningservices.models.MonitoringSignalBase]
+ """
+
+ _validation = {
+ 'compute_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'signals': {'required': True},
+ }
+
+ _attribute_map = {
+ 'compute_id': {'key': 'computeId', 'type': 'str'},
+ 'monitoring_target': {'key': 'monitoringTarget', 'type': 'str'},
+ 'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'signals': {'key': 'signals', 'type': '{MonitoringSignalBase}'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword compute_id: Required. [Required] The ARM resource ID of the compute resource to run
+ the monitoring job on.
+ :paramtype compute_id: str
+ :keyword monitoring_target: The ARM resource ID of either the model or deployment targeted by
+ this monitor.
+ :paramtype monitoring_target: str
+ :keyword notification_setting: The monitor's notification settings.
+ :paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword signals: Required. [Required] The signals to monitor.
+ :paramtype signals: dict[str, ~azure.mgmt.machinelearningservices.models.MonitoringSignalBase]
+ """
+ super(MonitorDefinition, self).__init__(**kwargs)
+ self.compute_id = kwargs['compute_id']
+ self.monitoring_target = kwargs.get('monitoring_target', None)
+ self.notification_setting = kwargs.get('notification_setting', None)
+ self.signals = kwargs['signals']
+
+
+class MonitoringDataSegment(msrest.serialization.Model):
+ """MonitoringDataSegment.
+
+ :ivar feature: The feature to segment the data on.
+ :vartype feature: str
+ :ivar values: Filters for only the specified values of the given segmented feature.
+ :vartype values: list[str]
+ """
+
+ _attribute_map = {
+ 'feature': {'key': 'feature', 'type': 'str'},
+ 'values': {'key': 'values', 'type': '[str]'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword feature: The feature to segment the data on.
+ :paramtype feature: str
+ :keyword values: Filters for only the specified values of the given segmented feature.
+ :paramtype values: list[str]
+ """
+ super(MonitoringDataSegment, self).__init__(**kwargs)
+ self.feature = kwargs.get('feature', None)
+ self.values = kwargs.get('values', None)
+
+
+class MonitoringInputData(msrest.serialization.Model):
+ """MonitoringInputData.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar asset: The data asset input to be leveraged by the monitoring job..
+ :vartype asset: any
+ :ivar data_context: Required. [Required] The context of the data source. Possible values
+ include: "ModelInputs", "ModelOutputs", "Training", "Test", "Validation", "GroundTruth".
+ :vartype data_context: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputDataContext
+ :ivar preprocessing_component_id: The ARM resource ID of the component resource used to
+ preprocess the data.
+ :vartype preprocessing_component_id: str
+ """
+
+ _validation = {
+ 'data_context': {'required': True},
+ }
+
+ _attribute_map = {
+ 'asset': {'key': 'asset', 'type': 'object'},
+ 'data_context': {'key': 'dataContext', 'type': 'str'},
+ 'preprocessing_component_id': {'key': 'preprocessingComponentId', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
"""
- super(ModelVersionProperties, self).__init__(**kwargs)
- self.flavors = kwargs.get('flavors', None)
- self.job_name = kwargs.get('job_name', None)
- self.model_type = kwargs.get('model_type', None)
- self.model_uri = kwargs.get('model_uri', None)
- self.provisioning_state = None
+ :keyword asset: The data asset input to be leveraged by the monitoring job..
+ :paramtype asset: any
+ :keyword data_context: Required. [Required] The context of the data source. Possible values
+ include: "ModelInputs", "ModelOutputs", "Training", "Test", "Validation", "GroundTruth".
+ :paramtype data_context: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputDataContext
+ :keyword preprocessing_component_id: The ARM resource ID of the component resource used to
+ preprocess the data.
+ :paramtype preprocessing_component_id: str
+ """
+ super(MonitoringInputData, self).__init__(**kwargs)
+ self.asset = kwargs.get('asset', None)
+ self.data_context = kwargs['data_context']
+ self.preprocessing_component_id = kwargs.get('preprocessing_component_id', None)
-class ModelVersionResourceArmPaginatedResult(msrest.serialization.Model):
- """A paginated list of ModelVersion entities.
+class MonitoringThreshold(msrest.serialization.Model):
+ """MonitoringThreshold.
- :ivar next_link: The link to the next page of ModelVersion objects. If null, there are no
- additional pages.
- :vartype next_link: str
- :ivar value: An array of objects of type ModelVersion.
- :vartype value: list[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :ivar value: The threshold value. If null, the set default is dependent on the metric type.
+ :vartype value: float
"""
_attribute_map = {
- 'next_link': {'key': 'nextLink', 'type': 'str'},
- 'value': {'key': 'value', 'type': '[ModelVersion]'},
+ 'value': {'key': 'value', 'type': 'float'},
}
def __init__(
@@ -17231,14 +19323,10 @@ def __init__(
**kwargs
):
"""
- :keyword next_link: The link to the next page of ModelVersion objects. If null, there are no
- additional pages.
- :paramtype next_link: str
- :keyword value: An array of objects of type ModelVersion.
- :paramtype value: list[~azure.mgmt.machinelearningservices.models.ModelVersion]
+ :keyword value: The threshold value. If null, the set default is dependent on the metric type.
+ :paramtype value: float
"""
- super(ModelVersionResourceArmPaginatedResult, self).__init__(**kwargs)
- self.next_link = kwargs.get('next_link', None)
+ super(MonitoringThreshold, self).__init__(**kwargs)
self.value = kwargs.get('value', None)
@@ -17248,7 +19336,8 @@ class Mpi(DistributionConfiguration):
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
:ivar process_count_per_instance: Number of processes per MPI node.
:vartype process_count_per_instance: int
@@ -17864,17 +19953,21 @@ def __init__(
class NotificationSetting(msrest.serialization.Model):
"""Configuration for notification.
- :ivar email_on: Send email notification to user on specified notification type.
+ :ivar email_on: Send email notification to user on specified notfication type.
:vartype email_on: list[str or
~azure.mgmt.machinelearningservices.models.EmailNotificationEnableType]
:ivar emails: This is the email recipient list which has a limitation of 499 characters in
- total concat with comma separator.
+ total concat with comma seperator.
:vartype emails: list[str]
+ :ivar webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :vartype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
"""
_attribute_map = {
'email_on': {'key': 'emailOn', 'type': '[str]'},
'emails': {'key': 'emails', 'type': '[str]'},
+ 'webhooks': {'key': 'webhooks', 'type': '{Webhook}'},
}
def __init__(
@@ -17882,16 +19975,158 @@ def __init__(
**kwargs
):
"""
- :keyword email_on: Send email notification to user on specified notification type.
+ :keyword email_on: Send email notification to user on specified notfication type.
:paramtype email_on: list[str or
~azure.mgmt.machinelearningservices.models.EmailNotificationEnableType]
:keyword emails: This is the email recipient list which has a limitation of 499 characters in
- total concat with comma separator.
+ total concat with comma seperator.
:paramtype emails: list[str]
+ :keyword webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :paramtype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
"""
super(NotificationSetting, self).__init__(**kwargs)
self.email_on = kwargs.get('email_on', None)
self.emails = kwargs.get('emails', None)
+ self.webhooks = kwargs.get('webhooks', None)
+
+
+class NumericalDataDriftMetricThreshold(DataDriftMetricThresholdBase):
+ """NumericalDataDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The numerical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataDriftMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The numerical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataDriftMetric
+ """
+ super(NumericalDataDriftMetricThreshold, self).__init__(**kwargs)
+ self.data_type = 'Numerical' # type: str
+ self.metric = kwargs['metric']
+
+
+class NumericalDataQualityMetricThreshold(DataQualityMetricThresholdBase):
+ """NumericalDataQualityMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The numerical data quality metric to calculate. Possible
+ values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataQualityMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The numerical data quality metric to calculate. Possible
+ values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataQualityMetric
+ """
+ super(NumericalDataQualityMetricThreshold, self).__init__(**kwargs)
+ self.data_type = 'Numerical' # type: str
+ self.metric = kwargs['metric']
+
+
+class NumericalPredictionDriftMetricThreshold(PredictionDriftMetricThresholdBase):
+ """NumericalPredictionDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The numerical prediction drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.NumericalPredictionDriftMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The numerical prediction drift metric to calculate.
+ Possible values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.NumericalPredictionDriftMetric
+ """
+ super(NumericalPredictionDriftMetricThreshold, self).__init__(**kwargs)
+ self.data_type = 'Numerical' # type: str
+ self.metric = kwargs['metric']
class Objective(msrest.serialization.Model):
@@ -17908,7 +20143,7 @@ class Objective(msrest.serialization.Model):
_validation = {
'goal': {'required': True},
- 'primary_metric': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'primary_metric': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -17932,6 +20167,101 @@ def __init__(
self.primary_metric = kwargs['primary_metric']
+class OneLakeDatastore(DatastoreProperties):
+ """OneLake (Trident) datastore configuration.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar credentials: Required. [Required] Account credentials.
+ :vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
+ by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
+ "AzureFile", "Hdfs", "OneLake".
+ :vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar is_default: Readonly property to indicate if datastore is the workspace default
+ datastore.
+ :vartype is_default: bool
+ :ivar artifact: Required. [Required] OneLake artifact backing the datastore.
+ :vartype artifact: ~azure.mgmt.machinelearningservices.models.OneLakeArtifact
+ :ivar endpoint: OneLake endpoint to use for the datastore.
+ :vartype endpoint: str
+ :ivar one_lake_workspace_name: Required. [Required] OneLake workspace name.
+ :vartype one_lake_workspace_name: str
+ :ivar service_data_access_auth_identity: Indicates which identity to use to authenticate
+ service data access to customer's storage. Possible values include: "None",
+ "WorkspaceSystemAssignedIdentity", "WorkspaceUserAssignedIdentity".
+ :vartype service_data_access_auth_identity: str or
+ ~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
+ """
+
+ _validation = {
+ 'credentials': {'required': True},
+ 'datastore_type': {'required': True},
+ 'is_default': {'readonly': True},
+ 'artifact': {'required': True},
+ 'one_lake_workspace_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'description': {'key': 'description', 'type': 'str'},
+ 'properties': {'key': 'properties', 'type': '{str}'},
+ 'tags': {'key': 'tags', 'type': '{str}'},
+ 'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
+ 'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'is_default': {'key': 'isDefault', 'type': 'bool'},
+ 'artifact': {'key': 'artifact', 'type': 'OneLakeArtifact'},
+ 'endpoint': {'key': 'endpoint', 'type': 'str'},
+ 'one_lake_workspace_name': {'key': 'oneLakeWorkspaceName', 'type': 'str'},
+ 'service_data_access_auth_identity': {'key': 'serviceDataAccessAuthIdentity', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword description: The asset description text.
+ :paramtype description: str
+ :keyword properties: The asset property dictionary.
+ :paramtype properties: dict[str, str]
+ :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :paramtype tags: dict[str, str]
+ :keyword credentials: Required. [Required] Account credentials.
+ :paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword artifact: Required. [Required] OneLake artifact backing the datastore.
+ :paramtype artifact: ~azure.mgmt.machinelearningservices.models.OneLakeArtifact
+ :keyword endpoint: OneLake endpoint to use for the datastore.
+ :paramtype endpoint: str
+ :keyword one_lake_workspace_name: Required. [Required] OneLake workspace name.
+ :paramtype one_lake_workspace_name: str
+ :keyword service_data_access_auth_identity: Indicates which identity to use to authenticate
+ service data access to customer's storage. Possible values include: "None",
+ "WorkspaceSystemAssignedIdentity", "WorkspaceUserAssignedIdentity".
+ :paramtype service_data_access_auth_identity: str or
+ ~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
+ """
+ super(OneLakeDatastore, self).__init__(**kwargs)
+ self.datastore_type = 'OneLake' # type: str
+ self.artifact = kwargs['artifact']
+ self.endpoint = kwargs.get('endpoint', None)
+ self.one_lake_workspace_name = kwargs['one_lake_workspace_name']
+ self.service_data_access_auth_identity = kwargs.get('service_data_access_auth_identity', None)
+
+
class OnlineDeployment(TrackedResource):
"""OnlineDeployment.
@@ -18560,7 +20890,7 @@ class PackageRequest(msrest.serialization.Model):
_validation = {
'inferencing_server': {'required': True},
- 'target_environment_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'target_environment_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -18774,6 +21104,54 @@ def __init__(
self.tags = kwargs.get('tags', None)
+class PartialJobBase(msrest.serialization.Model):
+ """Mutable base definition for a job.
+
+ :ivar partial_notification_setting: Mutable notification setting for the job.
+ :vartype partial_notification_setting:
+ ~azure.mgmt.machinelearningservices.models.PartialNotificationSetting
+ """
+
+ _attribute_map = {
+ 'partial_notification_setting': {'key': 'partialNotificationSetting', 'type': 'PartialNotificationSetting'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword partial_notification_setting: Mutable notification setting for the job.
+ :paramtype partial_notification_setting:
+ ~azure.mgmt.machinelearningservices.models.PartialNotificationSetting
+ """
+ super(PartialJobBase, self).__init__(**kwargs)
+ self.partial_notification_setting = kwargs.get('partial_notification_setting', None)
+
+
+class PartialJobBasePartialResource(msrest.serialization.Model):
+ """Azure Resource Manager resource envelope strictly used in update requests.
+
+ :ivar properties: Additional attributes of the entity.
+ :vartype properties: ~azure.mgmt.machinelearningservices.models.PartialJobBase
+ """
+
+ _attribute_map = {
+ 'properties': {'key': 'properties', 'type': 'PartialJobBase'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword properties: Additional attributes of the entity.
+ :paramtype properties: ~azure.mgmt.machinelearningservices.models.PartialJobBase
+ """
+ super(PartialJobBasePartialResource, self).__init__(**kwargs)
+ self.properties = kwargs.get('properties', None)
+
+
class PartialManagedServiceIdentity(msrest.serialization.Model):
"""Managed service identity (system assigned and/or user assigned identities).
@@ -18892,6 +21270,31 @@ def __init__(
self.sku = kwargs.get('sku', None)
+class PartialNotificationSetting(msrest.serialization.Model):
+ """Mutable configuration for notification.
+
+ :ivar webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :vartype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
+ """
+
+ _attribute_map = {
+ 'webhooks': {'key': 'webhooks', 'type': '{Webhook}'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :paramtype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
+ """
+ super(PartialNotificationSetting, self).__init__(**kwargs)
+ self.webhooks = kwargs.get('webhooks', None)
+
+
class PartialRegistryPartialTrackedResource(msrest.serialization.Model):
"""Strictly used in update requests.
@@ -19087,9 +21490,119 @@ def __init__(
:paramtype credentials:
~azure.mgmt.machinelearningservices.models.WorkspaceConnectionPersonalAccessToken
"""
- super(PATAuthTypeWorkspaceConnectionProperties, self).__init__(**kwargs)
- self.auth_type = 'PAT' # type: str
- self.credentials = kwargs.get('credentials', None)
+ super(PATAuthTypeWorkspaceConnectionProperties, self).__init__(**kwargs)
+ self.auth_type = 'PAT' # type: str
+ self.credentials = kwargs.get('credentials', None)
+
+
+class PendingUploadCredentialDto(msrest.serialization.Model):
+ """PendingUploadCredentialDto.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: SASCredentialDto.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credential_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "SAS".
+ :vartype credential_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialType
+ """
+
+ _validation = {
+ 'credential_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'credential_type': {'key': 'credentialType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'credential_type': {'SAS': 'SASCredentialDto'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(PendingUploadCredentialDto, self).__init__(**kwargs)
+ self.credential_type = None # type: Optional[str]
+
+
+class PendingUploadRequestDto(msrest.serialization.Model):
+ """PendingUploadRequestDto.
+
+ :ivar pending_upload_id: If PendingUploadId = null then random guid will be used.
+ :vartype pending_upload_id: str
+ :ivar pending_upload_type: TemporaryBlobReference is the only supported type. Possible values
+ include: "None", "TemporaryBlobReference".
+ :vartype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+
+ _attribute_map = {
+ 'pending_upload_id': {'key': 'pendingUploadId', 'type': 'str'},
+ 'pending_upload_type': {'key': 'pendingUploadType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword pending_upload_id: If PendingUploadId = null then random guid will be used.
+ :paramtype pending_upload_id: str
+ :keyword pending_upload_type: TemporaryBlobReference is the only supported type. Possible
+ values include: "None", "TemporaryBlobReference".
+ :paramtype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+ super(PendingUploadRequestDto, self).__init__(**kwargs)
+ self.pending_upload_id = kwargs.get('pending_upload_id', None)
+ self.pending_upload_type = kwargs.get('pending_upload_type', None)
+
+
+class PendingUploadResponseDto(msrest.serialization.Model):
+ """PendingUploadResponseDto.
+
+ :ivar blob_reference_for_consumption: Container level read, write, list SAS.
+ :vartype blob_reference_for_consumption:
+ ~azure.mgmt.machinelearningservices.models.BlobReferenceForConsumptionDto
+ :ivar pending_upload_id: ID for this upload request.
+ :vartype pending_upload_id: str
+ :ivar pending_upload_type: TemporaryBlobReference is the only supported type. Possible values
+ include: "None", "TemporaryBlobReference".
+ :vartype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+
+ _attribute_map = {
+ 'blob_reference_for_consumption': {'key': 'blobReferenceForConsumption', 'type': 'BlobReferenceForConsumptionDto'},
+ 'pending_upload_id': {'key': 'pendingUploadId', 'type': 'str'},
+ 'pending_upload_type': {'key': 'pendingUploadType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword blob_reference_for_consumption: Container level read, write, list SAS.
+ :paramtype blob_reference_for_consumption:
+ ~azure.mgmt.machinelearningservices.models.BlobReferenceForConsumptionDto
+ :keyword pending_upload_id: ID for this upload request.
+ :paramtype pending_upload_id: str
+ :keyword pending_upload_type: TemporaryBlobReference is the only supported type. Possible
+ values include: "None", "TemporaryBlobReference".
+ :paramtype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+ super(PendingUploadResponseDto, self).__init__(**kwargs)
+ self.blob_reference_for_consumption = kwargs.get('blob_reference_for_consumption', None)
+ self.pending_upload_id = kwargs.get('pending_upload_id', None)
+ self.pending_upload_type = kwargs.get('pending_upload_type', None)
class PersonalComputeInstanceSettings(msrest.serialization.Model):
@@ -19148,6 +21661,9 @@ class PipelineJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -19184,6 +21700,7 @@ class PipelineJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'inputs': {'key': 'inputs', 'type': '{JobInput}'},
@@ -19221,6 +21738,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -19244,6 +21764,83 @@ def __init__(
self.source_job_id = kwargs.get('source_job_id', None)
+class PredictionDriftMonitoringSignal(MonitoringSignalBase):
+ """PredictionDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.PredictionDriftMetricThresholdBase]
+ :ivar model_type: Required. [Required] The type of the model monitored. Possible values
+ include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar target_data: Required. [Required] The data which drift will be calculatd for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_thresholds': {'required': True},
+ 'model_type': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[PredictionDriftMetricThresholdBase]'},
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.PredictionDriftMetricThresholdBase]
+ :keyword model_type: Required. [Required] The type of the model monitored. Possible values
+ include: "Classification", "Regression".
+ :paramtype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :keyword target_data: Required. [Required] The data which drift will be calculatd for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(PredictionDriftMonitoringSignal, self).__init__(**kwargs)
+ self.signal_type = 'PredictionDrift' # type: str
+ self.baseline_data = kwargs['baseline_data']
+ self.metric_thresholds = kwargs['metric_thresholds']
+ self.model_type = kwargs['model_type']
+ self.target_data = kwargs['target_data']
+
+
class PrivateEndpoint(msrest.serialization.Model):
"""The Private Endpoint resource.
@@ -19631,7 +22228,8 @@ class PyTorch(DistributionConfiguration):
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
:ivar process_count_per_instance: Number of processes per node.
:vartype process_count_per_instance: int
@@ -19812,6 +22410,71 @@ def __init__(
self.seed = kwargs.get('seed', None)
+class Ray(DistributionConfiguration):
+ """Ray distribution configuration.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar distribution_type: Required. [Required] Specifies the type of distribution
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
+ :vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
+ :ivar address: The address of Ray head node.
+ :vartype address: str
+ :ivar dashboard_port: The port to bind the dashboard server to.
+ :vartype dashboard_port: int
+ :ivar head_node_additional_args: Additional arguments passed to ray start in head node.
+ :vartype head_node_additional_args: str
+ :ivar include_dashboard: Provide this argument to start the Ray dashboard GUI.
+ :vartype include_dashboard: bool
+ :ivar port: The port of the head ray process.
+ :vartype port: int
+ :ivar worker_node_additional_args: Additional arguments passed to ray start in worker node.
+ :vartype worker_node_additional_args: str
+ """
+
+ _validation = {
+ 'distribution_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'distribution_type': {'key': 'distributionType', 'type': 'str'},
+ 'address': {'key': 'address', 'type': 'str'},
+ 'dashboard_port': {'key': 'dashboardPort', 'type': 'int'},
+ 'head_node_additional_args': {'key': 'headNodeAdditionalArgs', 'type': 'str'},
+ 'include_dashboard': {'key': 'includeDashboard', 'type': 'bool'},
+ 'port': {'key': 'port', 'type': 'int'},
+ 'worker_node_additional_args': {'key': 'workerNodeAdditionalArgs', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword address: The address of Ray head node.
+ :paramtype address: str
+ :keyword dashboard_port: The port to bind the dashboard server to.
+ :paramtype dashboard_port: int
+ :keyword head_node_additional_args: Additional arguments passed to ray start in head node.
+ :paramtype head_node_additional_args: str
+ :keyword include_dashboard: Provide this argument to start the Ray dashboard GUI.
+ :paramtype include_dashboard: bool
+ :keyword port: The port of the head ray process.
+ :paramtype port: int
+ :keyword worker_node_additional_args: Additional arguments passed to ray start in worker node.
+ :paramtype worker_node_additional_args: str
+ """
+ super(Ray, self).__init__(**kwargs)
+ self.distribution_type = 'Ray' # type: str
+ self.address = kwargs.get('address', None)
+ self.dashboard_port = kwargs.get('dashboard_port', None)
+ self.head_node_additional_args = kwargs.get('head_node_additional_args', None)
+ self.include_dashboard = kwargs.get('include_dashboard', None)
+ self.port = kwargs.get('port', None)
+ self.worker_node_additional_args = kwargs.get('worker_node_additional_args', None)
+
+
class RecurrenceSchedule(msrest.serialization.Model):
"""RecurrenceSchedule.
@@ -20416,6 +23079,52 @@ def __init__(
self.training_data = kwargs['training_data']
+class RegressionModelPerformanceMetricThreshold(ModelPerformanceMetricThresholdBase):
+ """RegressionModelPerformanceMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar model_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The regression model performance metric to calculate.
+ Possible values include: "MeanAbsoluteError", "RootMeanSquaredError", "MeanSquaredError".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.RegressionModelPerformanceMetric
+ """
+
+ _validation = {
+ 'model_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The regression model performance metric to calculate.
+ Possible values include: "MeanAbsoluteError", "RootMeanSquaredError", "MeanSquaredError".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.RegressionModelPerformanceMetric
+ """
+ super(RegressionModelPerformanceMetricThreshold, self).__init__(**kwargs)
+ self.model_type = 'Regression' # type: str
+ self.metric = kwargs['metric']
+
+
class RegressionTrainingSettings(TrainingSettings):
"""Regression Training related configuration.
@@ -20507,6 +23216,33 @@ def __init__(
self.blocked_training_algorithms = kwargs.get('blocked_training_algorithms', None)
+class RequestLogging(msrest.serialization.Model):
+ """RequestLogging.
+
+ :ivar capture_headers: For payload logging, we only collect payload by default. If customers
+ also want to collect the specified headers, they can set them in captureHeaders so that backend
+ will collect those headers along with payload.
+ :vartype capture_headers: list[str]
+ """
+
+ _attribute_map = {
+ 'capture_headers': {'key': 'captureHeaders', 'type': '[str]'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword capture_headers: For payload logging, we only collect payload by default. If customers
+ also want to collect the specified headers, they can set them in captureHeaders so that backend
+ will collect those headers along with payload.
+ :paramtype capture_headers: list[str]
+ """
+ super(RequestLogging, self).__init__(**kwargs)
+ self.capture_headers = kwargs.get('capture_headers', None)
+
+
class ResourceId(msrest.serialization.Model):
"""Represents a resource ID. For example, for a subnet, it is the resource URL for the subnet.
@@ -20632,7 +23368,7 @@ class Route(msrest.serialization.Model):
"""
_validation = {
- 'path': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'path': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'port': {'required': True},
}
@@ -20718,6 +23454,53 @@ def __init__(
self.credentials = kwargs.get('credentials', None)
+class SASCredentialDto(PendingUploadCredentialDto):
+ """SASCredentialDto.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credential_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "SAS".
+ :vartype credential_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialType
+ :ivar sas_uri: Full SAS Uri, including the storage, container/blob path and SAS token.
+ :vartype sas_uri: str
+ :ivar wasbs_uri: Windows Azure Storage Blob formatted uri for mounting containers at root, a
+ subdirectory, or a specific file
+ example wasbs://[container_name]@[account_name].blob.core.windows.net/[path]?sas=[sas]
+ For now, the URI will just be the root path ([path] will be empty).
+ :vartype wasbs_uri: str
+ """
+
+ _validation = {
+ 'credential_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'credential_type': {'key': 'credentialType', 'type': 'str'},
+ 'sas_uri': {'key': 'sasUri', 'type': 'str'},
+ 'wasbs_uri': {'key': 'wasbsUri', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword sas_uri: Full SAS Uri, including the storage, container/blob path and SAS token.
+ :paramtype sas_uri: str
+ :keyword wasbs_uri: Windows Azure Storage Blob formatted uri for mounting containers at root, a
+ subdirectory, or a specific file
+ example wasbs://[container_name]@[account_name].blob.core.windows.net/[path]?sas=[sas]
+ For now, the URI will just be the root path ([path] will be empty).
+ :paramtype wasbs_uri: str
+ """
+ super(SASCredentialDto, self).__init__(**kwargs)
+ self.credential_type = 'SAS' # type: str
+ self.sas_uri = kwargs.get('sas_uri', None)
+ self.wasbs_uri = kwargs.get('wasbs_uri', None)
+
+
class SasDatastoreCredentials(DatastoreCredentials):
"""SAS datastore credentials configuration.
@@ -21119,6 +23902,37 @@ def __init__(
self.creation_script = kwargs.get('creation_script', None)
+class SecretConfiguration(msrest.serialization.Model):
+ """Secret Configuration definition.
+
+ :ivar uri: Secret Uri.
+ Sample Uri : https://myvault.vault.azure.net/secrets/mysecretname/secretversion.
+ :vartype uri: str
+ :ivar workspace_secret_name: Name of secret in workspace key vault.
+ :vartype workspace_secret_name: str
+ """
+
+ _attribute_map = {
+ 'uri': {'key': 'uri', 'type': 'str'},
+ 'workspace_secret_name': {'key': 'workspaceSecretName', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword uri: Secret Uri.
+ Sample Uri : https://myvault.vault.azure.net/secrets/mysecretname/secretversion.
+ :paramtype uri: str
+ :keyword workspace_secret_name: Name of secret in workspace key vault.
+ :paramtype workspace_secret_name: str
+ """
+ super(SecretConfiguration, self).__init__(**kwargs)
+ self.uri = kwargs.get('uri', None)
+ self.workspace_secret_name = kwargs.get('workspace_secret_name', None)
+
+
class ServiceManagedResourcesSettings(msrest.serialization.Model):
"""ServiceManagedResourcesSettings.
@@ -21554,6 +24368,76 @@ def __init__(
self.value = kwargs.get('value', None)
+class SkuResourceArmPaginatedResultAutoGenerated(msrest.serialization.Model):
+ """A paginated list of SkuResource entities.
+
+ :ivar next_link: The link to the next page of SkuResource objects. If null, there are no
+ additional pages.
+ :vartype next_link: str
+ :ivar value: An array of objects of type SkuResource.
+ :vartype value: list[~azure.mgmt.machinelearningservices.models.SkuResourceAutoGenerated]
+ """
+
+ _attribute_map = {
+ 'next_link': {'key': 'nextLink', 'type': 'str'},
+ 'value': {'key': 'value', 'type': '[SkuResourceAutoGenerated]'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword next_link: The link to the next page of SkuResource objects. If null, there are no
+ additional pages.
+ :paramtype next_link: str
+ :keyword value: An array of objects of type SkuResource.
+ :paramtype value: list[~azure.mgmt.machinelearningservices.models.SkuResourceAutoGenerated]
+ """
+ super(SkuResourceArmPaginatedResultAutoGenerated, self).__init__(**kwargs)
+ self.next_link = kwargs.get('next_link', None)
+ self.value = kwargs.get('value', None)
+
+
+class SkuResourceAutoGenerated(msrest.serialization.Model):
+ """Fulfills ARM Contract requirement to list all available SKUS for a resource.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ :ivar capacity: Gets or sets the Sku Capacity.
+ :vartype capacity: ~azure.mgmt.machinelearningservices.models.SkuCapacity
+ :ivar resource_type: The resource type name.
+ :vartype resource_type: str
+ :ivar sku: Gets or sets the Sku.
+ :vartype sku: ~azure.mgmt.machinelearningservices.models.SkuSettingAutoGenerated
+ """
+
+ _validation = {
+ 'resource_type': {'readonly': True},
+ }
+
+ _attribute_map = {
+ 'capacity': {'key': 'capacity', 'type': 'SkuCapacity'},
+ 'resource_type': {'key': 'resourceType', 'type': 'str'},
+ 'sku': {'key': 'sku', 'type': 'SkuSettingAutoGenerated'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword capacity: Gets or sets the Sku Capacity.
+ :paramtype capacity: ~azure.mgmt.machinelearningservices.models.SkuCapacity
+ :keyword sku: Gets or sets the Sku.
+ :paramtype sku: ~azure.mgmt.machinelearningservices.models.SkuSettingAutoGenerated
+ """
+ super(SkuResourceAutoGenerated, self).__init__(**kwargs)
+ self.capacity = kwargs.get('capacity', None)
+ self.resource_type = None
+ self.sku = kwargs.get('sku', None)
+
+
class SkuSetting(msrest.serialization.Model):
"""SkuSetting fulfills the need for stripped down SKU info in ARM contract.
@@ -21569,7 +24453,7 @@ class SkuSetting(msrest.serialization.Model):
"""
_validation = {
- 'name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -21595,6 +24479,47 @@ def __init__(
self.tier = kwargs.get('tier', None)
+class SkuSettingAutoGenerated(msrest.serialization.Model):
+ """SkuSetting fulfills the need for stripped down SKU info in ARM contract.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar name: Required. [Required] The name of the SKU. Ex - P3. It is typically a letter+number
+ code.
+ :vartype name: str
+ :ivar tier: This field is required to be implemented by the Resource Provider if the service
+ has more than one tier, but is not required on a PUT. Possible values include: "Free", "Basic",
+ "Standard", "Premium".
+ :vartype tier: str or ~azure.mgmt.machinelearningservices.models.SkuTier
+ """
+
+ _validation = {
+ 'name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'name': {'key': 'name', 'type': 'str'},
+ 'tier': {'key': 'tier', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword name: Required. [Required] The name of the SKU. Ex - P3. It is typically a
+ letter+number code.
+ :paramtype name: str
+ :keyword tier: This field is required to be implemented by the Resource Provider if the service
+ has more than one tier, but is not required on a PUT. Possible values include: "Free", "Basic",
+ "Standard", "Premium".
+ :paramtype tier: str or ~azure.mgmt.machinelearningservices.models.SkuTier
+ """
+ super(SkuSettingAutoGenerated, self).__init__(**kwargs)
+ self.name = kwargs['name']
+ self.tier = kwargs.get('tier', None)
+
+
class SparkJob(JobBaseProperties):
"""Spark job definition.
@@ -21628,6 +24553,9 @@ class SparkJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -21666,7 +24594,7 @@ class SparkJob(JobBaseProperties):
_validation = {
'job_type': {'required': True},
'status': {'readonly': True},
- 'code_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'code_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'entry': {'required': True},
}
@@ -21682,6 +24610,7 @@ class SparkJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'archives': {'key': 'archives', 'type': '[str]'},
@@ -21727,6 +24656,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -22124,6 +25056,9 @@ class SweepJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -22174,6 +25109,7 @@ class SweepJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'early_termination': {'key': 'earlyTermination', 'type': 'EarlyTerminationPolicy'},
@@ -22215,6 +25151,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -23181,7 +26120,8 @@ class TensorFlow(DistributionConfiguration):
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
:ivar parameter_server_count: Number of parameter server tasks.
:vartype parameter_server_count: int
@@ -23561,6 +26501,42 @@ def __init__(
self.size = kwargs.get('size', None)
+class TopNFeaturesByAttribution(MonitoringFeatureFilterBase):
+ """TopNFeaturesByAttribution.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ :ivar top: The number of top features to include.
+ :vartype top: int
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ 'top': {'key': 'top', 'type': 'int'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ :keyword top: The number of top features to include.
+ :paramtype top: int
+ """
+ super(TopNFeaturesByAttribution, self).__init__(**kwargs)
+ self.filter_type = 'TopNByAttribution' # type: str
+ self.top = kwargs.get('top', 10)
+
+
class TrialComponent(msrest.serialization.Model):
"""Trial component definition.
@@ -23585,7 +26561,7 @@ class TrialComponent(msrest.serialization.Model):
_validation = {
'command': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
- 'environment_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'environment_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -23682,7 +26658,7 @@ class TritonModelJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -23722,6 +26698,8 @@ class TritonModelJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -23742,6 +26720,7 @@ class TritonModelJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -23757,6 +26736,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -23768,6 +26749,7 @@ def __init__(
super(TritonModelJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
self.job_output_type = 'triton_model' # type: str
@@ -23918,9 +26900,13 @@ class UriFileDataVersion(DataVersionBaseProperties):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
Possible values include: "uri_file", "uri_folder", "mltable".
@@ -23928,21 +26914,29 @@ class UriFileDataVersion(DataVersionBaseProperties):
:ivar data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
"""
_validation = {
'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'data_type': {'key': 'dataType', 'type': 'str'},
'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -23956,13 +26950,23 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
"""
super(UriFileDataVersion, self).__init__(**kwargs)
self.data_type = 'uri_file' # type: str
@@ -23987,7 +26991,7 @@ class UriFileJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -24027,6 +27031,8 @@ class UriFileJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -24047,6 +27053,7 @@ class UriFileJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -24062,6 +27069,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -24073,6 +27082,7 @@ def __init__(
super(UriFileJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
self.job_output_type = 'uri_file' # type: str
@@ -24090,9 +27100,13 @@ class UriFolderDataVersion(DataVersionBaseProperties):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
Possible values include: "uri_file", "uri_folder", "mltable".
@@ -24100,21 +27114,29 @@ class UriFolderDataVersion(DataVersionBaseProperties):
:ivar data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
"""
_validation = {
'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'data_type': {'key': 'dataType', 'type': 'str'},
'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -24128,13 +27150,23 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
"""
super(UriFolderDataVersion, self).__init__(**kwargs)
self.data_type = 'uri_folder' # type: str
@@ -24159,7 +27191,7 @@ class UriFolderJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -24199,6 +27231,8 @@ class UriFolderJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -24219,6 +27253,7 @@ class UriFolderJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -24234,6 +27269,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -24245,6 +27282,7 @@ def __init__(
super(UriFolderJobOutput, self).__init__(**kwargs)
self.asset_name = kwargs.get('asset_name', None)
self.asset_version = kwargs.get('asset_version', None)
+ self.auto_delete_setting = kwargs.get('auto_delete_setting', None)
self.mode = kwargs.get('mode', None)
self.uri = kwargs.get('uri', None)
self.job_output_type = 'uri_folder' # type: str
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py
index 6c6866faf820..d97b2f796c51 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py
@@ -839,6 +839,73 @@ def __init__(
self.load_balancer_subnet = load_balancer_subnet
+class MonitoringFeatureFilterBase(msrest.serialization.Model):
+ """MonitoringFeatureFilterBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: AllFeatures, FeatureSubset, TopNFeaturesByAttribution.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'filter_type': {'AllFeatures': 'AllFeatures', 'FeatureSubset': 'FeatureSubset', 'TopNByAttribution': 'TopNFeaturesByAttribution'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(MonitoringFeatureFilterBase, self).__init__(**kwargs)
+ self.filter_type = None # type: Optional[str]
+
+
+class AllFeatures(MonitoringFeatureFilterBase):
+ """AllFeatures.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(AllFeatures, self).__init__(**kwargs)
+ self.filter_type = 'AllFeatures' # type: str
+
+
class Nodes(msrest.serialization.Model):
"""Abstract Nodes definition.
@@ -1572,9 +1639,13 @@ class AssetBase(ResourceBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
"""
@@ -1582,6 +1653,7 @@ class AssetBase(ResourceBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
}
@@ -1592,6 +1664,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
**kwargs
@@ -1603,12 +1676,17 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
"""
super(AssetBase, self).__init__(description=description, properties=properties, tags=tags, **kwargs)
+ self.auto_delete_setting = auto_delete_setting
self.is_anonymous = is_anonymous
self.is_archived = is_archived
@@ -1684,7 +1762,7 @@ class AssetJobInput(msrest.serialization.Model):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -1718,6 +1796,8 @@ class AssetJobOutput(msrest.serialization.Model):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -1728,6 +1808,7 @@ class AssetJobOutput(msrest.serialization.Model):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
}
@@ -1737,6 +1818,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
**kwargs
@@ -1746,6 +1828,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -1755,6 +1839,7 @@ def __init__(
super(AssetJobOutput, self).__init__(**kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
@@ -1833,6 +1918,40 @@ def __init__(
self.tenant_id = tenant_id
+class AutoDeleteSetting(msrest.serialization.Model):
+ """AutoDeleteSetting.
+
+ :ivar condition: When to check if an asset is expired. Possible values include:
+ "CreatedGreaterThan", "LastAccessedGreaterThan".
+ :vartype condition: str or ~azure.mgmt.machinelearningservices.models.AutoDeleteCondition
+ :ivar value: Expiration condition value.
+ :vartype value: str
+ """
+
+ _attribute_map = {
+ 'condition': {'key': 'condition', 'type': 'str'},
+ 'value': {'key': 'value', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ condition: Optional[Union[str, "AutoDeleteCondition"]] = None,
+ value: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword condition: When to check if an asset is expired. Possible values include:
+ "CreatedGreaterThan", "LastAccessedGreaterThan".
+ :paramtype condition: str or ~azure.mgmt.machinelearningservices.models.AutoDeleteCondition
+ :keyword value: Expiration condition value.
+ :paramtype value: str
+ """
+ super(AutoDeleteSetting, self).__init__(**kwargs)
+ self.condition = condition
+ self.value = value
+
+
class ForecastHorizon(msrest.serialization.Model):
"""The desired maximum forecast horizon in units of time-series frequency.
@@ -1967,6 +2086,9 @@ class JobBaseProperties(ResourceBase):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -1993,6 +2115,7 @@ class JobBaseProperties(ResourceBase):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
}
@@ -2014,6 +2137,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
**kwargs
):
@@ -2041,6 +2165,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -2054,6 +2181,7 @@ def __init__(
self.is_archived = is_archived
self.job_type = 'JobBaseProperties' # type: str
self.notification_setting = notification_setting
+ self.secrets_configuration = secrets_configuration
self.services = services
self.status = None
@@ -2093,6 +2221,9 @@ class AutoMLJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -2135,6 +2266,7 @@ class AutoMLJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'environment_id': {'key': 'environmentId', 'type': 'str'},
@@ -2159,6 +2291,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
environment_id: Optional[str] = None,
environment_variables: Optional[Dict[str, str]] = None,
@@ -2191,6 +2324,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -2210,7 +2346,7 @@ def __init__(
Tables/NLP/Image.
:paramtype task_details: ~azure.mgmt.machinelearningservices.models.AutoMLVertical
"""
- super(AutoMLJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, services=services, **kwargs)
+ super(AutoMLJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, secrets_configuration=secrets_configuration, services=services, **kwargs)
self.job_type = 'AutoML' # type: str
self.environment_id = environment_id
self.environment_variables = environment_variables
@@ -2644,7 +2780,7 @@ class DatastoreProperties(ResourceBase):
"""Base definition for datastore contents configuration.
You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: AzureBlobDatastore, AzureDataLakeGen1Datastore, AzureDataLakeGen2Datastore, AzureFileDatastore, HdfsDatastore.
+ sub-classes are: AzureBlobDatastore, AzureDataLakeGen1Datastore, AzureDataLakeGen2Datastore, AzureFileDatastore, HdfsDatastore, OneLakeDatastore.
Variables are only populated by the server, and will be ignored when sending a request.
@@ -2660,8 +2796,10 @@ class DatastoreProperties(ResourceBase):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2679,11 +2817,12 @@ class DatastoreProperties(ResourceBase):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
}
_subtype_map = {
- 'datastore_type': {'AzureBlob': 'AzureBlobDatastore', 'AzureDataLakeGen1': 'AzureDataLakeGen1Datastore', 'AzureDataLakeGen2': 'AzureDataLakeGen2Datastore', 'AzureFile': 'AzureFileDatastore', 'Hdfs': 'HdfsDatastore'}
+ 'datastore_type': {'AzureBlob': 'AzureBlobDatastore', 'AzureDataLakeGen1': 'AzureDataLakeGen1Datastore', 'AzureDataLakeGen2': 'AzureDataLakeGen2Datastore', 'AzureFile': 'AzureFileDatastore', 'Hdfs': 'HdfsDatastore', 'OneLake': 'OneLakeDatastore'}
}
def __init__(
@@ -2693,6 +2832,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
**kwargs
):
"""
@@ -2704,10 +2844,14 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
"""
super(DatastoreProperties, self).__init__(description=description, properties=properties, tags=tags, **kwargs)
self.credentials = credentials
self.datastore_type = 'DatastoreProperties' # type: str
+ self.intellectual_property = intellectual_property
self.is_default = None
@@ -2732,8 +2876,10 @@ class AzureBlobDatastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2766,6 +2912,7 @@ class AzureBlobDatastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'account_name': {'key': 'accountName', 'type': 'str'},
'container_name': {'key': 'containerName', 'type': 'str'},
@@ -2783,6 +2930,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
account_name: Optional[str] = None,
container_name: Optional[str] = None,
endpoint: Optional[str] = None,
@@ -2803,6 +2951,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword account_name: Storage account name.
:paramtype account_name: str
:keyword container_name: Storage account container name.
@@ -2817,7 +2968,7 @@ def __init__(
:paramtype service_data_access_auth_identity: str or
~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
"""
- super(AzureBlobDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
+ super(AzureBlobDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, intellectual_property=intellectual_property, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
self.resource_group = resource_group
self.subscription_id = subscription_id
self.datastore_type = 'AzureBlob' # type: str
@@ -2830,6 +2981,7 @@ def __init__(
self.properties = properties
self.tags = tags
self.credentials = credentials
+ self.intellectual_property = intellectual_property
self.is_default = None
@@ -2854,8 +3006,10 @@ class AzureDataLakeGen1Datastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2872,7 +3026,7 @@ class AzureDataLakeGen1Datastore(DatastoreProperties, AzureDatastore):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'store_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'store_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -2883,6 +3037,7 @@ class AzureDataLakeGen1Datastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'service_data_access_auth_identity': {'key': 'serviceDataAccessAuthIdentity', 'type': 'str'},
'store_name': {'key': 'storeName', 'type': 'str'},
@@ -2898,6 +3053,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
service_data_access_auth_identity: Optional[Union[str, "ServiceDataAccessAuthIdentity"]] = None,
**kwargs
):
@@ -2914,6 +3070,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword service_data_access_auth_identity: Indicates which identity to use to authenticate
service data access to customer's storage. Possible values include: "None",
"WorkspaceSystemAssignedIdentity", "WorkspaceUserAssignedIdentity".
@@ -2922,7 +3081,7 @@ def __init__(
:keyword store_name: Required. [Required] Azure Data Lake store name.
:paramtype store_name: str
"""
- super(AzureDataLakeGen1Datastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
+ super(AzureDataLakeGen1Datastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, intellectual_property=intellectual_property, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
self.resource_group = resource_group
self.subscription_id = subscription_id
self.datastore_type = 'AzureDataLakeGen1' # type: str
@@ -2932,6 +3091,7 @@ def __init__(
self.properties = properties
self.tags = tags
self.credentials = credentials
+ self.intellectual_property = intellectual_property
self.is_default = None
@@ -2956,8 +3116,10 @@ class AzureDataLakeGen2Datastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -2980,8 +3142,8 @@ class AzureDataLakeGen2Datastore(DatastoreProperties, AzureDatastore):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'account_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'filesystem': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'account_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'filesystem': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -2992,6 +3154,7 @@ class AzureDataLakeGen2Datastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'account_name': {'key': 'accountName', 'type': 'str'},
'endpoint': {'key': 'endpoint', 'type': 'str'},
@@ -3011,6 +3174,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
endpoint: Optional[str] = None,
protocol: Optional[str] = None,
service_data_access_auth_identity: Optional[Union[str, "ServiceDataAccessAuthIdentity"]] = None,
@@ -3029,6 +3193,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword account_name: Required. [Required] Storage account name.
:paramtype account_name: str
:keyword endpoint: Azure cloud endpoint for the storage account.
@@ -3043,7 +3210,7 @@ def __init__(
:paramtype service_data_access_auth_identity: str or
~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
"""
- super(AzureDataLakeGen2Datastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
+ super(AzureDataLakeGen2Datastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, intellectual_property=intellectual_property, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
self.resource_group = resource_group
self.subscription_id = subscription_id
self.datastore_type = 'AzureDataLakeGen2' # type: str
@@ -3056,9 +3223,88 @@ def __init__(
self.properties = properties
self.tags = tags
self.credentials = credentials
+ self.intellectual_property = intellectual_property
self.is_default = None
+class Webhook(msrest.serialization.Model):
+ """Webhook base.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: AzureDevOpsWebhook.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar event_type: Send callback on a specified notification event.
+ :vartype event_type: str
+ :ivar webhook_type: Required. [Required] Specifies the type of service to send a
+ callback.Constant filled by server. Possible values include: "AzureDevOps".
+ :vartype webhook_type: str or ~azure.mgmt.machinelearningservices.models.WebhookType
+ """
+
+ _validation = {
+ 'webhook_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'event_type': {'key': 'eventType', 'type': 'str'},
+ 'webhook_type': {'key': 'webhookType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'webhook_type': {'AzureDevOps': 'AzureDevOpsWebhook'}
+ }
+
+ def __init__(
+ self,
+ *,
+ event_type: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword event_type: Send callback on a specified notification event.
+ :paramtype event_type: str
+ """
+ super(Webhook, self).__init__(**kwargs)
+ self.event_type = event_type
+ self.webhook_type = None # type: Optional[str]
+
+
+class AzureDevOpsWebhook(Webhook):
+ """Webhook details specific for Azure DevOps.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar event_type: Send callback on a specified notification event.
+ :vartype event_type: str
+ :ivar webhook_type: Required. [Required] Specifies the type of service to send a
+ callback.Constant filled by server. Possible values include: "AzureDevOps".
+ :vartype webhook_type: str or ~azure.mgmt.machinelearningservices.models.WebhookType
+ """
+
+ _validation = {
+ 'webhook_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'event_type': {'key': 'eventType', 'type': 'str'},
+ 'webhook_type': {'key': 'webhookType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ event_type: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword event_type: Send callback on a specified notification event.
+ :paramtype event_type: str
+ """
+ super(AzureDevOpsWebhook, self).__init__(event_type=event_type, **kwargs)
+ self.webhook_type = 'AzureDevOps' # type: str
+
+
class AzureFileDatastore(DatastoreProperties, AzureDatastore):
"""Azure File datastore configuration.
@@ -3080,8 +3326,10 @@ class AzureFileDatastore(DatastoreProperties, AzureDatastore):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -3105,8 +3353,8 @@ class AzureFileDatastore(DatastoreProperties, AzureDatastore):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'account_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'file_share_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'account_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'file_share_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -3117,6 +3365,7 @@ class AzureFileDatastore(DatastoreProperties, AzureDatastore):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'account_name': {'key': 'accountName', 'type': 'str'},
'endpoint': {'key': 'endpoint', 'type': 'str'},
@@ -3136,6 +3385,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
endpoint: Optional[str] = None,
protocol: Optional[str] = None,
service_data_access_auth_identity: Optional[Union[str, "ServiceDataAccessAuthIdentity"]] = None,
@@ -3154,6 +3404,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword account_name: Required. [Required] Storage account name.
:paramtype account_name: str
:keyword endpoint: Azure cloud endpoint for the storage account.
@@ -3169,7 +3422,7 @@ def __init__(
:paramtype service_data_access_auth_identity: str or
~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
"""
- super(AzureFileDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
+ super(AzureFileDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, intellectual_property=intellectual_property, resource_group=resource_group, subscription_id=subscription_id, **kwargs)
self.resource_group = resource_group
self.subscription_id = subscription_id
self.datastore_type = 'AzureFile' # type: str
@@ -3182,6 +3435,7 @@ def __init__(
self.properties = properties
self.tags = tags
self.credentials = credentials
+ self.intellectual_property = intellectual_property
self.is_default = None
@@ -3450,7 +3704,7 @@ class BaseEnvironmentId(BaseEnvironmentSource):
_validation = {
'base_environment_source_type': {'required': True},
- 'resource_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'resource_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -4452,6 +4706,47 @@ def __init__(
self.selinux = selinux
+class BlobReferenceForConsumptionDto(msrest.serialization.Model):
+ """BlobReferenceForConsumptionDto.
+
+ :ivar blob_uri: Blob URI path for client to upload data.
+ Example: https://blob.windows.core.net/Container/Path.
+ :vartype blob_uri: str
+ :ivar credential: Credential info to access storage account.
+ :vartype credential: ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialDto
+ :ivar storage_account_arm_id: Arm ID of the storage account to use.
+ :vartype storage_account_arm_id: str
+ """
+
+ _attribute_map = {
+ 'blob_uri': {'key': 'blobUri', 'type': 'str'},
+ 'credential': {'key': 'credential', 'type': 'PendingUploadCredentialDto'},
+ 'storage_account_arm_id': {'key': 'storageAccountArmId', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ blob_uri: Optional[str] = None,
+ credential: Optional["PendingUploadCredentialDto"] = None,
+ storage_account_arm_id: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword blob_uri: Blob URI path for client to upload data.
+ Example: https://blob.windows.core.net/Container/Path.
+ :paramtype blob_uri: str
+ :keyword credential: Credential info to access storage account.
+ :paramtype credential: ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialDto
+ :keyword storage_account_arm_id: Arm ID of the storage account to use.
+ :paramtype storage_account_arm_id: str
+ """
+ super(BlobReferenceForConsumptionDto, self).__init__(**kwargs)
+ self.blob_uri = blob_uri
+ self.credential = credential
+ self.storage_account_arm_id = storage_account_arm_id
+
+
class BuildContext(msrest.serialization.Model):
"""Configuration settings for Docker build context.
@@ -4476,7 +4771,7 @@ class BuildContext(msrest.serialization.Model):
"""
_validation = {
- 'context_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'context_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -4514,165 +4809,446 @@ def __init__(
self.dockerfile_path = dockerfile_path
-class CertificateDatastoreCredentials(DatastoreCredentials):
- """Certificate datastore credentials configuration.
+class DataDriftMetricThresholdBase(msrest.serialization.Model):
+ """DataDriftMetricThresholdBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CategoricalDataDriftMetricThreshold, NumericalDataDriftMetricThreshold.
All required parameters must be populated in order to send to Azure.
- :ivar credentials_type: Required. [Required] Credential type used to authentication with
- storage.Constant filled by server. Possible values include: "AccountKey", "Certificate",
- "None", "Sas", "ServicePrincipal", "KerberosKeytab", "KerberosPassword".
- :vartype credentials_type: str or ~azure.mgmt.machinelearningservices.models.CredentialsType
- :ivar authority_url: Authority URL used for authentication.
- :vartype authority_url: str
- :ivar client_id: Required. [Required] Service principal client ID.
- :vartype client_id: str
- :ivar resource_url: Resource the service principal has access to.
- :vartype resource_url: str
- :ivar secrets: Required. [Required] Service principal secrets.
- :vartype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
- :ivar tenant_id: Required. [Required] ID of the tenant to which the service principal belongs.
- :vartype tenant_id: str
- :ivar thumbprint: Required. [Required] Thumbprint of the certificate used for authentication.
- :vartype thumbprint: str
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
"""
_validation = {
- 'credentials_type': {'required': True},
- 'client_id': {'required': True},
- 'secrets': {'required': True},
- 'tenant_id': {'required': True},
- 'thumbprint': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_type': {'required': True},
}
_attribute_map = {
- 'credentials_type': {'key': 'credentialsType', 'type': 'str'},
- 'authority_url': {'key': 'authorityUrl', 'type': 'str'},
- 'client_id': {'key': 'clientId', 'type': 'str'},
- 'resource_url': {'key': 'resourceUrl', 'type': 'str'},
- 'secrets': {'key': 'secrets', 'type': 'CertificateDatastoreSecrets'},
- 'tenant_id': {'key': 'tenantId', 'type': 'str'},
- 'thumbprint': {'key': 'thumbprint', 'type': 'str'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'Categorical': 'CategoricalDataDriftMetricThreshold', 'Numerical': 'NumericalDataDriftMetricThreshold'}
}
def __init__(
self,
*,
- client_id: str,
- secrets: "CertificateDatastoreSecrets",
- tenant_id: str,
- thumbprint: str,
- authority_url: Optional[str] = None,
- resource_url: Optional[str] = None,
+ threshold: Optional["MonitoringThreshold"] = None,
**kwargs
):
"""
- :keyword authority_url: Authority URL used for authentication.
- :paramtype authority_url: str
- :keyword client_id: Required. [Required] Service principal client ID.
- :paramtype client_id: str
- :keyword resource_url: Resource the service principal has access to.
- :paramtype resource_url: str
- :keyword secrets: Required. [Required] Service principal secrets.
- :paramtype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
- :keyword tenant_id: Required. [Required] ID of the tenant to which the service principal
- belongs.
- :paramtype tenant_id: str
- :keyword thumbprint: Required. [Required] Thumbprint of the certificate used for
- authentication.
- :paramtype thumbprint: str
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
"""
- super(CertificateDatastoreCredentials, self).__init__(**kwargs)
- self.credentials_type = 'Certificate' # type: str
- self.authority_url = authority_url
- self.client_id = client_id
- self.resource_url = resource_url
- self.secrets = secrets
- self.tenant_id = tenant_id
- self.thumbprint = thumbprint
+ super(DataDriftMetricThresholdBase, self).__init__(**kwargs)
+ self.data_type = None # type: Optional[str]
+ self.threshold = threshold
-class CertificateDatastoreSecrets(DatastoreSecrets):
- """Datastore certificate secrets.
+class CategoricalDataDriftMetricThreshold(DataDriftMetricThresholdBase):
+ """CategoricalDataDriftMetricThreshold.
All required parameters must be populated in order to send to Azure.
- :ivar secrets_type: Required. [Required] Credential type used to authentication with
- storage.Constant filled by server. Possible values include: "AccountKey", "Certificate", "Sas",
- "ServicePrincipal", "KerberosPassword", "KerberosKeytab".
- :vartype secrets_type: str or ~azure.mgmt.machinelearningservices.models.SecretsType
- :ivar certificate: Service principal certificate.
- :vartype certificate: str
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The categorical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex", "PearsonsChiSquaredTest".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.CategoricalDataDriftMetric
"""
_validation = {
- 'secrets_type': {'required': True},
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
}
_attribute_map = {
- 'secrets_type': {'key': 'secretsType', 'type': 'str'},
- 'certificate': {'key': 'certificate', 'type': 'str'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
}
def __init__(
self,
*,
- certificate: Optional[str] = None,
+ metric: Union[str, "CategoricalDataDriftMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
**kwargs
):
"""
- :keyword certificate: Service principal certificate.
- :paramtype certificate: str
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The categorical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex", "PearsonsChiSquaredTest".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.CategoricalDataDriftMetric
"""
- super(CertificateDatastoreSecrets, self).__init__(**kwargs)
- self.secrets_type = 'Certificate' # type: str
- self.certificate = certificate
+ super(CategoricalDataDriftMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.data_type = 'Categorical' # type: str
+ self.metric = metric
-class TableVertical(msrest.serialization.Model):
- """Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.
+class DataQualityMetricThresholdBase(msrest.serialization.Model):
+ """DataQualityMetricThresholdBase.
- :ivar cv_split_column_names: Columns to use for CVSplit data.
- :vartype cv_split_column_names: list[str]
- :ivar featurization_settings: Featurization inputs needed for AutoML job.
- :vartype featurization_settings:
- ~azure.mgmt.machinelearningservices.models.TableVerticalFeaturizationSettings
- :ivar fixed_parameters: Model/training parameters that will remain constant throughout
- training.
- :vartype fixed_parameters: ~azure.mgmt.machinelearningservices.models.TableFixedParameters
- :ivar limit_settings: Execution constraints for AutoMLJob.
- :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.TableVerticalLimitSettings
- :ivar n_cross_validations: Number of cross validation folds to be applied on training dataset
- when validation dataset is not provided.
- :vartype n_cross_validations: ~azure.mgmt.machinelearningservices.models.NCrossValidations
- :ivar search_space: Search space for sampling different combinations of models and their
- hyperparameters.
- :vartype search_space: list[~azure.mgmt.machinelearningservices.models.TableParameterSubspace]
- :ivar sweep_settings: Settings for model sweeping and hyperparameter tuning.
- :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.TableSweepSettings
- :ivar test_data: Test data input.
- :vartype test_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar test_data_size: The fraction of test dataset that needs to be set aside for validation
- purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype test_data_size: float
- :ivar validation_data: Validation data inputs.
- :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
- :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
- validation purpose.
- Values between (0.0 , 1.0)
- Applied when validation dataset is not provided.
- :vartype validation_data_size: float
- :ivar weight_column_name: The name of the sample weight column. Automated ML supports a
- weighted column as an input, causing rows in the data to be weighted up or down.
- :vartype weight_column_name: str
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CategoricalDataQualityMetricThreshold, NumericalDataQualityMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
"""
+ _validation = {
+ 'data_type': {'required': True},
+ }
+
_attribute_map = {
- 'cv_split_column_names': {'key': 'cvSplitColumnNames', 'type': '[str]'},
- 'featurization_settings': {'key': 'featurizationSettings', 'type': 'TableVerticalFeaturizationSettings'},
- 'fixed_parameters': {'key': 'fixedParameters', 'type': 'TableFixedParameters'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'Categorical': 'CategoricalDataQualityMetricThreshold', 'Numerical': 'NumericalDataQualityMetricThreshold'}
+ }
+
+ def __init__(
+ self,
+ *,
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(DataQualityMetricThresholdBase, self).__init__(**kwargs)
+ self.data_type = None # type: Optional[str]
+ self.threshold = threshold
+
+
+class CategoricalDataQualityMetricThreshold(DataQualityMetricThresholdBase):
+ """CategoricalDataQualityMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The categorical data quality metric to calculate. Possible
+ values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.CategoricalDataQualityMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: Union[str, "CategoricalDataQualityMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The categorical data quality metric to calculate.
+ Possible values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.CategoricalDataQualityMetric
+ """
+ super(CategoricalDataQualityMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.data_type = 'Categorical' # type: str
+ self.metric = metric
+
+
+class PredictionDriftMetricThresholdBase(msrest.serialization.Model):
+ """PredictionDriftMetricThresholdBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CategoricalPredictionDriftMetricThreshold, NumericalPredictionDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'Categorical': 'CategoricalPredictionDriftMetricThreshold', 'Numerical': 'NumericalPredictionDriftMetricThreshold'}
+ }
+
+ def __init__(
+ self,
+ *,
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(PredictionDriftMetricThresholdBase, self).__init__(**kwargs)
+ self.data_type = None # type: Optional[str]
+ self.threshold = threshold
+
+
+class CategoricalPredictionDriftMetricThreshold(PredictionDriftMetricThresholdBase):
+ """CategoricalPredictionDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The categorical prediction drift metric to calculate.
+ Possible values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "PearsonsChiSquaredTest".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.CategoricalPredictionDriftMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: Union[str, "CategoricalPredictionDriftMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The categorical prediction drift metric to calculate.
+ Possible values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "PearsonsChiSquaredTest".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.CategoricalPredictionDriftMetric
+ """
+ super(CategoricalPredictionDriftMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.data_type = 'Categorical' # type: str
+ self.metric = metric
+
+
+class CertificateDatastoreCredentials(DatastoreCredentials):
+ """Certificate datastore credentials configuration.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credentials_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "AccountKey", "Certificate",
+ "None", "Sas", "ServicePrincipal", "KerberosKeytab", "KerberosPassword".
+ :vartype credentials_type: str or ~azure.mgmt.machinelearningservices.models.CredentialsType
+ :ivar authority_url: Authority URL used for authentication.
+ :vartype authority_url: str
+ :ivar client_id: Required. [Required] Service principal client ID.
+ :vartype client_id: str
+ :ivar resource_url: Resource the service principal has access to.
+ :vartype resource_url: str
+ :ivar secrets: Required. [Required] Service principal secrets.
+ :vartype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
+ :ivar tenant_id: Required. [Required] ID of the tenant to which the service principal belongs.
+ :vartype tenant_id: str
+ :ivar thumbprint: Required. [Required] Thumbprint of the certificate used for authentication.
+ :vartype thumbprint: str
+ """
+
+ _validation = {
+ 'credentials_type': {'required': True},
+ 'client_id': {'required': True},
+ 'secrets': {'required': True},
+ 'tenant_id': {'required': True},
+ 'thumbprint': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'credentials_type': {'key': 'credentialsType', 'type': 'str'},
+ 'authority_url': {'key': 'authorityUrl', 'type': 'str'},
+ 'client_id': {'key': 'clientId', 'type': 'str'},
+ 'resource_url': {'key': 'resourceUrl', 'type': 'str'},
+ 'secrets': {'key': 'secrets', 'type': 'CertificateDatastoreSecrets'},
+ 'tenant_id': {'key': 'tenantId', 'type': 'str'},
+ 'thumbprint': {'key': 'thumbprint', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ client_id: str,
+ secrets: "CertificateDatastoreSecrets",
+ tenant_id: str,
+ thumbprint: str,
+ authority_url: Optional[str] = None,
+ resource_url: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword authority_url: Authority URL used for authentication.
+ :paramtype authority_url: str
+ :keyword client_id: Required. [Required] Service principal client ID.
+ :paramtype client_id: str
+ :keyword resource_url: Resource the service principal has access to.
+ :paramtype resource_url: str
+ :keyword secrets: Required. [Required] Service principal secrets.
+ :paramtype secrets: ~azure.mgmt.machinelearningservices.models.CertificateDatastoreSecrets
+ :keyword tenant_id: Required. [Required] ID of the tenant to which the service principal
+ belongs.
+ :paramtype tenant_id: str
+ :keyword thumbprint: Required. [Required] Thumbprint of the certificate used for
+ authentication.
+ :paramtype thumbprint: str
+ """
+ super(CertificateDatastoreCredentials, self).__init__(**kwargs)
+ self.credentials_type = 'Certificate' # type: str
+ self.authority_url = authority_url
+ self.client_id = client_id
+ self.resource_url = resource_url
+ self.secrets = secrets
+ self.tenant_id = tenant_id
+ self.thumbprint = thumbprint
+
+
+class CertificateDatastoreSecrets(DatastoreSecrets):
+ """Datastore certificate secrets.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar secrets_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "AccountKey", "Certificate", "Sas",
+ "ServicePrincipal", "KerberosPassword", "KerberosKeytab".
+ :vartype secrets_type: str or ~azure.mgmt.machinelearningservices.models.SecretsType
+ :ivar certificate: Service principal certificate.
+ :vartype certificate: str
+ """
+
+ _validation = {
+ 'secrets_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'secrets_type': {'key': 'secretsType', 'type': 'str'},
+ 'certificate': {'key': 'certificate', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ certificate: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword certificate: Service principal certificate.
+ :paramtype certificate: str
+ """
+ super(CertificateDatastoreSecrets, self).__init__(**kwargs)
+ self.secrets_type = 'Certificate' # type: str
+ self.certificate = certificate
+
+
+class TableVertical(msrest.serialization.Model):
+ """Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.
+
+ :ivar cv_split_column_names: Columns to use for CVSplit data.
+ :vartype cv_split_column_names: list[str]
+ :ivar featurization_settings: Featurization inputs needed for AutoML job.
+ :vartype featurization_settings:
+ ~azure.mgmt.machinelearningservices.models.TableVerticalFeaturizationSettings
+ :ivar fixed_parameters: Model/training parameters that will remain constant throughout
+ training.
+ :vartype fixed_parameters: ~azure.mgmt.machinelearningservices.models.TableFixedParameters
+ :ivar limit_settings: Execution constraints for AutoMLJob.
+ :vartype limit_settings: ~azure.mgmt.machinelearningservices.models.TableVerticalLimitSettings
+ :ivar n_cross_validations: Number of cross validation folds to be applied on training dataset
+ when validation dataset is not provided.
+ :vartype n_cross_validations: ~azure.mgmt.machinelearningservices.models.NCrossValidations
+ :ivar search_space: Search space for sampling different combinations of models and their
+ hyperparameters.
+ :vartype search_space: list[~azure.mgmt.machinelearningservices.models.TableParameterSubspace]
+ :ivar sweep_settings: Settings for model sweeping and hyperparameter tuning.
+ :vartype sweep_settings: ~azure.mgmt.machinelearningservices.models.TableSweepSettings
+ :ivar test_data: Test data input.
+ :vartype test_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar test_data_size: The fraction of test dataset that needs to be set aside for validation
+ purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype test_data_size: float
+ :ivar validation_data: Validation data inputs.
+ :vartype validation_data: ~azure.mgmt.machinelearningservices.models.MLTableJobInput
+ :ivar validation_data_size: The fraction of training dataset that needs to be set aside for
+ validation purpose.
+ Values between (0.0 , 1.0)
+ Applied when validation dataset is not provided.
+ :vartype validation_data_size: float
+ :ivar weight_column_name: The name of the sample weight column. Automated ML supports a
+ weighted column as an input, causing rows in the data to be weighted up or down.
+ :vartype weight_column_name: str
+ """
+
+ _attribute_map = {
+ 'cv_split_column_names': {'key': 'cvSplitColumnNames', 'type': '[str]'},
+ 'featurization_settings': {'key': 'featurizationSettings', 'type': 'TableVerticalFeaturizationSettings'},
+ 'fixed_parameters': {'key': 'fixedParameters', 'type': 'TableFixedParameters'},
'limit_settings': {'key': 'limitSettings', 'type': 'TableVerticalLimitSettings'},
'n_cross_validations': {'key': 'nCrossValidations', 'type': 'NCrossValidations'},
'search_space': {'key': 'searchSpace', 'type': '[TableParameterSubspace]'},
@@ -4949,6 +5525,100 @@ def __init__(
self.training_data = training_data
+class ModelPerformanceMetricThresholdBase(msrest.serialization.Model):
+ """ModelPerformanceMetricThresholdBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: ClassificationModelPerformanceMetricThreshold, RegressionModelPerformanceMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar model_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'model_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ _subtype_map = {
+ 'model_type': {'Classification': 'ClassificationModelPerformanceMetricThreshold', 'Regression': 'RegressionModelPerformanceMetricThreshold'}
+ }
+
+ def __init__(
+ self,
+ *,
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(ModelPerformanceMetricThresholdBase, self).__init__(**kwargs)
+ self.model_type = None # type: Optional[str]
+ self.threshold = threshold
+
+
+class ClassificationModelPerformanceMetricThreshold(ModelPerformanceMetricThresholdBase):
+ """ClassificationModelPerformanceMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar model_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The classification model performance to calculate. Possible
+ values include: "Accuracy", "Precision", "Recall", "F1Score".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationModelPerformanceMetric
+ """
+
+ _validation = {
+ 'model_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: Union[str, "ClassificationModelPerformanceMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The classification model performance to calculate.
+ Possible values include: "Accuracy", "Precision", "Recall", "F1Score".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.ClassificationModelPerformanceMetric
+ """
+ super(ClassificationModelPerformanceMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.model_type = 'Classification' # type: str
+ self.metric = metric
+
+
class TrainingSettings(msrest.serialization.Model):
"""Training related configuration.
@@ -5530,9 +6200,13 @@ class CodeVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar code_uri: Uri where code is located.
:vartype code_uri: str
@@ -5550,6 +6224,7 @@ class CodeVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'code_uri': {'key': 'codeUri', 'type': 'str'},
@@ -5562,6 +6237,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
code_uri: Optional[str] = None,
@@ -5574,14 +6250,18 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword code_uri: Uri where code is located.
:paramtype code_uri: str
"""
- super(CodeVersionProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ super(CodeVersionProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
self.code_uri = code_uri
self.provisioning_state = None
@@ -5620,6 +6300,62 @@ def __init__(
self.value = value
+class Collection(msrest.serialization.Model):
+ """Collection.
+
+ :ivar client_id: The msi client id used to collect logging to blob storage. If it's
+ null,backend will pick a registered endpoint identity to auth.
+ :vartype client_id: str
+ :ivar data_collection_mode: Enable or disable data collection. Possible values include:
+ "Enabled", "Disabled".
+ :vartype data_collection_mode: str or
+ ~azure.mgmt.machinelearningservices.models.DataCollectionMode
+ :ivar data_id: The data asset arm resource id. Client side will ensure data asset is pointing
+ to the blob storage, and backend will collect data to the blob storage.
+ :vartype data_id: str
+ :ivar sampling_rate: The sampling rate for collection. Sampling rate 1.0 means we collect 100%
+ of data by default.
+ :vartype sampling_rate: float
+ """
+
+ _attribute_map = {
+ 'client_id': {'key': 'clientId', 'type': 'str'},
+ 'data_collection_mode': {'key': 'dataCollectionMode', 'type': 'str'},
+ 'data_id': {'key': 'dataId', 'type': 'str'},
+ 'sampling_rate': {'key': 'samplingRate', 'type': 'float'},
+ }
+
+ def __init__(
+ self,
+ *,
+ client_id: Optional[str] = None,
+ data_collection_mode: Optional[Union[str, "DataCollectionMode"]] = None,
+ data_id: Optional[str] = None,
+ sampling_rate: Optional[float] = 1,
+ **kwargs
+ ):
+ """
+ :keyword client_id: The msi client id used to collect logging to blob storage. If it's
+ null,backend will pick a registered endpoint identity to auth.
+ :paramtype client_id: str
+ :keyword data_collection_mode: Enable or disable data collection. Possible values include:
+ "Enabled", "Disabled".
+ :paramtype data_collection_mode: str or
+ ~azure.mgmt.machinelearningservices.models.DataCollectionMode
+ :keyword data_id: The data asset arm resource id. Client side will ensure data asset is
+ pointing to the blob storage, and backend will collect data to the blob storage.
+ :paramtype data_id: str
+ :keyword sampling_rate: The sampling rate for collection. Sampling rate 1.0 means we collect
+ 100% of data by default.
+ :paramtype sampling_rate: float
+ """
+ super(Collection, self).__init__(**kwargs)
+ self.client_id = client_id
+ self.data_collection_mode = data_collection_mode
+ self.data_id = data_id
+ self.sampling_rate = sampling_rate
+
+
class ColumnTransformer(msrest.serialization.Model):
"""Column transformer parameters.
@@ -5687,6 +6423,9 @@ class CommandJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -5703,7 +6442,7 @@ class CommandJob(JobBaseProperties):
train.py".
:vartype command: str
:ivar distribution: Distribution configuration of the job. If set, this should be one of Mpi,
- Tensorflow, PyTorch, or null.
+ Tensorflow, PyTorch, Ray, or null.
:vartype distribution: ~azure.mgmt.machinelearningservices.models.DistributionConfiguration
:ivar environment_id: Required. [Required] The ARM resource ID of the Environment specification
for the job.
@@ -5728,7 +6467,7 @@ class CommandJob(JobBaseProperties):
'job_type': {'required': True},
'status': {'readonly': True},
'command': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
- 'environment_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'environment_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'parameters': {'readonly': True},
}
@@ -5744,6 +6483,7 @@ class CommandJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'autologger_settings': {'key': 'autologgerSettings', 'type': 'AutologgerSettings'},
@@ -5775,6 +6515,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
autologger_settings: Optional["AutologgerSettings"] = None,
code_id: Optional[str] = None,
@@ -5811,6 +6552,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -5823,7 +6567,7 @@ def __init__(
"python train.py".
:paramtype command: str
:keyword distribution: Distribution configuration of the job. If set, this should be one of
- Mpi, Tensorflow, PyTorch, or null.
+ Mpi, Tensorflow, PyTorch, Ray, or null.
:paramtype distribution: ~azure.mgmt.machinelearningservices.models.DistributionConfiguration
:keyword environment_id: Required. [Required] The ARM resource ID of the Environment
specification for the job.
@@ -5841,7 +6585,7 @@ def __init__(
:keyword resources: Compute Resource configuration for the job.
:paramtype resources: ~azure.mgmt.machinelearningservices.models.JobResourceConfiguration
"""
- super(CommandJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, services=services, **kwargs)
+ super(CommandJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, secrets_configuration=secrets_configuration, services=services, **kwargs)
self.job_type = 'Command' # type: str
self.autologger_settings = autologger_settings
self.code_id = code_id
@@ -6155,9 +6899,13 @@ class ComponentVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar component_spec: Defines Component definition details.
@@ -6172,6 +6920,8 @@ class ComponentVersionProperties(AssetBase):
include: "Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the component lifecycle.
+ :vartype stage: str
"""
_validation = {
@@ -6182,10 +6932,12 @@ class ComponentVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'component_spec': {'key': 'componentSpec', 'type': 'object'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -6194,9 +6946,11 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
component_spec: Optional[Any] = None,
+ stage: Optional[str] = None,
**kwargs
):
"""
@@ -6206,9 +6960,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword component_spec: Defines Component definition details.
@@ -6219,10 +6977,13 @@ def __init__(
href="https://docs.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-command"
/>.
:paramtype component_spec: any
+ :keyword stage: Stage in the component lifecycle.
+ :paramtype stage: str
"""
- super(ComponentVersionProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ super(ComponentVersionProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
self.component_spec = component_spec
self.provisioning_state = None
+ self.stage = stage
class ComponentVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -7421,6 +8182,80 @@ def __init__(
self.collections_throughput = collections_throughput
+class ScheduleActionBase(msrest.serialization.Model):
+ """ScheduleActionBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: JobScheduleAction, CreateMonitorAction, ImportDataAction, EndpointScheduleAction.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
+ :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
+ """
+
+ _validation = {
+ 'action_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'action_type': {'key': 'actionType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'action_type': {'CreateJob': 'JobScheduleAction', 'CreateMonitor': 'CreateMonitorAction', 'ImportData': 'ImportDataAction', 'InvokeBatchEndpoint': 'EndpointScheduleAction'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(ScheduleActionBase, self).__init__(**kwargs)
+ self.action_type = None # type: Optional[str]
+
+
+class CreateMonitorAction(ScheduleActionBase):
+ """CreateMonitorAction.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
+ :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
+ :ivar monitor_definition: Required. [Required] Defines the monitor.
+ :vartype monitor_definition: ~azure.mgmt.machinelearningservices.models.MonitorDefinition
+ """
+
+ _validation = {
+ 'action_type': {'required': True},
+ 'monitor_definition': {'required': True},
+ }
+
+ _attribute_map = {
+ 'action_type': {'key': 'actionType', 'type': 'str'},
+ 'monitor_definition': {'key': 'monitorDefinition', 'type': 'MonitorDefinition'},
+ }
+
+ def __init__(
+ self,
+ *,
+ monitor_definition: "MonitorDefinition",
+ **kwargs
+ ):
+ """
+ :keyword monitor_definition: Required. [Required] Defines the monitor.
+ :paramtype monitor_definition: ~azure.mgmt.machinelearningservices.models.MonitorDefinition
+ """
+ super(CreateMonitorAction, self).__init__(**kwargs)
+ self.action_type = 'CreateMonitor' # type: str
+ self.monitor_definition = monitor_definition
+
+
class TriggerBase(msrest.serialization.Model):
"""TriggerBase.
@@ -7517,7 +8352,7 @@ class CronTrigger(TriggerBase):
_validation = {
'trigger_type': {'required': True},
- 'expression': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'expression': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -7690,6 +8525,46 @@ def __init__(
self.inference_configuration = inference_configuration
+class CustomMetricThreshold(msrest.serialization.Model):
+ """CustomMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar metric: Required. [Required] The user-defined metric to calculate.
+ :vartype metric: str
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'metric': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'metric': {'key': 'metric', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: str,
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword metric: Required. [Required] The user-defined metric to calculate.
+ :paramtype metric: str
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(CustomMetricThreshold, self).__init__(**kwargs)
+ self.metric = metric
+ self.threshold = threshold
+
+
class JobInput(msrest.serialization.Model):
"""Command job definition.
@@ -7753,7 +8628,7 @@ class CustomModelJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -7841,6 +8716,8 @@ class CustomModelJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -7861,6 +8738,7 @@ class CustomModelJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -7872,6 +8750,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
description: Optional[str] = None,
@@ -7882,6 +8761,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -7890,15 +8771,150 @@ def __init__(
:keyword description: Description for the output.
:paramtype description: str
"""
- super(CustomModelJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, mode=mode, uri=uri, **kwargs)
+ super(CustomModelJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, auto_delete_setting=auto_delete_setting, mode=mode, uri=uri, **kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
self.job_output_type = 'custom_model' # type: str
self.description = description
+class MonitoringSignalBase(msrest.serialization.Model):
+ """MonitoringSignalBase.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: CustomMonitoringSignal, DataDriftMonitoringSignal, DataQualityMonitoringSignal, FeatureAttributionDriftMonitoringSignal, ModelPerformanceSignalBase, PredictionDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'signal_type': {'Custom': 'CustomMonitoringSignal', 'DataDrift': 'DataDriftMonitoringSignal', 'DataQuality': 'DataQualityMonitoringSignal', 'FeatureAttributionDrift': 'FeatureAttributionDriftMonitoringSignal', 'ModelPerformanceSignalBase': 'ModelPerformanceSignalBase', 'PredictionDrift': 'PredictionDriftMonitoringSignal'}
+ }
+
+ def __init__(
+ self,
+ *,
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ """
+ super(MonitoringSignalBase, self).__init__(**kwargs)
+ self.lookback_period = lookback_period
+ self.mode = mode
+ self.signal_type = None # type: Optional[str]
+
+
+class CustomMonitoringSignal(MonitoringSignalBase):
+ """CustomMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar component_id: Required. [Required] ARM resource ID of the component resource used to
+ calculate the custom metrics.
+ :vartype component_id: str
+ :ivar input_assets: Monitoring assets to take as input. Key is the component input port name,
+ value is the data asset.
+ :vartype input_assets: dict[str,
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputData]
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.CustomMetricThreshold]
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'component_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'metric_thresholds': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'component_id': {'key': 'componentId', 'type': 'str'},
+ 'input_assets': {'key': 'inputAssets', 'type': '{MonitoringInputData}'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[CustomMetricThreshold]'},
+ }
+
+ def __init__(
+ self,
+ *,
+ component_id: str,
+ metric_thresholds: List["CustomMetricThreshold"],
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ input_assets: Optional[Dict[str, "MonitoringInputData"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword component_id: Required. [Required] ARM resource ID of the component resource used to
+ calculate the custom metrics.
+ :paramtype component_id: str
+ :keyword input_assets: Monitoring assets to take as input. Key is the component input port
+ name, value is the data asset.
+ :paramtype input_assets: dict[str,
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputData]
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.CustomMetricThreshold]
+ """
+ super(CustomMonitoringSignal, self).__init__(lookback_period=lookback_period, mode=mode, **kwargs)
+ self.signal_type = 'Custom' # type: str
+ self.component_id = component_id
+ self.input_assets = input_assets
+ self.metric_thresholds = metric_thresholds
+
+
class CustomNCrossValidations(NCrossValidations):
"""N-Cross validations are specified by user.
@@ -8094,28 +9110,134 @@ class CustomTargetRollingWindowSize(TargetRollingWindowSize):
"""
_validation = {
- 'mode': {'required': True},
- 'value': {'required': True},
+ 'mode': {'required': True},
+ 'value': {'required': True},
+ }
+
+ _attribute_map = {
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'value': {'key': 'value', 'type': 'int'},
+ }
+
+ def __init__(
+ self,
+ *,
+ value: int,
+ **kwargs
+ ):
+ """
+ :keyword value: Required. [Required] TargetRollingWindowSize value.
+ :paramtype value: int
+ """
+ super(CustomTargetRollingWindowSize, self).__init__(**kwargs)
+ self.mode = 'Custom' # type: str
+ self.value = value
+
+
+class DataImportSource(msrest.serialization.Model):
+ """DataImportSource.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: DatabaseSource, FileSystemSource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar connection: Workspace connection for data import source storage.
+ :vartype connection: str
+ :ivar source_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "database", "file_system".
+ :vartype source_type: str or ~azure.mgmt.machinelearningservices.models.DataImportSourceType
+ """
+
+ _validation = {
+ 'source_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'connection': {'key': 'connection', 'type': 'str'},
+ 'source_type': {'key': 'sourceType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'source_type': {'database': 'DatabaseSource', 'file_system': 'FileSystemSource'}
+ }
+
+ def __init__(
+ self,
+ *,
+ connection: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword connection: Workspace connection for data import source storage.
+ :paramtype connection: str
+ """
+ super(DataImportSource, self).__init__(**kwargs)
+ self.connection = connection
+ self.source_type = None # type: Optional[str]
+
+
+class DatabaseSource(DataImportSource):
+ """DatabaseSource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar connection: Workspace connection for data import source storage.
+ :vartype connection: str
+ :ivar source_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "database", "file_system".
+ :vartype source_type: str or ~azure.mgmt.machinelearningservices.models.DataImportSourceType
+ :ivar query: SQL Query statement for data import Database source.
+ :vartype query: str
+ :ivar stored_procedure: SQL StoredProcedure on data import Database source.
+ :vartype stored_procedure: str
+ :ivar stored_procedure_params: SQL StoredProcedure parameters.
+ :vartype stored_procedure_params: list[dict[str, str]]
+ :ivar table_name: Name of the table on data import Database source.
+ :vartype table_name: str
+ """
+
+ _validation = {
+ 'source_type': {'required': True},
}
_attribute_map = {
- 'mode': {'key': 'mode', 'type': 'str'},
- 'value': {'key': 'value', 'type': 'int'},
+ 'connection': {'key': 'connection', 'type': 'str'},
+ 'source_type': {'key': 'sourceType', 'type': 'str'},
+ 'query': {'key': 'query', 'type': 'str'},
+ 'stored_procedure': {'key': 'storedProcedure', 'type': 'str'},
+ 'stored_procedure_params': {'key': 'storedProcedureParams', 'type': '[{str}]'},
+ 'table_name': {'key': 'tableName', 'type': 'str'},
}
def __init__(
self,
*,
- value: int,
+ connection: Optional[str] = None,
+ query: Optional[str] = None,
+ stored_procedure: Optional[str] = None,
+ stored_procedure_params: Optional[List[Dict[str, str]]] = None,
+ table_name: Optional[str] = None,
**kwargs
):
"""
- :keyword value: Required. [Required] TargetRollingWindowSize value.
- :paramtype value: int
+ :keyword connection: Workspace connection for data import source storage.
+ :paramtype connection: str
+ :keyword query: SQL Query statement for data import Database source.
+ :paramtype query: str
+ :keyword stored_procedure: SQL StoredProcedure on data import Database source.
+ :paramtype stored_procedure: str
+ :keyword stored_procedure_params: SQL StoredProcedure parameters.
+ :paramtype stored_procedure_params: list[dict[str, str]]
+ :keyword table_name: Name of the table on data import Database source.
+ :paramtype table_name: str
"""
- super(CustomTargetRollingWindowSize, self).__init__(**kwargs)
- self.mode = 'Custom' # type: str
- self.value = value
+ super(DatabaseSource, self).__init__(connection=connection, **kwargs)
+ self.source_type = 'database' # type: str
+ self.query = query
+ self.stored_procedure = stored_procedure
+ self.stored_procedure_params = stored_procedure_params
+ self.table_name = table_name
class DatabricksSchema(msrest.serialization.Model):
@@ -8335,6 +9457,71 @@ def __init__(
self.workspace_url = workspace_url
+class DataCollector(msrest.serialization.Model):
+ """DataCollector.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar collections: Required. [Required] The collection configuration. Each collection has it
+ own configuration to collect model data and the name of collection can be arbitrary string.
+ Model data collector can be used for either payload logging or custom logging or both of them.
+ Collection request and response are reserved for payload logging, others are for custom
+ logging.
+ :vartype collections: dict[str, ~azure.mgmt.machinelearningservices.models.Collection]
+ :ivar request_logging: The request logging configuration for mdc, it includes advanced logging
+ settings for all collections. It's optional.
+ :vartype request_logging: ~azure.mgmt.machinelearningservices.models.RequestLogging
+ :ivar rolling_rate: When model data is collected to blob storage, we need to roll the data to
+ different path to avoid logging all of them in a single blob file.
+ If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/.
+ If it's day, all data will be collected in blob path /yyyy/MM/dd/.
+ The other benefit of rolling path is that model monitoring ui is able to select a time range
+ of data very quickly. Possible values include: "Year", "Month", "Day", "Hour", "Minute".
+ :vartype rolling_rate: str or ~azure.mgmt.machinelearningservices.models.RollingRateType
+ """
+
+ _validation = {
+ 'collections': {'required': True},
+ }
+
+ _attribute_map = {
+ 'collections': {'key': 'collections', 'type': '{Collection}'},
+ 'request_logging': {'key': 'requestLogging', 'type': 'RequestLogging'},
+ 'rolling_rate': {'key': 'rollingRate', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ collections: Dict[str, "Collection"],
+ request_logging: Optional["RequestLogging"] = None,
+ rolling_rate: Optional[Union[str, "RollingRateType"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword collections: Required. [Required] The collection configuration. Each collection has it
+ own configuration to collect model data and the name of collection can be arbitrary string.
+ Model data collector can be used for either payload logging or custom logging or both of them.
+ Collection request and response are reserved for payload logging, others are for custom
+ logging.
+ :paramtype collections: dict[str, ~azure.mgmt.machinelearningservices.models.Collection]
+ :keyword request_logging: The request logging configuration for mdc, it includes advanced
+ logging settings for all collections. It's optional.
+ :paramtype request_logging: ~azure.mgmt.machinelearningservices.models.RequestLogging
+ :keyword rolling_rate: When model data is collected to blob storage, we need to roll the data
+ to different path to avoid logging all of them in a single blob file.
+ If the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/.
+ If it's day, all data will be collected in blob path /yyyy/MM/dd/.
+ The other benefit of rolling path is that model monitoring ui is able to select a time range
+ of data very quickly. Possible values include: "Year", "Month", "Day", "Hour", "Minute".
+ :paramtype rolling_rate: str or ~azure.mgmt.machinelearningservices.models.RollingRateType
+ """
+ super(DataCollector, self).__init__(**kwargs)
+ self.collections = collections
+ self.request_logging = request_logging
+ self.rolling_rate = rolling_rate
+
+
class DataContainer(Resource):
"""Azure Resource Manager resource envelope.
@@ -8488,6 +9675,94 @@ def __init__(
self.value = value
+class DataDriftMonitoringSignal(MonitoringSignalBase):
+ """DataDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar data_segment: The data segment used for scoping on a subset of the data population.
+ :vartype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :ivar features: The feature filter which identifies which feature to calculate drift over.
+ :vartype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataDriftMetricThresholdBase]
+ :ivar target_data: Required. [Required] The data which drift will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_thresholds': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'data_segment': {'key': 'dataSegment', 'type': 'MonitoringDataSegment'},
+ 'features': {'key': 'features', 'type': 'MonitoringFeatureFilterBase'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[DataDriftMetricThresholdBase]'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ *,
+ baseline_data: "MonitoringInputData",
+ metric_thresholds: List["DataDriftMetricThresholdBase"],
+ target_data: "MonitoringInputData",
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ data_segment: Optional["MonitoringDataSegment"] = None,
+ features: Optional["MonitoringFeatureFilterBase"] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword data_segment: The data segment used for scoping on a subset of the data population.
+ :paramtype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :keyword features: The feature filter which identifies which feature to calculate drift over.
+ :paramtype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataDriftMetricThresholdBase]
+ :keyword target_data: Required. [Required] The data which drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(DataDriftMonitoringSignal, self).__init__(lookback_period=lookback_period, mode=mode, **kwargs)
+ self.signal_type = 'DataDrift' # type: str
+ self.baseline_data = baseline_data
+ self.data_segment = data_segment
+ self.features = features
+ self.metric_thresholds = metric_thresholds
+ self.target_data = target_data
+
+
class DataFactory(Compute):
"""A DataFactory compute.
@@ -8570,6 +9845,216 @@ def __init__(
self.compute_type = 'DataFactory' # type: str
+class DataVersionBaseProperties(AssetBase):
+ """Data version base definition.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: MLTableData, UriFileDataVersion, UriFolderDataVersion.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :vartype is_anonymous: bool
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :vartype is_archived: bool
+ :ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "uri_file", "uri_folder", "mltable".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
+ :ivar data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'description': {'key': 'description', 'type': 'str'},
+ 'properties': {'key': 'properties', 'type': '{str}'},
+ 'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
+ 'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
+ 'is_archived': {'key': 'isArchived', 'type': 'bool'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'data_type': {'mltable': 'MLTableData', 'uri_file': 'UriFileDataVersion', 'uri_folder': 'UriFolderDataVersion'}
+ }
+
+ def __init__(
+ self,
+ *,
+ data_uri: str,
+ description: Optional[str] = None,
+ properties: Optional[Dict[str, str]] = None,
+ tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
+ is_anonymous: Optional[bool] = False,
+ is_archived: Optional[bool] = False,
+ intellectual_property: Optional["IntellectualProperty"] = None,
+ stage: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword description: The asset description text.
+ :paramtype description: str
+ :keyword properties: The asset property dictionary.
+ :paramtype properties: dict[str, str]
+ :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :paramtype tags: dict[str, str]
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :paramtype is_anonymous: bool
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :paramtype is_archived: bool
+ :keyword data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
+ """
+ super(DataVersionBaseProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ self.data_type = 'DataVersionBaseProperties' # type: str
+ self.data_uri = data_uri
+ self.intellectual_property = intellectual_property
+ self.stage = stage
+
+
+class DataImport(DataVersionBaseProperties):
+ """DataImport.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :vartype is_anonymous: bool
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :vartype is_archived: bool
+ :ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "uri_file", "uri_folder", "mltable".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
+ :ivar data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
+ :ivar asset_name: Name of the asset for data import job to create.
+ :vartype asset_name: str
+ :ivar source: Source data of the asset to import from.
+ :vartype source: ~azure.mgmt.machinelearningservices.models.DataImportSource
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'description': {'key': 'description', 'type': 'str'},
+ 'properties': {'key': 'properties', 'type': '{str}'},
+ 'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
+ 'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
+ 'is_archived': {'key': 'isArchived', 'type': 'bool'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
+ 'asset_name': {'key': 'assetName', 'type': 'str'},
+ 'source': {'key': 'source', 'type': 'DataImportSource'},
+ }
+
+ def __init__(
+ self,
+ *,
+ data_uri: str,
+ description: Optional[str] = None,
+ properties: Optional[Dict[str, str]] = None,
+ tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
+ is_anonymous: Optional[bool] = False,
+ is_archived: Optional[bool] = False,
+ intellectual_property: Optional["IntellectualProperty"] = None,
+ stage: Optional[str] = None,
+ asset_name: Optional[str] = None,
+ source: Optional["DataImportSource"] = None,
+ **kwargs
+ ):
+ """
+ :keyword description: The asset description text.
+ :paramtype description: str
+ :keyword properties: The asset property dictionary.
+ :paramtype properties: dict[str, str]
+ :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :paramtype tags: dict[str, str]
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
+ :paramtype is_anonymous: bool
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
+ :paramtype is_archived: bool
+ :keyword data_uri: Required. [Required] Uri of the data. Example:
+ https://go.microsoft.com/fwlink/?linkid=2202330.
+ :paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
+ :keyword asset_name: Name of the asset for data import job to create.
+ :paramtype asset_name: str
+ :keyword source: Source data of the asset to import from.
+ :paramtype source: ~azure.mgmt.machinelearningservices.models.DataImportSource
+ """
+ super(DataImport, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, intellectual_property=intellectual_property, stage=stage, **kwargs)
+ self.data_type = 'uri_folder' # type: str
+ self.asset_name = asset_name
+ self.source = source
+
+
class DataLakeAnalyticsSchema(msrest.serialization.Model):
"""DataLakeAnalyticsSchema.
@@ -8765,6 +10250,89 @@ def __init__(
self.path = path
+class DataQualityMonitoringSignal(MonitoringSignalBase):
+ """DataQualityMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar features: The features to calculate drift over.
+ :vartype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataQualityMetricThresholdBase]
+ :ivar target_data: Required. [Required] The data produced by the production service which drift
+ will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_thresholds': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'features': {'key': 'features', 'type': 'MonitoringFeatureFilterBase'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[DataQualityMetricThresholdBase]'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ *,
+ baseline_data: "MonitoringInputData",
+ metric_thresholds: List["DataQualityMetricThresholdBase"],
+ target_data: "MonitoringInputData",
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ features: Optional["MonitoringFeatureFilterBase"] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword features: The features to calculate drift over.
+ :paramtype features: ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterBase
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.DataQualityMetricThresholdBase]
+ :keyword target_data: Required. [Required] The data produced by the production service which
+ drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(DataQualityMonitoringSignal, self).__init__(lookback_period=lookback_period, mode=mode, **kwargs)
+ self.signal_type = 'DataQuality' # type: str
+ self.baseline_data = baseline_data
+ self.features = features
+ self.metric_thresholds = metric_thresholds
+ self.target_data = target_data
+
+
class DatasetExportSummary(ExportSummary):
"""DatasetExportSummary.
@@ -8921,113 +10489,37 @@ class DataVersionBase(Resource):
information.
:vartype system_data: ~azure.mgmt.machinelearningservices.models.SystemData
:ivar properties: Required. [Required] Additional attributes of the entity.
- :vartype properties: ~azure.mgmt.machinelearningservices.models.DataVersionBaseProperties
- """
-
- _validation = {
- 'id': {'readonly': True},
- 'name': {'readonly': True},
- 'type': {'readonly': True},
- 'system_data': {'readonly': True},
- 'properties': {'required': True},
- }
-
- _attribute_map = {
- 'id': {'key': 'id', 'type': 'str'},
- 'name': {'key': 'name', 'type': 'str'},
- 'type': {'key': 'type', 'type': 'str'},
- 'system_data': {'key': 'systemData', 'type': 'SystemData'},
- 'properties': {'key': 'properties', 'type': 'DataVersionBaseProperties'},
- }
-
- def __init__(
- self,
- *,
- properties: "DataVersionBaseProperties",
- **kwargs
- ):
- """
- :keyword properties: Required. [Required] Additional attributes of the entity.
- :paramtype properties: ~azure.mgmt.machinelearningservices.models.DataVersionBaseProperties
- """
- super(DataVersionBase, self).__init__(**kwargs)
- self.properties = properties
-
-
-class DataVersionBaseProperties(AssetBase):
- """Data version base definition.
-
- You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: MLTableData, UriFileDataVersion, UriFolderDataVersion.
-
- All required parameters must be populated in order to send to Azure.
-
- :ivar description: The asset description text.
- :vartype description: str
- :ivar properties: The asset property dictionary.
- :vartype properties: dict[str, str]
- :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
- :vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
- :vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
- :vartype is_archived: bool
- :ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
- Possible values include: "uri_file", "uri_folder", "mltable".
- :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.DataType
- :ivar data_uri: Required. [Required] Uri of the data. Example:
- https://go.microsoft.com/fwlink/?linkid=2202330.
- :vartype data_uri: str
+ :vartype properties: ~azure.mgmt.machinelearningservices.models.DataVersionBaseProperties
"""
_validation = {
- 'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'id': {'readonly': True},
+ 'name': {'readonly': True},
+ 'type': {'readonly': True},
+ 'system_data': {'readonly': True},
+ 'properties': {'required': True},
}
_attribute_map = {
- 'description': {'key': 'description', 'type': 'str'},
- 'properties': {'key': 'properties', 'type': '{str}'},
- 'tags': {'key': 'tags', 'type': '{str}'},
- 'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
- 'is_archived': {'key': 'isArchived', 'type': 'bool'},
- 'data_type': {'key': 'dataType', 'type': 'str'},
- 'data_uri': {'key': 'dataUri', 'type': 'str'},
- }
-
- _subtype_map = {
- 'data_type': {'mltable': 'MLTableData', 'uri_file': 'UriFileDataVersion', 'uri_folder': 'UriFolderDataVersion'}
+ 'id': {'key': 'id', 'type': 'str'},
+ 'name': {'key': 'name', 'type': 'str'},
+ 'type': {'key': 'type', 'type': 'str'},
+ 'system_data': {'key': 'systemData', 'type': 'SystemData'},
+ 'properties': {'key': 'properties', 'type': 'DataVersionBaseProperties'},
}
def __init__(
self,
*,
- data_uri: str,
- description: Optional[str] = None,
- properties: Optional[Dict[str, str]] = None,
- tags: Optional[Dict[str, str]] = None,
- is_anonymous: Optional[bool] = False,
- is_archived: Optional[bool] = False,
+ properties: "DataVersionBaseProperties",
**kwargs
):
"""
- :keyword description: The asset description text.
- :paramtype description: str
- :keyword properties: The asset property dictionary.
- :paramtype properties: dict[str, str]
- :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
- :paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
- :paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
- :paramtype is_archived: bool
- :keyword data_uri: Required. [Required] Uri of the data. Example:
- https://go.microsoft.com/fwlink/?linkid=2202330.
- :paramtype data_uri: str
+ :keyword properties: Required. [Required] Additional attributes of the entity.
+ :paramtype properties: ~azure.mgmt.machinelearningservices.models.DataVersionBaseProperties
"""
- super(DataVersionBaseProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
- self.data_type = 'DataVersionBaseProperties' # type: str
- self.data_uri = data_uri
+ super(DataVersionBase, self).__init__(**kwargs)
+ self.properties = properties
class DataVersionBaseResourceArmPaginatedResult(msrest.serialization.Model):
@@ -9195,6 +10687,10 @@ class ResourceConfiguration(msrest.serialization.Model):
:vartype instance_type: str
:ivar locations: Locations where the job can run.
:vartype locations: list[str]
+ :ivar max_instance_count: Optional max allowed number of instances or nodes to be used by the
+ compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :vartype max_instance_count: int
:ivar properties: Additional properties bag.
:vartype properties: dict[str, any]
"""
@@ -9203,6 +10699,7 @@ class ResourceConfiguration(msrest.serialization.Model):
'instance_count': {'key': 'instanceCount', 'type': 'int'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
'locations': {'key': 'locations', 'type': '[str]'},
+ 'max_instance_count': {'key': 'maxInstanceCount', 'type': 'int'},
'properties': {'key': 'properties', 'type': '{object}'},
}
@@ -9212,6 +10709,7 @@ def __init__(
instance_count: Optional[int] = 1,
instance_type: Optional[str] = None,
locations: Optional[List[str]] = None,
+ max_instance_count: Optional[int] = None,
properties: Optional[Dict[str, Any]] = None,
**kwargs
):
@@ -9222,6 +10720,10 @@ def __init__(
:paramtype instance_type: str
:keyword locations: Locations where the job can run.
:paramtype locations: list[str]
+ :keyword max_instance_count: Optional max allowed number of instances or nodes to be used by
+ the compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :paramtype max_instance_count: int
:keyword properties: Additional properties bag.
:paramtype properties: dict[str, any]
"""
@@ -9229,6 +10731,7 @@ def __init__(
self.instance_count = instance_count
self.instance_type = instance_type
self.locations = locations
+ self.max_instance_count = max_instance_count
self.properties = properties
@@ -9241,6 +10744,10 @@ class DeploymentResourceConfiguration(ResourceConfiguration):
:vartype instance_type: str
:ivar locations: Locations where the job can run.
:vartype locations: list[str]
+ :ivar max_instance_count: Optional max allowed number of instances or nodes to be used by the
+ compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :vartype max_instance_count: int
:ivar properties: Additional properties bag.
:vartype properties: dict[str, any]
"""
@@ -9249,6 +10756,7 @@ class DeploymentResourceConfiguration(ResourceConfiguration):
'instance_count': {'key': 'instanceCount', 'type': 'int'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
'locations': {'key': 'locations', 'type': '[str]'},
+ 'max_instance_count': {'key': 'maxInstanceCount', 'type': 'int'},
'properties': {'key': 'properties', 'type': '{object}'},
}
@@ -9258,6 +10766,7 @@ def __init__(
instance_count: Optional[int] = 1,
instance_type: Optional[str] = None,
locations: Optional[List[str]] = None,
+ max_instance_count: Optional[int] = None,
properties: Optional[Dict[str, Any]] = None,
**kwargs
):
@@ -9268,10 +10777,14 @@ def __init__(
:paramtype instance_type: str
:keyword locations: Locations where the job can run.
:paramtype locations: list[str]
+ :keyword max_instance_count: Optional max allowed number of instances or nodes to be used by
+ the compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :paramtype max_instance_count: int
:keyword properties: Additional properties bag.
:paramtype properties: dict[str, any]
"""
- super(DeploymentResourceConfiguration, self).__init__(instance_count=instance_count, instance_type=instance_type, locations=locations, properties=properties, **kwargs)
+ super(DeploymentResourceConfiguration, self).__init__(instance_count=instance_count, instance_type=instance_type, locations=locations, max_instance_count=max_instance_count, properties=properties, **kwargs)
class DiagnoseRequestProperties(msrest.serialization.Model):
@@ -9541,12 +11054,13 @@ class DistributionConfiguration(msrest.serialization.Model):
"""Base definition for job distribution configuration.
You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: Mpi, PyTorch, TensorFlow.
+ sub-classes are: Mpi, PyTorch, Ray, TensorFlow.
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
"""
@@ -9559,7 +11073,7 @@ class DistributionConfiguration(msrest.serialization.Model):
}
_subtype_map = {
- 'distribution_type': {'Mpi': 'Mpi', 'PyTorch': 'PyTorch', 'TensorFlow': 'TensorFlow'}
+ 'distribution_type': {'Mpi': 'Mpi', 'PyTorch': 'PyTorch', 'Ray': 'Ray', 'TensorFlow': 'TensorFlow'}
}
def __init__(
@@ -9904,48 +11418,14 @@ def __init__(
self.token_type = token_type
-class ScheduleActionBase(msrest.serialization.Model):
- """ScheduleActionBase.
-
- You probably want to use the sub-classes and not this class directly. Known
- sub-classes are: JobScheduleAction, EndpointScheduleAction.
-
- All required parameters must be populated in order to send to Azure.
-
- :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
- filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint".
- :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
- """
-
- _validation = {
- 'action_type': {'required': True},
- }
-
- _attribute_map = {
- 'action_type': {'key': 'actionType', 'type': 'str'},
- }
-
- _subtype_map = {
- 'action_type': {'CreateJob': 'JobScheduleAction', 'InvokeBatchEndpoint': 'EndpointScheduleAction'}
- }
-
- def __init__(
- self,
- **kwargs
- ):
- """
- """
- super(ScheduleActionBase, self).__init__(**kwargs)
- self.action_type = None # type: Optional[str]
-
-
class EndpointScheduleAction(ScheduleActionBase):
"""EndpointScheduleAction.
All required parameters must be populated in order to send to Azure.
:ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
- filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint".
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
:vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
:ivar endpoint_invocation_definition: Required. [Required] Defines Schedule action definition
details.
@@ -10243,9 +11723,13 @@ class EnvironmentVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar auto_rebuild: Defines if image needs to be rebuilt based on base image changes. Possible
values include: "Disabled", "OnBaseImageUpdate".
@@ -10284,12 +11768,17 @@ class EnvironmentVersionProperties(AssetBase):
:ivar inference_config: Defines configuration specific to inference.
:vartype inference_config:
~azure.mgmt.machinelearningservices.models.InferenceContainerProperties
+ :ivar intellectual_property: Intellectual Property details. Used if environment is an
+ Intellectual Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar os_type: The OS type of the environment. Possible values include: "Linux", "Windows".
:vartype os_type: str or ~azure.mgmt.machinelearningservices.models.OperatingSystemType
:ivar provisioning_state: Provisioning state for the environment version. Possible values
include: "Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the environment lifecycle assigned to this environment.
+ :vartype stage: str
"""
_validation = {
@@ -10301,6 +11790,7 @@ class EnvironmentVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'auto_rebuild': {'key': 'autoRebuild', 'type': 'str'},
@@ -10309,8 +11799,10 @@ class EnvironmentVersionProperties(AssetBase):
'environment_type': {'key': 'environmentType', 'type': 'str'},
'image': {'key': 'image', 'type': 'str'},
'inference_config': {'key': 'inferenceConfig', 'type': 'InferenceContainerProperties'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'os_type': {'key': 'osType', 'type': 'str'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -10319,6 +11811,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
auto_rebuild: Optional[Union[str, "AutoRebuildSetting"]] = None,
@@ -10326,7 +11819,9 @@ def __init__(
conda_file: Optional[str] = None,
image: Optional[str] = None,
inference_config: Optional["InferenceContainerProperties"] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
os_type: Optional[Union[str, "OperatingSystemType"]] = None,
+ stage: Optional[str] = None,
**kwargs
):
"""
@@ -10336,9 +11831,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword auto_rebuild: Defines if image needs to be rebuilt based on base image changes.
Possible values include: "Disabled", "OnBaseImageUpdate".
@@ -10367,18 +11866,26 @@ def __init__(
:keyword inference_config: Defines configuration specific to inference.
:paramtype inference_config:
~azure.mgmt.machinelearningservices.models.InferenceContainerProperties
+ :keyword intellectual_property: Intellectual Property details. Used if environment is an
+ Intellectual Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword os_type: The OS type of the environment. Possible values include: "Linux", "Windows".
:paramtype os_type: str or ~azure.mgmt.machinelearningservices.models.OperatingSystemType
+ :keyword stage: Stage in the environment lifecycle assigned to this environment.
+ :paramtype stage: str
"""
- super(EnvironmentVersionProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ super(EnvironmentVersionProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
self.auto_rebuild = auto_rebuild
self.build = build
self.conda_file = conda_file
self.environment_type = None
self.image = image
self.inference_config = inference_config
+ self.intellectual_property = intellectual_property
self.os_type = os_type
self.provisioning_state = None
+ self.stage = stage
class EnvironmentVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -10730,6 +12237,122 @@ def __init__(
self.value = value
+class FeatureAttributionDriftMonitoringSignal(MonitoringSignalBase):
+ """FeatureAttributionDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetricThreshold
+ :ivar target_data: Required. [Required] The data which drift will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_threshold': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'metric_threshold': {'key': 'metricThreshold', 'type': 'FeatureAttributionMetricThreshold'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ *,
+ baseline_data: "MonitoringInputData",
+ metric_threshold: "FeatureAttributionMetricThreshold",
+ target_data: "MonitoringInputData",
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetricThreshold
+ :keyword target_data: Required. [Required] The data which drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(FeatureAttributionDriftMonitoringSignal, self).__init__(lookback_period=lookback_period, mode=mode, **kwargs)
+ self.signal_type = 'FeatureAttributionDrift' # type: str
+ self.baseline_data = baseline_data
+ self.metric_threshold = metric_threshold
+ self.target_data = target_data
+
+
+class FeatureAttributionMetricThreshold(msrest.serialization.Model):
+ """FeatureAttributionMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar metric: Required. [Required] The feature attribution metric to calculate. Possible values
+ include: "NormalizedDiscountedCumulativeGain".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetric
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+
+ _validation = {
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'metric': {'key': 'metric', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: Union[str, "FeatureAttributionMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword metric: Required. [Required] The feature attribution metric to calculate. Possible
+ values include: "NormalizedDiscountedCumulativeGain".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.FeatureAttributionMetric
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ """
+ super(FeatureAttributionMetricThreshold, self).__init__(**kwargs)
+ self.metric = metric
+ self.threshold = threshold
+
+
class FeaturesetContainer(Resource):
"""Azure Resource Manager resource envelope.
@@ -11136,31 +12759,6 @@ def __init__(
self.tags = tags
-class FeaturesetVersionBackfillResponse(msrest.serialization.Model):
- """Response payload for creating a backfill request for a given feature set version.
-
- :ivar job_id: Job id created as part of request.
- :vartype job_id: str
- """
-
- _attribute_map = {
- 'job_id': {'key': 'jobId', 'type': 'str'},
- }
-
- def __init__(
- self,
- *,
- job_id: Optional[str] = None,
- **kwargs
- ):
- """
- :keyword job_id: Job id created as part of request.
- :paramtype job_id: str
- """
- super(FeaturesetVersionBackfillResponse, self).__init__(**kwargs)
- self.job_id = job_id
-
-
class FeaturesetVersionProperties(AssetBase):
"""Dto object representing feature set version.
@@ -11172,9 +12770,13 @@ class FeaturesetVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar entities: Specifies list of entities.
:vartype entities: list[str]
@@ -11199,6 +12801,7 @@ class FeaturesetVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'entities': {'key': 'entities', 'type': '[str]'},
@@ -11214,6 +12817,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
entities: Optional[List[str]] = None,
@@ -11229,9 +12833,13 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword entities: Specifies list of entities.
:paramtype entities: list[str]
@@ -11243,7 +12851,7 @@ def __init__(
:keyword stage: Specifies the asset stage.
:paramtype stage: str
"""
- super(FeaturesetVersionProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ super(FeaturesetVersionProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
self.entities = entities
self.materialization_settings = materialization_settings
self.provisioning_state = None
@@ -11500,9 +13108,13 @@ class FeaturestoreEntityVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar index_columns: Specifies index columns.
:vartype index_columns: list[~azure.mgmt.machinelearningservices.models.IndexColumn]
@@ -11510,6 +13122,8 @@ class FeaturestoreEntityVersionProperties(AssetBase):
values include: "Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Specifies the asset stage.
+ :vartype stage: str
"""
_validation = {
@@ -11520,10 +13134,12 @@ class FeaturestoreEntityVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'index_columns': {'key': 'indexColumns', 'type': '[IndexColumn]'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -11532,9 +13148,11 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
index_columns: Optional[List["IndexColumn"]] = None,
+ stage: Optional[str] = None,
**kwargs
):
"""
@@ -11544,16 +13162,23 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword index_columns: Specifies index columns.
:paramtype index_columns: list[~azure.mgmt.machinelearningservices.models.IndexColumn]
+ :keyword stage: Specifies the asset stage.
+ :paramtype stage: str
"""
- super(FeaturestoreEntityVersionProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ super(FeaturestoreEntityVersionProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
self.index_columns = index_columns
self.provisioning_state = None
+ self.stage = stage
class FeaturestoreEntityVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -11629,6 +13254,45 @@ def __init__(
self.online_store_connection_name = online_store_connection_name
+class FeatureSubset(MonitoringFeatureFilterBase):
+ """FeatureSubset.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ :ivar features: Required. [Required] The list of features to include.
+ :vartype features: list[str]
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ 'features': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ 'features': {'key': 'features', 'type': '[str]'},
+ }
+
+ def __init__(
+ self,
+ *,
+ features: List[str],
+ **kwargs
+ ):
+ """
+ :keyword features: Required. [Required] The list of features to include.
+ :paramtype features: list[str]
+ """
+ super(FeatureSubset, self).__init__(**kwargs)
+ self.filter_type = 'FeatureSubset' # type: str
+ self.features = features
+
+
class FeatureWindow(msrest.serialization.Model):
"""Specifies the feature window.
@@ -11686,6 +13350,48 @@ def __init__(
self.dataset_language = dataset_language
+class FileSystemSource(DataImportSource):
+ """FileSystemSource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar connection: Workspace connection for data import source storage.
+ :vartype connection: str
+ :ivar source_type: Required. [Required] Specifies the type of data.Constant filled by server.
+ Possible values include: "database", "file_system".
+ :vartype source_type: str or ~azure.mgmt.machinelearningservices.models.DataImportSourceType
+ :ivar path: Path on data import FileSystem source.
+ :vartype path: str
+ """
+
+ _validation = {
+ 'source_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'connection': {'key': 'connection', 'type': 'str'},
+ 'source_type': {'key': 'sourceType', 'type': 'str'},
+ 'path': {'key': 'path', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ connection: Optional[str] = None,
+ path: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword connection: Workspace connection for data import source storage.
+ :paramtype connection: str
+ :keyword path: Path on data import FileSystem source.
+ :paramtype path: str
+ """
+ super(FileSystemSource, self).__init__(connection=connection, **kwargs)
+ self.source_type = 'file_system' # type: str
+ self.path = path
+
+
class FlavorData(msrest.serialization.Model):
"""FlavorData.
@@ -11920,6 +13626,11 @@ class ForecastingSettings(msrest.serialization.Model):
:ivar feature_lags: Flag for generating lags for the numeric features with 'auto' or null.
Possible values include: "None", "Auto".
:vartype feature_lags: str or ~azure.mgmt.machinelearningservices.models.FeatureLags
+ :ivar features_unknown_at_forecast_time: The feature columns that are available for training
+ but unknown at the time of forecast/inference.
+ If features_unknown_at_forecast_time is not set, it is assumed that all the feature columns in
+ the dataset are known at inference time.
+ :vartype features_unknown_at_forecast_time: list[str]
:ivar forecast_horizon: The desired maximum forecast horizon in units of time-series frequency.
:vartype forecast_horizon: ~azure.mgmt.machinelearningservices.models.ForecastHorizon
:ivar frequency: When forecasting, this parameter represents the period with which the forecast
@@ -11964,6 +13675,7 @@ class ForecastingSettings(msrest.serialization.Model):
'country_or_region_for_holidays': {'key': 'countryOrRegionForHolidays', 'type': 'str'},
'cv_step_size': {'key': 'cvStepSize', 'type': 'int'},
'feature_lags': {'key': 'featureLags', 'type': 'str'},
+ 'features_unknown_at_forecast_time': {'key': 'featuresUnknownAtForecastTime', 'type': '[str]'},
'forecast_horizon': {'key': 'forecastHorizon', 'type': 'ForecastHorizon'},
'frequency': {'key': 'frequency', 'type': 'str'},
'seasonality': {'key': 'seasonality', 'type': 'Seasonality'},
@@ -11982,6 +13694,7 @@ def __init__(
country_or_region_for_holidays: Optional[str] = None,
cv_step_size: Optional[int] = None,
feature_lags: Optional[Union[str, "FeatureLags"]] = None,
+ features_unknown_at_forecast_time: Optional[List[str]] = None,
forecast_horizon: Optional["ForecastHorizon"] = None,
frequency: Optional[str] = None,
seasonality: Optional["Seasonality"] = None,
@@ -12006,6 +13719,11 @@ def __init__(
:keyword feature_lags: Flag for generating lags for the numeric features with 'auto' or null.
Possible values include: "None", "Auto".
:paramtype feature_lags: str or ~azure.mgmt.machinelearningservices.models.FeatureLags
+ :keyword features_unknown_at_forecast_time: The feature columns that are available for training
+ but unknown at the time of forecast/inference.
+ If features_unknown_at_forecast_time is not set, it is assumed that all the feature columns in
+ the dataset are known at inference time.
+ :paramtype features_unknown_at_forecast_time: list[str]
:keyword forecast_horizon: The desired maximum forecast horizon in units of time-series
frequency.
:paramtype forecast_horizon: ~azure.mgmt.machinelearningservices.models.ForecastHorizon
@@ -12051,6 +13769,7 @@ def __init__(
self.country_or_region_for_holidays = country_or_region_for_holidays
self.cv_step_size = cv_step_size
self.feature_lags = feature_lags
+ self.features_unknown_at_forecast_time = features_unknown_at_forecast_time
self.forecast_horizon = forecast_horizon
self.frequency = frequency
self.seasonality = seasonality
@@ -12352,8 +14071,10 @@ class HdfsDatastore(DatastoreProperties):
:vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
:ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
- "AzureFile", "Hdfs".
+ "AzureFile", "Hdfs", "OneLake".
:vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar is_default: Readonly property to indicate if datastore is the workspace default
datastore.
:vartype is_default: bool
@@ -12370,7 +14091,7 @@ class HdfsDatastore(DatastoreProperties):
'credentials': {'required': True},
'datastore_type': {'required': True},
'is_default': {'readonly': True},
- 'name_node_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'name_node_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -12379,6 +14100,7 @@ class HdfsDatastore(DatastoreProperties):
'tags': {'key': 'tags', 'type': '{str}'},
'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'is_default': {'key': 'isDefault', 'type': 'bool'},
'hdfs_server_certificate': {'key': 'hdfsServerCertificate', 'type': 'str'},
'name_node_address': {'key': 'nameNodeAddress', 'type': 'str'},
@@ -12393,6 +14115,7 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
hdfs_server_certificate: Optional[str] = None,
protocol: Optional[str] = "http",
**kwargs
@@ -12406,6 +14129,9 @@ def __init__(
:paramtype tags: dict[str, str]
:keyword credentials: Required. [Required] Account credentials.
:paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword hdfs_server_certificate: The TLS cert of the HDFS server. Needs to be a base64 encoded
string. Required if "Https" protocol is selected.
:paramtype hdfs_server_certificate: str
@@ -12414,7 +14140,7 @@ def __init__(
:keyword protocol: Protocol used to communicate with the storage account (Https/Http).
:paramtype protocol: str
"""
- super(HdfsDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, **kwargs)
+ super(HdfsDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, intellectual_property=intellectual_property, **kwargs)
self.datastore_type = 'Hdfs' # type: str
self.hdfs_server_certificate = hdfs_server_certificate
self.name_node_address = name_node_address
@@ -12599,7 +14325,7 @@ class IdAssetReference(AssetReferenceBase):
_validation = {
'reference_type': {'required': True},
- 'asset_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'asset_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -13389,11 +15115,11 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:code:`
Some examples are:
-
+```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
-`
+````
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
@@ -13663,11 +15389,11 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:code:`
Some examples are:
-
+```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
-`
+````
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
@@ -13945,11 +15671,11 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:code:`
Some examples are:
-
+```
ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";
-`
+````
For more details on how to compose distribution expressions please check the documentation:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
@@ -15028,6 +16754,14 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
Note: The training run may get into CUDA OOM if the size is too big.
Note: This settings is only supported for the 'yolov5' algorithm.
:vartype image_size: int
+ :ivar log_training_metrics: Enable computing and logging training metrics. Possible values
+ include: "Enable", "Disable".
+ :vartype log_training_metrics: str or
+ ~azure.mgmt.machinelearningservices.models.LogTrainingMetrics
+ :ivar log_validation_loss: Enable computing and logging validation loss. Possible values
+ include: "Enable", "Disable".
+ :vartype log_validation_loss: str or
+ ~azure.mgmt.machinelearningservices.models.LogValidationLoss
:ivar max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
Note: This settings is not supported for the 'yolov5' algorithm.
@@ -15107,6 +16841,8 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
'box_detections_per_image': {'key': 'boxDetectionsPerImage', 'type': 'int'},
'box_score_threshold': {'key': 'boxScoreThreshold', 'type': 'float'},
'image_size': {'key': 'imageSize', 'type': 'int'},
+ 'log_training_metrics': {'key': 'logTrainingMetrics', 'type': 'str'},
+ 'log_validation_loss': {'key': 'logValidationLoss', 'type': 'str'},
'max_size': {'key': 'maxSize', 'type': 'int'},
'min_size': {'key': 'minSize', 'type': 'int'},
'model_size': {'key': 'modelSize', 'type': 'str'},
@@ -15157,6 +16893,8 @@ def __init__(
box_detections_per_image: Optional[int] = None,
box_score_threshold: Optional[float] = None,
image_size: Optional[int] = None,
+ log_training_metrics: Optional[Union[str, "LogTrainingMetrics"]] = None,
+ log_validation_loss: Optional[Union[str, "LogValidationLoss"]] = None,
max_size: Optional[int] = None,
min_size: Optional[int] = None,
model_size: Optional[Union[str, "ModelSize"]] = None,
@@ -15273,6 +17011,14 @@ def __init__(
Note: The training run may get into CUDA OOM if the size is too big.
Note: This settings is only supported for the 'yolov5' algorithm.
:paramtype image_size: int
+ :keyword log_training_metrics: Enable computing and logging training metrics. Possible values
+ include: "Enable", "Disable".
+ :paramtype log_training_metrics: str or
+ ~azure.mgmt.machinelearningservices.models.LogTrainingMetrics
+ :keyword log_validation_loss: Enable computing and logging validation loss. Possible values
+ include: "Enable", "Disable".
+ :paramtype log_validation_loss: str or
+ ~azure.mgmt.machinelearningservices.models.LogValidationLoss
:keyword max_size: Maximum size of the image to be rescaled before feeding it to the backbone.
Must be a positive integer. Note: training run may get into CUDA OOM if the size is too big.
Note: This settings is not supported for the 'yolov5' algorithm.
@@ -15319,6 +17065,8 @@ def __init__(
self.box_detections_per_image = box_detections_per_image
self.box_score_threshold = box_score_threshold
self.image_size = image_size
+ self.log_training_metrics = log_training_metrics
+ self.log_validation_loss = log_validation_loss
self.max_size = max_size
self.min_size = min_size
self.model_size = model_size
@@ -15497,6 +17245,45 @@ def __init__(
self.sampling_algorithm = sampling_algorithm
+class ImportDataAction(ScheduleActionBase):
+ """ImportDataAction.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
+ :vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
+ :ivar data_import_definition: Required. [Required] Defines Schedule action definition details.
+ :vartype data_import_definition: ~azure.mgmt.machinelearningservices.models.DataImport
+ """
+
+ _validation = {
+ 'action_type': {'required': True},
+ 'data_import_definition': {'required': True},
+ }
+
+ _attribute_map = {
+ 'action_type': {'key': 'actionType', 'type': 'str'},
+ 'data_import_definition': {'key': 'dataImportDefinition', 'type': 'DataImport'},
+ }
+
+ def __init__(
+ self,
+ *,
+ data_import_definition: "DataImport",
+ **kwargs
+ ):
+ """
+ :keyword data_import_definition: Required. [Required] Defines Schedule action definition
+ details.
+ :paramtype data_import_definition: ~azure.mgmt.machinelearningservices.models.DataImport
+ """
+ super(ImportDataAction, self).__init__(**kwargs)
+ self.action_type = 'ImportData' # type: str
+ self.data_import_definition = data_import_definition
+
+
class IndexColumn(msrest.serialization.Model):
"""Dto object representing index column.
@@ -15626,14 +17413,56 @@ def __init__(
**kwargs
):
"""
- :keyword requests: Resource requests for this instance type.
- :paramtype requests: dict[str, str]
- :keyword limits: Resource limits for this instance type.
- :paramtype limits: dict[str, str]
+ :keyword requests: Resource requests for this instance type.
+ :paramtype requests: dict[str, str]
+ :keyword limits: Resource limits for this instance type.
+ :paramtype limits: dict[str, str]
+ """
+ super(InstanceTypeSchemaResources, self).__init__(**kwargs)
+ self.requests = requests
+ self.limits = limits
+
+
+class IntellectualProperty(msrest.serialization.Model):
+ """Intellectual Property details for a resource.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar protection_level: Protection level of the Intellectual Property. Possible values include:
+ "All", "None".
+ :vartype protection_level: str or ~azure.mgmt.machinelearningservices.models.ProtectionLevel
+ :ivar publisher: Required. [Required] Publisher of the Intellectual Property. Must be the same
+ as Registry publisher name.
+ :vartype publisher: str
+ """
+
+ _validation = {
+ 'publisher': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'protection_level': {'key': 'protectionLevel', 'type': 'str'},
+ 'publisher': {'key': 'publisher', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ publisher: str,
+ protection_level: Optional[Union[str, "ProtectionLevel"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword protection_level: Protection level of the Intellectual Property. Possible values
+ include: "All", "None".
+ :paramtype protection_level: str or ~azure.mgmt.machinelearningservices.models.ProtectionLevel
+ :keyword publisher: Required. [Required] Publisher of the Intellectual Property. Must be the
+ same as Registry publisher name.
+ :paramtype publisher: str
"""
- super(InstanceTypeSchemaResources, self).__init__(**kwargs)
- self.requests = requests
- self.limits = limits
+ super(IntellectualProperty, self).__init__(**kwargs)
+ self.protection_level = protection_level
+ self.publisher = publisher
class JobBase(Resource):
@@ -15731,6 +17560,10 @@ class JobResourceConfiguration(ResourceConfiguration):
:vartype instance_type: str
:ivar locations: Locations where the job can run.
:vartype locations: list[str]
+ :ivar max_instance_count: Optional max allowed number of instances or nodes to be used by the
+ compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :vartype max_instance_count: int
:ivar properties: Additional properties bag.
:vartype properties: dict[str, any]
:ivar docker_args: Extra arguments to pass to the Docker run command. This would override any
@@ -15751,6 +17584,7 @@ class JobResourceConfiguration(ResourceConfiguration):
'instance_count': {'key': 'instanceCount', 'type': 'int'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
'locations': {'key': 'locations', 'type': '[str]'},
+ 'max_instance_count': {'key': 'maxInstanceCount', 'type': 'int'},
'properties': {'key': 'properties', 'type': '{object}'},
'docker_args': {'key': 'dockerArgs', 'type': 'str'},
'shm_size': {'key': 'shmSize', 'type': 'str'},
@@ -15762,6 +17596,7 @@ def __init__(
instance_count: Optional[int] = 1,
instance_type: Optional[str] = None,
locations: Optional[List[str]] = None,
+ max_instance_count: Optional[int] = None,
properties: Optional[Dict[str, Any]] = None,
docker_args: Optional[str] = None,
shm_size: Optional[str] = "2g",
@@ -15774,6 +17609,10 @@ def __init__(
:paramtype instance_type: str
:keyword locations: Locations where the job can run.
:paramtype locations: list[str]
+ :keyword max_instance_count: Optional max allowed number of instances or nodes to be used by
+ the compute target.
+ For use with elastic training, currently supported by PyTorch distribution type only.
+ :paramtype max_instance_count: int
:keyword properties: Additional properties bag.
:paramtype properties: dict[str, any]
:keyword docker_args: Extra arguments to pass to the Docker run command. This would override
@@ -15785,7 +17624,7 @@ def __init__(
b(bytes), k(kilobytes), m(megabytes), or g(gigabytes).
:paramtype shm_size: str
"""
- super(JobResourceConfiguration, self).__init__(instance_count=instance_count, instance_type=instance_type, locations=locations, properties=properties, **kwargs)
+ super(JobResourceConfiguration, self).__init__(instance_count=instance_count, instance_type=instance_type, locations=locations, max_instance_count=max_instance_count, properties=properties, **kwargs)
self.docker_args = docker_args
self.shm_size = shm_size
@@ -15796,7 +17635,8 @@ class JobScheduleAction(ScheduleActionBase):
All required parameters must be populated in order to send to Azure.
:ivar action_type: Required. [Required] Specifies the action type of the schedule.Constant
- filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint".
+ filled by server. Possible values include: "CreateJob", "InvokeBatchEndpoint", "ImportData",
+ "CreateMonitor".
:vartype action_type: str or ~azure.mgmt.machinelearningservices.models.ScheduleActionType
:ivar job_definition: Required. [Required] Defines Schedule action definition details.
:vartype job_definition: ~azure.mgmt.machinelearningservices.models.JobBaseProperties
@@ -15912,9 +17752,9 @@ class KerberosCredentials(msrest.serialization.Model):
"""
_validation = {
- 'kerberos_kdc_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_principal': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_realm': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_kdc_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_principal': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_realm': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -15967,9 +17807,9 @@ class KerberosKeytabCredentials(DatastoreCredentials, KerberosCredentials):
"""
_validation = {
- 'kerberos_kdc_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_principal': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_realm': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_kdc_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_principal': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_realm': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'credentials_type': {'required': True},
'secrets': {'required': True},
}
@@ -16068,9 +17908,9 @@ class KerberosPasswordCredentials(DatastoreCredentials, KerberosCredentials):
"""
_validation = {
- 'kerberos_kdc_address': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_principal': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'kerberos_realm': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_kdc_address': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_principal': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'kerberos_realm': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'credentials_type': {'required': True},
'secrets': {'required': True},
}
@@ -16294,6 +18134,8 @@ class OnlineDeploymentProperties(EndpointDeploymentPropertiesBase):
:vartype properties: dict[str, str]
:ivar app_insights_enabled: If true, enables Application Insights logging.
:vartype app_insights_enabled: bool
+ :ivar data_collector: The mdc configuration, we disable mdc when it's null.
+ :vartype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:ivar egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -16339,6 +18181,7 @@ class OnlineDeploymentProperties(EndpointDeploymentPropertiesBase):
'environment_variables': {'key': 'environmentVariables', 'type': '{str}'},
'properties': {'key': 'properties', 'type': '{str}'},
'app_insights_enabled': {'key': 'appInsightsEnabled', 'type': 'bool'},
+ 'data_collector': {'key': 'dataCollector', 'type': 'DataCollector'},
'egress_public_network_access': {'key': 'egressPublicNetworkAccess', 'type': 'str'},
'endpoint_compute_type': {'key': 'endpointComputeType', 'type': 'str'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
@@ -16364,6 +18207,7 @@ def __init__(
environment_variables: Optional[Dict[str, str]] = None,
properties: Optional[Dict[str, str]] = None,
app_insights_enabled: Optional[bool] = False,
+ data_collector: Optional["DataCollector"] = None,
egress_public_network_access: Optional[Union[str, "EgressPublicNetworkAccessType"]] = None,
instance_type: Optional[str] = None,
liveness_probe: Optional["ProbeSettings"] = None,
@@ -16388,6 +18232,8 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword app_insights_enabled: If true, enables Application Insights logging.
:paramtype app_insights_enabled: bool
+ :keyword data_collector: The mdc configuration, we disable mdc when it's null.
+ :paramtype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:keyword egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -16414,6 +18260,7 @@ def __init__(
"""
super(OnlineDeploymentProperties, self).__init__(code_configuration=code_configuration, description=description, environment_id=environment_id, environment_variables=environment_variables, properties=properties, **kwargs)
self.app_insights_enabled = app_insights_enabled
+ self.data_collector = data_collector
self.egress_public_network_access = egress_public_network_access
self.endpoint_compute_type = 'OnlineDeploymentProperties' # type: str
self.instance_type = instance_type
@@ -16446,6 +18293,8 @@ class KubernetesOnlineDeployment(OnlineDeploymentProperties):
:vartype properties: dict[str, str]
:ivar app_insights_enabled: If true, enables Application Insights logging.
:vartype app_insights_enabled: bool
+ :ivar data_collector: The mdc configuration, we disable mdc when it's null.
+ :vartype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:ivar egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -16495,6 +18344,7 @@ class KubernetesOnlineDeployment(OnlineDeploymentProperties):
'environment_variables': {'key': 'environmentVariables', 'type': '{str}'},
'properties': {'key': 'properties', 'type': '{str}'},
'app_insights_enabled': {'key': 'appInsightsEnabled', 'type': 'bool'},
+ 'data_collector': {'key': 'dataCollector', 'type': 'DataCollector'},
'egress_public_network_access': {'key': 'egressPublicNetworkAccess', 'type': 'str'},
'endpoint_compute_type': {'key': 'endpointComputeType', 'type': 'str'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
@@ -16517,6 +18367,7 @@ def __init__(
environment_variables: Optional[Dict[str, str]] = None,
properties: Optional[Dict[str, str]] = None,
app_insights_enabled: Optional[bool] = False,
+ data_collector: Optional["DataCollector"] = None,
egress_public_network_access: Optional[Union[str, "EgressPublicNetworkAccessType"]] = None,
instance_type: Optional[str] = None,
liveness_probe: Optional["ProbeSettings"] = None,
@@ -16542,6 +18393,8 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword app_insights_enabled: If true, enables Application Insights logging.
:paramtype app_insights_enabled: bool
+ :keyword data_collector: The mdc configuration, we disable mdc when it's null.
+ :paramtype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:keyword egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -16570,7 +18423,7 @@ def __init__(
:paramtype container_resource_requirements:
~azure.mgmt.machinelearningservices.models.ContainerResourceRequirements
"""
- super(KubernetesOnlineDeployment, self).__init__(code_configuration=code_configuration, description=description, environment_id=environment_id, environment_variables=environment_variables, properties=properties, app_insights_enabled=app_insights_enabled, egress_public_network_access=egress_public_network_access, instance_type=instance_type, liveness_probe=liveness_probe, model=model, model_mount_path=model_mount_path, readiness_probe=readiness_probe, request_settings=request_settings, scale_settings=scale_settings, **kwargs)
+ super(KubernetesOnlineDeployment, self).__init__(code_configuration=code_configuration, description=description, environment_id=environment_id, environment_variables=environment_variables, properties=properties, app_insights_enabled=app_insights_enabled, data_collector=data_collector, egress_public_network_access=egress_public_network_access, instance_type=instance_type, liveness_probe=liveness_probe, model=model, model_mount_path=model_mount_path, readiness_probe=readiness_probe, request_settings=request_settings, scale_settings=scale_settings, **kwargs)
self.endpoint_compute_type = 'Kubernetes' # type: str
self.container_resource_requirements = container_resource_requirements
@@ -16944,6 +18797,9 @@ class LabelingJobProperties(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -17000,6 +18856,7 @@ class LabelingJobProperties(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'created_date_time': {'key': 'createdDateTime', 'type': 'iso-8601'},
@@ -17027,6 +18884,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
data_configuration: Optional["LabelingDataConfiguration"] = None,
job_instructions: Optional["LabelingJobInstructions"] = None,
@@ -17059,6 +18917,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -17077,7 +18938,7 @@ def __init__(
:paramtype ml_assist_configuration:
~azure.mgmt.machinelearningservices.models.MLAssistConfiguration
"""
- super(LabelingJobProperties, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, services=services, **kwargs)
+ super(LabelingJobProperties, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, secrets_configuration=secrets_configuration, services=services, **kwargs)
self.job_type = 'Labeling' # type: str
self.created_date_time = None
self.data_configuration = data_configuration
@@ -17164,6 +19025,86 @@ def __init__(
self.annotation_type = annotation_type
+class OneLakeArtifact(msrest.serialization.Model):
+ """OneLake artifact (data source) configuration.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: LakehouseArtifact.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar artifact_name: Required. [Required] OneLake artifact name.
+ :vartype artifact_name: str
+ :ivar artifact_type: Required. [Required] OneLake artifact type.Constant filled by server.
+ Possible values include: "Lakehouse".
+ :vartype artifact_type: str or ~azure.mgmt.machinelearningservices.models.OneLakeArtifactType
+ """
+
+ _validation = {
+ 'artifact_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'artifact_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'artifact_name': {'key': 'artifactName', 'type': 'str'},
+ 'artifact_type': {'key': 'artifactType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'artifact_type': {'Lakehouse': 'LakehouseArtifact'}
+ }
+
+ def __init__(
+ self,
+ *,
+ artifact_name: str,
+ **kwargs
+ ):
+ """
+ :keyword artifact_name: Required. [Required] OneLake artifact name.
+ :paramtype artifact_name: str
+ """
+ super(OneLakeArtifact, self).__init__(**kwargs)
+ self.artifact_name = artifact_name
+ self.artifact_type = None # type: Optional[str]
+
+
+class LakehouseArtifact(OneLakeArtifact):
+ """LakehouseArtifact.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar artifact_name: Required. [Required] OneLake artifact name.
+ :vartype artifact_name: str
+ :ivar artifact_type: Required. [Required] OneLake artifact type.Constant filled by server.
+ Possible values include: "Lakehouse".
+ :vartype artifact_type: str or ~azure.mgmt.machinelearningservices.models.OneLakeArtifactType
+ """
+
+ _validation = {
+ 'artifact_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'artifact_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'artifact_name': {'key': 'artifactName', 'type': 'str'},
+ 'artifact_type': {'key': 'artifactType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ artifact_name: str,
+ **kwargs
+ ):
+ """
+ :keyword artifact_name: Required. [Required] OneLake artifact name.
+ :paramtype artifact_name: str
+ """
+ super(LakehouseArtifact, self).__init__(artifact_name=artifact_name, **kwargs)
+ self.artifact_type = 'Lakehouse' # type: str
+
+
class ListAmlUserFeatureResult(msrest.serialization.Model):
"""The List Aml user feature operation response.
@@ -17388,7 +19329,7 @@ class LiteralJobInput(JobInput):
_validation = {
'job_input_type': {'required': True},
- 'value': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'value': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -17560,6 +19501,8 @@ class ManagedOnlineDeployment(OnlineDeploymentProperties):
:vartype properties: dict[str, str]
:ivar app_insights_enabled: If true, enables Application Insights logging.
:vartype app_insights_enabled: bool
+ :ivar data_collector: The mdc configuration, we disable mdc when it's null.
+ :vartype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:ivar egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -17605,6 +19548,7 @@ class ManagedOnlineDeployment(OnlineDeploymentProperties):
'environment_variables': {'key': 'environmentVariables', 'type': '{str}'},
'properties': {'key': 'properties', 'type': '{str}'},
'app_insights_enabled': {'key': 'appInsightsEnabled', 'type': 'bool'},
+ 'data_collector': {'key': 'dataCollector', 'type': 'DataCollector'},
'egress_public_network_access': {'key': 'egressPublicNetworkAccess', 'type': 'str'},
'endpoint_compute_type': {'key': 'endpointComputeType', 'type': 'str'},
'instance_type': {'key': 'instanceType', 'type': 'str'},
@@ -17626,6 +19570,7 @@ def __init__(
environment_variables: Optional[Dict[str, str]] = None,
properties: Optional[Dict[str, str]] = None,
app_insights_enabled: Optional[bool] = False,
+ data_collector: Optional["DataCollector"] = None,
egress_public_network_access: Optional[Union[str, "EgressPublicNetworkAccessType"]] = None,
instance_type: Optional[str] = None,
liveness_probe: Optional["ProbeSettings"] = None,
@@ -17650,6 +19595,8 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword app_insights_enabled: If true, enables Application Insights logging.
:paramtype app_insights_enabled: bool
+ :keyword data_collector: The mdc configuration, we disable mdc when it's null.
+ :paramtype data_collector: ~azure.mgmt.machinelearningservices.models.DataCollector
:keyword egress_public_network_access: If Enabled, allow egress public network access. If
Disabled, this will create secure egress. Default: Enabled. Possible values include: "Enabled",
"Disabled".
@@ -17674,7 +19621,7 @@ def __init__(
and to DefaultScaleSettings for ManagedOnlineDeployment.
:paramtype scale_settings: ~azure.mgmt.machinelearningservices.models.OnlineScaleSettings
"""
- super(ManagedOnlineDeployment, self).__init__(code_configuration=code_configuration, description=description, environment_id=environment_id, environment_variables=environment_variables, properties=properties, app_insights_enabled=app_insights_enabled, egress_public_network_access=egress_public_network_access, instance_type=instance_type, liveness_probe=liveness_probe, model=model, model_mount_path=model_mount_path, readiness_probe=readiness_probe, request_settings=request_settings, scale_settings=scale_settings, **kwargs)
+ super(ManagedOnlineDeployment, self).__init__(code_configuration=code_configuration, description=description, environment_id=environment_id, environment_variables=environment_variables, properties=properties, app_insights_enabled=app_insights_enabled, data_collector=data_collector, egress_public_network_access=egress_public_network_access, instance_type=instance_type, liveness_probe=liveness_probe, model=model, model_mount_path=model_mount_path, readiness_probe=readiness_probe, request_settings=request_settings, scale_settings=scale_settings, **kwargs)
self.endpoint_compute_type = 'Managed' # type: str
@@ -17945,8 +19892,8 @@ class MLAssistConfigurationEnabled(MLAssistConfiguration):
_validation = {
'ml_assist': {'required': True},
- 'inferencing_compute_binding': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
- 'training_compute_binding': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'inferencing_compute_binding': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'training_compute_binding': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -17994,7 +19941,7 @@ class MLFlowModelJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -18038,6 +19985,8 @@ class MLFlowModelJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -18058,6 +20007,7 @@ class MLFlowModelJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -18069,6 +20019,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
description: Optional[str] = None,
@@ -18079,6 +20030,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -18087,9 +20040,10 @@ def __init__(
:keyword description: Description for the output.
:paramtype description: str
"""
- super(MLFlowModelJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, mode=mode, uri=uri, **kwargs)
+ super(MLFlowModelJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, auto_delete_setting=auto_delete_setting, mode=mode, uri=uri, **kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
self.job_output_type = 'mlflow_model' # type: str
@@ -18107,9 +20061,13 @@ class MLTableData(DataVersionBaseProperties):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
Possible values include: "uri_file", "uri_folder", "mltable".
@@ -18117,23 +20075,31 @@ class MLTableData(DataVersionBaseProperties):
:ivar data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
:ivar referenced_uris: Uris referenced in the MLTable definition (required for lineage).
:vartype referenced_uris: list[str]
"""
_validation = {
'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'data_type': {'key': 'dataType', 'type': 'str'},
'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
'referenced_uris': {'key': 'referencedUris', 'type': '[str]'},
}
@@ -18144,8 +20110,11 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
+ intellectual_property: Optional["IntellectualProperty"] = None,
+ stage: Optional[str] = None,
referenced_uris: Optional[List[str]] = None,
**kwargs
):
@@ -18156,17 +20125,27 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
:keyword referenced_uris: Uris referenced in the MLTable definition (required for lineage).
:paramtype referenced_uris: list[str]
"""
- super(MLTableData, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, **kwargs)
+ super(MLTableData, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, intellectual_property=intellectual_property, stage=stage, **kwargs)
self.data_type = 'mltable' # type: str
self.referenced_uris = referenced_uris
@@ -18190,7 +20169,7 @@ class MLTableJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -18234,6 +20213,8 @@ class MLTableJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -18254,6 +20235,7 @@ class MLTableJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -18265,6 +20247,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
description: Optional[str] = None,
@@ -18275,6 +20258,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -18283,9 +20268,10 @@ def __init__(
:keyword description: Description for the output.
:paramtype description: str
"""
- super(MLTableJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, mode=mode, uri=uri, **kwargs)
+ super(MLTableJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, auto_delete_setting=auto_delete_setting, mode=mode, uri=uri, **kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
self.job_output_type = 'mltable' # type: str
@@ -18531,6 +20517,89 @@ def __init__(
self.path = path
+class ModelPerformanceSignalBase(MonitoringSignalBase):
+ """ModelPerformanceSignalBase.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar data_segment: The data segment.
+ :vartype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :ivar metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.ModelPerformanceMetricThresholdBase
+ :ivar target_data: Required. [Required] The data produced by the production service which drift
+ will be calculated for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_threshold': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'data_segment': {'key': 'dataSegment', 'type': 'MonitoringDataSegment'},
+ 'metric_threshold': {'key': 'metricThreshold', 'type': 'ModelPerformanceMetricThresholdBase'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ *,
+ baseline_data: "MonitoringInputData",
+ metric_threshold: "ModelPerformanceMetricThresholdBase",
+ target_data: "MonitoringInputData",
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ data_segment: Optional["MonitoringDataSegment"] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword data_segment: The data segment.
+ :paramtype data_segment: ~azure.mgmt.machinelearningservices.models.MonitoringDataSegment
+ :keyword metric_threshold: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_threshold:
+ ~azure.mgmt.machinelearningservices.models.ModelPerformanceMetricThresholdBase
+ :keyword target_data: Required. [Required] The data produced by the production service which
+ drift will be calculated for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(ModelPerformanceSignalBase, self).__init__(lookback_period=lookback_period, mode=mode, **kwargs)
+ self.signal_type = 'ModelPerformanceSignalBase' # type: str
+ self.baseline_data = baseline_data
+ self.data_segment = data_segment
+ self.metric_threshold = metric_threshold
+ self.target_data = target_data
+
+
class ModelVersion(Resource):
"""Azure Resource Manager resource envelope.
@@ -18594,12 +20663,19 @@ class ModelVersionProperties(AssetBase):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar flavors: Mapping of model flavors to their properties.
:vartype flavors: dict[str, ~azure.mgmt.machinelearningservices.models.FlavorData]
+ :ivar intellectual_property: Intellectual Property details. Used if model is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:ivar job_name: Name of the training job which produced this model.
:vartype job_name: str
:ivar model_type: The storage format for this entity. Used for NCD.
@@ -18610,6 +20686,8 @@ class ModelVersionProperties(AssetBase):
"Succeeded", "Failed", "Canceled", "Creating", "Updating", "Deleting".
:vartype provisioning_state: str or
~azure.mgmt.machinelearningservices.models.AssetProvisioningState
+ :ivar stage: Stage in the model lifecycle assigned to this model.
+ :vartype stage: str
"""
_validation = {
@@ -18620,13 +20698,16 @@ class ModelVersionProperties(AssetBase):
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'flavors': {'key': 'flavors', 'type': '{FlavorData}'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
'job_name': {'key': 'jobName', 'type': 'str'},
'model_type': {'key': 'modelType', 'type': 'str'},
'model_uri': {'key': 'modelUri', 'type': 'str'},
'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -18635,12 +20716,15 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
flavors: Optional[Dict[str, "FlavorData"]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
job_name: Optional[str] = None,
model_type: Optional[str] = None,
model_uri: Optional[str] = None,
+ stage: Optional[str] = None,
**kwargs
):
"""
@@ -18650,25 +20734,37 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword flavors: Mapping of model flavors to their properties.
:paramtype flavors: dict[str, ~azure.mgmt.machinelearningservices.models.FlavorData]
+ :keyword intellectual_property: Intellectual Property details. Used if model is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
:keyword job_name: Name of the training job which produced this model.
:paramtype job_name: str
:keyword model_type: The storage format for this entity. Used for NCD.
:paramtype model_type: str
:keyword model_uri: The URI path to the model contents.
:paramtype model_uri: str
+ :keyword stage: Stage in the model lifecycle assigned to this model.
+ :paramtype stage: str
"""
- super(ModelVersionProperties, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
+ super(ModelVersionProperties, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, **kwargs)
self.flavors = flavors
+ self.intellectual_property = intellectual_property
self.job_name = job_name
self.model_type = model_type
self.model_uri = model_uri
self.provisioning_state = None
+ self.stage = stage
class ModelVersionResourceArmPaginatedResult(msrest.serialization.Model):
@@ -18705,13 +20801,179 @@ def __init__(
self.value = value
+class MonitorDefinition(msrest.serialization.Model):
+ """MonitorDefinition.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar compute_id: Required. [Required] The ARM resource ID of the compute resource to run the
+ monitoring job on.
+ :vartype compute_id: str
+ :ivar monitoring_target: The ARM resource ID of either the model or deployment targeted by this
+ monitor.
+ :vartype monitoring_target: str
+ :ivar notification_setting: The monitor's notification settings.
+ :vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar signals: Required. [Required] The signals to monitor.
+ :vartype signals: dict[str, ~azure.mgmt.machinelearningservices.models.MonitoringSignalBase]
+ """
+
+ _validation = {
+ 'compute_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ 'signals': {'required': True},
+ }
+
+ _attribute_map = {
+ 'compute_id': {'key': 'computeId', 'type': 'str'},
+ 'monitoring_target': {'key': 'monitoringTarget', 'type': 'str'},
+ 'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'signals': {'key': 'signals', 'type': '{MonitoringSignalBase}'},
+ }
+
+ def __init__(
+ self,
+ *,
+ compute_id: str,
+ signals: Dict[str, "MonitoringSignalBase"],
+ monitoring_target: Optional[str] = None,
+ notification_setting: Optional["NotificationSetting"] = None,
+ **kwargs
+ ):
+ """
+ :keyword compute_id: Required. [Required] The ARM resource ID of the compute resource to run
+ the monitoring job on.
+ :paramtype compute_id: str
+ :keyword monitoring_target: The ARM resource ID of either the model or deployment targeted by
+ this monitor.
+ :paramtype monitoring_target: str
+ :keyword notification_setting: The monitor's notification settings.
+ :paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword signals: Required. [Required] The signals to monitor.
+ :paramtype signals: dict[str, ~azure.mgmt.machinelearningservices.models.MonitoringSignalBase]
+ """
+ super(MonitorDefinition, self).__init__(**kwargs)
+ self.compute_id = compute_id
+ self.monitoring_target = monitoring_target
+ self.notification_setting = notification_setting
+ self.signals = signals
+
+
+class MonitoringDataSegment(msrest.serialization.Model):
+ """MonitoringDataSegment.
+
+ :ivar feature: The feature to segment the data on.
+ :vartype feature: str
+ :ivar values: Filters for only the specified values of the given segmented feature.
+ :vartype values: list[str]
+ """
+
+ _attribute_map = {
+ 'feature': {'key': 'feature', 'type': 'str'},
+ 'values': {'key': 'values', 'type': '[str]'},
+ }
+
+ def __init__(
+ self,
+ *,
+ feature: Optional[str] = None,
+ values: Optional[List[str]] = None,
+ **kwargs
+ ):
+ """
+ :keyword feature: The feature to segment the data on.
+ :paramtype feature: str
+ :keyword values: Filters for only the specified values of the given segmented feature.
+ :paramtype values: list[str]
+ """
+ super(MonitoringDataSegment, self).__init__(**kwargs)
+ self.feature = feature
+ self.values = values
+
+
+class MonitoringInputData(msrest.serialization.Model):
+ """MonitoringInputData.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar asset: The data asset input to be leveraged by the monitoring job..
+ :vartype asset: any
+ :ivar data_context: Required. [Required] The context of the data source. Possible values
+ include: "ModelInputs", "ModelOutputs", "Training", "Test", "Validation", "GroundTruth".
+ :vartype data_context: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputDataContext
+ :ivar preprocessing_component_id: The ARM resource ID of the component resource used to
+ preprocess the data.
+ :vartype preprocessing_component_id: str
+ """
+
+ _validation = {
+ 'data_context': {'required': True},
+ }
+
+ _attribute_map = {
+ 'asset': {'key': 'asset', 'type': 'object'},
+ 'data_context': {'key': 'dataContext', 'type': 'str'},
+ 'preprocessing_component_id': {'key': 'preprocessingComponentId', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ data_context: Union[str, "MonitoringInputDataContext"],
+ asset: Optional[Any] = None,
+ preprocessing_component_id: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword asset: The data asset input to be leveraged by the monitoring job..
+ :paramtype asset: any
+ :keyword data_context: Required. [Required] The context of the data source. Possible values
+ include: "ModelInputs", "ModelOutputs", "Training", "Test", "Validation", "GroundTruth".
+ :paramtype data_context: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringInputDataContext
+ :keyword preprocessing_component_id: The ARM resource ID of the component resource used to
+ preprocess the data.
+ :paramtype preprocessing_component_id: str
+ """
+ super(MonitoringInputData, self).__init__(**kwargs)
+ self.asset = asset
+ self.data_context = data_context
+ self.preprocessing_component_id = preprocessing_component_id
+
+
+class MonitoringThreshold(msrest.serialization.Model):
+ """MonitoringThreshold.
+
+ :ivar value: The threshold value. If null, the set default is dependent on the metric type.
+ :vartype value: float
+ """
+
+ _attribute_map = {
+ 'value': {'key': 'value', 'type': 'float'},
+ }
+
+ def __init__(
+ self,
+ *,
+ value: Optional[float] = None,
+ **kwargs
+ ):
+ """
+ :keyword value: The threshold value. If null, the set default is dependent on the metric type.
+ :paramtype value: float
+ """
+ super(MonitoringThreshold, self).__init__(**kwargs)
+ self.value = value
+
+
class Mpi(DistributionConfiguration):
"""MPI distribution configuration.
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
:ivar process_count_per_instance: Number of processes per MPI node.
:vartype process_count_per_instance: int
@@ -19335,81 +21597,237 @@ def __init__(
self.status_code = status_code
-class NotebookResourceInfo(msrest.serialization.Model):
- """NotebookResourceInfo.
+class NotebookResourceInfo(msrest.serialization.Model):
+ """NotebookResourceInfo.
+
+ :ivar fqdn:
+ :vartype fqdn: str
+ :ivar resource_id: the data plane resourceId that used to initialize notebook component.
+ :vartype resource_id: str
+ :ivar notebook_preparation_error: The error that occurs when preparing notebook.
+ :vartype notebook_preparation_error:
+ ~azure.mgmt.machinelearningservices.models.NotebookPreparationError
+ """
+
+ _attribute_map = {
+ 'fqdn': {'key': 'fqdn', 'type': 'str'},
+ 'resource_id': {'key': 'resourceId', 'type': 'str'},
+ 'notebook_preparation_error': {'key': 'notebookPreparationError', 'type': 'NotebookPreparationError'},
+ }
+
+ def __init__(
+ self,
+ *,
+ fqdn: Optional[str] = None,
+ resource_id: Optional[str] = None,
+ notebook_preparation_error: Optional["NotebookPreparationError"] = None,
+ **kwargs
+ ):
+ """
+ :keyword fqdn:
+ :paramtype fqdn: str
+ :keyword resource_id: the data plane resourceId that used to initialize notebook component.
+ :paramtype resource_id: str
+ :keyword notebook_preparation_error: The error that occurs when preparing notebook.
+ :paramtype notebook_preparation_error:
+ ~azure.mgmt.machinelearningservices.models.NotebookPreparationError
+ """
+ super(NotebookResourceInfo, self).__init__(**kwargs)
+ self.fqdn = fqdn
+ self.resource_id = resource_id
+ self.notebook_preparation_error = notebook_preparation_error
+
+
+class NotificationSetting(msrest.serialization.Model):
+ """Configuration for notification.
+
+ :ivar email_on: Send email notification to user on specified notfication type.
+ :vartype email_on: list[str or
+ ~azure.mgmt.machinelearningservices.models.EmailNotificationEnableType]
+ :ivar emails: This is the email recipient list which has a limitation of 499 characters in
+ total concat with comma seperator.
+ :vartype emails: list[str]
+ :ivar webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :vartype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
+ """
+
+ _attribute_map = {
+ 'email_on': {'key': 'emailOn', 'type': '[str]'},
+ 'emails': {'key': 'emails', 'type': '[str]'},
+ 'webhooks': {'key': 'webhooks', 'type': '{Webhook}'},
+ }
+
+ def __init__(
+ self,
+ *,
+ email_on: Optional[List[Union[str, "EmailNotificationEnableType"]]] = None,
+ emails: Optional[List[str]] = None,
+ webhooks: Optional[Dict[str, "Webhook"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword email_on: Send email notification to user on specified notfication type.
+ :paramtype email_on: list[str or
+ ~azure.mgmt.machinelearningservices.models.EmailNotificationEnableType]
+ :keyword emails: This is the email recipient list which has a limitation of 499 characters in
+ total concat with comma seperator.
+ :paramtype emails: list[str]
+ :keyword webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :paramtype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
+ """
+ super(NotificationSetting, self).__init__(**kwargs)
+ self.email_on = email_on
+ self.emails = emails
+ self.webhooks = webhooks
+
+
+class NumericalDataDriftMetricThreshold(DataDriftMetricThresholdBase):
+ """NumericalDataDriftMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The numerical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataDriftMetric
+ """
+
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: Union[str, "NumericalDataDriftMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The numerical data drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataDriftMetric
+ """
+ super(NumericalDataDriftMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.data_type = 'Numerical' # type: str
+ self.metric = metric
+
+
+class NumericalDataQualityMetricThreshold(DataQualityMetricThresholdBase):
+ """NumericalDataQualityMetricThreshold.
- :ivar fqdn:
- :vartype fqdn: str
- :ivar resource_id: the data plane resourceId that used to initialize notebook component.
- :vartype resource_id: str
- :ivar notebook_preparation_error: The error that occurs when preparing notebook.
- :vartype notebook_preparation_error:
- ~azure.mgmt.machinelearningservices.models.NotebookPreparationError
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The numerical data quality metric to calculate. Possible
+ values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :vartype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataQualityMetric
"""
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
_attribute_map = {
- 'fqdn': {'key': 'fqdn', 'type': 'str'},
- 'resource_id': {'key': 'resourceId', 'type': 'str'},
- 'notebook_preparation_error': {'key': 'notebookPreparationError', 'type': 'NotebookPreparationError'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
}
def __init__(
self,
*,
- fqdn: Optional[str] = None,
- resource_id: Optional[str] = None,
- notebook_preparation_error: Optional["NotebookPreparationError"] = None,
+ metric: Union[str, "NumericalDataQualityMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
**kwargs
):
"""
- :keyword fqdn:
- :paramtype fqdn: str
- :keyword resource_id: the data plane resourceId that used to initialize notebook component.
- :paramtype resource_id: str
- :keyword notebook_preparation_error: The error that occurs when preparing notebook.
- :paramtype notebook_preparation_error:
- ~azure.mgmt.machinelearningservices.models.NotebookPreparationError
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The numerical data quality metric to calculate. Possible
+ values include: "NullValueRate", "DataTypeErrorRate", "OutOfBoundsRate".
+ :paramtype metric: str or ~azure.mgmt.machinelearningservices.models.NumericalDataQualityMetric
"""
- super(NotebookResourceInfo, self).__init__(**kwargs)
- self.fqdn = fqdn
- self.resource_id = resource_id
- self.notebook_preparation_error = notebook_preparation_error
+ super(NumericalDataQualityMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.data_type = 'Numerical' # type: str
+ self.metric = metric
-class NotificationSetting(msrest.serialization.Model):
- """Configuration for notification.
+class NumericalPredictionDriftMetricThreshold(PredictionDriftMetricThresholdBase):
+ """NumericalPredictionDriftMetricThreshold.
- :ivar email_on: Send email notification to user on specified notification type.
- :vartype email_on: list[str or
- ~azure.mgmt.machinelearningservices.models.EmailNotificationEnableType]
- :ivar emails: This is the email recipient list which has a limitation of 499 characters in
- total concat with comma separator.
- :vartype emails: list[str]
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar data_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Numerical", "Categorical".
+ :vartype data_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringFeatureDataType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The numerical prediction drift metric to calculate. Possible
+ values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.NumericalPredictionDriftMetric
"""
+ _validation = {
+ 'data_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
_attribute_map = {
- 'email_on': {'key': 'emailOn', 'type': '[str]'},
- 'emails': {'key': 'emails', 'type': '[str]'},
+ 'data_type': {'key': 'dataType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
}
def __init__(
self,
*,
- email_on: Optional[List[Union[str, "EmailNotificationEnableType"]]] = None,
- emails: Optional[List[str]] = None,
+ metric: Union[str, "NumericalPredictionDriftMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
**kwargs
):
"""
- :keyword email_on: Send email notification to user on specified notification type.
- :paramtype email_on: list[str or
- ~azure.mgmt.machinelearningservices.models.EmailNotificationEnableType]
- :keyword emails: This is the email recipient list which has a limitation of 499 characters in
- total concat with comma separator.
- :paramtype emails: list[str]
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The numerical prediction drift metric to calculate.
+ Possible values include: "JensenShannonDistance", "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance", "TwoSampleKolmogorovSmirnovTest".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.NumericalPredictionDriftMetric
"""
- super(NotificationSetting, self).__init__(**kwargs)
- self.email_on = email_on
- self.emails = emails
+ super(NumericalPredictionDriftMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.data_type = 'Numerical' # type: str
+ self.metric = metric
class Objective(msrest.serialization.Model):
@@ -19426,7 +21844,7 @@ class Objective(msrest.serialization.Model):
_validation = {
'goal': {'required': True},
- 'primary_metric': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'primary_metric': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -19453,6 +21871,111 @@ def __init__(
self.primary_metric = primary_metric
+class OneLakeDatastore(DatastoreProperties):
+ """OneLake (Trident) datastore configuration.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar description: The asset description text.
+ :vartype description: str
+ :ivar properties: The asset property dictionary.
+ :vartype properties: dict[str, str]
+ :ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :vartype tags: dict[str, str]
+ :ivar credentials: Required. [Required] Account credentials.
+ :vartype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :ivar datastore_type: Required. [Required] Storage type backing the datastore.Constant filled
+ by server. Possible values include: "AzureBlob", "AzureDataLakeGen1", "AzureDataLakeGen2",
+ "AzureFile", "Hdfs", "OneLake".
+ :vartype datastore_type: str or ~azure.mgmt.machinelearningservices.models.DatastoreType
+ :ivar intellectual_property: Intellectual Property details.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar is_default: Readonly property to indicate if datastore is the workspace default
+ datastore.
+ :vartype is_default: bool
+ :ivar artifact: Required. [Required] OneLake artifact backing the datastore.
+ :vartype artifact: ~azure.mgmt.machinelearningservices.models.OneLakeArtifact
+ :ivar endpoint: OneLake endpoint to use for the datastore.
+ :vartype endpoint: str
+ :ivar one_lake_workspace_name: Required. [Required] OneLake workspace name.
+ :vartype one_lake_workspace_name: str
+ :ivar service_data_access_auth_identity: Indicates which identity to use to authenticate
+ service data access to customer's storage. Possible values include: "None",
+ "WorkspaceSystemAssignedIdentity", "WorkspaceUserAssignedIdentity".
+ :vartype service_data_access_auth_identity: str or
+ ~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
+ """
+
+ _validation = {
+ 'credentials': {'required': True},
+ 'datastore_type': {'required': True},
+ 'is_default': {'readonly': True},
+ 'artifact': {'required': True},
+ 'one_lake_workspace_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'description': {'key': 'description', 'type': 'str'},
+ 'properties': {'key': 'properties', 'type': '{str}'},
+ 'tags': {'key': 'tags', 'type': '{str}'},
+ 'credentials': {'key': 'credentials', 'type': 'DatastoreCredentials'},
+ 'datastore_type': {'key': 'datastoreType', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'is_default': {'key': 'isDefault', 'type': 'bool'},
+ 'artifact': {'key': 'artifact', 'type': 'OneLakeArtifact'},
+ 'endpoint': {'key': 'endpoint', 'type': 'str'},
+ 'one_lake_workspace_name': {'key': 'oneLakeWorkspaceName', 'type': 'str'},
+ 'service_data_access_auth_identity': {'key': 'serviceDataAccessAuthIdentity', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ credentials: "DatastoreCredentials",
+ artifact: "OneLakeArtifact",
+ one_lake_workspace_name: str,
+ description: Optional[str] = None,
+ properties: Optional[Dict[str, str]] = None,
+ tags: Optional[Dict[str, str]] = None,
+ intellectual_property: Optional["IntellectualProperty"] = None,
+ endpoint: Optional[str] = None,
+ service_data_access_auth_identity: Optional[Union[str, "ServiceDataAccessAuthIdentity"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword description: The asset description text.
+ :paramtype description: str
+ :keyword properties: The asset property dictionary.
+ :paramtype properties: dict[str, str]
+ :keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
+ :paramtype tags: dict[str, str]
+ :keyword credentials: Required. [Required] Account credentials.
+ :paramtype credentials: ~azure.mgmt.machinelearningservices.models.DatastoreCredentials
+ :keyword intellectual_property: Intellectual Property details.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword artifact: Required. [Required] OneLake artifact backing the datastore.
+ :paramtype artifact: ~azure.mgmt.machinelearningservices.models.OneLakeArtifact
+ :keyword endpoint: OneLake endpoint to use for the datastore.
+ :paramtype endpoint: str
+ :keyword one_lake_workspace_name: Required. [Required] OneLake workspace name.
+ :paramtype one_lake_workspace_name: str
+ :keyword service_data_access_auth_identity: Indicates which identity to use to authenticate
+ service data access to customer's storage. Possible values include: "None",
+ "WorkspaceSystemAssignedIdentity", "WorkspaceUserAssignedIdentity".
+ :paramtype service_data_access_auth_identity: str or
+ ~azure.mgmt.machinelearningservices.models.ServiceDataAccessAuthIdentity
+ """
+ super(OneLakeDatastore, self).__init__(description=description, properties=properties, tags=tags, credentials=credentials, intellectual_property=intellectual_property, **kwargs)
+ self.datastore_type = 'OneLake' # type: str
+ self.artifact = artifact
+ self.endpoint = endpoint
+ self.one_lake_workspace_name = one_lake_workspace_name
+ self.service_data_access_auth_identity = service_data_access_auth_identity
+
+
class OnlineDeployment(TrackedResource):
"""OnlineDeployment.
@@ -20130,7 +22653,7 @@ class PackageRequest(msrest.serialization.Model):
_validation = {
'inferencing_server': {'required': True},
- 'target_environment_name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'target_environment_name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -20361,6 +22884,58 @@ def __init__(
self.tags = tags
+class PartialJobBase(msrest.serialization.Model):
+ """Mutable base definition for a job.
+
+ :ivar partial_notification_setting: Mutable notification setting for the job.
+ :vartype partial_notification_setting:
+ ~azure.mgmt.machinelearningservices.models.PartialNotificationSetting
+ """
+
+ _attribute_map = {
+ 'partial_notification_setting': {'key': 'partialNotificationSetting', 'type': 'PartialNotificationSetting'},
+ }
+
+ def __init__(
+ self,
+ *,
+ partial_notification_setting: Optional["PartialNotificationSetting"] = None,
+ **kwargs
+ ):
+ """
+ :keyword partial_notification_setting: Mutable notification setting for the job.
+ :paramtype partial_notification_setting:
+ ~azure.mgmt.machinelearningservices.models.PartialNotificationSetting
+ """
+ super(PartialJobBase, self).__init__(**kwargs)
+ self.partial_notification_setting = partial_notification_setting
+
+
+class PartialJobBasePartialResource(msrest.serialization.Model):
+ """Azure Resource Manager resource envelope strictly used in update requests.
+
+ :ivar properties: Additional attributes of the entity.
+ :vartype properties: ~azure.mgmt.machinelearningservices.models.PartialJobBase
+ """
+
+ _attribute_map = {
+ 'properties': {'key': 'properties', 'type': 'PartialJobBase'},
+ }
+
+ def __init__(
+ self,
+ *,
+ properties: Optional["PartialJobBase"] = None,
+ **kwargs
+ ):
+ """
+ :keyword properties: Additional attributes of the entity.
+ :paramtype properties: ~azure.mgmt.machinelearningservices.models.PartialJobBase
+ """
+ super(PartialJobBasePartialResource, self).__init__(**kwargs)
+ self.properties = properties
+
+
class PartialManagedServiceIdentity(msrest.serialization.Model):
"""Managed service identity (system assigned and/or user assigned identities).
@@ -20490,6 +23065,33 @@ def __init__(
self.sku = sku
+class PartialNotificationSetting(msrest.serialization.Model):
+ """Mutable configuration for notification.
+
+ :ivar webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :vartype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
+ """
+
+ _attribute_map = {
+ 'webhooks': {'key': 'webhooks', 'type': '{Webhook}'},
+ }
+
+ def __init__(
+ self,
+ *,
+ webhooks: Optional[Dict[str, "Webhook"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword webhooks: Send webhook callback to a service. Key is a user-provided name for the
+ webhook.
+ :paramtype webhooks: dict[str, ~azure.mgmt.machinelearningservices.models.Webhook]
+ """
+ super(PartialNotificationSetting, self).__init__(**kwargs)
+ self.webhooks = webhooks
+
+
class PartialRegistryPartialTrackedResource(msrest.serialization.Model):
"""Strictly used in update requests.
@@ -20708,6 +23310,123 @@ def __init__(
self.credentials = credentials
+class PendingUploadCredentialDto(msrest.serialization.Model):
+ """PendingUploadCredentialDto.
+
+ You probably want to use the sub-classes and not this class directly. Known
+ sub-classes are: SASCredentialDto.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credential_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "SAS".
+ :vartype credential_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialType
+ """
+
+ _validation = {
+ 'credential_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'credential_type': {'key': 'credentialType', 'type': 'str'},
+ }
+
+ _subtype_map = {
+ 'credential_type': {'SAS': 'SASCredentialDto'}
+ }
+
+ def __init__(
+ self,
+ **kwargs
+ ):
+ """
+ """
+ super(PendingUploadCredentialDto, self).__init__(**kwargs)
+ self.credential_type = None # type: Optional[str]
+
+
+class PendingUploadRequestDto(msrest.serialization.Model):
+ """PendingUploadRequestDto.
+
+ :ivar pending_upload_id: If PendingUploadId = null then random guid will be used.
+ :vartype pending_upload_id: str
+ :ivar pending_upload_type: TemporaryBlobReference is the only supported type. Possible values
+ include: "None", "TemporaryBlobReference".
+ :vartype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+
+ _attribute_map = {
+ 'pending_upload_id': {'key': 'pendingUploadId', 'type': 'str'},
+ 'pending_upload_type': {'key': 'pendingUploadType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ pending_upload_id: Optional[str] = None,
+ pending_upload_type: Optional[Union[str, "PendingUploadType"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword pending_upload_id: If PendingUploadId = null then random guid will be used.
+ :paramtype pending_upload_id: str
+ :keyword pending_upload_type: TemporaryBlobReference is the only supported type. Possible
+ values include: "None", "TemporaryBlobReference".
+ :paramtype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+ super(PendingUploadRequestDto, self).__init__(**kwargs)
+ self.pending_upload_id = pending_upload_id
+ self.pending_upload_type = pending_upload_type
+
+
+class PendingUploadResponseDto(msrest.serialization.Model):
+ """PendingUploadResponseDto.
+
+ :ivar blob_reference_for_consumption: Container level read, write, list SAS.
+ :vartype blob_reference_for_consumption:
+ ~azure.mgmt.machinelearningservices.models.BlobReferenceForConsumptionDto
+ :ivar pending_upload_id: ID for this upload request.
+ :vartype pending_upload_id: str
+ :ivar pending_upload_type: TemporaryBlobReference is the only supported type. Possible values
+ include: "None", "TemporaryBlobReference".
+ :vartype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+
+ _attribute_map = {
+ 'blob_reference_for_consumption': {'key': 'blobReferenceForConsumption', 'type': 'BlobReferenceForConsumptionDto'},
+ 'pending_upload_id': {'key': 'pendingUploadId', 'type': 'str'},
+ 'pending_upload_type': {'key': 'pendingUploadType', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ blob_reference_for_consumption: Optional["BlobReferenceForConsumptionDto"] = None,
+ pending_upload_id: Optional[str] = None,
+ pending_upload_type: Optional[Union[str, "PendingUploadType"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword blob_reference_for_consumption: Container level read, write, list SAS.
+ :paramtype blob_reference_for_consumption:
+ ~azure.mgmt.machinelearningservices.models.BlobReferenceForConsumptionDto
+ :keyword pending_upload_id: ID for this upload request.
+ :paramtype pending_upload_id: str
+ :keyword pending_upload_type: TemporaryBlobReference is the only supported type. Possible
+ values include: "None", "TemporaryBlobReference".
+ :paramtype pending_upload_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadType
+ """
+ super(PendingUploadResponseDto, self).__init__(**kwargs)
+ self.blob_reference_for_consumption = blob_reference_for_consumption
+ self.pending_upload_id = pending_upload_id
+ self.pending_upload_type = pending_upload_type
+
+
class PersonalComputeInstanceSettings(msrest.serialization.Model):
"""Settings for a personal compute instance.
@@ -20766,6 +23485,9 @@ class PipelineJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -20802,6 +23524,7 @@ class PipelineJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'inputs': {'key': 'inputs', 'type': '{JobInput}'},
@@ -20824,6 +23547,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
inputs: Optional[Dict[str, "JobInput"]] = None,
jobs: Optional[Dict[str, Any]] = None,
@@ -20856,6 +23580,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -20870,13 +23597,97 @@ def __init__(
:keyword source_job_id: ARM resource ID of source job.
:paramtype source_job_id: str
"""
- super(PipelineJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, services=services, **kwargs)
- self.job_type = 'Pipeline' # type: str
- self.inputs = inputs
- self.jobs = jobs
- self.outputs = outputs
- self.settings = settings
- self.source_job_id = source_job_id
+ super(PipelineJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, secrets_configuration=secrets_configuration, services=services, **kwargs)
+ self.job_type = 'Pipeline' # type: str
+ self.inputs = inputs
+ self.jobs = jobs
+ self.outputs = outputs
+ self.settings = settings
+ self.source_job_id = source_job_id
+
+
+class PredictionDriftMonitoringSignal(MonitoringSignalBase):
+ """PredictionDriftMonitoringSignal.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :vartype lookback_period: ~datetime.timedelta
+ :ivar mode: The current notification mode for this signal. Possible values include: "Disabled",
+ "Enabled".
+ :vartype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :ivar signal_type: Required. [Required] Specifies the type of signal to monitor.Constant filled
+ by server. Possible values include: "DataDrift", "PredictionDrift", "DataQuality",
+ "FeatureAttributionDrift", "Custom", "ModelPerformance".
+ :vartype signal_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringSignalType
+ :ivar baseline_data: Required. [Required] The data to calculate drift against.
+ :vartype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :ivar metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :vartype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.PredictionDriftMetricThresholdBase]
+ :ivar model_type: Required. [Required] The type of the model monitored. Possible values
+ include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar target_data: Required. [Required] The data which drift will be calculatd for.
+ :vartype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+
+ _validation = {
+ 'signal_type': {'required': True},
+ 'baseline_data': {'required': True},
+ 'metric_thresholds': {'required': True},
+ 'model_type': {'required': True},
+ 'target_data': {'required': True},
+ }
+
+ _attribute_map = {
+ 'lookback_period': {'key': 'lookbackPeriod', 'type': 'duration'},
+ 'mode': {'key': 'mode', 'type': 'str'},
+ 'signal_type': {'key': 'signalType', 'type': 'str'},
+ 'baseline_data': {'key': 'baselineData', 'type': 'MonitoringInputData'},
+ 'metric_thresholds': {'key': 'metricThresholds', 'type': '[PredictionDriftMetricThresholdBase]'},
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'target_data': {'key': 'targetData', 'type': 'MonitoringInputData'},
+ }
+
+ def __init__(
+ self,
+ *,
+ baseline_data: "MonitoringInputData",
+ metric_thresholds: List["PredictionDriftMetricThresholdBase"],
+ model_type: Union[str, "MonitoringModelType"],
+ target_data: "MonitoringInputData",
+ lookback_period: Optional[datetime.timedelta] = None,
+ mode: Optional[Union[str, "MonitoringNotificationMode"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword lookback_period: The amount of time a single monitor should look back over the target
+ data on a given run.
+ :paramtype lookback_period: ~datetime.timedelta
+ :keyword mode: The current notification mode for this signal. Possible values include:
+ "Disabled", "Enabled".
+ :paramtype mode: str or ~azure.mgmt.machinelearningservices.models.MonitoringNotificationMode
+ :keyword baseline_data: Required. [Required] The data to calculate drift against.
+ :paramtype baseline_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ :keyword metric_thresholds: Required. [Required] A list of metrics to calculate and their
+ associated thresholds.
+ :paramtype metric_thresholds:
+ list[~azure.mgmt.machinelearningservices.models.PredictionDriftMetricThresholdBase]
+ :keyword model_type: Required. [Required] The type of the model monitored. Possible values
+ include: "Classification", "Regression".
+ :paramtype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :keyword target_data: Required. [Required] The data which drift will be calculatd for.
+ :paramtype target_data: ~azure.mgmt.machinelearningservices.models.MonitoringInputData
+ """
+ super(PredictionDriftMonitoringSignal, self).__init__(lookback_period=lookback_period, mode=mode, **kwargs)
+ self.signal_type = 'PredictionDrift' # type: str
+ self.baseline_data = baseline_data
+ self.metric_thresholds = metric_thresholds
+ self.model_type = model_type
+ self.target_data = target_data
class PrivateEndpoint(msrest.serialization.Model):
@@ -21293,7 +24104,8 @@ class PyTorch(DistributionConfiguration):
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
:ivar process_count_per_instance: Number of processes per node.
:vartype process_count_per_instance: int
@@ -21491,6 +24303,78 @@ def __init__(
self.seed = seed
+class Ray(DistributionConfiguration):
+ """Ray distribution configuration.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar distribution_type: Required. [Required] Specifies the type of distribution
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
+ :vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
+ :ivar address: The address of Ray head node.
+ :vartype address: str
+ :ivar dashboard_port: The port to bind the dashboard server to.
+ :vartype dashboard_port: int
+ :ivar head_node_additional_args: Additional arguments passed to ray start in head node.
+ :vartype head_node_additional_args: str
+ :ivar include_dashboard: Provide this argument to start the Ray dashboard GUI.
+ :vartype include_dashboard: bool
+ :ivar port: The port of the head ray process.
+ :vartype port: int
+ :ivar worker_node_additional_args: Additional arguments passed to ray start in worker node.
+ :vartype worker_node_additional_args: str
+ """
+
+ _validation = {
+ 'distribution_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'distribution_type': {'key': 'distributionType', 'type': 'str'},
+ 'address': {'key': 'address', 'type': 'str'},
+ 'dashboard_port': {'key': 'dashboardPort', 'type': 'int'},
+ 'head_node_additional_args': {'key': 'headNodeAdditionalArgs', 'type': 'str'},
+ 'include_dashboard': {'key': 'includeDashboard', 'type': 'bool'},
+ 'port': {'key': 'port', 'type': 'int'},
+ 'worker_node_additional_args': {'key': 'workerNodeAdditionalArgs', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ address: Optional[str] = None,
+ dashboard_port: Optional[int] = None,
+ head_node_additional_args: Optional[str] = None,
+ include_dashboard: Optional[bool] = None,
+ port: Optional[int] = None,
+ worker_node_additional_args: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword address: The address of Ray head node.
+ :paramtype address: str
+ :keyword dashboard_port: The port to bind the dashboard server to.
+ :paramtype dashboard_port: int
+ :keyword head_node_additional_args: Additional arguments passed to ray start in head node.
+ :paramtype head_node_additional_args: str
+ :keyword include_dashboard: Provide this argument to start the Ray dashboard GUI.
+ :paramtype include_dashboard: bool
+ :keyword port: The port of the head ray process.
+ :paramtype port: int
+ :keyword worker_node_additional_args: Additional arguments passed to ray start in worker node.
+ :paramtype worker_node_additional_args: str
+ """
+ super(Ray, self).__init__(**kwargs)
+ self.distribution_type = 'Ray' # type: str
+ self.address = address
+ self.dashboard_port = dashboard_port
+ self.head_node_additional_args = head_node_additional_args
+ self.include_dashboard = include_dashboard
+ self.port = port
+ self.worker_node_additional_args = worker_node_additional_args
+
+
class RecurrenceSchedule(msrest.serialization.Model):
"""RecurrenceSchedule.
@@ -22156,6 +25040,55 @@ def __init__(
self.training_data = training_data
+class RegressionModelPerformanceMetricThreshold(ModelPerformanceMetricThresholdBase):
+ """RegressionModelPerformanceMetricThreshold.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar model_type: Required. [Required] Specifies the data type of the metric threshold.Constant
+ filled by server. Possible values include: "Classification", "Regression".
+ :vartype model_type: str or ~azure.mgmt.machinelearningservices.models.MonitoringModelType
+ :ivar threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :vartype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :ivar metric: Required. [Required] The regression model performance metric to calculate.
+ Possible values include: "MeanAbsoluteError", "RootMeanSquaredError", "MeanSquaredError".
+ :vartype metric: str or
+ ~azure.mgmt.machinelearningservices.models.RegressionModelPerformanceMetric
+ """
+
+ _validation = {
+ 'model_type': {'required': True},
+ 'metric': {'required': True},
+ }
+
+ _attribute_map = {
+ 'model_type': {'key': 'modelType', 'type': 'str'},
+ 'threshold': {'key': 'threshold', 'type': 'MonitoringThreshold'},
+ 'metric': {'key': 'metric', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ metric: Union[str, "RegressionModelPerformanceMetric"],
+ threshold: Optional["MonitoringThreshold"] = None,
+ **kwargs
+ ):
+ """
+ :keyword threshold: The threshold value. If null, a default value will be set depending on the
+ selected metric.
+ :paramtype threshold: ~azure.mgmt.machinelearningservices.models.MonitoringThreshold
+ :keyword metric: Required. [Required] The regression model performance metric to calculate.
+ Possible values include: "MeanAbsoluteError", "RootMeanSquaredError", "MeanSquaredError".
+ :paramtype metric: str or
+ ~azure.mgmt.machinelearningservices.models.RegressionModelPerformanceMetric
+ """
+ super(RegressionModelPerformanceMetricThreshold, self).__init__(threshold=threshold, **kwargs)
+ self.model_type = 'Regression' # type: str
+ self.metric = metric
+
+
class RegressionTrainingSettings(TrainingSettings):
"""Regression Training related configuration.
@@ -22258,6 +25191,35 @@ def __init__(
self.blocked_training_algorithms = blocked_training_algorithms
+class RequestLogging(msrest.serialization.Model):
+ """RequestLogging.
+
+ :ivar capture_headers: For payload logging, we only collect payload by default. If customers
+ also want to collect the specified headers, they can set them in captureHeaders so that backend
+ will collect those headers along with payload.
+ :vartype capture_headers: list[str]
+ """
+
+ _attribute_map = {
+ 'capture_headers': {'key': 'captureHeaders', 'type': '[str]'},
+ }
+
+ def __init__(
+ self,
+ *,
+ capture_headers: Optional[List[str]] = None,
+ **kwargs
+ ):
+ """
+ :keyword capture_headers: For payload logging, we only collect payload by default. If customers
+ also want to collect the specified headers, they can set them in captureHeaders so that backend
+ will collect those headers along with payload.
+ :paramtype capture_headers: list[str]
+ """
+ super(RequestLogging, self).__init__(**kwargs)
+ self.capture_headers = capture_headers
+
+
class ResourceId(msrest.serialization.Model):
"""Represents a resource ID. For example, for a subnet, it is the resource URL for the subnet.
@@ -22385,7 +25347,7 @@ class Route(msrest.serialization.Model):
"""
_validation = {
- 'path': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'path': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'port': {'required': True},
}
@@ -22480,6 +25442,56 @@ def __init__(
self.credentials = credentials
+class SASCredentialDto(PendingUploadCredentialDto):
+ """SASCredentialDto.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar credential_type: Required. [Required] Credential type used to authentication with
+ storage.Constant filled by server. Possible values include: "SAS".
+ :vartype credential_type: str or
+ ~azure.mgmt.machinelearningservices.models.PendingUploadCredentialType
+ :ivar sas_uri: Full SAS Uri, including the storage, container/blob path and SAS token.
+ :vartype sas_uri: str
+ :ivar wasbs_uri: Windows Azure Storage Blob formatted uri for mounting containers at root, a
+ subdirectory, or a specific file
+ example wasbs://[container_name]@[account_name].blob.core.windows.net/[path]?sas=[sas]
+ For now, the URI will just be the root path ([path] will be empty).
+ :vartype wasbs_uri: str
+ """
+
+ _validation = {
+ 'credential_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'credential_type': {'key': 'credentialType', 'type': 'str'},
+ 'sas_uri': {'key': 'sasUri', 'type': 'str'},
+ 'wasbs_uri': {'key': 'wasbsUri', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ sas_uri: Optional[str] = None,
+ wasbs_uri: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword sas_uri: Full SAS Uri, including the storage, container/blob path and SAS token.
+ :paramtype sas_uri: str
+ :keyword wasbs_uri: Windows Azure Storage Blob formatted uri for mounting containers at root, a
+ subdirectory, or a specific file
+ example wasbs://[container_name]@[account_name].blob.core.windows.net/[path]?sas=[sas]
+ For now, the URI will just be the root path ([path] will be empty).
+ :paramtype wasbs_uri: str
+ """
+ super(SASCredentialDto, self).__init__(**kwargs)
+ self.credential_type = 'SAS' # type: str
+ self.sas_uri = sas_uri
+ self.wasbs_uri = wasbs_uri
+
+
class SasDatastoreCredentials(DatastoreCredentials):
"""SAS datastore credentials configuration.
@@ -22916,6 +25928,40 @@ def __init__(
self.creation_script = creation_script
+class SecretConfiguration(msrest.serialization.Model):
+ """Secret Configuration definition.
+
+ :ivar uri: Secret Uri.
+ Sample Uri : https://myvault.vault.azure.net/secrets/mysecretname/secretversion.
+ :vartype uri: str
+ :ivar workspace_secret_name: Name of secret in workspace key vault.
+ :vartype workspace_secret_name: str
+ """
+
+ _attribute_map = {
+ 'uri': {'key': 'uri', 'type': 'str'},
+ 'workspace_secret_name': {'key': 'workspaceSecretName', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ uri: Optional[str] = None,
+ workspace_secret_name: Optional[str] = None,
+ **kwargs
+ ):
+ """
+ :keyword uri: Secret Uri.
+ Sample Uri : https://myvault.vault.azure.net/secrets/mysecretname/secretversion.
+ :paramtype uri: str
+ :keyword workspace_secret_name: Name of secret in workspace key vault.
+ :paramtype workspace_secret_name: str
+ """
+ super(SecretConfiguration, self).__init__(**kwargs)
+ self.uri = uri
+ self.workspace_secret_name = workspace_secret_name
+
+
class ServiceManagedResourcesSettings(msrest.serialization.Model):
"""ServiceManagedResourcesSettings.
@@ -23392,6 +26438,82 @@ def __init__(
self.value = value
+class SkuResourceArmPaginatedResultAutoGenerated(msrest.serialization.Model):
+ """A paginated list of SkuResource entities.
+
+ :ivar next_link: The link to the next page of SkuResource objects. If null, there are no
+ additional pages.
+ :vartype next_link: str
+ :ivar value: An array of objects of type SkuResource.
+ :vartype value: list[~azure.mgmt.machinelearningservices.models.SkuResourceAutoGenerated]
+ """
+
+ _attribute_map = {
+ 'next_link': {'key': 'nextLink', 'type': 'str'},
+ 'value': {'key': 'value', 'type': '[SkuResourceAutoGenerated]'},
+ }
+
+ def __init__(
+ self,
+ *,
+ next_link: Optional[str] = None,
+ value: Optional[List["SkuResourceAutoGenerated"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword next_link: The link to the next page of SkuResource objects. If null, there are no
+ additional pages.
+ :paramtype next_link: str
+ :keyword value: An array of objects of type SkuResource.
+ :paramtype value: list[~azure.mgmt.machinelearningservices.models.SkuResourceAutoGenerated]
+ """
+ super(SkuResourceArmPaginatedResultAutoGenerated, self).__init__(**kwargs)
+ self.next_link = next_link
+ self.value = value
+
+
+class SkuResourceAutoGenerated(msrest.serialization.Model):
+ """Fulfills ARM Contract requirement to list all available SKUS for a resource.
+
+ Variables are only populated by the server, and will be ignored when sending a request.
+
+ :ivar capacity: Gets or sets the Sku Capacity.
+ :vartype capacity: ~azure.mgmt.machinelearningservices.models.SkuCapacity
+ :ivar resource_type: The resource type name.
+ :vartype resource_type: str
+ :ivar sku: Gets or sets the Sku.
+ :vartype sku: ~azure.mgmt.machinelearningservices.models.SkuSettingAutoGenerated
+ """
+
+ _validation = {
+ 'resource_type': {'readonly': True},
+ }
+
+ _attribute_map = {
+ 'capacity': {'key': 'capacity', 'type': 'SkuCapacity'},
+ 'resource_type': {'key': 'resourceType', 'type': 'str'},
+ 'sku': {'key': 'sku', 'type': 'SkuSettingAutoGenerated'},
+ }
+
+ def __init__(
+ self,
+ *,
+ capacity: Optional["SkuCapacity"] = None,
+ sku: Optional["SkuSettingAutoGenerated"] = None,
+ **kwargs
+ ):
+ """
+ :keyword capacity: Gets or sets the Sku Capacity.
+ :paramtype capacity: ~azure.mgmt.machinelearningservices.models.SkuCapacity
+ :keyword sku: Gets or sets the Sku.
+ :paramtype sku: ~azure.mgmt.machinelearningservices.models.SkuSettingAutoGenerated
+ """
+ super(SkuResourceAutoGenerated, self).__init__(**kwargs)
+ self.capacity = capacity
+ self.resource_type = None
+ self.sku = sku
+
+
class SkuSetting(msrest.serialization.Model):
"""SkuSetting fulfills the need for stripped down SKU info in ARM contract.
@@ -23407,7 +26529,7 @@ class SkuSetting(msrest.serialization.Model):
"""
_validation = {
- 'name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'name': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -23436,6 +26558,50 @@ def __init__(
self.tier = tier
+class SkuSettingAutoGenerated(msrest.serialization.Model):
+ """SkuSetting fulfills the need for stripped down SKU info in ARM contract.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar name: Required. [Required] The name of the SKU. Ex - P3. It is typically a letter+number
+ code.
+ :vartype name: str
+ :ivar tier: This field is required to be implemented by the Resource Provider if the service
+ has more than one tier, but is not required on a PUT. Possible values include: "Free", "Basic",
+ "Standard", "Premium".
+ :vartype tier: str or ~azure.mgmt.machinelearningservices.models.SkuTier
+ """
+
+ _validation = {
+ 'name': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ }
+
+ _attribute_map = {
+ 'name': {'key': 'name', 'type': 'str'},
+ 'tier': {'key': 'tier', 'type': 'str'},
+ }
+
+ def __init__(
+ self,
+ *,
+ name: str,
+ tier: Optional[Union[str, "SkuTier"]] = None,
+ **kwargs
+ ):
+ """
+ :keyword name: Required. [Required] The name of the SKU. Ex - P3. It is typically a
+ letter+number code.
+ :paramtype name: str
+ :keyword tier: This field is required to be implemented by the Resource Provider if the service
+ has more than one tier, but is not required on a PUT. Possible values include: "Free", "Basic",
+ "Standard", "Premium".
+ :paramtype tier: str or ~azure.mgmt.machinelearningservices.models.SkuTier
+ """
+ super(SkuSettingAutoGenerated, self).__init__(**kwargs)
+ self.name = name
+ self.tier = tier
+
+
class SparkJob(JobBaseProperties):
"""Spark job definition.
@@ -23469,6 +26635,9 @@ class SparkJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -23507,7 +26676,7 @@ class SparkJob(JobBaseProperties):
_validation = {
'job_type': {'required': True},
'status': {'readonly': True},
- 'code_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'code_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'entry': {'required': True},
}
@@ -23523,6 +26692,7 @@ class SparkJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'archives': {'key': 'archives', 'type': '[str]'},
@@ -23555,6 +26725,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
archives: Optional[List[str]] = None,
args: Optional[str] = None,
@@ -23593,6 +26764,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -23623,7 +26797,7 @@ def __init__(
:keyword resources: Compute Resource configuration for the job.
:paramtype resources: ~azure.mgmt.machinelearningservices.models.SparkResourceConfiguration
"""
- super(SparkJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, services=services, **kwargs)
+ super(SparkJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, secrets_configuration=secrets_configuration, services=services, **kwargs)
self.job_type = 'Spark' # type: str
self.archives = archives
self.args = args
@@ -24011,6 +27185,9 @@ class SweepJob(JobBaseProperties):
:vartype job_type: str or ~azure.mgmt.machinelearningservices.models.JobType
:ivar notification_setting: Notification setting for the job.
:vartype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :ivar secrets_configuration: Configuration for secrets to be made available during runtime.
+ :vartype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:ivar services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:vartype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -24061,6 +27238,7 @@ class SweepJob(JobBaseProperties):
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'job_type': {'key': 'jobType', 'type': 'str'},
'notification_setting': {'key': 'notificationSetting', 'type': 'NotificationSetting'},
+ 'secrets_configuration': {'key': 'secretsConfiguration', 'type': '{SecretConfiguration}'},
'services': {'key': 'services', 'type': '{JobService}'},
'status': {'key': 'status', 'type': 'str'},
'early_termination': {'key': 'earlyTermination', 'type': 'EarlyTerminationPolicy'},
@@ -24091,6 +27269,7 @@ def __init__(
identity: Optional["IdentityConfiguration"] = None,
is_archived: Optional[bool] = False,
notification_setting: Optional["NotificationSetting"] = None,
+ secrets_configuration: Optional[Dict[str, "SecretConfiguration"]] = None,
services: Optional[Dict[str, "JobService"]] = None,
early_termination: Optional["EarlyTerminationPolicy"] = None,
inputs: Optional[Dict[str, "JobInput"]] = None,
@@ -24123,6 +27302,9 @@ def __init__(
:paramtype is_archived: bool
:keyword notification_setting: Notification setting for the job.
:paramtype notification_setting: ~azure.mgmt.machinelearningservices.models.NotificationSetting
+ :keyword secrets_configuration: Configuration for secrets to be made available during runtime.
+ :paramtype secrets_configuration: dict[str,
+ ~azure.mgmt.machinelearningservices.models.SecretConfiguration]
:keyword services: List of JobEndpoints.
For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
:paramtype services: dict[str, ~azure.mgmt.machinelearningservices.models.JobService]
@@ -24147,7 +27329,7 @@ def __init__(
:keyword trial: Required. [Required] Trial component definition.
:paramtype trial: ~azure.mgmt.machinelearningservices.models.TrialComponent
"""
- super(SweepJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, services=services, **kwargs)
+ super(SweepJob, self).__init__(description=description, properties=properties, tags=tags, component_id=component_id, compute_id=compute_id, display_name=display_name, experiment_name=experiment_name, identity=identity, is_archived=is_archived, notification_setting=notification_setting, secrets_configuration=secrets_configuration, services=services, **kwargs)
self.job_type = 'Sweep' # type: str
self.early_termination = early_termination
self.inputs = inputs
@@ -25194,7 +28376,8 @@ class TensorFlow(DistributionConfiguration):
All required parameters must be populated in order to send to Azure.
:ivar distribution_type: Required. [Required] Specifies the type of distribution
- framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi".
+ framework.Constant filled by server. Possible values include: "PyTorch", "TensorFlow", "Mpi",
+ "Ray".
:vartype distribution_type: str or ~azure.mgmt.machinelearningservices.models.DistributionType
:ivar parameter_server_count: Number of parameter server tasks.
:vartype parameter_server_count: int
@@ -25610,6 +28793,44 @@ def __init__(
self.size = size
+class TopNFeaturesByAttribution(MonitoringFeatureFilterBase):
+ """TopNFeaturesByAttribution.
+
+ All required parameters must be populated in order to send to Azure.
+
+ :ivar filter_type: Required. [Required] Specifies the feature filter to leverage when selecting
+ features to calculate metrics over.Constant filled by server. Possible values include:
+ "AllFeatures", "TopNByAttribution", "FeatureSubset".
+ :vartype filter_type: str or
+ ~azure.mgmt.machinelearningservices.models.MonitoringFeatureFilterType
+ :ivar top: The number of top features to include.
+ :vartype top: int
+ """
+
+ _validation = {
+ 'filter_type': {'required': True},
+ }
+
+ _attribute_map = {
+ 'filter_type': {'key': 'filterType', 'type': 'str'},
+ 'top': {'key': 'top', 'type': 'int'},
+ }
+
+ def __init__(
+ self,
+ *,
+ top: Optional[int] = 10,
+ **kwargs
+ ):
+ """
+ :keyword top: The number of top features to include.
+ :paramtype top: int
+ """
+ super(TopNFeaturesByAttribution, self).__init__(**kwargs)
+ self.filter_type = 'TopNByAttribution' # type: str
+ self.top = top
+
+
class TrialComponent(msrest.serialization.Model):
"""Trial component definition.
@@ -25634,7 +28855,7 @@ class TrialComponent(msrest.serialization.Model):
_validation = {
'command': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
- 'environment_id': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'environment_id': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
@@ -25740,7 +28961,7 @@ class TritonModelJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -25784,6 +29005,8 @@ class TritonModelJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -25804,6 +29027,7 @@ class TritonModelJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -25815,6 +29039,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
description: Optional[str] = None,
@@ -25825,6 +29050,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -25833,9 +29060,10 @@ def __init__(
:keyword description: Description for the output.
:paramtype description: str
"""
- super(TritonModelJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, mode=mode, uri=uri, **kwargs)
+ super(TritonModelJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, auto_delete_setting=auto_delete_setting, mode=mode, uri=uri, **kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
self.job_output_type = 'triton_model' # type: str
@@ -25993,9 +29221,13 @@ class UriFileDataVersion(DataVersionBaseProperties):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
Possible values include: "uri_file", "uri_folder", "mltable".
@@ -26003,21 +29235,29 @@ class UriFileDataVersion(DataVersionBaseProperties):
:ivar data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
"""
_validation = {
'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'data_type': {'key': 'dataType', 'type': 'str'},
'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -26027,8 +29267,11 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
+ intellectual_property: Optional["IntellectualProperty"] = None,
+ stage: Optional[str] = None,
**kwargs
):
"""
@@ -26038,15 +29281,25 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
"""
- super(UriFileDataVersion, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, **kwargs)
+ super(UriFileDataVersion, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, intellectual_property=intellectual_property, stage=stage, **kwargs)
self.data_type = 'uri_file' # type: str
@@ -26069,7 +29322,7 @@ class UriFileJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -26113,6 +29366,8 @@ class UriFileJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -26133,6 +29388,7 @@ class UriFileJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -26144,6 +29400,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
description: Optional[str] = None,
@@ -26154,6 +29411,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -26162,9 +29421,10 @@ def __init__(
:keyword description: Description for the output.
:paramtype description: str
"""
- super(UriFileJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, mode=mode, uri=uri, **kwargs)
+ super(UriFileJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, auto_delete_setting=auto_delete_setting, mode=mode, uri=uri, **kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
self.job_output_type = 'uri_file' # type: str
@@ -26182,9 +29442,13 @@ class UriFolderDataVersion(DataVersionBaseProperties):
:vartype properties: dict[str, str]
:ivar tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:vartype tags: dict[str, str]
- :ivar is_anonymous: If the name version are system generated (anonymous registration).
+ :ivar auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :ivar is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:vartype is_anonymous: bool
- :ivar is_archived: Is the asset archived?.
+ :ivar is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:vartype is_archived: bool
:ivar data_type: Required. [Required] Specifies the type of data.Constant filled by server.
Possible values include: "uri_file", "uri_folder", "mltable".
@@ -26192,21 +29456,29 @@ class UriFolderDataVersion(DataVersionBaseProperties):
:ivar data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:vartype data_uri: str
+ :ivar intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :vartype intellectual_property: ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :ivar stage: Stage in the data lifecycle assigned to this data asset.
+ :vartype stage: str
"""
_validation = {
'data_type': {'required': True},
- 'data_uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'data_uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
}
_attribute_map = {
'description': {'key': 'description', 'type': 'str'},
'properties': {'key': 'properties', 'type': '{str}'},
'tags': {'key': 'tags', 'type': '{str}'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'is_anonymous': {'key': 'isAnonymous', 'type': 'bool'},
'is_archived': {'key': 'isArchived', 'type': 'bool'},
'data_type': {'key': 'dataType', 'type': 'str'},
'data_uri': {'key': 'dataUri', 'type': 'str'},
+ 'intellectual_property': {'key': 'intellectualProperty', 'type': 'IntellectualProperty'},
+ 'stage': {'key': 'stage', 'type': 'str'},
}
def __init__(
@@ -26216,8 +29488,11 @@ def __init__(
description: Optional[str] = None,
properties: Optional[Dict[str, str]] = None,
tags: Optional[Dict[str, str]] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
is_anonymous: Optional[bool] = False,
is_archived: Optional[bool] = False,
+ intellectual_property: Optional["IntellectualProperty"] = None,
+ stage: Optional[str] = None,
**kwargs
):
"""
@@ -26227,15 +29502,25 @@ def __init__(
:paramtype properties: dict[str, str]
:keyword tags: A set of tags. Tag dictionary. Tags can be added, removed, and updated.
:paramtype tags: dict[str, str]
- :keyword is_anonymous: If the name version are system generated (anonymous registration).
+ :keyword auto_delete_setting: Specifies the lifecycle setting of managed data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
+ :keyword is_anonymous: If the name version are system generated (anonymous registration). For
+ types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous.
:paramtype is_anonymous: bool
- :keyword is_archived: Is the asset archived?.
+ :keyword is_archived: Is the asset archived? For types where Stage is defined, when Stage is
+ provided it will be used to populate IsArchived.
:paramtype is_archived: bool
:keyword data_uri: Required. [Required] Uri of the data. Example:
https://go.microsoft.com/fwlink/?linkid=2202330.
:paramtype data_uri: str
+ :keyword intellectual_property: Intellectual Property details. Used if data is an Intellectual
+ Property.
+ :paramtype intellectual_property:
+ ~azure.mgmt.machinelearningservices.models.IntellectualProperty
+ :keyword stage: Stage in the data lifecycle assigned to this data asset.
+ :paramtype stage: str
"""
- super(UriFolderDataVersion, self).__init__(description=description, properties=properties, tags=tags, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, **kwargs)
+ super(UriFolderDataVersion, self).__init__(description=description, properties=properties, tags=tags, auto_delete_setting=auto_delete_setting, is_anonymous=is_anonymous, is_archived=is_archived, data_uri=data_uri, intellectual_property=intellectual_property, stage=stage, **kwargs)
self.data_type = 'uri_folder' # type: str
@@ -26258,7 +29543,7 @@ class UriFolderJobInput(JobInput, AssetJobInput):
"""
_validation = {
- 'uri': {'required': True, 'pattern': r'[a-zA-Z0-9_]'},
+ 'uri': {'required': True, 'min_length': 1, 'pattern': r'[a-zA-Z0-9_]'},
'job_input_type': {'required': True},
}
@@ -26302,6 +29587,8 @@ class UriFolderJobOutput(JobOutput, AssetJobOutput):
:vartype asset_name: str
:ivar asset_version: Output Asset Version.
:vartype asset_version: str
+ :ivar auto_delete_setting: Auto delete setting of output data asset.
+ :vartype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:ivar mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:vartype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -26322,6 +29609,7 @@ class UriFolderJobOutput(JobOutput, AssetJobOutput):
_attribute_map = {
'asset_name': {'key': 'assetName', 'type': 'str'},
'asset_version': {'key': 'assetVersion', 'type': 'str'},
+ 'auto_delete_setting': {'key': 'autoDeleteSetting', 'type': 'AutoDeleteSetting'},
'mode': {'key': 'mode', 'type': 'str'},
'uri': {'key': 'uri', 'type': 'str'},
'description': {'key': 'description', 'type': 'str'},
@@ -26333,6 +29621,7 @@ def __init__(
*,
asset_name: Optional[str] = None,
asset_version: Optional[str] = None,
+ auto_delete_setting: Optional["AutoDeleteSetting"] = None,
mode: Optional[Union[str, "OutputDeliveryMode"]] = None,
uri: Optional[str] = None,
description: Optional[str] = None,
@@ -26343,6 +29632,8 @@ def __init__(
:paramtype asset_name: str
:keyword asset_version: Output Asset Version.
:paramtype asset_version: str
+ :keyword auto_delete_setting: Auto delete setting of output data asset.
+ :paramtype auto_delete_setting: ~azure.mgmt.machinelearningservices.models.AutoDeleteSetting
:keyword mode: Output Asset Delivery Mode. Possible values include: "ReadWriteMount", "Upload",
"Direct".
:paramtype mode: str or ~azure.mgmt.machinelearningservices.models.OutputDeliveryMode
@@ -26351,9 +29642,10 @@ def __init__(
:keyword description: Description for the output.
:paramtype description: str
"""
- super(UriFolderJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, mode=mode, uri=uri, **kwargs)
+ super(UriFolderJobOutput, self).__init__(description=description, asset_name=asset_name, asset_version=asset_version, auto_delete_setting=auto_delete_setting, mode=mode, uri=uri, **kwargs)
self.asset_name = asset_name
self.asset_version = asset_version
+ self.auto_delete_setting = auto_delete_setting
self.mode = mode
self.uri = uri
self.job_output_type = 'uri_folder' # type: str
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/__init__.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/__init__.py
index 0eb66403ac68..0b1b8b50da59 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/__init__.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/__init__.py
@@ -21,8 +21,6 @@
from ._registry_code_versions_operations import RegistryCodeVersionsOperations
from ._registry_component_containers_operations import RegistryComponentContainersOperations
from ._registry_component_versions_operations import RegistryComponentVersionsOperations
-from ._registry_data_containers_operations import RegistryDataContainersOperations
-from ._registry_data_versions_operations import RegistryDataVersionsOperations
from ._registry_environment_containers_operations import RegistryEnvironmentContainersOperations
from ._registry_environment_versions_operations import RegistryEnvironmentVersionsOperations
from ._registry_model_containers_operations import RegistryModelContainersOperations
@@ -66,8 +64,6 @@
'RegistryCodeVersionsOperations',
'RegistryComponentContainersOperations',
'RegistryComponentVersionsOperations',
- 'RegistryDataContainersOperations',
- 'RegistryDataVersionsOperations',
'RegistryEnvironmentContainersOperations',
'RegistryEnvironmentVersionsOperations',
'RegistryModelContainersOperations',
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_code_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_code_versions_operations.py
index 55f3273303b7..c3c45d1e5a58 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_code_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_code_versions_operations.py
@@ -43,6 +43,8 @@ def build_list_request(
order_by = kwargs.pop('order_by', None) # type: Optional[str]
top = kwargs.pop('top', None) # type: Optional[int]
skip = kwargs.pop('skip', None) # type: Optional[str]
+ hash = kwargs.pop('hash', None) # type: Optional[str]
+ hash_version = kwargs.pop('hash_version', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -65,6 +67,10 @@ def build_list_request(
_query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
if skip is not None:
_query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
+ if hash is not None:
+ _query_parameters['hash'] = _SERIALIZER.query("hash", hash, 'str')
+ if hash_version is not None:
+ _query_parameters['hashVersion'] = _SERIALIZER.query("hash_version", hash_version, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -204,6 +210,50 @@ def build_create_or_update_request(
**kwargs
)
+
+def build_create_or_get_pending_upload_request(
+ subscription_id, # type: str
+ resource_group_name, # type: str
+ workspace_name, # type: str
+ name, # type: str
+ version, # type: str
+ **kwargs # type: Any
+):
+ # type: (...) -> HttpRequest
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', None) # type: Optional[str]
+
+ accept = "application/json"
+ # Construct URL
+ _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/pendingUpload/{version}") # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
+ "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
+ "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$'),
+ "name": _SERIALIZER.url("name", name, 'str'),
+ "version": _SERIALIZER.url("version", version, 'str'),
+ }
+
+ _url = _format_url_section(_url, **path_format_arguments)
+
+ # Construct parameters
+ _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
+ _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
+
+ # Construct headers
+ _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
+ if content_type is not None:
+ _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+ _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+ return HttpRequest(
+ method="POST",
+ url=_url,
+ params=_query_parameters,
+ headers=_header_parameters,
+ **kwargs
+ )
+
# fmt: on
class CodeVersionsOperations(object):
"""CodeVersionsOperations operations.
@@ -236,6 +286,8 @@ def list(
order_by=None, # type: Optional[str]
top=None, # type: Optional[int]
skip=None, # type: Optional[str]
+ hash=None, # type: Optional[str]
+ hash_version=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.CodeVersionResourceArmPaginatedResult"]
@@ -255,6 +307,11 @@ def list(
:type top: int
:param skip: Continuation token for pagination.
:type skip: str
+ :param hash: If specified, return CodeVersion assets with specified content hash value,
+ regardless of name.
+ :type hash: str
+ :param hash_version: Hash algorithm version when listing by hash.
+ :type hash_version: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either CodeVersionResourceArmPaginatedResult or the
result of cls(response)
@@ -281,6 +338,8 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ hash=hash,
+ hash_version=hash_version,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -297,6 +356,8 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ hash=hash,
+ hash_version=hash_version,
template_url=next_link,
)
request = _convert_request(request)
@@ -550,3 +611,80 @@ def create_or_update(
create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}"} # type: ignore
+
+ @distributed_trace
+ def create_or_get_pending_upload(
+ self,
+ resource_group_name, # type: str
+ workspace_name, # type: str
+ name, # type: str
+ version, # type: str
+ body, # type: "_models.PendingUploadRequestDto"
+ **kwargs # type: Any
+ ):
+ # type: (...) -> "_models.PendingUploadResponseDto"
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace.
+ :type workspace_name: str
+ :param name: Container name. This is case-sensitive.
+ :type name: str
+ :param version: Version identifier. This is case-sensitive.
+ :type version: str
+ :param body: Pending upload request object.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.PendingUploadResponseDto"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PendingUploadRequestDto')
+
+ request = build_create_or_get_pending_upload_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ workspace_name=workspace_name,
+ name=name,
+ version=version,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.create_or_get_pending_upload.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('PendingUploadResponseDto', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_pending_upload.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/pendingUpload/{version}"} # type: ignore
+
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_component_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_component_versions_operations.py
index e30e5b03258b..9010e1a9b7ec 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_component_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_component_versions_operations.py
@@ -43,6 +43,7 @@ def build_list_request(
order_by = kwargs.pop('order_by', None) # type: Optional[str]
top = kwargs.pop('top', None) # type: Optional[int]
skip = kwargs.pop('skip', None) # type: Optional[str]
+ stage = kwargs.pop('stage', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
accept = "application/json"
@@ -66,6 +67,8 @@ def build_list_request(
_query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
if skip is not None:
_query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
+ if stage is not None:
+ _query_parameters['stage'] = _SERIALIZER.query("stage", stage, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
@@ -239,6 +242,7 @@ def list(
order_by=None, # type: Optional[str]
top=None, # type: Optional[int]
skip=None, # type: Optional[str]
+ stage=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
**kwargs # type: Any
):
@@ -259,6 +263,8 @@ def list(
:type top: int
:param skip: Continuation token for pagination.
:type skip: str
+ :param stage: Component stage.
+ :type stage: str
:param list_view_type: View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
:keyword callable cls: A custom type or function that will be passed the direct response
@@ -287,6 +293,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
list_view_type=list_view_type,
template_url=self.list.metadata['url'],
)
@@ -304,6 +311,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
list_view_type=list_view_type,
template_url=next_link,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_data_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_data_versions_operations.py
index 986894856362..d10d6de821a0 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_data_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_data_versions_operations.py
@@ -44,6 +44,7 @@ def build_list_request(
top = kwargs.pop('top', None) # type: Optional[int]
skip = kwargs.pop('skip', None) # type: Optional[str]
tags = kwargs.pop('tags', None) # type: Optional[str]
+ stage = kwargs.pop('stage', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
accept = "application/json"
@@ -69,6 +70,8 @@ def build_list_request(
_query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
if tags is not None:
_query_parameters['$tags'] = _SERIALIZER.query("tags", tags, 'str')
+ if stage is not None:
+ _query_parameters['stage'] = _SERIALIZER.query("stage", stage, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
@@ -243,6 +246,7 @@ def list(
top=None, # type: Optional[int]
skip=None, # type: Optional[str]
tags=None, # type: Optional[str]
+ stage=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
**kwargs # type: Any
):
@@ -268,6 +272,8 @@ def list(
:param tags: Comma-separated list of tag names (and optionally values). Example:
tag1,tag2=value2.
:type tags: str
+ :param stage: data stage.
+ :type stage: str
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
@@ -298,6 +304,7 @@ def prepare_request(next_link=None):
top=top,
skip=skip,
tags=tags,
+ stage=stage,
list_view_type=list_view_type,
template_url=self.list.metadata['url'],
)
@@ -316,6 +323,7 @@ def prepare_request(next_link=None):
top=top,
skip=skip,
tags=tags,
+ stage=stage,
list_view_type=list_view_type,
template_url=next_link,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_containers_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_containers_operations.py
index ffa8f4be2634..2aff90979ba6 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_containers_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_containers_operations.py
@@ -44,6 +44,10 @@ def build_list_request(
skip = kwargs.pop('skip', None) # type: Optional[str]
tags = kwargs.pop('tags', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size = kwargs.pop('page_size', 20) # type: Optional[int]
+ name = kwargs.pop('name', None) # type: Optional[str]
+ description = kwargs.pop('description', None) # type: Optional[str]
+ created_by = kwargs.pop('created_by', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -65,6 +69,14 @@ def build_list_request(
_query_parameters['tags'] = _SERIALIZER.query("tags", tags, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
+ if page_size is not None:
+ _query_parameters['pageSize'] = _SERIALIZER.query("page_size", page_size, 'int')
+ if name is not None:
+ _query_parameters['name'] = _SERIALIZER.query("name", name, 'str')
+ if description is not None:
+ _query_parameters['description'] = _SERIALIZER.query("description", description, 'str')
+ if created_by is not None:
+ _query_parameters['createdBy'] = _SERIALIZER.query("created_by", created_by, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -229,6 +241,10 @@ def list(
skip=None, # type: Optional[str]
tags=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size=20, # type: Optional[int]
+ name=None, # type: Optional[str]
+ description=None, # type: Optional[str]
+ created_by=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.FeaturesetContainerResourceArmPaginatedResult"]
@@ -248,6 +264,14 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param name: name for the featureset.
+ :type name: str
+ :param description: description for the feature set.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FeaturesetContainerResourceArmPaginatedResult or
the result of cls(response)
@@ -273,6 +297,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -288,6 +316,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=next_link,
)
request = _convert_request(request)
@@ -640,7 +672,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_versions_operations.py
index b51817043670..997032c5ef4f 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featureset_versions_operations.py
@@ -45,6 +45,12 @@ def build_list_request(
skip = kwargs.pop('skip', None) # type: Optional[str]
tags = kwargs.pop('tags', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size = kwargs.pop('page_size', 20) # type: Optional[int]
+ version_name = kwargs.pop('version_name', None) # type: Optional[str]
+ version = kwargs.pop('version', None) # type: Optional[str]
+ description = kwargs.pop('description', None) # type: Optional[str]
+ created_by = kwargs.pop('created_by', None) # type: Optional[str]
+ stage = kwargs.pop('stage', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -67,6 +73,18 @@ def build_list_request(
_query_parameters['tags'] = _SERIALIZER.query("tags", tags, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
+ if page_size is not None:
+ _query_parameters['pageSize'] = _SERIALIZER.query("page_size", page_size, 'int')
+ if version_name is not None:
+ _query_parameters['versionName'] = _SERIALIZER.query("version_name", version_name, 'str')
+ if version is not None:
+ _query_parameters['version'] = _SERIALIZER.query("version", version, 'str')
+ if description is not None:
+ _query_parameters['description'] = _SERIALIZER.query("description", description, 'str')
+ if created_by is not None:
+ _query_parameters['createdBy'] = _SERIALIZER.query("created_by", created_by, 'str')
+ if stage is not None:
+ _query_parameters['stage'] = _SERIALIZER.query("stage", stage, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -307,6 +325,8 @@ def build_list_features_request(
api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
skip = kwargs.pop('skip', None) # type: Optional[str]
tags = kwargs.pop('tags', None) # type: Optional[str]
+ feature_name = kwargs.pop('feature_name', None) # type: Optional[str]
+ description = kwargs.pop('description', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -328,6 +348,10 @@ def build_list_features_request(
_query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
if tags is not None:
_query_parameters['$tags'] = _SERIALIZER.query("tags", tags, 'str')
+ if feature_name is not None:
+ _query_parameters['featureName'] = _SERIALIZER.query("feature_name", feature_name, 'str')
+ if description is not None:
+ _query_parameters['description'] = _SERIALIZER.query("description", description, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -426,6 +450,12 @@ def list(
skip=None, # type: Optional[str]
tags=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size=20, # type: Optional[int]
+ version_name=None, # type: Optional[str]
+ version=None, # type: Optional[str]
+ description=None, # type: Optional[str]
+ created_by=None, # type: Optional[str]
+ stage=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.FeaturesetVersionResourceArmPaginatedResult"]
@@ -447,6 +477,18 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param version_name: name for the featureset version.
+ :type version_name: str
+ :param version: featureset version.
+ :type version: str
+ :param description: description for the feature set version.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
+ :param stage: stage.
+ :type stage: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FeaturesetVersionResourceArmPaginatedResult or the
result of cls(response)
@@ -473,6 +515,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -489,6 +537,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=next_link,
)
request = _convert_request(request)
@@ -857,7 +911,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
@@ -880,8 +934,8 @@ def _backfill_initial(
body, # type: "_models.FeaturesetVersionBackfillRequest"
**kwargs # type: Any
):
- # type: (...) -> Optional["_models.FeaturesetVersionBackfillResponse"]
- cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.FeaturesetVersionBackfillResponse"]]
+ # type: (...) -> Optional["_models.FeaturesetJob"]
+ cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.FeaturesetJob"]]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
@@ -920,7 +974,7 @@ def _backfill_initial(
deserialized = None
response_headers = {}
if response.status_code == 200:
- deserialized = self._deserialize('FeaturesetVersionBackfillResponse', pipeline_response)
+ deserialized = self._deserialize('FeaturesetJob', pipeline_response)
if response.status_code == 202:
response_headers['Location']=self._deserialize('str', response.headers.get('Location'))
@@ -945,7 +999,7 @@ def begin_backfill(
body, # type: "_models.FeaturesetVersionBackfillRequest"
**kwargs # type: Any
):
- # type: (...) -> LROPoller["_models.FeaturesetVersionBackfillResponse"]
+ # type: (...) -> LROPoller["_models.FeaturesetJob"]
"""Backfill.
Backfill.
@@ -968,16 +1022,15 @@ def begin_backfill(
:paramtype polling: bool or ~azure.core.polling.PollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
- :return: An instance of LROPoller that returns either FeaturesetVersionBackfillResponse or the
- result of cls(response)
- :rtype:
- ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.FeaturesetVersionBackfillResponse]
+ :return: An instance of LROPoller that returns either FeaturesetJob or the result of
+ cls(response)
+ :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.FeaturesetJob]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType["_models.FeaturesetVersionBackfillResponse"]
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.FeaturesetJob"]
lro_delay = kwargs.pop(
'polling_interval',
self._config.polling_interval
@@ -999,7 +1052,7 @@ def begin_backfill(
def get_long_running_output(pipeline_response):
response = pipeline_response.http_response
- deserialized = self._deserialize('FeaturesetVersionBackfillResponse', pipeline_response)
+ deserialized = self._deserialize('FeaturesetJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
@@ -1105,6 +1158,8 @@ def list_features(
version, # type: str
skip=None, # type: Optional[str]
tags=None, # type: Optional[str]
+ feature_name=None, # type: Optional[str]
+ description=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.FeatureArmPaginatedResult"]
@@ -1125,6 +1180,10 @@ def list_features(
:param tags: Comma-separated list of tag names (and optionally values). Example:
tag1,tag2=value2.
:type tags: str
+ :param feature_name: feature name.
+ :type feature_name: str
+ :param description: description.
+ :type description: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either FeatureArmPaginatedResult or the result of
cls(response)
@@ -1151,6 +1210,8 @@ def prepare_request(next_link=None):
api_version=api_version,
skip=skip,
tags=tags,
+ feature_name=feature_name,
+ description=description,
template_url=self.list_features.metadata['url'],
)
request = _convert_request(request)
@@ -1167,6 +1228,8 @@ def prepare_request(next_link=None):
api_version=api_version,
skip=skip,
tags=tags,
+ feature_name=feature_name,
+ description=description,
template_url=next_link,
)
request = _convert_request(request)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_containers_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_containers_operations.py
index e2f5f479971e..651e55b2840f 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_containers_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_containers_operations.py
@@ -44,6 +44,10 @@ def build_list_request(
skip = kwargs.pop('skip', None) # type: Optional[str]
tags = kwargs.pop('tags', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size = kwargs.pop('page_size', 20) # type: Optional[int]
+ name = kwargs.pop('name', None) # type: Optional[str]
+ description = kwargs.pop('description', None) # type: Optional[str]
+ created_by = kwargs.pop('created_by', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -65,6 +69,14 @@ def build_list_request(
_query_parameters['tags'] = _SERIALIZER.query("tags", tags, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
+ if page_size is not None:
+ _query_parameters['pageSize'] = _SERIALIZER.query("page_size", page_size, 'int')
+ if name is not None:
+ _query_parameters['name'] = _SERIALIZER.query("name", name, 'str')
+ if description is not None:
+ _query_parameters['description'] = _SERIALIZER.query("description", description, 'str')
+ if created_by is not None:
+ _query_parameters['createdBy'] = _SERIALIZER.query("created_by", created_by, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -229,6 +241,10 @@ def list(
skip=None, # type: Optional[str]
tags=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size=20, # type: Optional[int]
+ name=None, # type: Optional[str]
+ description=None, # type: Optional[str]
+ created_by=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.FeaturestoreEntityContainerResourceArmPaginatedResult"]
@@ -248,6 +264,14 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param name: name for the featurestore entity.
+ :type name: str
+ :param description: description for the featurestore entity.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either
FeaturestoreEntityContainerResourceArmPaginatedResult or the result of cls(response)
@@ -273,6 +297,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -288,6 +316,10 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ name=name,
+ description=description,
+ created_by=created_by,
template_url=next_link,
)
request = _convert_request(request)
@@ -640,7 +672,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_versions_operations.py
index 77c8f97d399c..5aa6b530e8a7 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_featurestore_entity_versions_operations.py
@@ -45,6 +45,12 @@ def build_list_request(
skip = kwargs.pop('skip', None) # type: Optional[str]
tags = kwargs.pop('tags', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size = kwargs.pop('page_size', 20) # type: Optional[int]
+ version_name = kwargs.pop('version_name', None) # type: Optional[str]
+ version = kwargs.pop('version', None) # type: Optional[str]
+ description = kwargs.pop('description', None) # type: Optional[str]
+ created_by = kwargs.pop('created_by', None) # type: Optional[str]
+ stage = kwargs.pop('stage', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -67,6 +73,18 @@ def build_list_request(
_query_parameters['tags'] = _SERIALIZER.query("tags", tags, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
+ if page_size is not None:
+ _query_parameters['pageSize'] = _SERIALIZER.query("page_size", page_size, 'int')
+ if version_name is not None:
+ _query_parameters['versionName'] = _SERIALIZER.query("version_name", version_name, 'str')
+ if version is not None:
+ _query_parameters['version'] = _SERIALIZER.query("version", version, 'str')
+ if description is not None:
+ _query_parameters['description'] = _SERIALIZER.query("description", description, 'str')
+ if created_by is not None:
+ _query_parameters['createdBy'] = _SERIALIZER.query("created_by", created_by, 'str')
+ if stage is not None:
+ _query_parameters['stage'] = _SERIALIZER.query("stage", stage, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -238,6 +256,12 @@ def list(
skip=None, # type: Optional[str]
tags=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
+ page_size=20, # type: Optional[int]
+ version_name=None, # type: Optional[str]
+ version=None, # type: Optional[str]
+ description=None, # type: Optional[str]
+ created_by=None, # type: Optional[str]
+ stage=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.FeaturestoreEntityVersionResourceArmPaginatedResult"]
@@ -259,6 +283,18 @@ def list(
:param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
ListViewType.All]View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
+ :param page_size: page size.
+ :type page_size: int
+ :param version_name: name for the featurestore entity version.
+ :type version_name: str
+ :param version: featurestore entity version.
+ :type version: str
+ :param description: description for the feature entity version.
+ :type description: str
+ :param created_by: createdBy user name.
+ :type created_by: str
+ :param stage: stage.
+ :type stage: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either
FeaturestoreEntityVersionResourceArmPaginatedResult or the result of cls(response)
@@ -285,6 +321,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -301,6 +343,12 @@ def prepare_request(next_link=None):
skip=skip,
tags=tags,
list_view_type=list_view_type,
+ page_size=page_size,
+ version_name=version_name,
+ version=version,
+ description=description,
+ created_by=created_by,
+ stage=stage,
template_url=next_link,
)
request = _convert_request(request)
@@ -669,7 +717,7 @@ def get_long_running_output(pipeline_response):
return deserialized
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
+ if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'original-uri'}, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_jobs_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_jobs_operations.py
index 74e3176d8962..cd8858df2038 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_jobs_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_jobs_operations.py
@@ -169,6 +169,48 @@ def build_get_request(
)
+def build_update_request(
+ subscription_id, # type: str
+ resource_group_name, # type: str
+ workspace_name, # type: str
+ id, # type: str
+ **kwargs # type: Any
+):
+ # type: (...) -> HttpRequest
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', None) # type: Optional[str]
+
+ accept = "application/json"
+ # Construct URL
+ _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}") # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
+ "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
+ "workspaceName": _SERIALIZER.url("workspace_name", workspace_name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$'),
+ "id": _SERIALIZER.url("id", id, 'str'),
+ }
+
+ _url = _format_url_section(_url, **path_format_arguments)
+
+ # Construct parameters
+ _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
+ _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
+
+ # Construct headers
+ _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
+ if content_type is not None:
+ _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+ _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+ return HttpRequest(
+ method="PATCH",
+ url=_url,
+ params=_query_parameters,
+ headers=_header_parameters,
+ **kwargs
+ )
+
+
def build_create_or_update_request(
subscription_id, # type: str
resource_group_name, # type: str
@@ -581,6 +623,79 @@ def get(
get.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}"} # type: ignore
+ @distributed_trace
+ def update(
+ self,
+ resource_group_name, # type: str
+ workspace_name, # type: str
+ id, # type: str
+ body, # type: "_models.PartialJobBasePartialResource"
+ **kwargs # type: Any
+ ):
+ # type: (...) -> "_models.JobBase"
+ """Updates a Job.
+
+ Updates a Job.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param workspace_name: Name of Azure Machine Learning workspace.
+ :type workspace_name: str
+ :param id: The name and identifier for the Job. This is case-sensitive.
+ :type id: str
+ :param body: Job definition to apply during the operation.
+ :type body: ~azure.mgmt.machinelearningservices.models.PartialJobBasePartialResource
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: JobBase, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.JobBase
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.JobBase"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PartialJobBasePartialResource')
+
+ request = build_update_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ workspace_name=workspace_name,
+ id=id,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.update.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('JobBase', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}"} # type: ignore
+
+
@distributed_trace
def create_or_update(
self,
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_model_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_model_versions_operations.py
index 4720632a3813..47b137841c9e 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_model_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_model_versions_operations.py
@@ -51,6 +51,7 @@ def build_list_request(
tags = kwargs.pop('tags', None) # type: Optional[str]
properties = kwargs.pop('properties', None) # type: Optional[str]
feed = kwargs.pop('feed', None) # type: Optional[str]
+ stage = kwargs.pop('stage', None) # type: Optional[str]
list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
accept = "application/json"
@@ -86,6 +87,8 @@ def build_list_request(
_query_parameters['properties'] = _SERIALIZER.query("properties", properties, 'str')
if feed is not None:
_query_parameters['feed'] = _SERIALIZER.query("feed", feed, 'str')
+ if stage is not None:
+ _query_parameters['stage'] = _SERIALIZER.query("stage", stage, 'str')
if list_view_type is not None:
_query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
@@ -309,6 +312,7 @@ def list(
tags=None, # type: Optional[str]
properties=None, # type: Optional[str]
feed=None, # type: Optional[str]
+ stage=None, # type: Optional[str]
list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
**kwargs # type: Any
):
@@ -343,6 +347,8 @@ def list(
:type properties: str
:param feed: Name of the feed.
:type feed: str
+ :param stage: Model stage.
+ :type stage: str
:param list_view_type: View type for including/excluding (for example) archived entities.
:type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
:keyword callable cls: A custom type or function that will be passed the direct response
@@ -377,6 +383,7 @@ def prepare_request(next_link=None):
tags=tags,
properties=properties,
feed=feed,
+ stage=stage,
list_view_type=list_view_type,
template_url=self.list.metadata['url'],
)
@@ -400,6 +407,7 @@ def prepare_request(next_link=None):
tags=tags,
properties=properties,
feed=feed,
+ stage=stage,
list_view_type=list_view_type,
template_url=next_link,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_online_endpoints_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_online_endpoints_operations.py
index ea7dc3dc3a5a..135438526900 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_online_endpoints_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_online_endpoints_operations.py
@@ -1199,9 +1199,9 @@ def get_token(
**kwargs # type: Any
):
# type: (...) -> "_models.EndpointAuthToken"
- """Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ """Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
- Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.
+ Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.
:param resource_group_name: The name of the resource group. The name is case insensitive.
:type resource_group_name: str
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_code_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_code_versions_operations.py
index d8d4a1291dc9..258335c27a05 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_code_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_code_versions_operations.py
@@ -206,6 +206,50 @@ def build_create_or_update_request_initial(
**kwargs
)
+
+def build_create_or_get_pending_upload_request(
+ subscription_id, # type: str
+ resource_group_name, # type: str
+ registry_name, # type: str
+ code_name, # type: str
+ version, # type: str
+ **kwargs # type: Any
+):
+ # type: (...) -> HttpRequest
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', None) # type: Optional[str]
+
+ accept = "application/json"
+ # Construct URL
+ _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/pendingUpload/{version}") # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
+ "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
+ "registryName": _SERIALIZER.url("registry_name", registry_name, 'str'),
+ "codeName": _SERIALIZER.url("code_name", code_name, 'str'),
+ "version": _SERIALIZER.url("version", version, 'str'),
+ }
+
+ _url = _format_url_section(_url, **path_format_arguments)
+
+ # Construct parameters
+ _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
+ _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
+
+ # Construct headers
+ _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
+ if content_type is not None:
+ _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+ _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+ return HttpRequest(
+ method="POST",
+ url=_url,
+ params=_query_parameters,
+ headers=_header_parameters,
+ **kwargs
+ )
+
# fmt: on
class RegistryCodeVersionsOperations(object):
"""RegistryCodeVersionsOperations operations.
@@ -679,3 +723,80 @@ def get_long_running_output(pipeline_response):
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}"} # type: ignore
+
+ @distributed_trace
+ def create_or_get_pending_upload(
+ self,
+ resource_group_name, # type: str
+ registry_name, # type: str
+ code_name, # type: str
+ version, # type: str
+ body, # type: "_models.PendingUploadRequestDto"
+ **kwargs # type: Any
+ ):
+ # type: (...) -> "_models.PendingUploadResponseDto"
+ """Generate a storage location and credential for the client to upload a code asset to.
+
+ Generate a storage location and credential for the client to upload a code asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry.
+ :type registry_name: str
+ :param code_name: Pending upload name. This is case-sensitive.
+ :type code_name: str
+ :param version: Version identifier. This is case-sensitive.
+ :type version: str
+ :param body: Pending upload request object.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.PendingUploadResponseDto"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PendingUploadRequestDto')
+
+ request = build_create_or_get_pending_upload_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ code_name=code_name,
+ version=version,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.create_or_get_pending_upload.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('PendingUploadResponseDto', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_pending_upload.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/pendingUpload/{version}"} # type: ignore
+
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_component_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_component_versions_operations.py
index da4b4e13a127..58b8ee77ce5f 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_component_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_component_versions_operations.py
@@ -45,6 +45,7 @@ def build_list_request(
order_by = kwargs.pop('order_by', None) # type: Optional[str]
top = kwargs.pop('top', None) # type: Optional[int]
skip = kwargs.pop('skip', None) # type: Optional[str]
+ stage = kwargs.pop('stage', None) # type: Optional[str]
accept = "application/json"
# Construct URL
@@ -67,6 +68,8 @@ def build_list_request(
_query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
if skip is not None:
_query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
+ if stage is not None:
+ _query_parameters['stage'] = _SERIALIZER.query("stage", stage, 'str')
# Construct headers
_header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
@@ -238,6 +241,7 @@ def list(
order_by=None, # type: Optional[str]
top=None, # type: Optional[int]
skip=None, # type: Optional[str]
+ stage=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.ComponentVersionResourceArmPaginatedResult"]
@@ -257,6 +261,8 @@ def list(
:type top: int
:param skip: Continuation token for pagination.
:type skip: str
+ :param stage: Component stage.
+ :type stage: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either ComponentVersionResourceArmPaginatedResult or the
result of cls(response)
@@ -283,6 +289,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
template_url=self.list.metadata['url'],
)
request = _convert_request(request)
@@ -299,6 +306,7 @@ def prepare_request(next_link=None):
order_by=order_by,
top=top,
skip=skip,
+ stage=stage,
template_url=next_link,
)
request = _convert_request(request)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_containers_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_containers_operations.py
deleted file mode 100644
index 70d634f11907..000000000000
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_containers_operations.py
+++ /dev/null
@@ -1,644 +0,0 @@
-# pylint: disable=too-many-lines
-# coding=utf-8
-# --------------------------------------------------------------------------
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License. See License.txt in the project root for license information.
-# Code generated by Microsoft (R) AutoRest Code Generator.
-# Changes may cause incorrect behavior and will be lost if the code is regenerated.
-# --------------------------------------------------------------------------
-from typing import TYPE_CHECKING
-
-from msrest import Serializer
-
-from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
-from azure.core.paging import ItemPaged
-from azure.core.pipeline import PipelineResponse
-from azure.core.pipeline.transport import HttpResponse
-from azure.core.polling import LROPoller, NoPolling, PollingMethod
-from azure.core.rest import HttpRequest
-from azure.core.tracing.decorator import distributed_trace
-from azure.mgmt.core.exceptions import ARMErrorFormat
-from azure.mgmt.core.polling.arm_polling import ARMPolling
-
-from .. import models as _models
-from .._vendor import _convert_request, _format_url_section
-
-if TYPE_CHECKING:
- # pylint: disable=unused-import,ungrouped-imports
- from typing import Any, Callable, Dict, Iterable, Optional, TypeVar, Union
- T = TypeVar('T')
- ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
-
-_SERIALIZER = Serializer()
-_SERIALIZER.client_side_validation = False
-# fmt: off
-
-def build_list_request(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- skip = kwargs.pop('skip', None) # type: Optional[str]
- list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
- if skip is not None:
- _query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
- if list_view_type is not None:
- _query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="GET",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-
-def build_delete_request_initial(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$'),
- "name": _SERIALIZER.url("name", name, 'str'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="DELETE",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-
-def build_get_request(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str'),
- "name": _SERIALIZER.url("name", name, 'str'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="GET",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-
-def build_create_or_update_request_initial(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', None) # type: Optional[str]
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str'),
- "name": _SERIALIZER.url("name", name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- if content_type is not None:
- _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="PUT",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-# fmt: on
-class RegistryDataContainersOperations(object):
- """RegistryDataContainersOperations operations.
-
- You should not instantiate this class directly. Instead, you should create a Client instance that
- instantiates it for you and attaches it as an attribute.
-
- :ivar models: Alias to model classes used in this operation group.
- :type models: ~azure.mgmt.machinelearningservices.models
- :param client: Client for service requests.
- :param config: Configuration of service client.
- :param serializer: An object model serializer.
- :param deserializer: An object model deserializer.
- """
-
- models = _models
-
- def __init__(self, client, config, serializer, deserializer):
- self._client = client
- self._serialize = serializer
- self._deserialize = deserializer
- self._config = config
-
- @distributed_trace
- def list(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- skip=None, # type: Optional[str]
- list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
- **kwargs # type: Any
- ):
- # type: (...) -> Iterable["_models.DataContainerResourceArmPaginatedResult"]
- """List containers.
-
- List containers.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param skip: Continuation token for pagination.
- :type skip: str
- :param list_view_type: View type for including/excluding (for example) archived entities.
- :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: An iterator like instance of either DataContainerResourceArmPaginatedResult or the
- result of cls(response)
- :rtype:
- ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.DataContainerResourceArmPaginatedResult]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainerResourceArmPaginatedResult"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
- def prepare_request(next_link=None):
- if not next_link:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- api_version=api_version,
- skip=skip,
- list_view_type=list_view_type,
- template_url=self.list.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- else:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- api_version=api_version,
- skip=skip,
- list_view_type=list_view_type,
- template_url=next_link,
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
- request.method = "GET"
- return request
-
- def extract_data(pipeline_response):
- deserialized = self._deserialize("DataContainerResourceArmPaginatedResult", pipeline_response)
- list_of_elem = deserialized.value
- if cls:
- list_of_elem = cls(list_of_elem)
- return deserialized.next_link or None, iter(list_of_elem)
-
- def get_next(next_link=None):
- request = prepare_request(next_link)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- return pipeline_response
-
-
- return ItemPaged(
- get_next, extract_data
- )
- list.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data"} # type: ignore
-
- def _delete_initial( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
- ):
- # type: (...) -> None
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_delete_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- template_url=self._delete_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 202, 204]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 202:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Location']=self._deserialize('str', response.headers.get('Location'))
- response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After'))
-
-
- if cls:
- return cls(pipeline_response, None, response_headers)
-
- _delete_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
-
- @distributed_trace
- def begin_delete( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
- ):
- # type: (...) -> LROPoller[None]
- """Delete container.
-
- Delete container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
- operation to not poll, or pass in your own initialized polling object for a personal polling
- strategy.
- :paramtype polling: bool or ~azure.core.polling.PollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of LROPoller that returns either None or the result of cls(response)
- :rtype: ~azure.core.polling.LROPoller[None]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = self._delete_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- if cls:
- return cls(pipeline_response, None, {})
-
-
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
- elif polling is False: polling_method = NoPolling()
- else: polling_method = polling
- if cont_token:
- return LROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_delete.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
- @distributed_trace
- def get(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
- ):
- # type: (...) -> "_models.DataContainer"
- """Get container.
-
- Get container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: DataContainer, or the result of cls(response)
- :rtype: ~azure.mgmt.machinelearningservices.models.DataContainer
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainer"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_get_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- template_url=self.get.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- deserialized = self._deserialize('DataContainer', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, {})
-
- return deserialized
-
- get.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
-
- def _create_or_update_initial(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- body, # type: "_models.DataContainer"
- **kwargs # type: Any
- ):
- # type: (...) -> "_models.DataContainer"
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainer"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
-
- _json = self._serialize.body(body, 'DataContainer')
-
- request = build_create_or_update_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- content_type=content_type,
- json=_json,
- template_url=self._create_or_update_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 201]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 200:
- deserialized = self._deserialize('DataContainer', pipeline_response)
-
- if response.status_code == 201:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation'))
-
- deserialized = self._deserialize('DataContainer', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, response_headers)
-
- return deserialized
-
- _create_or_update_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
-
-
- @distributed_trace
- def begin_create_or_update(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- body, # type: "_models.DataContainer"
- **kwargs # type: Any
- ):
- # type: (...) -> LROPoller["_models.DataContainer"]
- """Create or update container.
-
- Create or update container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param body: Container entity to create or update.
- :type body: ~azure.mgmt.machinelearningservices.models.DataContainer
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
- operation to not poll, or pass in your own initialized polling object for a personal polling
- strategy.
- :paramtype polling: bool or ~azure.core.polling.PollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of LROPoller that returns either DataContainer or the result of
- cls(response)
- :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataContainer]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
- polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataContainer"]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = self._create_or_update_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- body=body,
- api_version=api_version,
- content_type=content_type,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- response = pipeline_response.http_response
- deserialized = self._deserialize('DataContainer', pipeline_response)
- if cls:
- return cls(pipeline_response, deserialized, {})
- return deserialized
-
-
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
- elif polling is False: polling_method = NoPolling()
- else: polling_method = polling
- if cont_token:
- return LROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}"} # type: ignore
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_versions_operations.py
deleted file mode 100644
index 10c10f16a214..000000000000
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_data_versions_operations.py
+++ /dev/null
@@ -1,702 +0,0 @@
-# pylint: disable=too-many-lines
-# coding=utf-8
-# --------------------------------------------------------------------------
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License. See License.txt in the project root for license information.
-# Code generated by Microsoft (R) AutoRest Code Generator.
-# Changes may cause incorrect behavior and will be lost if the code is regenerated.
-# --------------------------------------------------------------------------
-from typing import TYPE_CHECKING
-
-from msrest import Serializer
-
-from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
-from azure.core.paging import ItemPaged
-from azure.core.pipeline import PipelineResponse
-from azure.core.pipeline.transport import HttpResponse
-from azure.core.polling import LROPoller, NoPolling, PollingMethod
-from azure.core.rest import HttpRequest
-from azure.core.tracing.decorator import distributed_trace
-from azure.mgmt.core.exceptions import ARMErrorFormat
-from azure.mgmt.core.polling.arm_polling import ARMPolling
-
-from .. import models as _models
-from .._vendor import _convert_request, _format_url_section
-
-if TYPE_CHECKING:
- # pylint: disable=unused-import,ungrouped-imports
- from typing import Any, Callable, Dict, Iterable, Optional, TypeVar, Union
- T = TypeVar('T')
- ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
-
-_SERIALIZER = Serializer()
-_SERIALIZER.client_side_validation = False
-# fmt: off
-
-def build_list_request(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- order_by = kwargs.pop('order_by', None) # type: Optional[str]
- top = kwargs.pop('top', None) # type: Optional[int]
- skip = kwargs.pop('skip', None) # type: Optional[str]
- tags = kwargs.pop('tags', None) # type: Optional[str]
- list_view_type = kwargs.pop('list_view_type', None) # type: Optional[Union[str, "_models.ListViewType"]]
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$'),
- "name": _SERIALIZER.url("name", name, 'str'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
- if order_by is not None:
- _query_parameters['$orderBy'] = _SERIALIZER.query("order_by", order_by, 'str')
- if top is not None:
- _query_parameters['$top'] = _SERIALIZER.query("top", top, 'int')
- if skip is not None:
- _query_parameters['$skip'] = _SERIALIZER.query("skip", skip, 'str')
- if tags is not None:
- _query_parameters['$tags'] = _SERIALIZER.query("tags", tags, 'str')
- if list_view_type is not None:
- _query_parameters['listViewType'] = _SERIALIZER.query("list_view_type", list_view_type, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="GET",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-
-def build_delete_request_initial(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$'),
- "name": _SERIALIZER.url("name", name, 'str'),
- "version": _SERIALIZER.url("version", version, 'str'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="DELETE",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-
-def build_get_request(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str'),
- "name": _SERIALIZER.url("name", name, 'str'),
- "version": _SERIALIZER.url("version", version, 'str'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="GET",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-
-def build_create_or_update_request_initial(
- subscription_id, # type: str
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- **kwargs # type: Any
-):
- # type: (...) -> HttpRequest
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', None) # type: Optional[str]
-
- accept = "application/json"
- # Construct URL
- _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}") # pylint: disable=line-too-long
- path_format_arguments = {
- "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
- "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
- "registryName": _SERIALIZER.url("registry_name", registry_name, 'str'),
- "name": _SERIALIZER.url("name", name, 'str', pattern=r'^[a-zA-Z0-9][a-zA-Z0-9\-_]{0,254}$'),
- "version": _SERIALIZER.url("version", version, 'str'),
- }
-
- _url = _format_url_section(_url, **path_format_arguments)
-
- # Construct parameters
- _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
- _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
-
- # Construct headers
- _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
- if content_type is not None:
- _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
- _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
-
- return HttpRequest(
- method="PUT",
- url=_url,
- params=_query_parameters,
- headers=_header_parameters,
- **kwargs
- )
-
-# fmt: on
-class RegistryDataVersionsOperations(object):
- """RegistryDataVersionsOperations operations.
-
- You should not instantiate this class directly. Instead, you should create a Client instance that
- instantiates it for you and attaches it as an attribute.
-
- :ivar models: Alias to model classes used in this operation group.
- :type models: ~azure.mgmt.machinelearningservices.models
- :param client: Client for service requests.
- :param config: Configuration of service client.
- :param serializer: An object model serializer.
- :param deserializer: An object model deserializer.
- """
-
- models = _models
-
- def __init__(self, client, config, serializer, deserializer):
- self._client = client
- self._serialize = serializer
- self._deserialize = deserializer
- self._config = config
-
- @distributed_trace
- def list(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- order_by=None, # type: Optional[str]
- top=None, # type: Optional[int]
- skip=None, # type: Optional[str]
- tags=None, # type: Optional[str]
- list_view_type=None, # type: Optional[Union[str, "_models.ListViewType"]]
- **kwargs # type: Any
- ):
- # type: (...) -> Iterable["_models.DataVersionBaseResourceArmPaginatedResult"]
- """List data versions in the data container.
-
- List data versions in the data container.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Data container's name.
- :type name: str
- :param order_by: Please choose OrderBy value from ['createdtime', 'modifiedtime'].
- :type order_by: str
- :param top: Top count of results, top count cannot be greater than the page size.
- If topCount > page size, results with be default page size count
- will be returned.
- :type top: int
- :param skip: Continuation token for pagination.
- :type skip: str
- :param tags: Comma-separated list of tag names (and optionally values). Example:
- tag1,tag2=value2.
- :type tags: str
- :param list_view_type: [ListViewType.ActiveOnly, ListViewType.ArchivedOnly,
- ListViewType.All]View type for including/excluding (for example) archived entities.
- :type list_view_type: str or ~azure.mgmt.machinelearningservices.models.ListViewType
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: An iterator like instance of either DataVersionBaseResourceArmPaginatedResult or the
- result of cls(response)
- :rtype:
- ~azure.core.paging.ItemPaged[~azure.mgmt.machinelearningservices.models.DataVersionBaseResourceArmPaginatedResult]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBaseResourceArmPaginatedResult"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
- def prepare_request(next_link=None):
- if not next_link:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- order_by=order_by,
- top=top,
- skip=skip,
- tags=tags,
- list_view_type=list_view_type,
- template_url=self.list.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- else:
-
- request = build_list_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- api_version=api_version,
- order_by=order_by,
- top=top,
- skip=skip,
- tags=tags,
- list_view_type=list_view_type,
- template_url=next_link,
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
- request.method = "GET"
- return request
-
- def extract_data(pipeline_response):
- deserialized = self._deserialize("DataVersionBaseResourceArmPaginatedResult", pipeline_response)
- list_of_elem = deserialized.value
- if cls:
- list_of_elem = cls(list_of_elem)
- return deserialized.next_link or None, iter(list_of_elem)
-
- def get_next(next_link=None):
- request = prepare_request(next_link)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- return pipeline_response
-
-
- return ItemPaged(
- get_next, extract_data
- )
- list.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions"} # type: ignore
-
- def _delete_initial( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- **kwargs # type: Any
- ):
- # type: (...) -> None
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_delete_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- template_url=self._delete_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 202, 204]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 202:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Location']=self._deserialize('str', response.headers.get('Location'))
- response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After'))
-
-
- if cls:
- return cls(pipeline_response, None, response_headers)
-
- _delete_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
-
- @distributed_trace
- def begin_delete( # pylint: disable=inconsistent-return-statements
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- **kwargs # type: Any
- ):
- # type: (...) -> LROPoller[None]
- """Delete version.
-
- Delete version.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param version: Version identifier.
- :type version: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
- operation to not poll, or pass in your own initialized polling object for a personal polling
- strategy.
- :paramtype polling: bool or ~azure.core.polling.PollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of LROPoller that returns either None or the result of cls(response)
- :rtype: ~azure.core.polling.LROPoller[None]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType[None]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = self._delete_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- if cls:
- return cls(pipeline_response, None, {})
-
-
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
- elif polling is False: polling_method = NoPolling()
- else: polling_method = polling
- if cont_token:
- return LROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_delete.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
- @distributed_trace
- def get(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- **kwargs # type: Any
- ):
- # type: (...) -> "_models.DataVersionBase"
- """Get version.
-
- Get version.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param version: Version identifier.
- :type version: str
- :keyword callable cls: A custom type or function that will be passed the direct response
- :return: DataVersionBase, or the result of cls(response)
- :rtype: ~azure.mgmt.machinelearningservices.models.DataVersionBase
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBase"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
-
-
- request = build_get_request(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- template_url=self.get.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
- raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
-
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, {})
-
- return deserialized
-
- get.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
-
- def _create_or_update_initial(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- body, # type: "_models.DataVersionBase"
- **kwargs # type: Any
- ):
- # type: (...) -> "_models.DataVersionBase"
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBase"]
- error_map = {
- 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
- }
- error_map.update(kwargs.pop('error_map', {}))
-
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
-
- _json = self._serialize.body(body, 'DataVersionBase')
-
- request = build_create_or_update_request_initial(
- subscription_id=self._config.subscription_id,
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- api_version=api_version,
- content_type=content_type,
- json=_json,
- template_url=self._create_or_update_initial.metadata['url'],
- )
- request = _convert_request(request)
- request.url = self._client.format_url(request.url)
-
- pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
- request,
- stream=False,
- **kwargs
- )
- response = pipeline_response.http_response
-
- if response.status_code not in [200, 201]:
- map_error(status_code=response.status_code, response=response, error_map=error_map)
- raise HttpResponseError(response=response, error_format=ARMErrorFormat)
-
- response_headers = {}
- if response.status_code == 200:
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
-
- if response.status_code == 201:
- response_headers['x-ms-async-operation-timeout']=self._deserialize('duration', response.headers.get('x-ms-async-operation-timeout'))
- response_headers['Azure-AsyncOperation']=self._deserialize('str', response.headers.get('Azure-AsyncOperation'))
-
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
-
- if cls:
- return cls(pipeline_response, deserialized, response_headers)
-
- return deserialized
-
- _create_or_update_initial.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
-
-
- @distributed_trace
- def begin_create_or_update(
- self,
- resource_group_name, # type: str
- registry_name, # type: str
- name, # type: str
- version, # type: str
- body, # type: "_models.DataVersionBase"
- **kwargs # type: Any
- ):
- # type: (...) -> LROPoller["_models.DataVersionBase"]
- """Create or update version.
-
- Create or update version.
-
- :param resource_group_name: The name of the resource group. The name is case insensitive.
- :type resource_group_name: str
- :param registry_name: Name of Azure Machine Learning registry.
- :type registry_name: str
- :param name: Container name.
- :type name: str
- :param version: Version identifier.
- :type version: str
- :param body: Version entity to create or update.
- :type body: ~azure.mgmt.machinelearningservices.models.DataVersionBase
- :keyword callable cls: A custom type or function that will be passed the direct response
- :keyword str continuation_token: A continuation token to restart a poller from a saved state.
- :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this
- operation to not poll, or pass in your own initialized polling object for a personal polling
- strategy.
- :paramtype polling: bool or ~azure.core.polling.PollingMethod
- :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
- Retry-After header is present.
- :return: An instance of LROPoller that returns either DataVersionBase or the result of
- cls(response)
- :rtype:
- ~azure.core.polling.LROPoller[~azure.mgmt.machinelearningservices.models.DataVersionBase]
- :raises: ~azure.core.exceptions.HttpResponseError
- """
- api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
- content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
- polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod]
- cls = kwargs.pop('cls', None) # type: ClsType["_models.DataVersionBase"]
- lro_delay = kwargs.pop(
- 'polling_interval',
- self._config.polling_interval
- )
- cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
- if cont_token is None:
- raw_result = self._create_or_update_initial(
- resource_group_name=resource_group_name,
- registry_name=registry_name,
- name=name,
- version=version,
- body=body,
- api_version=api_version,
- content_type=content_type,
- cls=lambda x,y,z: x,
- **kwargs
- )
- kwargs.pop('error_map', None)
-
- def get_long_running_output(pipeline_response):
- response = pipeline_response.http_response
- deserialized = self._deserialize('DataVersionBase', pipeline_response)
- if cls:
- return cls(pipeline_response, deserialized, {})
- return deserialized
-
-
- if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs)
- elif polling is False: polling_method = NoPolling()
- else: polling_method = polling
- if cont_token:
- return LROPoller.from_continuation_token(
- polling_method=polling_method,
- continuation_token=cont_token,
- client=self._client,
- deserialization_callback=get_long_running_output
- )
- return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
-
- begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}"} # type: ignore
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_model_versions_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_model_versions_operations.py
index 3487402fef07..95806826fd51 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_model_versions_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_registry_model_versions_operations.py
@@ -221,6 +221,50 @@ def build_create_or_update_request_initial(
**kwargs
)
+
+def build_create_or_get_pending_upload_request(
+ subscription_id, # type: str
+ resource_group_name, # type: str
+ registry_name, # type: str
+ model_name, # type: str
+ version, # type: str
+ **kwargs # type: Any
+):
+ # type: (...) -> HttpRequest
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', None) # type: Optional[str]
+
+ accept = "application/json"
+ # Construct URL
+ _url = kwargs.pop("template_url", "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/pendingUpload/{version}") # pylint: disable=line-too-long
+ path_format_arguments = {
+ "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1),
+ "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1),
+ "registryName": _SERIALIZER.url("registry_name", registry_name, 'str'),
+ "modelName": _SERIALIZER.url("model_name", model_name, 'str'),
+ "version": _SERIALIZER.url("version", version, 'str'),
+ }
+
+ _url = _format_url_section(_url, **path_format_arguments)
+
+ # Construct parameters
+ _query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
+ _query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
+
+ # Construct headers
+ _header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
+ if content_type is not None:
+ _header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
+ _header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
+
+ return HttpRequest(
+ method="POST",
+ url=_url,
+ params=_query_parameters,
+ headers=_header_parameters,
+ **kwargs
+ )
+
# fmt: on
class RegistryModelVersionsOperations(object):
"""RegistryModelVersionsOperations operations.
@@ -721,3 +765,80 @@ def get_long_running_output(pipeline_response):
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_create_or_update.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}"} # type: ignore
+
+ @distributed_trace
+ def create_or_get_pending_upload(
+ self,
+ resource_group_name, # type: str
+ registry_name, # type: str
+ model_name, # type: str
+ version, # type: str
+ body, # type: "_models.PendingUploadRequestDto"
+ **kwargs # type: Any
+ ):
+ # type: (...) -> "_models.PendingUploadResponseDto"
+ """Generate a storage location and credential for the client to upload a model asset to.
+
+ Generate a storage location and credential for the client to upload a model asset to.
+
+ :param resource_group_name: The name of the resource group. The name is case insensitive.
+ :type resource_group_name: str
+ :param registry_name: Name of Azure Machine Learning registry.
+ :type registry_name: str
+ :param model_name: Model name. This is case-sensitive.
+ :type model_name: str
+ :param version: Version identifier. This is case-sensitive.
+ :type version: str
+ :param body: Pending upload request object.
+ :type body: ~azure.mgmt.machinelearningservices.models.PendingUploadRequestDto
+ :keyword callable cls: A custom type or function that will be passed the direct response
+ :return: PendingUploadResponseDto, or the result of cls(response)
+ :rtype: ~azure.mgmt.machinelearningservices.models.PendingUploadResponseDto
+ :raises: ~azure.core.exceptions.HttpResponseError
+ """
+ cls = kwargs.pop('cls', None) # type: ClsType["_models.PendingUploadResponseDto"]
+ error_map = {
+ 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
+ }
+ error_map.update(kwargs.pop('error_map', {}))
+
+ api_version = kwargs.pop('api_version', "2023-04-01-preview") # type: str
+ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
+
+ _json = self._serialize.body(body, 'PendingUploadRequestDto')
+
+ request = build_create_or_get_pending_upload_request(
+ subscription_id=self._config.subscription_id,
+ resource_group_name=resource_group_name,
+ registry_name=registry_name,
+ model_name=model_name,
+ version=version,
+ api_version=api_version,
+ content_type=content_type,
+ json=_json,
+ template_url=self.create_or_get_pending_upload.metadata['url'],
+ )
+ request = _convert_request(request)
+ request.url = self._client.format_url(request.url)
+
+ pipeline_response = self._client._pipeline.run( # pylint: disable=protected-access
+ request,
+ stream=False,
+ **kwargs
+ )
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200]:
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
+ raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
+
+ deserialized = self._deserialize('PendingUploadResponseDto', pipeline_response)
+
+ if cls:
+ return cls(pipeline_response, deserialized, {})
+
+ return deserialized
+
+ create_or_get_pending_upload.metadata = {'url': "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/pendingUpload/{version}"} # type: ignore
+
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json
index 9e59cf732cb6..65b5f265d228 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json
@@ -1,22782 +1,24903 @@
{
- "swagger": "2.0",
- "info": {
- "title": "Azure Machine Learning Services",
- "version": "2023-04-01-preview"
- },
- "host": "management.azure.com",
- "schemes": [
- "https"
- ],
- "paths": {
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes": {
- "get": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "List containers.",
- "operationId": "RegistryCodeContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeContainerResourceArmPaginatedResult"
- }
- }
+ "swagger": "2.0",
+ "info": {
+ "title": "Azure Machine Learning Services",
+ "version": "2023-04-01-preview"
+ },
+ "host": "management.azure.com",
+ "schemes": [
+ "https"
+ ],
+ "paths": {
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes": {
+ "get": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "List containers.",
+ "operationId": "RegistryCodeContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List Registry Code Container.": {
- "$ref": "./examples/Registry/CodeContainer/list.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}": {
- "delete": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "Delete container.",
- "operationId": "RegistryCodeContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "Delete Registry Code Container.": {
- "$ref": "./examples/Registry/CodeContainer/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
}
- },
- "get": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "Get container.",
- "operationId": "RegistryCodeContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Registry Code Container.": {
- "$ref": "./examples/Registry/CodeContainer/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "RegistryCodeContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
+ "x-ms-examples": {
+ "List Registry Code Container.": {
+ "$ref": "./examples/Registry/CodeContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}": {
+ "delete": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "RegistryCodeContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "CreateOrUpdate Registry Code Container.": {
- "$ref": "./examples/Registry/CodeContainer/createOrUpdate.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions": {
- "get": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "List versions.",
- "operationId": "RegistryCodeVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeVersionResourceArmPaginatedResult"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "List Registry Code Version.": {
- "$ref": "./examples/Registry/CodeVersion/list.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Registry Code Container.": {
+ "$ref": "./examples/Registry/CodeContainer/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}": {
- "delete": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "Delete version.",
- "operationId": "RegistryCodeVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ "get": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "RegistryCodeContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Registry Code Version.": {
- "$ref": "./examples/Registry/CodeVersion/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "get": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "Get version.",
- "operationId": "RegistryCodeVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Registry Code Version.": {
- "$ref": "./examples/Registry/CodeVersion/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
}
}
},
- "put": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "RegistryCodeVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "codeName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Registry Code Version.": {
- "$ref": "./examples/Registry/CodeVersion/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "x-ms-examples": {
+ "Get Registry Code Container.": {
+ "$ref": "./examples/Registry/CodeContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components": {
- "get": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "List containers.",
- "operationId": "RegistryComponentContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ "put": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "RegistryCodeContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Registry Component Container.": {
- "$ref": "./examples/Registry/ComponentContainer/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}": {
- "delete": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "Delete container.",
- "operationId": "RegistryComponentContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
},
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
}
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Code Container.": {
+ "$ref": "./examples/Registry/CodeContainer/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions": {
+ "get": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "RegistryCodeVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Registry Component Container.": {
- "$ref": "./examples/Registry/ComponentContainer/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
}
- },
- "get": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "Get container.",
- "operationId": "RegistryComponentContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Registry Component Container.": {
- "$ref": "./examples/Registry/ComponentContainer/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "RegistryComponentContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
+ "x-ms-examples": {
+ "List Registry Code Version.": {
+ "$ref": "./examples/Registry/CodeVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "RegistryCodeVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "CreateOrUpdate Registry Component Container.": {
- "$ref": "./examples/Registry/ComponentContainer/createOrUpdate.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions": {
- "get": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "List versions.",
- "operationId": "RegistryComponentVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResourceArmPaginatedResult"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "List Registry Component Version.": {
- "$ref": "./examples/Registry/ComponentVersion/list.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "204": {
+ "description": "No Content"
}
+ },
+ "x-ms-examples": {
+ "Delete Registry Code Version.": {
+ "$ref": "./examples/Registry/CodeVersion/delete.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}": {
- "delete": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "Delete version.",
- "operationId": "RegistryComponentVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ "get": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "RegistryCodeVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Registry Component Version.": {
- "$ref": "./examples/Registry/ComponentVersion/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "get": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "Get version.",
- "operationId": "RegistryComponentVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Registry Component Version.": {
- "$ref": "./examples/Registry/ComponentVersion/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
}
}
},
- "put": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "RegistryComponentVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "componentName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Registry Component Version.": {
- "$ref": "./examples/Registry/ComponentVersion/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "x-ms-examples": {
+ "Get Registry Code Version.": {
+ "$ref": "./examples/Registry/CodeVersion/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data": {
- "get": {
- "tags": [
- "DataContainerRegistry"
- ],
- "summary": "List containers.",
- "operationId": "RegistryDataContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ "put": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "RegistryCodeVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataContainerResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "RegistryList Registry Data Container.": {
- "$ref": "./examples/Registry/DataContainer/registryList.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}": {
- "delete": {
- "tags": [
- "DataContainerRegistry"
- ],
- "summary": "Delete container.",
- "operationId": "RegistryDataContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
},
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
- },
- "x-ms-examples": {
- "Delete Registry Data Container.": {
- "$ref": "./examples/Registry/DataContainer/delete.json"
}
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
}
},
- "get": {
- "tags": [
- "DataContainerRegistry"
- ],
- "summary": "Get container.",
- "operationId": "RegistryDataContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
- }
- },
- "x-ms-examples": {
- "Get Registry Data Container.": {
- "$ref": "./examples/Registry/DataContainer/get.json"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Code Version.": {
+ "$ref": "./examples/Registry/CodeVersion/createOrUpdate.json"
}
},
- "put": {
- "tags": [
- "DataContainerRegistry"
- ],
- "summary": "Create or update container.",
- "operationId": "RegistryDataContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/codes/{codeName}/versions/pendingUpload/{version}": {
+ "post": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Generate a storage location and credential for the client to upload a code asset to.",
+ "operationId": "RegistryCodeVersions_CreateOrGetPendingUpload",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "CreateOrUpdate Registry Data Container.": {
- "$ref": "./examples/Registry/DataContainer/createOrUpdate.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "azure-async-operation"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions": {
- "get": {
- "tags": [
- "DataVersionRegistry"
- ],
- "summary": "List data versions in the data container",
- "operationId": "RegistryDataVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Data container's name",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Please choose OrderBy value from ['createdtime', 'modifiedtime']",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Top count of results, top count cannot be greater than the page size.\r\n If topCount > page size, results with be default page size count will be returned",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "$tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "codeName",
+ "description": "Pending upload name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Pending upload request object",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PendingUploadRequestDto"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "RegistryList Registry Data Version Base.": {
- "$ref": "./examples/Registry/DataVersionBase/registryList.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/PendingUploadResponseDto"
}
- },
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrGetPendingUpload Registry Code Version.": {
+ "$ref": "./examples/Registry/CodeVersion/createOrGetPendingUpload.json"
}
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/data/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "DataVersionRegistry"
- ],
- "summary": "Delete version.",
- "operationId": "RegistryDataVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9_-]{2,32}$"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components": {
+ "get": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "List containers.",
+ "operationId": "RegistryComponentContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Registry Data Version Base.": {
- "$ref": "./examples/Registry/DataVersionBase/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
}
- },
- "get": {
- "tags": [
- "DataVersionRegistry"
- ],
- "summary": "Get version.",
- "operationId": "RegistryDataVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Registry Data Version Base.": {
- "$ref": "./examples/Registry/DataVersionBase/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "DataVersionRegistry"
- ],
- "summary": "Create or update version.",
- "operationId": "RegistryDataVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
+ "x-ms-examples": {
+ "List Registry Component Container.": {
+ "$ref": "./examples/Registry/ComponentContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}": {
+ "delete": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "RegistryComponentContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
},
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Registry Data Version Base.": {
- "$ref": "./examples/Registry/DataVersionBase/createOrUpdate.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "azure-async-operation"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Registry Component Container.": {
+ "$ref": "./examples/Registry/ComponentContainer/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments": {
- "get": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "List environment containers.",
- "operationId": "RegistryEnvironmentContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "RegistryComponentContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Registry Environment Container.": {
- "$ref": "./examples/Registry/EnvironmentContainer/list.json"
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Registry Component Container.": {
+ "$ref": "./examples/Registry/ComponentContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}": {
- "delete": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "Delete container.",
- "operationId": "RegistryEnvironmentContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "put": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "RegistryComponentContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Registry Environment Container.": {
- "$ref": "./examples/Registry/EnvironmentContainer/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
- }
- },
- "get": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "Get container.",
- "operationId": "RegistryEnvironmentContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
},
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
}
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Component Container.": {
+ "$ref": "./examples/Registry/ComponentContainer/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions": {
+ "get": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "RegistryComponentVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "stage",
+ "description": "Component stage.",
+ "type": "string"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "x-ms-examples": {
- "Get Registry Environment Container.": {
- "$ref": "./examples/Registry/EnvironmentContainer/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "RegistryEnvironmentContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
+ "x-ms-examples": {
+ "List Registry Component Version.": {
+ "$ref": "./examples/Registry/ComponentVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/components/{componentName}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "RegistryComponentVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
},
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Registry Environment Container.": {
- "$ref": "./examples/Registry/EnvironmentContainer/createOrUpdate.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Registry Component Version.": {
+ "$ref": "./examples/Registry/ComponentVersion/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions": {
- "get": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "List versions.",
- "operationId": "RegistryEnvironmentVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "RegistryComponentVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Registry Environment Version.": {
- "$ref": "./examples/Registry/EnvironmentVersion/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Registry Component Version.": {
+ "$ref": "./examples/Registry/ComponentVersion/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}": {
- "delete": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "Delete version.",
- "operationId": "RegistryEnvironmentVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "put": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "RegistryComponentVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "componentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Registry Environment Version.": {
- "$ref": "./examples/Registry/EnvironmentVersion/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
- }
- },
- "get": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "Get version.",
- "operationId": "RegistryEnvironmentVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
},
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
}
- },
- "x-ms-examples": {
- "Get Registry Environment Version.": {
- "$ref": "./examples/Registry/EnvironmentVersion/get.json"
- }
}
},
- "put": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "RegistryEnvironmentVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "environmentName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Component Version.": {
+ "$ref": "./examples/Registry/ComponentVersion/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments": {
+ "get": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "List environment containers.",
+ "operationId": "RegistryEnvironmentContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
},
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
+ {
+ "value": "All"
}
- }
+ ]
}
- },
- "x-ms-examples": {
- "CreateOrUpdate Registry Environment Version.": {
- "$ref": "./examples/Registry/EnvironmentVersion/createOrUpdate.json"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResourceArmPaginatedResult"
+ }
}
+ },
+ "x-ms-examples": {
+ "List Registry Environment Container.": {
+ "$ref": "./examples/Registry/EnvironmentContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models": {
- "get": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "List model containers.",
- "operationId": "RegistryModelContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelContainerResourceArmPaginatedResult"
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}": {
+ "delete": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "RegistryEnvironmentContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "List Registry Model Container.": {
- "$ref": "./examples/Registry/ModelContainer/list.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Registry Environment Container.": {
+ "$ref": "./examples/Registry/EnvironmentContainer/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}": {
- "delete": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "Delete container.",
- "operationId": "RegistryModelContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ "get": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "RegistryEnvironmentContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Registry Model Container.": {
- "$ref": "./examples/Registry/ModelContainer/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "get": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "Get container.",
- "operationId": "RegistryModelContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Registry Model Container.": {
- "$ref": "./examples/Registry/ModelContainer/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
}
},
- "put": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "Create or update model container.",
- "operationId": "RegistryModelContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Registry Model Container.": {
- "$ref": "./examples/Registry/ModelContainer/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "x-ms-examples": {
+ "Get Registry Environment Container.": {
+ "$ref": "./examples/Registry/EnvironmentContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions": {
- "get": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "List versions.",
- "operationId": "RegistryModelVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "in": "query",
- "name": "version",
- "description": "Version identifier.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "description",
- "description": "Model description.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "properties",
- "description": "Comma-separated list of property names (and optionally values). Example: prop1,prop2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ "put": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "RegistryEnvironmentContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelVersionResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Registry Model Version.": {
- "$ref": "./examples/Registry/ModelVersion/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}": {
- "delete": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Delete version.",
- "operationId": "RegistryModelVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
},
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Environment Container.": {
+ "$ref": "./examples/Registry/EnvironmentContainer/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions": {
+ "get": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "RegistryEnvironmentVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ ]
}
- },
- "x-ms-examples": {
- "Delete Registry Model Version.": {
- "$ref": "./examples/Registry/ModelVersion/delete.json"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResourceArmPaginatedResult"
+ }
}
},
- "get": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Get version.",
- "operationId": "RegistryModelVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
+ "x-ms-examples": {
+ "List Registry Environment Version.": {
+ "$ref": "./examples/Registry/EnvironmentVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/environments/{environmentName}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "RegistryEnvironmentVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "Get Registry Model Version.": {
- "$ref": "./examples/Registry/ModelVersion/get.json"
- }
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
}
},
- "put": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "RegistryModelVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "in": "path",
- "name": "registryName",
- "description": "Name of Azure Machine Learning registry.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "modelName",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Registry Model Version.": {
- "$ref": "./examples/Registry/ModelVersion/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "x-ms-examples": {
+ "Delete Registry Environment Version.": {
+ "$ref": "./examples/Registry/EnvironmentVersion/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints": {
- "get": {
- "tags": [
- "BatchEndpoint"
- ],
- "summary": "Lists Batch inference endpoint in the workspace.",
- "operationId": "BatchEndpoints_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "count",
- "description": "Number of endpoints to be retrieved in a page of results.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchEndpointTrackedResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "RegistryEnvironmentVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Workspace Batch Endpoint.": {
- "$ref": "./examples/Workspace/BatchEndpoint/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Registry Environment Version.": {
+ "$ref": "./examples/Registry/EnvironmentVersion/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}": {
- "delete": {
- "tags": [
- "BatchEndpoint"
- ],
- "summary": "Delete Batch Inference Endpoint (asynchronous).",
- "operationId": "BatchEndpoints_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "put": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "RegistryEnvironmentVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "environmentName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "204": {
- "description": "No Content"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Workspace Batch Endpoint.": {
- "$ref": "./examples/Workspace/BatchEndpoint/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
- }
- },
- "get": {
- "tags": [
- "BatchEndpoint"
- ],
- "summary": "Gets a batch inference endpoint by name.",
- "operationId": "BatchEndpoints_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Name for the Batch Endpoint.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
},
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchEndpointTrackedResource"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
}
- },
- "x-ms-examples": {
- "Get Workspace Batch Endpoint.": {
- "$ref": "./examples/Workspace/BatchEndpoint/get.json"
- }
}
},
- "patch": {
- "tags": [
- "BatchEndpoint"
- ],
- "summary": "Update a batch inference endpoint (asynchronous).",
- "operationId": "BatchEndpoints_Update",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Name for the Batch inference endpoint.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Mutable batch inference endpoint definition object.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/PartialMinimalTrackedResourceWithIdentity"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchEndpointTrackedResource"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Environment Version.": {
+ "$ref": "./examples/Registry/EnvironmentVersion/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models": {
+ "get": {
+ "tags": [
+ "ModelContainer"
+ ],
+ "summary": "List model containers.",
+ "operationId": "RegistryModelContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
+ ]
}
- },
- "x-ms-examples": {
- "Update Workspace Batch Endpoint.": {
- "$ref": "./examples/Workspace/BatchEndpoint/update.json"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true
- },
- "put": {
- "tags": [
- "BatchEndpoint"
- ],
- "summary": "Creates a batch inference endpoint (asynchronous).",
- "operationId": "BatchEndpoints_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Name for the Batch inference endpoint.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Batch inference endpoint definition object.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/BatchEndpointTrackedResource"
- }
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResourceArmPaginatedResult"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchEndpointTrackedResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/BatchEndpointTrackedResource"
+ }
+ },
+ "x-ms-examples": {
+ "List Registry Model Container.": {
+ "$ref": "./examples/Registry/ModelContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}": {
+ "delete": {
+ "tags": [
+ "ModelContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "RegistryModelContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
},
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Batch Endpoint.": {
- "$ref": "./examples/Workspace/BatchEndpoint/createOrUpdate.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Registry Model Container.": {
+ "$ref": "./examples/Registry/ModelContainer/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}/deployments": {
- "get": {
- "tags": [
- "BatchDeployment"
- ],
- "summary": "Lists Batch inference deployments in the workspace.",
- "operationId": "BatchDeployments_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Endpoint name",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Top of list.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchDeploymentTrackedResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "ModelContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "RegistryModelContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Workspace Batch Deployment.": {
- "$ref": "./examples/Workspace/BatchDeployment/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Registry Model Container.": {
+ "$ref": "./examples/Registry/ModelContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}/deployments/{deploymentName}": {
- "delete": {
- "tags": [
- "BatchDeployment"
- ],
- "summary": "Delete Batch Inference deployment (asynchronous).",
- "operationId": "BatchDeployments_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Endpoint name",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "Inference deployment identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ "put": {
+ "tags": [
+ "ModelContainer"
+ ],
+ "summary": "Create or update model container.",
+ "operationId": "RegistryModelContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Workspace Batch Deployment.": {
- "$ref": "./examples/Workspace/BatchDeployment/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
- }
- },
- "get": {
- "tags": [
- "BatchDeployment"
- ],
- "summary": "Gets a batch inference deployment by id.",
- "operationId": "BatchDeployments_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Endpoint name",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "The identifier for the Batch deployments.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchDeploymentTrackedResource"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Workspace Batch Deployment.": {
- "$ref": "./examples/Workspace/BatchDeployment/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
}
- }
- },
- "patch": {
- "tags": [
- "BatchDeployment"
- ],
- "summary": "Update a batch inference deployment (asynchronous).",
- "operationId": "BatchDeployments_Update",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "The identifier for the Batch inference deployment.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
},
- {
- "in": "body",
- "name": "body",
- "description": "Batch inference deployment definition object.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchDeploymentTrackedResource"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Model Container.": {
+ "$ref": "./examples/Registry/ModelContainer/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions": {
+ "get": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "RegistryModelVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "in": "query",
+ "name": "version",
+ "description": "Version identifier.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "description",
+ "description": "Model description.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "properties",
+ "description": "Comma-separated list of property names (and optionally values). Example: prop1,prop2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
+ ]
}
- },
- "x-ms-examples": {
- "Update Workspace Batch Deployment.": {
- "$ref": "./examples/Workspace/BatchDeployment/update.json"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true
- },
- "put": {
- "tags": [
- "BatchDeployment"
- ],
- "summary": "Creates/updates a batch inference deployment (asynchronous).",
- "operationId": "BatchDeployments_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "The identifier for the Batch inference deployment.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Batch inference deployment definition object.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/BatchDeploymentTrackedResource"
- }
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResourceArmPaginatedResult"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/BatchDeploymentTrackedResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/BatchDeploymentTrackedResource"
+ }
+ },
+ "x-ms-examples": {
+ "List Registry Model Version.": {
+ "$ref": "./examples/Registry/ModelVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "RegistryModelVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
},
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Batch Deployment.": {
- "$ref": "./examples/Workspace/BatchDeployment/createOrUpdate.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Registry Model Version.": {
+ "$ref": "./examples/Registry/ModelVersion/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}/listkeys": {
- "post": {
- "tags": [
- "BatchEndpoint"
- ],
- "summary": "Lists batch Inference Endpoint keys.",
- "operationId": "BatchEndpoints_ListKeys",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EndpointAuthKeys"
- }
+ "get": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "RegistryModelVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "ListKeys Workspace Batch Endpoint.": {
- "$ref": "./examples/Workspace/BatchEndpoint/listKeys.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
}
}
+ },
+ "x-ms-examples": {
+ "Get Registry Model Version.": {
+ "$ref": "./examples/Registry/ModelVersion/get.json"
+ }
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes": {
- "get": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "List containers.",
- "operationId": "CodeContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ "put": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "RegistryModelVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeContainerResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Workspace Code Container.": {
- "$ref": "./examples/Workspace/CodeContainer/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}": {
- "delete": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "Delete container.",
- "operationId": "CodeContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
},
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
- },
- "x-ms-examples": {
- "Delete Workspace Code Container.": {
- "$ref": "./examples/Workspace/CodeContainer/delete.json"
}
}
},
- "get": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "Get container.",
- "operationId": "CodeContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
- }
- },
- "x-ms-examples": {
- "Get Workspace Code Container.": {
- "$ref": "./examples/Workspace/CodeContainer/get.json"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Registry Model Version.": {
+ "$ref": "./examples/Registry/ModelVersion/createOrUpdate.json"
}
},
- "put": {
- "tags": [
- "CodeContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "CodeContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/registries/{registryName}/models/{modelName}/versions/pendingUpload/{version}": {
+ "post": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "Generate a storage location and credential for the client to upload a model asset to.",
+ "operationId": "RegistryModelVersions_CreateOrGetPendingUpload",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "registryName",
+ "description": "Name of Azure Machine Learning registry.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "modelName",
+ "description": "Model name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Pending upload request object",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PendingUploadRequestDto"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/CodeContainerResource"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Code Container.": {
- "$ref": "./examples/Workspace/CodeContainer/createOrUpdate.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/PendingUploadResponseDto"
}
}
+ },
+ "x-ms-examples": {
+ "CreateOrGetPendingUpload Registry Model Version.": {
+ "$ref": "./examples/Registry/ModelVersion/createOrGetPendingUpload.json"
+ }
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions": {
- "get": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "List versions.",
- "operationId": "CodeVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeVersionResourceArmPaginatedResult"
- }
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints": {
+ "get": {
+ "tags": [
+ "BatchEndpoint"
+ ],
+ "summary": "Lists Batch inference endpoint in the workspace.",
+ "operationId": "BatchEndpoints_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List Workspace Code Version.": {
- "$ref": "./examples/Workspace/CodeVersion/list.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "count",
+ "description": "Number of endpoints to be retrieved in a page of results.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "Delete version.",
- "operationId": "CodeVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Workspace Code Version.": {
- "$ref": "./examples/Workspace/CodeVersion/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchEndpointTrackedResourceArmPaginatedResult"
}
}
},
- "get": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "Get version.",
- "operationId": "CodeVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- }
- }
- },
- "x-ms-examples": {
- "Get Workspace Code Version.": {
- "$ref": "./examples/Workspace/CodeVersion/get.json"
- }
+ "x-ms-examples": {
+ "List Workspace Batch Endpoint.": {
+ "$ref": "./examples/Workspace/BatchEndpoint/list.json"
}
},
- "put": {
- "tags": [
- "CodeVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "CodeVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- }
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}": {
+ "delete": {
+ "tags": [
+ "BatchEndpoint"
+ ],
+ "summary": "Delete Batch Inference Endpoint (asynchronous).",
+ "operationId": "BatchEndpoints_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference Endpoint name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/CodeVersionResource"
+ },
+ "200": {
+ "description": "Success"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Code Version.": {
- "$ref": "./examples/Workspace/CodeVersion/createOrUpdate.json"
- }
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Batch Endpoint.": {
+ "$ref": "./examples/Workspace/BatchEndpoint/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components": {
- "get": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "List component containers.",
- "operationId": "ComponentContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "BatchEndpoint"
+ ],
+ "summary": "Gets a batch inference endpoint by name.",
+ "operationId": "BatchEndpoints_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List Workspace Component Container.": {
- "$ref": "./examples/Workspace/ComponentContainer/list.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Name for the Batch Endpoint.",
+ "required": true,
+ "type": "string"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components/{name}": {
- "delete": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "Delete container.",
- "operationId": "ComponentContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Workspace Component Container.": {
- "$ref": "./examples/Workspace/ComponentContainer/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchEndpointTrackedResource"
}
}
},
- "get": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "Get container.",
- "operationId": "ComponentContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
- }
+ "x-ms-examples": {
+ "Get Workspace Batch Endpoint.": {
+ "$ref": "./examples/Workspace/BatchEndpoint/get.json"
+ }
+ }
+ },
+ "patch": {
+ "tags": [
+ "BatchEndpoint"
+ ],
+ "summary": "Update a batch inference endpoint (asynchronous).",
+ "operationId": "BatchEndpoints_Update",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Name for the Batch inference endpoint.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "x-ms-examples": {
- "Get Workspace Component Container.": {
- "$ref": "./examples/Workspace/ComponentContainer/get.json"
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Mutable batch inference endpoint definition object.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PartialMinimalTrackedResourceWithIdentity"
}
}
- },
- "put": {
- "tags": [
- "ComponentContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "ComponentContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchEndpointTrackedResource"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Component Container.": {
- "$ref": "./examples/Workspace/ComponentContainer/createOrUpdate.json"
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
}
}
- }
+ },
+ "x-ms-examples": {
+ "Update Workspace Batch Endpoint.": {
+ "$ref": "./examples/Workspace/BatchEndpoint/update.json"
+ }
+ },
+ "x-ms-long-running-operation": true
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components/{name}/versions": {
- "get": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "List component versions.",
- "operationId": "ComponentVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Component name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ "put": {
+ "tags": [
+ "BatchEndpoint"
+ ],
+ "summary": "Creates a batch inference endpoint (asynchronous).",
+ "operationId": "BatchEndpoints_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Name for the Batch inference endpoint.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Batch inference endpoint definition object.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/BatchEndpointTrackedResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Workspace Component Version.": {
- "$ref": "./examples/Workspace/ComponentVersion/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchEndpointTrackedResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "Delete version.",
- "operationId": "ComponentVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/BatchEndpointTrackedResource"
},
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
- },
- "x-ms-examples": {
- "Delete Workspace Component Version.": {
- "$ref": "./examples/Workspace/ComponentVersion/delete.json"
}
}
},
- "get": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "Get version.",
- "operationId": "ComponentVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
- }
- },
- "x-ms-examples": {
- "Get Workspace Component Version.": {
- "$ref": "./examples/Workspace/ComponentVersion/get.json"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Batch Endpoint.": {
+ "$ref": "./examples/Workspace/BatchEndpoint/createOrUpdate.json"
}
},
- "put": {
- "tags": [
- "ComponentVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "ComponentVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ComponentVersionResource"
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}/deployments": {
+ "get": {
+ "tags": [
+ "BatchDeployment"
+ ],
+ "summary": "Lists Batch inference deployments in the workspace.",
+ "operationId": "BatchDeployments_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Endpoint name",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Top of list.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Component Version.": {
- "$ref": "./examples/Workspace/ComponentVersion/createOrUpdate.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResourceArmPaginatedResult"
}
}
+ },
+ "x-ms-examples": {
+ "List Workspace Batch Deployment.": {
+ "$ref": "./examples/Workspace/BatchDeployment/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data": {
- "get": {
- "tags": [
- "DataContainer"
- ],
- "summary": "List data containers.",
- "operationId": "DataContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataContainerResourceArmPaginatedResult"
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}/deployments/{deploymentName}": {
+ "delete": {
+ "tags": [
+ "BatchDeployment"
+ ],
+ "summary": "Delete Batch Inference deployment (asynchronous).",
+ "operationId": "BatchDeployments_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Endpoint name",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "Inference deployment identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "List Workspace Data Container.": {
- "$ref": "./examples/Workspace/DataContainer/list.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Batch Deployment.": {
+ "$ref": "./examples/Workspace/BatchDeployment/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data/{name}": {
- "delete": {
- "tags": [
- "DataContainer"
- ],
- "summary": "Delete container.",
- "operationId": "DataContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ "get": {
+ "tags": [
+ "BatchDeployment"
+ ],
+ "summary": "Gets a batch inference deployment by id.",
+ "operationId": "BatchDeployments_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Endpoint name",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "The identifier for the Batch deployments.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Workspace Data Container.": {
- "$ref": "./examples/Workspace/DataContainer/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResource"
}
}
},
- "get": {
- "tags": [
- "DataContainer"
- ],
- "summary": "Get container.",
- "operationId": "DataContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
- }
+ "x-ms-examples": {
+ "Get Workspace Batch Deployment.": {
+ "$ref": "./examples/Workspace/BatchDeployment/get.json"
+ }
+ }
+ },
+ "patch": {
+ "tags": [
+ "BatchDeployment"
+ ],
+ "summary": "Update a batch inference deployment (asynchronous).",
+ "operationId": "BatchDeployments_Update",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "The identifier for the Batch inference deployment.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "x-ms-examples": {
- "Get Workspace Data Container.": {
- "$ref": "./examples/Workspace/DataContainer/get.json"
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Batch inference deployment definition object.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties"
}
}
- },
- "put": {
- "tags": [
- "DataContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "DataContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/DataContainerResource"
- }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResource"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Data Container.": {
- "$ref": "./examples/Workspace/DataContainer/createOrUpdate.json"
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
}
}
- }
+ },
+ "x-ms-examples": {
+ "Update Workspace Batch Deployment.": {
+ "$ref": "./examples/Workspace/BatchDeployment/update.json"
+ }
+ },
+ "x-ms-long-running-operation": true
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data/{name}/versions": {
- "get": {
- "tags": [
- "DataVersion"
- ],
- "summary": "List data versions in the data container",
- "operationId": "DataVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Data container's name",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Please choose OrderBy value from ['createdtime', 'modifiedtime']",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Top count of results, top count cannot be greater than the page size.\r\n If topCount > page size, results with be default page size count will be returned",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "$tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ "put": {
+ "tags": [
+ "BatchDeployment"
+ ],
+ "summary": "Creates/updates a batch inference deployment (asynchronous).",
+ "operationId": "BatchDeployments_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "The identifier for the Batch inference deployment.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Batch inference deployment definition object.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Workspace Data Version Base.": {
- "$ref": "./examples/Workspace/DataVersionBase/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "DataVersion"
- ],
- "summary": "Delete version.",
- "operationId": "DataVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResource"
},
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
- },
- "x-ms-examples": {
- "Delete Workspace Data Version Base.": {
- "$ref": "./examples/Workspace/DataVersionBase/delete.json"
}
}
},
- "get": {
- "tags": [
- "DataVersion"
- ],
- "summary": "Get version.",
- "operationId": "DataVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
- }
- },
- "x-ms-examples": {
- "Get Workspace Data Version Base.": {
- "$ref": "./examples/Workspace/DataVersionBase/get.json"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Batch Deployment.": {
+ "$ref": "./examples/Workspace/BatchDeployment/createOrUpdate.json"
}
},
- "put": {
- "tags": [
- "DataVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "DataVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/batchEndpoints/{endpointName}/listkeys": {
+ "post": {
+ "tags": [
+ "BatchEndpoint"
+ ],
+ "summary": "Lists batch Inference Endpoint keys.",
+ "operationId": "BatchEndpoints_ListKeys",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference Endpoint name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Data Version Base.": {
- "$ref": "./examples/Workspace/DataVersionBase/createOrUpdate.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EndpointAuthKeys"
}
}
+ },
+ "x-ms-examples": {
+ "ListKeys Workspace Batch Endpoint.": {
+ "$ref": "./examples/Workspace/BatchEndpoint/listKeys.json"
+ }
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores": {
- "get": {
- "tags": [
- "Datastore"
- ],
- "summary": "List datastores.",
- "operationId": "Datastores_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "count",
- "description": "Maximum number of results to return.",
- "type": "integer",
- "format": "int32",
- "default": 30
- },
- {
- "in": "query",
- "name": "isDefault",
- "description": "Filter down to the workspace default datastore.",
- "type": "boolean"
- },
- {
- "in": "query",
- "name": "names",
- "description": "Names of datastores to return.",
- "type": "array",
- "items": {
- "type": "string"
- }
- },
- {
- "in": "query",
- "name": "searchText",
- "description": "Text to search for in the datastore names.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "orderBy",
- "description": "Order by property (createdtime | modifiedtime | name).",
- "type": "string"
- },
- {
- "in": "query",
- "name": "orderByAsc",
- "description": "Order by property in ascending order.",
- "type": "boolean",
- "default": false
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DatastoreResourceArmPaginatedResult"
- }
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes": {
+ "get": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "List containers.",
+ "operationId": "CodeContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List datastores.": {
- "$ref": "./examples/Datastore/list.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores/{name}": {
- "delete": {
- "tags": [
- "Datastore"
- ],
- "summary": "Delete datastore.",
- "operationId": "Datastores_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Datastore name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete datastore.": {
- "$ref": "./examples/Datastore/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResourceArmPaginatedResult"
}
}
},
- "get": {
- "tags": [
- "Datastore"
- ],
- "summary": "Get datastore.",
- "operationId": "Datastores_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Datastore name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DatastoreResource"
- }
- }
- },
- "x-ms-examples": {
- "Get datastore.": {
- "$ref": "./examples/Datastore/get.json"
- }
+ "x-ms-examples": {
+ "List Workspace Code Container.": {
+ "$ref": "./examples/Workspace/CodeContainer/list.json"
}
},
- "put": {
- "tags": [
- "Datastore"
- ],
- "summary": "Create or update datastore.",
- "operationId": "Datastores_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Datastore name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "skipValidation",
- "description": "Flag to skip validation.",
- "type": "boolean",
- "default": false
- },
- {
- "in": "body",
- "name": "body",
- "description": "Datastore entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/DatastoreResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DatastoreResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/DatastoreResource"
- }
- }
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}": {
+ "delete": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "CodeContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "CreateOrUpdate datastore (AzureBlob w/ AccountKey).": {
- "$ref": "./examples/Datastore/AzureBlobWAccountKey/createOrUpdate.json"
- },
- "CreateOrUpdate datastore (Azure Data Lake Gen1 w/ ServicePrincipal).": {
- "$ref": "./examples/Datastore/AzureDataLakeGen1WServicePrincipal/createOrUpdate.json"
- },
- "CreateOrUpdate datastore (Azure Data Lake Gen2 w/ Service Principal).": {
- "$ref": "./examples/Datastore/AzureDataLakeGen2WServicePrincipal/createOrUpdate.json"
- },
- "CreateOrUpdate datastore (Azure File store w/ AccountKey).": {
- "$ref": "./examples/Datastore/AzureFileWAccountKey/createOrUpdate.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
+ },
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Code Container.": {
+ "$ref": "./examples/Workspace/CodeContainer/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores/{name}/listSecrets": {
- "post": {
- "tags": [
- "Datastore"
- ],
- "summary": "Get datastore secrets.",
- "operationId": "Datastores_ListSecrets",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Datastore name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "description": "Base definition for datastore secrets.",
- "$ref": "#/definitions/DatastoreSecrets"
- }
+ "get": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "CodeContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get datastore secrets.": {
- "$ref": "./examples/Datastore/listSecrets.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
}
}
+ },
+ "x-ms-examples": {
+ "Get Workspace Code Container.": {
+ "$ref": "./examples/Workspace/CodeContainer/get.json"
+ }
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments": {
- "get": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "List environment containers.",
- "operationId": "EnvironmentContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResourceArmPaginatedResult"
- }
- }
+ "put": {
+ "tags": [
+ "CodeContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "CodeContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List Workspace Environment Container.": {
- "$ref": "./examples/Workspace/EnvironmentContainer/list.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
+ }
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments/{name}": {
- "delete": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "Delete container.",
- "operationId": "EnvironmentContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
}
},
- "x-ms-examples": {
- "Delete Workspace Environment Container.": {
- "$ref": "./examples/Workspace/EnvironmentContainer/delete.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/CodeContainerResource"
}
}
},
- "get": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "Get container.",
- "operationId": "EnvironmentContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Code Container.": {
+ "$ref": "./examples/Workspace/CodeContainer/createOrUpdate.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions": {
+ "get": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "CodeVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "hash",
+ "description": "If specified, return CodeVersion assets with specified content hash value, regardless of name",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "hashVersion",
+ "description": "Hash algorithm version when listing by hash",
+ "type": "string"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Workspace Environment Container.": {
- "$ref": "./examples/Workspace/EnvironmentContainer/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "EnvironmentContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "EnvironmentContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
- }
+ "x-ms-examples": {
+ "List Workspace Code Version.": {
+ "$ref": "./examples/Workspace/CodeVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "CodeVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Environment Container.": {
- "$ref": "./examples/Workspace/EnvironmentContainer/createOrUpdate.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
+ },
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Code Version.": {
+ "$ref": "./examples/Workspace/CodeVersion/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments/{name}/versions": {
- "get": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "List versions.",
- "operationId": "EnvironmentVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "CodeVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Workspace Environment Version.": {
- "$ref": "./examples/Workspace/EnvironmentVersion/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Workspace Code Version.": {
+ "$ref": "./examples/Workspace/CodeVersion/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "Delete version.",
- "operationId": "EnvironmentVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "put": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "CodeVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
}
},
- "x-ms-examples": {
- "Delete Workspace Environment Version.": {
- "$ref": "./examples/Workspace/EnvironmentVersion/delete.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/CodeVersionResource"
}
}
},
- "get": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "Get version.",
- "operationId": "EnvironmentVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Code Version.": {
+ "$ref": "./examples/Workspace/CodeVersion/createOrUpdate.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/codes/{name}/versions/pendingUpload/{version}": {
+ "post": {
+ "tags": [
+ "CodeVersion"
+ ],
+ "summary": "Generate a storage location and credential for the client to upload a code asset to.",
+ "operationId": "CodeVersions_CreateOrGetPendingUpload",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Pending upload request object",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PendingUploadRequestDto"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Workspace Environment Version.": {
- "$ref": "./examples/Workspace/EnvironmentVersion/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/PendingUploadResponseDto"
}
}
},
- "put": {
- "tags": [
- "EnvironmentVersion"
- ],
- "summary": "Creates or updates an EnvironmentVersion.",
- "operationId": "EnvironmentVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Name of EnvironmentVersion. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version of EnvironmentVersion.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Definition of EnvironmentVersion.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- }
+ "x-ms-examples": {
+ "CreateOrGetPendingUpload Workspace Code Version.": {
+ "$ref": "./examples/Workspace/CodeVersion/createOrGetPendingUpload.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components": {
+ "get": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "List component containers.",
+ "operationId": "ComponentContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/EnvironmentVersionResource"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Environment Version.": {
- "$ref": "./examples/Workspace/EnvironmentVersion/createOrUpdate.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResourceArmPaginatedResult"
}
}
+ },
+ "x-ms-examples": {
+ "List Workspace Component Container.": {
+ "$ref": "./examples/Workspace/ComponentContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets": {
- "get": {
- "tags": [
- "FeaturesetContainer"
- ],
- "summary": "List featurestore entity containers.",
- "operationId": "FeaturesetContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetContainerResourceArmPaginatedResult"
- }
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components/{name}": {
+ "delete": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "ComponentContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "x-ms-examples": {
- "List Workspace Featureset Container.": {
- "$ref": "./examples/Workspace/FeaturesetContainer/list.json"
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Component Container.": {
+ "$ref": "./examples/Workspace/ComponentContainer/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}": {
- "delete": {
- "tags": [
- "FeaturesetContainer"
- ],
- "summary": "Delete container.",
- "operationId": "FeaturesetContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "204": {
- "description": "No Content"
- }
+ "get": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "ComponentContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Workspace Featureset Container.": {
- "$ref": "./examples/Workspace/FeaturesetContainer/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "get": {
- "tags": [
- "FeaturesetContainer"
- ],
- "summary": "Get container.",
- "operationId": "FeaturesetContainers_GetEntity",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetContainerResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "GetEntity Workspace Featureset Container.": {
- "$ref": "./examples/Workspace/FeaturesetContainer/getEntity.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
}
}
},
- "put": {
- "tags": [
- "FeaturesetContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "FeaturesetContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/FeaturesetContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/FeaturesetContainerResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Workspace Featureset Container.": {
- "$ref": "./examples/Workspace/FeaturesetContainer/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "azure-async-operation"
+ "x-ms-examples": {
+ "Get Workspace Component Container.": {
+ "$ref": "./examples/Workspace/ComponentContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions": {
- "get": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "List versions.",
- "operationId": "FeaturesetVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Featureset name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ "put": {
+ "tags": [
+ "ComponentContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "ComponentContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ComponentContainerResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Component Container.": {
+ "$ref": "./examples/Workspace/ComponentContainer/createOrUpdate.json"
}
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "Delete version.",
- "operationId": "FeaturesetVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components/{name}/versions": {
+ "get": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "List component versions.",
+ "operationId": "ComponentVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Component name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "stage",
+ "description": "Component stage.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
- },
- "204": {
- "description": "No Content"
+ ]
}
- },
- "x-ms-examples": {
- "Delete Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/delete.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
}
- },
- "get": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "Get version.",
- "operationId": "FeaturesetVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "FeaturesetVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "azure-async-operation"
+ "x-ms-examples": {
+ "List Workspace Component Version.": {
+ "$ref": "./examples/Workspace/ComponentVersion/list.json"
}
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/backfill": {
- "post": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "Backfill.",
- "operationId": "FeaturesetVersions_Backfill",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Feature set version backfill request entity.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionBackfillRequest"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetVersionBackfillResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/components/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "ComponentVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Backfill Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/backfill.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/getFeature": {
- "post": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "Get feature.",
- "operationId": "FeaturesetVersions_GetFeature",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Feature set name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Feature set version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Feature Name request. This is case-sensitive.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/GetFeatureRequest"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/Feature"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "GetFeature Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/getFeature.json"
- }
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Component Version.": {
+ "$ref": "./examples/Workspace/ComponentVersion/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/listFeatures": {
- "post": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "List Features.",
- "operationId": "FeaturesetVersions_ListFeatures",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Featureset name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Featureset Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "$tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeatureArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "ComponentVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "ListFeatures Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/listFeatures.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/listMaterializationJobs": {
- "post": {
- "tags": [
- "FeaturesetVersion"
- ],
- "summary": "List materialization Jobs.",
- "operationId": "FeaturesetVersions_ListMaterializationJobs",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "filters",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "featureWindowStart",
- "description": "Start time of the feature window to filter materialization jobs.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "featureWindowEnd",
- "description": "End time of the feature window to filter materialization jobs.",
- "type": "string"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturesetJobArmPaginatedResult"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "ListMaterializationJobs Workspace Featureset Version.": {
- "$ref": "./examples/Workspace/FeaturesetVersion/listMaterializationJobs.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
}
- },
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ }
+ },
+ "x-ms-examples": {
+ "Get Workspace Component Version.": {
+ "$ref": "./examples/Workspace/ComponentVersion/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities": {
- "get": {
- "tags": [
- "FeaturestoreEntityContainer"
- ],
- "summary": "List featurestore entity containers.",
- "operationId": "FeaturestoreEntityContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ "put": {
+ "tags": [
+ "ComponentVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "ComponentVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityContainerResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Workspace Featurestore Entity Container.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityContainer/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ComponentVersionResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Component Version.": {
+ "$ref": "./examples/Workspace/ComponentVersion/createOrUpdate.json"
}
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities/{name}": {
- "delete": {
- "tags": [
- "FeaturestoreEntityContainer"
- ],
- "summary": "Delete container.",
- "operationId": "FeaturestoreEntityContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data": {
+ "get": {
+ "tags": [
+ "DataContainer"
+ ],
+ "summary": "List data containers.",
+ "operationId": "DataContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
- },
- "204": {
- "description": "No Content"
+ ]
}
- },
- "x-ms-examples": {
- "Delete Workspace Featurestore Entity Container.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityContainer/delete.json"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DataContainerResourceArmPaginatedResult"
+ }
}
},
- "get": {
- "tags": [
- "FeaturestoreEntityContainer"
- ],
- "summary": "Get container.",
- "operationId": "FeaturestoreEntityContainers_GetEntity",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityContainerResource"
- }
- }
+ "x-ms-examples": {
+ "List Workspace Data Container.": {
+ "$ref": "./examples/Workspace/DataContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data/{name}": {
+ "delete": {
+ "tags": [
+ "DataContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "DataContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "GetEntity Workspace Featurestore Entity Container.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityContainer/getEntity.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
+ },
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
}
},
- "put": {
- "tags": [
- "FeaturestoreEntityContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "FeaturestoreEntityContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityContainerResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Workspace Featurestore Entity Container.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityContainer/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "azure-async-operation"
+ "x-ms-examples": {
+ "Delete Workspace Data Container.": {
+ "$ref": "./examples/Workspace/DataContainer/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities/{name}/versions": {
- "get": {
- "tags": [
- "FeaturestoreEntityVersion"
- ],
- "summary": "List versions.",
- "operationId": "FeaturestoreEntityVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Feature entity name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityVersionResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "DataContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "DataContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List Workspace Featurestore Entity Version.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityVersion/list.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "FeaturestoreEntityVersion"
- ],
- "summary": "Delete version.",
- "operationId": "FeaturestoreEntityVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "204": {
- "description": "No Content"
- }
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "x-ms-examples": {
- "Delete Workspace Featurestore Entity Version.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityVersion/delete.json"
- }
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "get": {
- "tags": [
- "FeaturestoreEntityVersion"
- ],
- "summary": "Get version.",
- "operationId": "FeaturestoreEntityVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityVersionResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Workspace Featurestore Entity Version.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityVersion/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DataContainerResource"
}
}
},
- "put": {
- "tags": [
- "FeaturestoreEntityVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "FeaturestoreEntityVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityVersionResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/FeaturestoreEntityVersionResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Workspace Featurestore Entity Version.": {
- "$ref": "./examples/Workspace/FeaturestoreEntityVersion/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "azure-async-operation"
+ "x-ms-examples": {
+ "Get Workspace Data Container.": {
+ "$ref": "./examples/Workspace/DataContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs": {
- "get": {
- "tags": [
- "Job"
- ],
- "summary": "Lists Jobs in the workspace.",
- "operationId": "Jobs_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "jobType",
- "description": "Type of job to be returned.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "tag",
- "description": "Jobs returned will have this tag key.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- },
- {
- "in": "query",
- "name": "assetName",
- "description": "Asset name the job's named output is registered with",
- "type": "string"
- },
- {
- "in": "query",
- "name": "scheduled",
- "description": "Indicator whether the job is scheduled job.",
- "type": "boolean"
- },
- {
- "in": "query",
- "name": "scheduleId",
- "description": "The scheduled id for listing the job triggered from",
- "type": "string"
+ "put": {
+ "tags": [
+ "DataContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "DataContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/DataContainerResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/JobBaseResourceArmPaginatedResult"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Command Job.": {
- "$ref": "./examples/Job/CommandJob/list.json"
- },
- "List AutoML Job.": {
- "$ref": "./examples/Job/AutoMLJob/list.json"
- },
- "List Sweep Job.": {
- "$ref": "./examples/Job/SweepJob/list.json"
- },
- "List Pipeline Job.": {
- "$ref": "./examples/Job/PipelineJob/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DataContainerResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/DataContainerResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Data Container.": {
+ "$ref": "./examples/Workspace/DataContainer/createOrUpdate.json"
}
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}": {
- "delete": {
- "tags": [
- "Job"
- ],
- "summary": "Deletes a Job (asynchronous).",
- "operationId": "Jobs_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the Job. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data/{name}/versions": {
+ "get": {
+ "tags": [
+ "DataVersion"
+ ],
+ "summary": "List data versions in the data container",
+ "operationId": "DataVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Data container's name",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Please choose OrderBy value from ['createdtime', 'modifiedtime']",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Top count of results, top count cannot be greater than the page size.\r\n If topCount > page size, results with be default page size count will be returned",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "$tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "stage",
+ "description": "data stage",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
- },
- "204": {
- "description": "No Content"
- }
- },
- "x-ms-examples": {
- "Delete Job.": {
- "$ref": "./examples/Job/delete.json"
+ ]
}
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
}
- },
- "get": {
- "tags": [
- "Job"
- ],
- "summary": "Gets a Job by name/id.",
- "operationId": "Jobs_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the Job. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/JobBaseResource"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Command Job.": {
- "$ref": "./examples/Job/CommandJob/get.json"
- },
- "Get AutoML Job.": {
- "$ref": "./examples/Job/AutoMLJob/get.json"
- },
- "Get Sweep Job.": {
- "$ref": "./examples/Job/SweepJob/get.json"
- },
- "Get Pipeline Job.": {
- "$ref": "./examples/Job/PipelineJob/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DataVersionBaseResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "Job"
- ],
- "summary": "Creates and executes a Job.",
- "operationId": "Jobs_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the Job. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Job definition object.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/JobBaseResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/JobBaseResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/JobBaseResource"
- }
- }
- },
- "x-ms-examples": {
- "CreateOrUpdate Command Job.": {
- "$ref": "./examples/Job/CommandJob/createOrUpdate.json"
- },
- "CreateOrUpdate AutoML Job.": {
- "$ref": "./examples/Job/AutoMLJob/createOrUpdate.json"
- },
- "CreateOrUpdate Sweep Job.": {
- "$ref": "./examples/Job/SweepJob/createOrUpdate.json"
- },
- "CreateOrUpdate Pipeline Job.": {
- "$ref": "./examples/Job/PipelineJob/createOrUpdate.json"
- }
+ "x-ms-examples": {
+ "List Workspace Data Version Base.": {
+ "$ref": "./examples/Workspace/DataVersionBase/list.json"
}
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}/cancel": {
- "post": {
- "tags": [
- "Job"
- ],
- "summary": "Cancels a Job (asynchronous).",
- "operationId": "Jobs_Cancel",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the Job. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/data/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "DataVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "DataVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "Cancel Job.": {
- "$ref": "./examples/Job/cancel.json"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Data Version Base.": {
+ "$ref": "./examples/Workspace/DataVersionBase/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs": {
- "get": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Lists labeling jobs in the workspace.",
- "operationId": "LabelingJobs_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Number of labeling jobs to return.",
- "type": "integer",
- "format": "int32"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/LabelingJobResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "DataVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "DataVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Labeling Job.": {
- "$ref": "./examples/LabelingJob/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DataVersionBaseResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Workspace Data Version Base.": {
+ "$ref": "./examples/Workspace/DataVersionBase/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}": {
- "delete": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Delete a labeling job.",
- "operationId": "LabelingJobs_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the LabelingJob.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "put": {
+ "tags": [
+ "DataVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "DataVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/DataVersionBaseResource"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DataVersionBaseResource"
}
},
- "x-ms-examples": {
- "Delete Labeling Job.": {
- "$ref": "./examples/LabelingJob/delete.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/DataVersionBaseResource"
}
}
},
- "get": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Gets a labeling job by name/id.",
- "operationId": "LabelingJobs_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the LabelingJob.",
- "required": true,
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Data Version Base.": {
+ "$ref": "./examples/Workspace/DataVersionBase/createOrUpdate.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores": {
+ "get": {
+ "tags": [
+ "Datastore"
+ ],
+ "summary": "List datastores.",
+ "operationId": "Datastores_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "count",
+ "description": "Maximum number of results to return.",
+ "type": "integer",
+ "format": "int32",
+ "default": 30
+ },
+ {
+ "in": "query",
+ "name": "isDefault",
+ "description": "Filter down to the workspace default datastore.",
+ "type": "boolean"
+ },
+ {
+ "in": "query",
+ "name": "names",
+ "description": "Names of datastores to return.",
+ "type": "array",
+ "items": {
"type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "includeJobInstructions",
- "description": "Boolean value to indicate whether to include JobInstructions in response.",
- "type": "boolean",
- "default": false
- },
- {
- "in": "query",
- "name": "includeLabelCategories",
- "description": "Boolean value to indicate Whether to include LabelCategories in response.",
- "type": "boolean",
- "default": false
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/LabelingJobResource"
- }
+ },
+ {
+ "in": "query",
+ "name": "searchText",
+ "description": "Text to search for in the datastore names.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "orderBy",
+ "description": "Order by property (createdtime | modifiedtime | name).",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "orderByAsc",
+ "description": "Order by property in ascending order.",
+ "type": "boolean",
+ "default": false
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Labeling Job.": {
- "$ref": "./examples/LabelingJob/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DatastoreResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Creates or updates a labeling job (asynchronous).",
- "operationId": "LabelingJobs_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the LabelingJob.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "LabelingJob definition object.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/LabelingJobResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/LabelingJobResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/LabelingJobResource"
- }
- }
+ "x-ms-examples": {
+ "List datastores.": {
+ "$ref": "./examples/Datastore/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores/{name}": {
+ "delete": {
+ "tags": [
+ "Datastore"
+ ],
+ "summary": "Delete datastore.",
+ "operationId": "Datastores_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "CreateOrUpdate Labeling Job.": {
- "$ref": "./examples/LabelingJob/createOrUpdate.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Datastore name.",
+ "required": true,
+ "type": "string"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}/exportLabels": {
- "post": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Export labels from a labeling job (asynchronous).",
- "operationId": "LabelingJobs_ExportLabels",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the LabelingJob.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "The export summary.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ExportSummary"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ExportSummary"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "ExportLabels Labeling Job.": {
- "$ref": "./examples/LabelingJob/exportLabels.json"
- }
+ "200": {
+ "description": "Success"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete datastore.": {
+ "$ref": "./examples/Datastore/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}/pause": {
- "post": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Pause a labeling job.",
- "operationId": "LabelingJobs_Pause",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the LabelingJob.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
+ "get": {
+ "tags": [
+ "Datastore"
+ ],
+ "summary": "Get datastore.",
+ "operationId": "Datastores_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Datastore name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Pause Labeling Job.": {
- "$ref": "./examples/LabelingJob/pause.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DatastoreResource"
}
}
+ },
+ "x-ms-examples": {
+ "Get datastore.": {
+ "$ref": "./examples/Datastore/get.json"
+ }
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}/resume": {
- "post": {
- "tags": [
- "LabelingJob"
- ],
- "summary": "Resume a labeling job (asynchronous).",
- "operationId": "LabelingJobs_Resume",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "id",
- "description": "The name and identifier for the LabelingJob.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- }
+ "put": {
+ "tags": [
+ "Datastore"
+ ],
+ "summary": "Create or update datastore.",
+ "operationId": "Datastores_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Resume Labeling Job.": {
- "$ref": "./examples/LabelingJob/resume.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Datastore name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "skipValidation",
+ "description": "Flag to skip validation.",
+ "type": "boolean",
+ "default": false
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Datastore entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/DatastoreResource"
+ }
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models": {
- "get": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "List model containers.",
- "operationId": "ModelContainers_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "count",
- "description": "Maximum number of results to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelContainerResourceArmPaginatedResult"
- }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DatastoreResource"
}
},
- "x-ms-examples": {
- "List Workspace Model Container.": {
- "$ref": "./examples/Workspace/ModelContainer/list.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/DatastoreResource"
}
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate datastore (AzureBlob w/ AccountKey).": {
+ "$ref": "./examples/Datastore/AzureBlobWAccountKey/createOrUpdate.json"
+ },
+ "CreateOrUpdate datastore (Azure Data Lake Gen1 w/ ServicePrincipal).": {
+ "$ref": "./examples/Datastore/AzureDataLakeGen1WServicePrincipal/createOrUpdate.json"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "CreateOrUpdate datastore (Azure Data Lake Gen2 w/ Service Principal).": {
+ "$ref": "./examples/Datastore/AzureDataLakeGen2WServicePrincipal/createOrUpdate.json"
+ },
+ "CreateOrUpdate datastore (Azure File store w/ AccountKey).": {
+ "$ref": "./examples/Datastore/AzureFileWAccountKey/createOrUpdate.json"
}
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}": {
- "delete": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "Delete container.",
- "operationId": "ModelContainers_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datastores/{name}/listSecrets": {
+ "post": {
+ "tags": [
+ "Datastore"
+ ],
+ "summary": "Get datastore secrets.",
+ "operationId": "Datastores_ListSecrets",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Datastore name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Delete Workspace Model Container.": {
- "$ref": "./examples/Workspace/ModelContainer/delete.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "description": "Base definition for datastore secrets.",
+ "$ref": "#/definitions/DatastoreSecrets"
}
}
},
- "get": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "Get container.",
- "operationId": "ModelContainers_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ "x-ms-examples": {
+ "Get datastore secrets.": {
+ "$ref": "./examples/Datastore/listSecrets.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments": {
+ "get": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "List environment containers.",
+ "operationId": "EnvironmentContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "Get Workspace Model Container.": {
- "$ref": "./examples/Workspace/ModelContainer/get.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResourceArmPaginatedResult"
}
}
},
- "put": {
- "tags": [
- "ModelContainer"
- ],
- "summary": "Create or update container.",
- "operationId": "ModelContainers_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Container entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ModelContainerResource"
- }
- }
+ "x-ms-examples": {
+ "List Workspace Environment Container.": {
+ "$ref": "./examples/Workspace/EnvironmentContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments/{name}": {
+ "delete": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "EnvironmentContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Model Container.": {
- "$ref": "./examples/Workspace/ModelContainer/createOrUpdate.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
+ },
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Environment Container.": {
+ "$ref": "./examples/Workspace/EnvironmentContainer/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}/versions": {
- "get": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "List model versions.",
- "operationId": "ModelVersions_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Model name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Maximum number of records to return.",
- "type": "integer",
- "format": "int32"
- },
- {
- "in": "query",
- "name": "version",
- "description": "Model version.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "description",
- "description": "Model description.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "offset",
- "description": "Number of initial results to skip.",
- "type": "integer",
- "format": "int32"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "properties",
- "description": "Comma-separated list of property names (and optionally values). Example: prop1,prop2=value2",
- "type": "string"
- },
- {
- "in": "query",
- "name": "feed",
- "description": "Name of the feed.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "View type for including/excluding (for example) archived entities.",
- "type": "string",
- "default": "ActiveOnly",
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelVersionResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "EnvironmentContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "List Workspace Model Version.": {
- "$ref": "./examples/Workspace/ModelVersion/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Workspace Environment Container.": {
+ "$ref": "./examples/Workspace/EnvironmentContainer/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}/versions/{version}": {
- "delete": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Delete version.",
- "operationId": "ModelVersions_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- }
+ "put": {
+ "tags": [
+ "EnvironmentContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "EnvironmentContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "x-ms-examples": {
- "Delete Workspace Model Version.": {
- "$ref": "./examples/Workspace/ModelVersion/delete.json"
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
}
- },
- "get": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Get version.",
- "operationId": "ModelVersions_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
},
- "x-ms-examples": {
- "Get Workspace Model Version.": {
- "$ref": "./examples/Workspace/ModelVersion/get.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
}
},
- "put": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Create or update version.",
- "operationId": "ModelVersions_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Version entity to create or update.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Environment Container.": {
+ "$ref": "./examples/Workspace/EnvironmentContainer/createOrUpdate.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments/{name}/versions": {
+ "get": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "EnvironmentVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ModelVersionResource"
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Model Version.": {
- "$ref": "./examples/Workspace/ModelVersion/createOrUpdate.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResourceArmPaginatedResult"
}
}
+ },
+ "x-ms-examples": {
+ "List Workspace Environment Version.": {
+ "$ref": "./examples/Workspace/EnvironmentVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
}
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}/versions/{version}/package": {
- "post": {
- "tags": [
- "ModelVersion"
- ],
- "summary": "Model Version Package operation.",
- "operationId": "ModelVersions_Package",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Container name. This is case-sensitive.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "version",
- "description": "Version identifier. This is case-sensitive.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Package operation request body.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/PackageRequest"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/PackageResponse"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/environments/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "EnvironmentVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "Package Workspace Model Version.": {
- "$ref": "./examples/Workspace/ModelVersion/package.json"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Environment Version.": {
+ "$ref": "./examples/Workspace/EnvironmentVersion/delete.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints": {
- "get": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "List Online Endpoints.",
- "operationId": "OnlineEndpoints_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "name",
- "description": "Name of the endpoint.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "count",
- "description": "Number of endpoints to be retrieved in a page of results.",
- "type": "integer",
- "format": "int32"
- },
- {
- "in": "query",
- "name": "computeType",
- "description": "EndpointComputeType to be filtered by.",
- "type": "string",
- "enum": [
- "Managed",
- "Kubernetes",
- "AzureMLCompute"
- ],
- "x-ms-enum": {
- "name": "EndpointComputeType",
- "modelAsString": true
- }
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "tags",
- "description": "A set of tags with which to filter the returned models. It is a comma separated string of tags key or tags key=value. Example: tagKey1,tagKey2,tagKey3=value3 .",
- "type": "string"
- },
- {
- "in": "query",
- "name": "properties",
- "description": "A set of properties with which to filter the returned models. It is a comma separated string of properties key and/or properties key=value Example: propKey1,propKey2,propKey3=value3 .",
- "type": "string"
- },
- {
- "in": "query",
- "name": "orderBy",
- "description": "The option to order the response.",
- "type": "string",
- "enum": [
- "CreatedAtDesc",
- "CreatedAtAsc",
- "UpdatedAtDesc",
- "UpdatedAtAsc"
- ],
- "x-ms-enum": {
- "name": "OrderString",
- "modelAsString": true
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineEndpointTrackedResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "EnvironmentVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "x-ms-examples": {
- "List Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/list.json"
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Workspace Environment Version.": {
+ "$ref": "./examples/Workspace/EnvironmentVersion/get.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}": {
- "delete": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "Delete Online Endpoint (asynchronous).",
- "operationId": "OnlineEndpoints_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "204": {
- "description": "No Content"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- },
- "200": {
- "description": "Success"
- }
+ "put": {
+ "tags": [
+ "EnvironmentVersion"
+ ],
+ "summary": "Creates or updates an EnvironmentVersion.",
+ "operationId": "EnvironmentVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Name of EnvironmentVersion. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version of EnvironmentVersion.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Definition of EnvironmentVersion.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
+ }
}
- },
- "get": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "Get Online Endpoint.",
- "operationId": "OnlineEndpoints_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineEndpointTrackedResource"
- }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
}
},
- "x-ms-examples": {
- "Get Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/get.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
}
}
},
- "patch": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "Update Online Endpoint (asynchronous).",
- "operationId": "OnlineEndpoints_Update",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Online Endpoint entity to apply during operation.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/PartialMinimalTrackedResourceWithIdentity"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineEndpointTrackedResource"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Environment Version.": {
+ "$ref": "./examples/Workspace/EnvironmentVersion/createOrUpdate.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets": {
+ "get": {
+ "tags": [
+ "FeaturesetContainer"
+ ],
+ "summary": "List featurestore entity containers.",
+ "operationId": "FeaturesetContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
+ ]
}
},
- "x-ms-examples": {
- "Update Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/update.json"
+ {
+ "in": "query",
+ "name": "pageSize",
+ "description": "page size",
+ "type": "integer",
+ "format": "int32",
+ "default": 20
+ },
+ {
+ "in": "query",
+ "name": "name",
+ "description": "name for the featureset",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "description",
+ "description": "description for the feature set",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "createdBy",
+ "description": "createdBy user name",
+ "type": "string"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetContainerResourceArmPaginatedResult"
+ }
+ }
},
- "put": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "Create or update Online Endpoint (asynchronous).",
- "operationId": "OnlineEndpoints_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Online Endpoint entity to apply during operation.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/OnlineEndpointTrackedResource"
- }
+ "x-ms-examples": {
+ "List Workspace Featureset Container.": {
+ "$ref": "./examples/Workspace/FeaturesetContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}": {
+ "delete": {
+ "tags": [
+ "FeaturesetContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "FeaturesetContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineEndpointTrackedResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/OnlineEndpointTrackedResource"
+ },
+ "200": {
+ "description": "Success"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
},
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Workspace Featureset Container.": {
+ "$ref": "./examples/Workspace/FeaturesetContainer/delete.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments": {
- "get": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "List Inference Endpoint Deployments.",
- "operationId": "OnlineDeployments_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "$orderBy",
- "description": "Ordering of list.",
- "type": "string"
- },
- {
- "in": "query",
- "name": "$top",
- "description": "Top of list.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResourceArmPaginatedResult"
- }
- }
+ "get": {
+ "tags": [
+ "FeaturesetContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "FeaturesetContainers_GetEntity",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-examples": {
- "List Online Deployments.": {
- "$ref": "./examples/OnlineDeployment/list.json"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetContainerResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "GetEntity Workspace Featureset Container.": {
+ "$ref": "./examples/Workspace/FeaturesetContainer/getEntity.json"
}
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}": {
- "delete": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "Delete Inference Endpoint Deployment (asynchronous).",
- "operationId": "OnlineDeployments_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "Inference Endpoint Deployment name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "204": {
- "description": "No Content"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- }
+ "put": {
+ "tags": [
+ "FeaturesetContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "FeaturesetContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Delete Workspace Online Deployment.": {
- "$ref": "./examples/Workspace/OnlineDeployment/delete.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/FeaturesetContainerResource"
+ }
}
- },
- "get": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "Get Inference Deployment Deployment.",
- "operationId": "OnlineDeployments_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "Inference Endpoint Deployment name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResource"
- }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetContainerResource"
}
},
- "x-ms-examples": {
- "Get Managed Online Deployment.": {
- "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/get.json"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetContainerResource"
},
- "Get Kubernetes Online Deployment.": {
- "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/get.json"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
}
}
},
- "patch": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "Update Online Deployment (asynchronous).",
- "operationId": "OnlineDeployments_Update",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "Inference Endpoint Deployment name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Online Endpoint entity to apply during operation.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/PartialMinimalTrackedResourceWithSku"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResource"
- }
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Featureset Container.": {
+ "$ref": "./examples/Workspace/FeaturesetContainer/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions": {
+ "get": {
+ "tags": [
+ "FeaturesetVersion"
+ ],
+ "summary": "List versions.",
+ "operationId": "FeaturesetVersions_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Featureset name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
+ {
+ "value": "All"
}
- }
+ ]
}
},
- "x-ms-examples": {
- "Update Managed Online Deployment.": {
- "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/update.json"
- },
- "Update Kubernetes Online Deployment.": {
- "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/update.json"
+ {
+ "in": "query",
+ "name": "pageSize",
+ "description": "page size",
+ "type": "integer",
+ "format": "int32",
+ "default": 20
+ },
+ {
+ "in": "query",
+ "name": "versionName",
+ "description": "name for the featureset version",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "version",
+ "description": "featureset version",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "description",
+ "description": "description for the feature set version",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "createdBy",
+ "description": "createdBy user name",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "stage",
+ "description": "stage",
+ "type": "string"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-long-running-operation": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetVersionResourceArmPaginatedResult"
+ }
+ }
},
- "put": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "Create or update Inference Endpoint Deployment (asynchronous).",
- "operationId": "OnlineDeployments_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "Inference Endpoint Deployment name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Inference Endpoint entity to apply during operation.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResource"
- }
+ "x-ms-examples": {
+ "List Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "FeaturesetVersion"
+ ],
+ "summary": "Delete version.",
+ "operationId": "FeaturesetVersions_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResource"
+ },
+ "200": {
+ "description": "Success"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
},
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
}
}
},
- "x-ms-examples": {
- "CreateOrUpdate Managed Online Deployment.": {
- "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/createOrUpdate.json"
- },
- "CreateOrUpdate Kubernetes Online Deployment.": {
- "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/createOrUpdate.json"
- }
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "204": {
+ "description": "No Content"
}
+ },
+ "x-ms-examples": {
+ "Delete Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/delete.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}/getLogs": {
- "post": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "Polls an Endpoint operation.",
- "operationId": "OnlineDeployments_GetLogs",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "The name and identifier for the endpoint.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "The request containing parameters for retrieving logs.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/DeploymentLogsRequest"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/DeploymentLogs"
- }
- }
+ "get": {
+ "tags": [
+ "FeaturesetVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "FeaturesetVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "Get Online Deployment Logs.": {
- "$ref": "./examples/OnlineDeployment/getLogs.json"
- }
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}/skus": {
- "get": {
- "tags": [
- "OnlineDeployment"
- ],
- "summary": "List Inference Endpoint Deployment Skus.",
- "operationId": "OnlineDeployments_ListSkus",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Inference endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "in": "path",
- "name": "deploymentName",
- "description": "Inference Endpoint Deployment name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "query",
- "name": "count",
- "description": "Number of Skus to be retrieved in a page of results.",
- "type": "integer",
- "format": "int32"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/SkuResourceArmPaginatedResult"
- }
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-examples": {
- "List Managed Online Deployment Skus.": {
- "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/listSkus.json"
- },
- "List Kubernetes Online Deployment Skus.": {
- "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/listSkus.json"
- }
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/listKeys": {
- "post": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "List EndpointAuthKeys for an Endpoint using Key-based authentication.",
- "operationId": "OnlineEndpoints_ListKeys",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EndpointAuthKeys"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "ListKeys Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/listKeys.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetVersionResource"
}
}
+ },
+ "x-ms-examples": {
+ "Get Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/get.json"
+ }
}
},
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/regenerateKeys": {
- "post": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "Regenerate EndpointAuthKeys for an Endpoint using Key-based authentication (asynchronous).",
- "operationId": "OnlineEndpoints_RegenerateKeys",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "RegenerateKeys request .",
- "required": true,
- "schema": {
- "$ref": "#/definitions/RegenerateEndpointKeysRequest"
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
- },
- "202": {
- "description": "Accepted",
- "headers": {
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
- }
- }
+ "put": {
+ "tags": [
+ "FeaturesetVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "FeaturesetVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "x-ms-examples": {
- "RegenerateKeys Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/regenerateKeys.json"
- }
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/token": {
- "post": {
- "tags": [
- "OnlineEndpoint"
- ],
- "summary": "Retrieve a valid AAD token for an Endpoint using AMLToken-based authentication.",
- "operationId": "OnlineEndpoints_GetToken",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "endpointName",
- "description": "Online Endpoint name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/EndpointAuthToken"
- }
- }
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "x-ms-examples": {
- "GetToken Workspace Online Endpoint.": {
- "$ref": "./examples/Workspace/OnlineEndpoint/getToken.json"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/FeaturesetVersionResource"
}
}
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/schedules": {
- "get": {
- "tags": [
- "Schedule"
- ],
- "summary": "List schedules in specified workspace.",
- "operationId": "Schedules_List",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
- },
- {
- "in": "query",
- "name": "listViewType",
- "description": "Status filter for schedule.",
- "type": "string",
- "default": "EnabledOnly",
- "enum": [
- "EnabledOnly",
- "DisabledOnly",
- "All"
- ],
- "x-ms-enum": {
- "name": "ScheduleListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "EnabledOnly"
- },
- {
- "value": "DisabledOnly"
- },
- {
- "value": "All"
- }
- ]
- }
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ScheduleResourceArmPaginatedResult"
- }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "List Schedules.": {
- "$ref": "./examples/Schedule/list.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetVersionResource"
}
},
- "x-ms-pageable": {
- "nextLinkName": "nextLink"
- }
- }
- },
- "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/schedules/{name}": {
- "delete": {
- "tags": [
- "Schedule"
- ],
- "summary": "Delete schedule.",
- "operationId": "Schedules_Delete",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Schedule name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success"
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetVersionResource"
},
- "202": {
- "description": "Accepted",
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Location": {
- "description": "URI to poll for asynchronous operation result.",
- "type": "string"
- },
- "Retry-After": {
- "description": "Duration the client should wait between requests, in seconds.",
- "type": "integer",
- "format": "int32",
- "maximum": 600,
- "minimum": 10
- }
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
}
- },
- "204": {
- "description": "No Content"
- }
- },
- "x-ms-examples": {
- "Delete Schedule.": {
- "$ref": "./examples/Schedule/delete.json"
}
- },
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "location"
}
},
- "get": {
- "tags": [
- "Schedule"
- ],
- "summary": "Get schedule.",
- "operationId": "Schedules_Get",
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Schedule name.",
- "required": true,
- "type": "string"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- }
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ScheduleResource"
- }
- }
- },
- "x-ms-examples": {
- "Get Schedule.": {
- "$ref": "./examples/Schedule/get.json"
- }
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/createOrUpdate.json"
}
},
- "put": {
- "tags": [
- "Schedule"
- ],
- "summary": "Create or update schedule.",
- "operationId": "Schedules_CreateOrUpdate",
- "consumes": [
- "application/json"
- ],
- "produces": [
- "application/json"
- ],
- "parameters": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
- },
- {
- "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
- },
- {
- "in": "path",
- "name": "name",
- "description": "Schedule name.",
- "required": true,
- "type": "string",
- "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
- },
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
- },
- {
- "in": "body",
- "name": "body",
- "description": "Schedule definition.",
- "required": true,
- "schema": {
- "$ref": "#/definitions/ScheduleResource"
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/backfill": {
+ "post": {
+ "tags": [
+ "FeaturesetVersion"
+ ],
+ "summary": "Backfill.",
+ "operationId": "FeaturesetVersions_Backfill",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Feature set version backfill request entity.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/FeaturesetVersionBackfillRequest"
}
- ],
- "responses": {
- "default": {
- "description": "Error",
- "schema": {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
- }
- },
- "200": {
- "description": "Success",
- "schema": {
- "$ref": "#/definitions/ScheduleResource"
- }
- },
- "201": {
- "description": "Created",
- "schema": {
- "$ref": "#/definitions/ScheduleResource"
- },
- "headers": {
- "x-ms-async-operation-timeout": {
- "description": "Timeout for the client to use when polling the asynchronous operation.",
- "type": "string",
- "format": "duration"
- },
- "Azure-AsyncOperation": {
- "description": "URI to poll for asynchronous operation status.",
- "type": "string"
- }
- }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
},
- "x-ms-examples": {
- "CreateOrUpdate Schedule.": {
- "$ref": "./examples/Schedule/createOrUpdate.json"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetJob"
}
},
- "x-ms-long-running-operation": true,
- "x-ms-long-running-operation-options": {
- "final-state-via": "original-uri"
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Backfill Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/backfill.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
}
}
},
- "definitions": {
- "AccountKeyDatastoreCredentials": {
- "description": "Account key datastore credentials configuration.",
- "required": [
- "secrets"
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/getFeature": {
+ "post": {
+ "tags": [
+ "FeaturesetVersion"
+ ],
+ "summary": "Get feature.",
+ "operationId": "FeaturesetVersions_GetFeature",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Feature set name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Feature set version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
{
- "$ref": "#/definitions/DatastoreCredentials"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Feature Name request. This is case-sensitive.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/GetFeatureRequest"
+ }
}
],
- "properties": {
- "secrets": {
- "description": "[Required] Storage account secrets.",
- "$ref": "#/definitions/AccountKeyDatastoreSecrets",
- "x-ms-mutability": [
- "create",
- "update"
- ],
- "x-ms-secret": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/Feature"
+ }
}
},
- "x-ms-discriminator-value": "AccountKey",
- "additionalProperties": false
- },
- "AccountKeyDatastoreSecrets": {
- "description": "Datastore account key secrets.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/DatastoreSecrets"
+ "x-ms-examples": {
+ "GetFeature Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/getFeature.json"
}
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/listFeatures": {
+ "post": {
+ "tags": [
+ "FeaturesetVersion"
],
- "properties": {
- "key": {
- "description": "Storage account key.",
- "type": "string",
- "x-nullable": true
- }
- },
- "x-ms-discriminator-value": "AccountKey",
- "additionalProperties": false
- },
- "AllNodes": {
- "description": "All nodes means the service will be running on all of the nodes of the job",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/Nodes"
- }
+ "summary": "List Features.",
+ "operationId": "FeaturesetVersions_ListFeatures",
+ "produces": [
+ "application/json"
],
- "x-ms-discriminator-value": "All",
- "additionalProperties": false
- },
- "AmlToken": {
- "description": "AML Token identity configuration.",
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/IdentityConfiguration"
- }
- ],
- "x-ms-discriminator-value": "AMLToken",
- "additionalProperties": false
- },
- "AssetBase": {
- "type": "object",
- "allOf": [
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
{
- "$ref": "#/definitions/ResourceBase"
- }
- ],
- "properties": {
- "isAnonymous": {
- "description": "If the name version are system generated (anonymous registration).",
- "default": false,
- "type": "boolean",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "isArchived": {
- "description": "Is the asset archived?",
- "default": false,
- "type": "boolean",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "additionalProperties": false
- },
- "AssetContainer": {
- "type": "object",
- "allOf": [
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
{
- "$ref": "#/definitions/ResourceBase"
- }
- ],
- "properties": {
- "isArchived": {
- "description": "Is the asset archived?",
- "default": false,
- "type": "boolean",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- },
- "latestVersion": {
- "description": "The latest version inside this container.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "nextVersion": {
- "description": "The next auto incremental version",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "AssetJobInput": {
- "description": "Asset input type.",
- "required": [
- "uri"
- ],
- "type": "object",
- "properties": {
- "mode": {
- "description": "Input Asset Delivery Mode.",
- "default": "ReadOnlyMount",
- "$ref": "#/definitions/InputDeliveryMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "uri": {
- "description": "[Required] Input Asset URI.",
- "pattern": "[a-zA-Z0-9_]",
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Featureset name. This is case-sensitive.",
+ "required": true,
"type": "string"
- }
- },
- "additionalProperties": false
- },
- "AssetJobOutput": {
- "description": "Asset output type.",
- "type": "object",
- "properties": {
- "assetName": {
- "description": "Output Asset Name.",
- "type": "string",
- "x-nullable": true
},
- "assetVersion": {
- "description": "Output Asset Version.",
- "type": "string",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Featureset Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "mode": {
- "description": "Output Asset Delivery Mode.",
- "default": "ReadWriteMount",
- "$ref": "#/definitions/OutputDeliveryMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "uri": {
- "description": "Output Asset URI.",
- "type": "string",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "$tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "featureName",
+ "description": "feature name.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "description",
+ "description": "description.",
+ "type": "string"
}
- },
- "additionalProperties": false
- },
- "AssetProvisioningState": {
- "description": "Provisioning state of registry asset.",
- "enum": [
- "Succeeded",
- "Failed",
- "Canceled",
- "Creating",
- "Updating",
- "Deleting"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "AssetProvisioningState",
- "modelAsString": true,
- "values": [
- {
- "value": "Succeeded"
- },
- {
- "value": "Failed"
- },
- {
- "value": "Canceled"
- },
- {
- "value": "Creating"
- },
- {
- "value": "Updating"
- },
- {
- "value": "Deleting"
- }
- ]
- },
- "additionalProperties": false
- },
- "AssetReferenceBase": {
- "description": "Base definition for asset references.",
- "required": [
- "referenceType"
],
- "type": "object",
- "properties": {
- "referenceType": {
- "description": "[Required] Specifies the type of asset reference.",
- "$ref": "#/definitions/ReferenceType"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeatureArmPaginatedResult"
+ }
}
},
- "discriminator": "referenceType"
- },
- "AutoForecastHorizon": {
- "description": "Forecast horizon determined automatically by system.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ForecastHorizon"
- }
- ],
- "x-ms-discriminator-value": "Auto",
- "additionalProperties": false
- },
- "AutologgerSettings": {
- "description": "Settings for Autologger.",
- "required": [
- "mlflowAutologger"
- ],
- "type": "object",
- "properties": {
- "mlflowAutologger": {
- "description": "[Required] Indicates whether mlflow autologger is enabled.",
- "$ref": "#/definitions/MLFlowAutologgerState",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "x-ms-examples": {
+ "ListFeatures Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/listFeatures.json"
}
},
- "additionalProperties": false
- },
- "AutoMLJob": {
- "description": "AutoMLJob class.\r\nUse this class for executing AutoML tasks like Classification/Regression etc.\r\nSee TaskType enum for all the tasks supported.",
- "required": [
- "taskDetails"
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featuresets/{name}/versions/{version}/listMaterializationJobs": {
+ "post": {
+ "tags": [
+ "FeaturesetVersion"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/JobBase"
- }
+ "summary": "List materialization Jobs.",
+ "operationId": "FeaturesetVersions_ListMaterializationJobs",
+ "produces": [
+ "application/json"
],
- "properties": {
- "environmentId": {
- "description": "The ARM resource ID of the Environment specification for the job.\r\nThis is optional value to provide, if not provided, AutoML will default this to Production AutoML curated environment version when running the job.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "environmentVariables": {
- "description": "Environment variables included in the job.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "outputs": {
- "description": "Mapping of output data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Job output definition container information on where to find job output/logs.",
- "$ref": "#/definitions/JobOutput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "queueSettings": {
- "description": "Queue settings for the job",
- "$ref": "#/definitions/QueueSettings",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "resources": {
- "description": "Compute Resource configuration for the job.",
- "default": "{}",
- "$ref": "#/definitions/JobResourceConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "taskDetails": {
- "description": "[Required] This represents scenario which can be one of Tables/NLP/Image",
- "$ref": "#/definitions/AutoMLVertical"
- }
- },
- "x-ms-discriminator-value": "AutoML",
- "additionalProperties": false
- },
- "AutoMLVertical": {
- "description": "AutoML vertical class.\r\nBase class for AutoML verticals - TableVertical/ImageVertical/NLPVertical",
- "required": [
- "taskType",
- "trainingData"
- ],
- "type": "object",
- "properties": {
- "logVerbosity": {
- "description": "Log verbosity for the job.",
- "default": "Info",
- "$ref": "#/definitions/LogVerbosity"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "targetColumnName": {
- "description": "Target column name: This is prediction values column.\r\nAlso known as label column name in context of classification tasks.",
- "type": "string",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
},
- "taskType": {
- "description": "[Required] Task type for AutoMLJob.",
- "$ref": "#/definitions/TaskType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "in": "query",
+ "name": "filters",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "featureWindowStart",
+ "description": "Start time of the feature window to filter materialization jobs.",
+ "type": "string"
},
- "trainingData": {
- "description": "[Required] Training data input.",
- "$ref": "#/definitions/MLTableJobInput"
- }
- },
- "discriminator": "taskType"
- },
- "AutoNCrossValidations": {
- "description": "N-Cross validations determined automatically.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/NCrossValidations"
+ "in": "query",
+ "name": "featureWindowEnd",
+ "description": "End time of the feature window to filter materialization jobs.",
+ "type": "string"
}
],
- "x-ms-discriminator-value": "Auto",
- "additionalProperties": false
- },
- "AutoRebuildSetting": {
- "description": "AutoRebuild setting for the derived image",
- "enum": [
- "Disabled",
- "OnBaseImageUpdate"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "AutoRebuildSetting",
- "modelAsString": true,
- "values": [
- {
- "value": "Disabled"
- },
- {
- "value": "OnBaseImageUpdate"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturesetJobArmPaginatedResult"
+ }
+ }
},
- "additionalProperties": false
- },
- "AutoSeasonality": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/Seasonality"
+ "x-ms-examples": {
+ "ListMaterializationJobs Workspace Featureset Version.": {
+ "$ref": "./examples/Workspace/FeaturesetVersion/listMaterializationJobs.json"
}
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities": {
+ "get": {
+ "tags": [
+ "FeaturestoreEntityContainer"
],
- "x-ms-discriminator-value": "Auto",
- "additionalProperties": false
- },
- "AutoTargetLags": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/TargetLags"
- }
+ "summary": "List featurestore entity containers.",
+ "operationId": "FeaturestoreEntityContainers_List",
+ "produces": [
+ "application/json"
],
- "x-ms-discriminator-value": "Auto",
- "additionalProperties": false
- },
- "AutoTargetRollingWindowSize": {
- "description": "Target lags rolling window determined automatically.",
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/TargetRollingWindowSize"
- }
- ],
- "x-ms-discriminator-value": "Auto",
- "additionalProperties": false
- },
- "AzureBlobDatastore": {
- "description": "Azure Blob datastore configuration.",
- "type": "object",
- "allOf": [
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
{
- "$ref": "#/definitions/AzureDatastore"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
{
- "$ref": "#/definitions/Datastore"
- }
- ],
- "properties": {
- "accountName": {
- "description": "Storage account name.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "containerName": {
- "description": "Storage account container name.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "endpoint": {
- "description": "Azure cloud endpoint for the storage account.",
- "type": "string",
- "example": "core.windows.net",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
},
- "protocol": {
- "description": "Protocol used to communicate with the storage account.",
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
"type": "string",
- "example": "https",
- "x-ms-mutability": [
- "create",
- "read"
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
],
- "x-nullable": true
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
+ }
+ },
+ {
+ "in": "query",
+ "name": "pageSize",
+ "description": "page size",
+ "type": "integer",
+ "format": "int32",
+ "default": 20
+ },
+ {
+ "in": "query",
+ "name": "name",
+ "description": "name for the featurestore entity",
+ "type": "string"
},
- "serviceDataAccessAuthIdentity": {
- "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
- "default": "None",
- "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "x-ms-discriminator-value": "AzureBlob",
- "additionalProperties": false
- },
- "AzureDataLakeGen1Datastore": {
- "description": "Azure Data Lake Gen1 datastore configuration.",
- "required": [
- "storeName"
- ],
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/AzureDatastore"
+ "in": "query",
+ "name": "description",
+ "description": "description for the featurestore entity",
+ "type": "string"
},
{
- "$ref": "#/definitions/Datastore"
+ "in": "query",
+ "name": "createdBy",
+ "description": "createdBy user name",
+ "type": "string"
}
],
- "properties": {
- "serviceDataAccessAuthIdentity": {
- "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
- "default": "None",
- "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "storeName": {
- "description": "[Required] Azure Data Lake store name.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityContainerResourceArmPaginatedResult"
+ }
}
},
- "x-ms-discriminator-value": "AzureDataLakeGen1",
- "additionalProperties": false
- },
- "AzureDataLakeGen2Datastore": {
- "description": "Azure Data Lake Gen2 datastore configuration.",
- "required": [
- "accountName",
- "filesystem"
+ "x-ms-examples": {
+ "List Workspace Featurestore Entity Container.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities/{name}": {
+ "delete": {
+ "tags": [
+ "FeaturestoreEntityContainer"
],
- "type": "object",
- "allOf": [
+ "summary": "Delete container.",
+ "operationId": "FeaturestoreEntityContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
{
- "$ref": "#/definitions/AzureDatastore"
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
{
- "$ref": "#/definitions/Datastore"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "accountName": {
- "description": "[Required] Storage account name.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "endpoint": {
- "description": "Azure cloud endpoint for the storage account.",
- "type": "string",
- "example": "core.windows.net",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "filesystem": {
- "description": "[Required] The name of the Data Lake Gen2 filesystem.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "200": {
+ "description": "Success"
},
- "protocol": {
- "description": "Protocol used to communicate with the storage account.",
- "type": "string",
- "example": "https",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
},
- "serviceDataAccessAuthIdentity": {
- "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
- "default": "None",
- "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "204": {
+ "description": "No Content"
}
},
- "x-ms-discriminator-value": "AzureDataLakeGen2",
- "additionalProperties": false
- },
- "AzureDatastore": {
- "description": "Base definition for Azure datastore contents configuration.",
- "type": "object",
- "properties": {
- "resourceGroup": {
- "description": "Azure Resource Group name",
- "type": "string",
- "x-nullable": true
- },
- "subscriptionId": {
- "description": "Azure Subscription Id",
- "type": "string",
- "x-nullable": true
+ "x-ms-examples": {
+ "Delete Workspace Featurestore Entity Container.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityContainer/delete.json"
}
},
- "additionalProperties": false
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
},
- "AzureFileDatastore": {
- "description": "Azure File datastore configuration.",
- "required": [
- "accountName",
- "fileShareName"
+ "get": {
+ "tags": [
+ "FeaturestoreEntityContainer"
+ ],
+ "summary": "Get container.",
+ "operationId": "FeaturestoreEntityContainers_GetEntity",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/AzureDatastore"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
{
- "$ref": "#/definitions/Datastore"
- }
- ],
- "properties": {
- "accountName": {
- "description": "[Required] Storage account name.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "endpoint": {
- "description": "Azure cloud endpoint for the storage account.",
- "type": "string",
- "example": "core.windows.net",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "fileShareName": {
- "description": "[Required] The name of the Azure file share that the datastore points to.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "protocol": {
- "description": "Protocol used to communicate with the storage account.",
- "type": "string",
- "example": "https",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "serviceDataAccessAuthIdentity": {
- "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
- "default": "None",
- "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "x-ms-discriminator-value": "AzureFile",
- "additionalProperties": false
- },
- "AzureMLBatchInferencingServer": {
- "description": "Azure ML batch inferencing server configurations.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/InferencingServer"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "codeConfiguration": {
- "description": "Code configuration for AML batch inferencing server.",
- "$ref": "#/definitions/CodeConfiguration",
- "x-nullable": true
- }
- },
- "x-ms-discriminator-value": "AzureMLBatch",
- "additionalProperties": false
- },
- "AzureMLOnlineInferencingServer": {
- "description": "Azure ML online inferencing configurations.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/InferencingServer"
- }
- ],
- "properties": {
- "codeConfiguration": {
- "description": "Code configuration for AML inferencing server.",
- "$ref": "#/definitions/CodeConfiguration",
- "x-nullable": true
- }
- },
- "x-ms-discriminator-value": "AzureMLOnline",
- "additionalProperties": false
- },
- "BanditPolicy": {
- "description": "Defines an early termination policy based on slack criteria, and a frequency and delay interval for evaluation",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/EarlyTerminationPolicy"
- }
- ],
- "properties": {
- "slackAmount": {
- "format": "float",
- "description": "Absolute distance allowed from the best performing run.",
- "default": 0,
- "type": "number"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "slackFactor": {
- "format": "float",
- "description": "Ratio of the allowed distance from the best performing run.",
- "default": 0,
- "type": "number"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityContainerResource"
+ }
}
},
- "x-ms-discriminator-value": "Bandit",
- "additionalProperties": false
+ "x-ms-examples": {
+ "GetEntity Workspace Featurestore Entity Container.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityContainer/getEntity.json"
+ }
+ }
},
- "BaseEnvironmentId": {
- "description": "Base environment type.",
- "required": [
- "resourceId"
+ "put": {
+ "tags": [
+ "FeaturestoreEntityContainer"
+ ],
+ "summary": "Create or update container.",
+ "operationId": "FeaturestoreEntityContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
{
- "$ref": "#/definitions/BaseEnvironmentSource"
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityContainerResource"
+ }
}
],
- "properties": {
- "resourceId": {
- "description": "[Required] Resource id accepting ArmId or AzureMlId.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityContainerResource"
+ }
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityContainerResource"
+ },
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
+ }
}
},
- "x-ms-discriminator-value": "EnvironmentAsset",
- "additionalProperties": false
- },
- "BaseEnvironmentSource": {
- "required": [
- "baseEnvironmentSourceType"
- ],
- "type": "object",
- "properties": {
- "baseEnvironmentSourceType": {
- "description": "[Required] Base environment type.",
- "$ref": "#/definitions/BaseEnvironmentSourceType"
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Featurestore Entity Container.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityContainer/createOrUpdate.json"
}
},
- "discriminator": "baseEnvironmentSourceType"
- },
- "BaseEnvironmentSourceType": {
- "description": "Base environment type.",
- "enum": [
- "EnvironmentAsset"
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities/{name}/versions": {
+ "get": {
+ "tags": [
+ "FeaturestoreEntityVersion"
],
- "type": "string",
- "x-ms-enum": {
- "name": "BaseEnvironmentSourceType",
- "modelAsString": true,
- "values": [
- {
- "value": "EnvironmentAsset"
- }
- ]
- },
- "additionalProperties": false
- },
- "BatchDeployment": {
- "description": "Batch inference settings per deployment.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/EndpointDeploymentPropertiesBase"
- }
+ "summary": "List versions.",
+ "operationId": "FeaturestoreEntityVersions_List",
+ "produces": [
+ "application/json"
],
- "properties": {
- "compute": {
- "description": "Compute target for batch inference operation.",
- "type": "string",
- "x-nullable": true
- },
- "deploymentConfiguration": {
- "description": "Properties relevant to different deployment types.",
- "$ref": "#/definitions/BatchDeploymentConfiguration",
- "x-nullable": true
- },
- "errorThreshold": {
- "format": "int32",
- "description": "Error threshold, if the error count for the entire input goes above this value,\r\nthe batch inference will be aborted. Range is [-1, int.MaxValue].\r\nFor FileDataset, this value is the count of file failures.\r\nFor TabularDataset, this value is the count of record failures.\r\nIf set to -1 (the lower bound), all failures during batch inference will be ignored.",
- "default": -1,
- "type": "integer"
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "loggingLevel": {
- "description": "Logging level for batch inference operation.",
- "default": "Info",
- "$ref": "#/definitions/BatchLoggingLevel"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "maxConcurrencyPerInstance": {
- "format": "int32",
- "description": "Indicates maximum number of parallelism per instance.",
- "default": 1,
- "type": "integer"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "miniBatchSize": {
- "format": "int64",
- "description": "Size of the mini-batch passed to each batch invocation.\r\nFor FileDataset, this is the number of files per mini-batch.\r\nFor TabularDataset, this is the size of the records in bytes, per mini-batch.",
- "default": 10,
- "type": "integer"
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Feature entity name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "model": {
- "description": "Reference to the model asset for the endpoint deployment.",
- "$ref": "#/definitions/AssetReferenceBase",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "outputAction": {
- "description": "Indicates how the output will be organized.",
- "default": "AppendRow",
- "$ref": "#/definitions/BatchOutputAction"
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
},
- "outputFileName": {
- "description": "Customized output file name for append_row output action.",
- "default": "predictions.csv",
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
"type": "string"
},
- "provisioningState": {
- "description": "Provisioning state for the endpoint deployment.",
- "$ref": "#/definitions/DeploymentProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "resources": {
- "description": "Indicates compute configuration for the job.\r\nIf not provided, will default to the defaults defined in ResourceConfiguration.",
- "$ref": "#/definitions/DeploymentResourceConfiguration",
- "x-nullable": true
- },
- "retrySettings": {
- "description": "Retry Settings for the batch inference operation.\r\nIf not provided, will default to the defaults defined in BatchRetrySettings.",
- "$ref": "#/definitions/BatchRetrySettings",
- "x-nullable": true
- }
- },
- "x-ms-client-name": "BatchDeploymentProperties",
- "additionalProperties": false
- },
- "BatchDeploymentConfiguration": {
- "description": "Properties relevant to different deployment types.",
- "required": [
- "deploymentConfigurationType"
- ],
- "type": "object",
- "properties": {
- "deploymentConfigurationType": {
- "description": "[Required] The type of the deployment",
- "$ref": "#/definitions/BatchDeploymentConfigurationType"
- }
- },
- "discriminator": "deploymentConfigurationType"
- },
- "BatchDeploymentConfigurationType": {
- "description": "The enumerated property types for batch deployments.",
- "enum": [
- "Model",
- "PipelineComponent"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "BatchDeploymentConfigurationType",
- "modelAsString": true,
- "values": [
- {
- "value": "Model"
- },
- {
- "value": "PipelineComponent"
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "[ListViewType.ActiveOnly, ListViewType.ArchivedOnly, ListViewType.All]View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
}
- ]
- },
- "additionalProperties": false
- },
- "BatchDeploymentTrackedResource": {
- "required": [
- "location",
- "properties"
- ],
- "type": "object",
- "allOf": [
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
- }
- ],
- "properties": {
- "identity": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ "in": "query",
+ "name": "pageSize",
+ "description": "page size",
+ "type": "integer",
+ "format": "int32",
+ "default": 20
},
- "kind": {
- "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
+ {
+ "in": "query",
+ "name": "versionName",
+ "description": "name for the featurestore entity version",
"type": "string"
},
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/BatchDeployment"
+ {
+ "in": "query",
+ "name": "version",
+ "description": "featurestore entity version",
+ "type": "string"
},
- "sku": {
- "description": "Sku details required for ARM contract for Autoscaling.",
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
- }
- },
- "x-ms-client-name": "BatchDeployment",
- "additionalProperties": false
- },
- "BatchDeploymentTrackedResourceArmPaginatedResult": {
- "description": "A paginated list of BatchDeployment entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of BatchDeployment objects. If null, there are no additional pages.",
+ {
+ "in": "query",
+ "name": "description",
+ "description": "description for the feature entity version",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "createdBy",
+ "description": "createdBy user name",
"type": "string"
},
- "value": {
- "description": "An array of objects of type BatchDeployment.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/BatchDeploymentTrackedResource"
- }
- }
- },
- "additionalProperties": false
- },
- "BatchEndpoint": {
- "description": "Batch endpoint configuration.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/EndpointPropertiesBase"
+ "in": "query",
+ "name": "stage",
+ "description": "stage",
+ "type": "string"
}
],
- "properties": {
- "defaults": {
- "description": "Default values for Batch Endpoint.",
- "$ref": "#/definitions/BatchEndpointDefaults",
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "provisioningState": {
- "description": "Provisioning state for the endpoint.",
- "$ref": "#/definitions/EndpointProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityVersionResourceArmPaginatedResult"
+ }
}
},
- "x-ms-client-name": "BatchEndpointProperties",
- "additionalProperties": false
- },
- "BatchEndpointDefaults": {
- "description": "Batch endpoint default values",
- "type": "object",
- "properties": {
- "deploymentName": {
- "description": "Name of the deployment that will be default for the endpoint.\r\nThis deployment will end up getting 100% traffic when the endpoint scoring URL is invoked.",
- "type": "string",
- "x-nullable": true
+ "x-ms-examples": {
+ "List Workspace Featurestore Entity Version.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityVersion/list.json"
}
},
- "additionalProperties": false
- },
- "BatchEndpointTrackedResource": {
- "required": [
- "location",
- "properties"
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/featurestoreEntities/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "FeaturestoreEntityVersion"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
- }
+ "summary": "Delete version.",
+ "operationId": "FeaturestoreEntityVersions_Delete",
+ "produces": [
+ "application/json"
],
- "properties": {
- "identity": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "kind": {
- "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
- "type": "string"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/BatchEndpoint"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "sku": {
- "description": "Sku details required for ARM contract for Autoscaling.",
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
- }
- },
- "x-ms-client-name": "BatchEndpoint",
- "additionalProperties": false
- },
- "BatchEndpointTrackedResourceArmPaginatedResult": {
- "description": "A paginated list of BatchEndpoint entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of BatchEndpoint objects. If null, there are no additional pages.",
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
"type": "string"
},
- "value": {
- "description": "An array of objects of type BatchEndpoint.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/BatchEndpointTrackedResource"
- }
- }
- },
- "additionalProperties": false
- },
- "BatchLoggingLevel": {
- "description": "Log verbosity for batch inferencing.\r\nIncreasing verbosity order for logging is : Warning, Info and Debug.\r\nThe default value is Info.",
- "enum": [
- "Info",
- "Warning",
- "Debug"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "BatchLoggingLevel",
- "modelAsString": true,
- "values": [
- {
- "value": "Info"
- },
- {
- "value": "Warning"
- },
- {
- "value": "Debug"
- }
- ]
- },
- "additionalProperties": false
- },
- "BatchOutputAction": {
- "description": "Enum to determine how batch inferencing will handle output",
- "enum": [
- "SummaryOnly",
- "AppendRow"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "BatchOutputAction",
- "modelAsString": true,
- "values": [
- {
- "value": "SummaryOnly"
- },
- {
- "value": "AppendRow"
- }
- ]
- },
- "additionalProperties": false
- },
- "BatchPipelineComponentDeploymentConfiguration": {
- "description": "Properties for a Batch Pipeline Component Deployment.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/BatchDeploymentConfiguration"
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "componentId": {
- "description": "The ARM id of the component to be run.",
- "$ref": "#/definitions/IdAssetReference",
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "description": {
- "description": "The description which will be applied to the job.",
- "type": "string",
- "x-nullable": true
+ "200": {
+ "description": "Success"
},
- "settings": {
- "description": "Run-time settings for the pipeline job.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
},
- "tags": {
- "description": "The tags which will be applied to the job.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "204": {
+ "description": "No Content"
}
},
- "x-ms-discriminator-value": "PipelineComponent",
- "additionalProperties": false
- },
- "BatchRetrySettings": {
- "description": "Retry settings for a batch inference operation.",
- "type": "object",
- "properties": {
- "maxRetries": {
- "format": "int32",
- "description": "Maximum retry count for a mini-batch",
- "default": 3,
- "type": "integer"
- },
- "timeout": {
- "format": "duration",
- "description": "Invocation timeout for a mini-batch, in ISO 8601 format.",
- "default": "PT30S",
- "type": "string"
+ "x-ms-examples": {
+ "Delete Workspace Featurestore Entity Version.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityVersion/delete.json"
}
},
- "additionalProperties": false
- },
- "BayesianSamplingAlgorithm": {
- "description": "Defines a Sampling Algorithm that generates values based on previous values",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/SamplingAlgorithm"
- }
- ],
- "x-ms-discriminator-value": "Bayesian",
- "additionalProperties": false
- },
- "BlockedTransformers": {
- "description": "Enum for all classification models supported by AutoML.",
- "enum": [
- "TextTargetEncoder",
- "OneHotEncoder",
- "CatTargetEncoder",
- "TfIdf",
- "WoETargetEncoder",
- "LabelEncoder",
- "WordEmbedding",
- "NaiveBayes",
- "CountVectorizer",
- "HashOneHotEncoder"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "BlockedTransformers",
- "modelAsString": true,
- "values": [
- {
- "value": "TextTargetEncoder",
- "description": "Target encoding for text data."
- },
- {
- "value": "OneHotEncoder",
- "description": "Ohe hot encoding creates a binary feature transformation."
- },
- {
- "value": "CatTargetEncoder",
- "description": "Target encoding for categorical data."
- },
- {
- "value": "TfIdf",
- "description": "Tf-Idf stands for, term-frequency times inverse document-frequency. This is a common term weighting scheme for identifying information from documents."
- },
- {
- "value": "WoETargetEncoder",
- "description": "Weight of Evidence encoding is a technique used to encode categorical variables. It uses the natural log of the P(1)/P(0) to create weights."
- },
- {
- "value": "LabelEncoder",
- "description": "Label encoder converts labels/categorical variables in a numerical form."
- },
- {
- "value": "WordEmbedding",
- "description": "Word embedding helps represents words or phrases as a vector, or a series of numbers."
- },
- {
- "value": "NaiveBayes",
- "description": "Naive Bayes is a classified that is used for classification of discrete features that are categorically distributed."
- },
- {
- "value": "CountVectorizer",
- "description": "Count Vectorizer converts a collection of text documents to a matrix of token counts."
- },
- {
- "value": "HashOneHotEncoder",
- "description": "Hashing One Hot Encoder can turn categorical variables into a limited number of new features. This is often used for high-cardinality categorical features."
- }
- ]
- },
- "additionalProperties": false
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
},
- "BuildContext": {
- "description": "Configuration settings for Docker build context",
- "required": [
- "contextUri"
+ "get": {
+ "tags": [
+ "FeaturestoreEntityVersion"
],
- "type": "object",
- "properties": {
- "contextUri": {
- "description": "[Required] URI of the Docker build context used to build the image. Supports blob URIs on environment creation and may return blob or Git URIs.\r\n",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "example": "https://storage-account.blob.core.windows.net/azureml/DockerBuildContext/95ddede6b9b8c4e90472db3acd0a8d28/",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "dockerfilePath": {
- "description": "Path to the Dockerfile in the build context.\r\n",
- "default": "Dockerfile",
- "type": "string",
- "example": "prod/Dockerfile",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "additionalProperties": false
- },
- "CertificateDatastoreCredentials": {
- "description": "Certificate datastore credentials configuration.",
- "required": [
- "clientId",
- "secrets",
- "tenantId",
- "thumbprint"
+ "summary": "Get version.",
+ "operationId": "FeaturestoreEntityVersions_Get",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/DatastoreCredentials"
- }
- ],
- "properties": {
- "authorityUrl": {
- "description": "Authority URL used for authentication.",
- "type": "string",
- "x-nullable": true
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "clientId": {
- "format": "uuid",
- "description": "[Required] Service principal client ID.",
- "type": "string"
- },
- "resourceUrl": {
- "description": "Resource the service principal has access to.",
- "type": "string",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "secrets": {
- "description": "[Required] Service principal secrets.",
- "$ref": "#/definitions/CertificateDatastoreSecrets",
- "x-ms-mutability": [
- "create",
- "update"
- ],
- "x-ms-secret": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "tenantId": {
- "format": "uuid",
- "description": "[Required] ID of the tenant to which the service principal belongs.",
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
"type": "string"
},
- "thumbprint": {
- "description": "[Required] Thumbprint of the certificate used for authentication.",
- "pattern": "[a-zA-Z0-9_]",
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
"type": "string"
- }
- },
- "x-ms-discriminator-value": "Certificate",
- "additionalProperties": false
- },
- "CertificateDatastoreSecrets": {
- "description": "Datastore certificate secrets.",
- "type": "object",
- "allOf": [
+ },
{
- "$ref": "#/definitions/DatastoreSecrets"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "certificate": {
- "description": "Service principal certificate.",
- "type": "string",
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityVersionResource"
+ }
}
},
- "x-ms-discriminator-value": "Certificate",
- "additionalProperties": false
+ "x-ms-examples": {
+ "Get Workspace Featurestore Entity Version.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityVersion/get.json"
+ }
+ }
},
- "Classification": {
- "description": "Classification task in AutoML Table vertical.",
- "type": "object",
- "allOf": [
+ "put": {
+ "tags": [
+ "FeaturestoreEntityVersion"
+ ],
+ "summary": "Create or update version.",
+ "operationId": "FeaturestoreEntityVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
{
- "$ref": "#/definitions/TableVertical"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
{
- "$ref": "#/definitions/AutoMLVertical"
- }
- ],
- "properties": {
- "positiveLabel": {
- "description": "Positive label for binary metrics calculation.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
"type": "string",
- "x-nullable": true
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "primaryMetric": {
- "description": "Primary metric for the task.",
- "default": "AUCWeighted",
- "$ref": "#/definitions/ClassificationPrimaryMetrics"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "trainingSettings": {
- "description": "Inputs for training phase for an AutoML Job.",
- "$ref": "#/definitions/ClassificationTrainingSettings",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityVersionResource"
+ }
}
- },
- "x-ms-discriminator-value": "Classification",
- "additionalProperties": false
- },
- "ClassificationModels": {
- "description": "Enum for all classification models supported by AutoML.",
- "enum": [
- "LogisticRegression",
- "SGD",
- "MultinomialNaiveBayes",
- "BernoulliNaiveBayes",
- "SVM",
- "LinearSVM",
- "KNN",
- "DecisionTree",
- "RandomForest",
- "ExtremeRandomTrees",
- "LightGBM",
- "GradientBoosting",
- "XGBoostClassifier"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ClassificationModels",
- "modelAsString": true,
- "values": [
- {
- "value": "LogisticRegression",
- "description": "Logistic regression is a fundamental classification technique.\nIt belongs to the group of linear classifiers and is somewhat similar to polynomial and linear regression.\nLogistic regression is fast and relatively uncomplicated, and it's convenient for you to interpret the results.\nAlthough it's essentially a method for binary classification, it can also be applied to multiclass problems."
- },
- {
- "value": "SGD",
- "description": "SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning applications\nto find the model parameters that correspond to the best fit between predicted and actual outputs."
- },
- {
- "value": "MultinomialNaiveBayes",
- "description": "The multinomial Naive Bayes classifier is suitable for classification with discrete features (e.g., word counts for text classification).\nThe multinomial distribution normally requires integer feature counts. However, in practice, fractional counts such as tf-idf may also work."
- },
- {
- "value": "BernoulliNaiveBayes",
- "description": "Naive Bayes classifier for multivariate Bernoulli models."
- },
- {
- "value": "SVM",
- "description": "A support vector machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems.\nAfter giving an SVM model sets of labeled training data for each category, they're able to categorize new text."
- },
- {
- "value": "LinearSVM",
- "description": "A support vector machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems.\nAfter giving an SVM model sets of labeled training data for each category, they're able to categorize new text.\nLinear SVM performs best when input data is linear, i.e., data can be easily classified by drawing the straight line between classified values on a plotted graph."
- },
- {
- "value": "KNN",
- "description": "K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new datapoints\nwhich further means that the new data point will be assigned a value based on how closely it matches the points in the training set."
- },
- {
- "value": "DecisionTree",
- "description": "Decision Trees are a non-parametric supervised learning method used for both classification and regression tasks.\nThe goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features."
- },
- {
- "value": "RandomForest",
- "description": "Random forest is a supervised learning algorithm.\nThe \"forest\" it builds, is an ensemble of decision trees, usually trained with the 'bagging' method.\nThe general idea of the bagging method is that a combination of learning models increases the overall result."
- },
- {
- "value": "ExtremeRandomTrees",
- "description": "Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many decision trees. It is related to the widely used random forest algorithm."
- },
- {
- "value": "LightGBM",
- "description": "LightGBM is a gradient boosting framework that uses tree based learning algorithms."
- },
- {
- "value": "GradientBoosting",
- "description": "The technique of transiting week learners into a strong learner is called Boosting. The gradient boosting algorithm process works on this theory of execution."
- },
- {
- "value": "XGBoostClassifier",
- "description": "XGBoost: Extreme Gradient Boosting Algorithm. This algorithm is used for structured data where target column values can be divided into distinct class values."
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
- },
- "additionalProperties": false
- },
- "ClassificationMultilabelPrimaryMetrics": {
- "description": "Primary metrics for classification multilabel tasks.",
- "enum": [
- "AUCWeighted",
- "Accuracy",
- "NormMacroRecall",
- "AveragePrecisionScoreWeighted",
- "PrecisionScoreWeighted",
- "IOU"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ClassificationMultilabelPrimaryMetrics",
- "modelAsString": true,
- "values": [
- {
- "value": "AUCWeighted",
- "description": "AUC is the Area under the curve.\nThis metric represents arithmetic mean of the score for each class,\nweighted by the number of true instances in each class."
- },
- {
- "value": "Accuracy",
- "description": "Accuracy is the ratio of predictions that exactly match the true class labels."
- },
- {
- "value": "NormMacroRecall",
- "description": "Normalized macro recall is recall macro-averaged and normalized, so that random\nperformance has a score of 0, and perfect performance has a score of 1."
- },
- {
- "value": "AveragePrecisionScoreWeighted",
- "description": "The arithmetic mean of the average precision score for each class, weighted by\nthe number of true instances in each class."
- },
- {
- "value": "PrecisionScoreWeighted",
- "description": "The arithmetic mean of precision for each class, weighted by number of true instances in each class."
- },
- {
- "value": "IOU",
- "description": "Intersection Over Union. Intersection of predictions divided by union of predictions."
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityVersionResource"
}
- ]
- },
- "additionalProperties": false
- },
- "ClassificationPrimaryMetrics": {
- "description": "Primary metrics for classification tasks.",
- "enum": [
- "AUCWeighted",
- "Accuracy",
- "NormMacroRecall",
- "AveragePrecisionScoreWeighted",
- "PrecisionScoreWeighted"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ClassificationPrimaryMetrics",
- "modelAsString": true,
- "values": [
- {
- "value": "AUCWeighted",
- "description": "AUC is the Area under the curve.\nThis metric represents arithmetic mean of the score for each class,\nweighted by the number of true instances in each class."
- },
- {
- "value": "Accuracy",
- "description": "Accuracy is the ratio of predictions that exactly match the true class labels."
- },
- {
- "value": "NormMacroRecall",
- "description": "Normalized macro recall is recall macro-averaged and normalized, so that random\nperformance has a score of 0, and perfect performance has a score of 1."
- },
- {
- "value": "AveragePrecisionScoreWeighted",
- "description": "The arithmetic mean of the average precision score for each class, weighted by\nthe number of true instances in each class."
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/FeaturestoreEntityVersionResource"
},
- {
- "value": "PrecisionScoreWeighted",
- "description": "The arithmetic mean of precision for each class, weighted by number of true instances in each class."
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
}
- ]
+ }
},
- "additionalProperties": false
- },
- "ClassificationTrainingSettings": {
- "description": "Classification Training related configuration.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/TrainingSettings"
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Featurestore Entity Version.": {
+ "$ref": "./examples/Workspace/FeaturestoreEntityVersion/createOrUpdate.json"
}
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs": {
+ "get": {
+ "tags": [
+ "Job"
],
- "properties": {
- "allowedTrainingAlgorithms": {
- "description": "Allowed models for classification task.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ClassificationModels"
- },
- "x-nullable": true
+ "summary": "Lists Jobs in the workspace.",
+ "operationId": "Jobs_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "blockedTrainingAlgorithms": {
- "description": "Blocked models for classification task.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ClassificationModels"
- },
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "CocoExportSummary": {
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/ExportSummary"
- }
- ],
- "properties": {
- "containerName": {
- "description": "The container name to which the labels will be exported.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "snapshotPath": {
- "description": "The output path where the labels will be exported.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- }
- },
- "x-ms-discriminator-value": "Coco",
- "additionalProperties": false
- },
- "CodeConfiguration": {
- "description": "Configuration for a scoring code asset.",
- "required": [
- "scoringScript"
- ],
- "type": "object",
- "properties": {
- "codeId": {
- "description": "ARM resource ID of the code asset.",
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "jobType",
+ "description": "Type of job to be returned.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "tag",
+ "description": "Jobs returned will have this tag key.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
"type": "string",
- "x-ms-mutability": [
- "create",
- "read"
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
],
- "x-nullable": true
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
+ }
},
- "scoringScript": {
- "description": "[Required] The script to execute on startup. eg. \"score.py\"",
- "minLength": 1,
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "additionalProperties": false
- },
- "CodeContainer": {
- "description": "Container for code asset versions.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/AssetContainer"
- }
- ],
- "properties": {
- "provisioningState": {
- "description": "Provisioning state for the code container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- }
- },
- "x-ms-client-name": "CodeContainerProperties",
- "additionalProperties": false
- },
- "CodeContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
+ "in": "query",
+ "name": "assetName",
+ "description": "Asset name the job's named output is registered with",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "scheduled",
+ "description": "Indicator whether the job is scheduled job.",
+ "type": "boolean"
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "in": "query",
+ "name": "scheduleId",
+ "description": "The scheduled id for listing the job triggered from",
+ "type": "string"
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/CodeContainer"
- }
- },
- "x-ms-client-name": "CodeContainer",
- "additionalProperties": false
- },
- "CodeContainerResourceArmPaginatedResult": {
- "description": "A paginated list of CodeContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of CodeContainer objects. If null, there are no additional pages.",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type CodeContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/CodeContainerResource"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/JobBaseResourceArmPaginatedResult"
}
}
},
- "additionalProperties": false
- },
- "CodeVersion": {
- "description": "Code asset version details.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetBase"
- }
- ],
- "properties": {
- "codeUri": {
- "description": "Uri where code is located",
- "type": "string",
- "example": "https://blobStorage/folderName",
- "x-nullable": true
+ "x-ms-examples": {
+ "List Command Job.": {
+ "$ref": "./examples/Job/CommandJob/list.json"
+ },
+ "List AutoML Job.": {
+ "$ref": "./examples/Job/AutoMLJob/list.json"
},
- "provisioningState": {
- "description": "Provisioning state for the code version.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "List Sweep Job.": {
+ "$ref": "./examples/Job/SweepJob/list.json"
+ },
+ "List Pipeline Job.": {
+ "$ref": "./examples/Job/PipelineJob/list.json"
}
},
- "x-ms-client-name": "CodeVersionProperties",
- "additionalProperties": false
- },
- "CodeVersionResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}": {
+ "delete": {
+ "tags": [
+ "Job"
+ ],
+ "summary": "Deletes a Job (asynchronous).",
+ "operationId": "Jobs_Delete",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the Job. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/CodeVersion"
- }
- },
- "x-ms-client-name": "CodeVersion",
- "additionalProperties": false
- },
- "CodeVersionResourceArmPaginatedResult": {
- "description": "A paginated list of CodeVersion entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of CodeVersion objects. If null, there are no additional pages.",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type CodeVersion.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/CodeVersionResource"
+ "200": {
+ "description": "Success"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
}
+ },
+ "204": {
+ "description": "No Content"
}
},
- "additionalProperties": false
- },
- "ColumnTransformer": {
- "description": "Column transformer parameters.",
- "type": "object",
- "properties": {
- "fields": {
- "description": "Fields to apply transformer logic on.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-nullable": true
- },
- "parameters": {
- "description": "Different properties to be passed to transformer.\r\nInput expected is dictionary of key,value pairs in JSON format.",
- "type": "object",
- "x-nullable": true
+ "x-ms-examples": {
+ "Delete Job.": {
+ "$ref": "./examples/Job/delete.json"
}
},
- "additionalProperties": false
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
},
- "CommandJob": {
- "description": "Command job definition.",
- "required": [
- "command",
- "environmentId"
+ "get": {
+ "tags": [
+ "Job"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/JobBase"
- }
+ "summary": "Gets a Job by name/id.",
+ "operationId": "Jobs_Get",
+ "produces": [
+ "application/json"
],
- "properties": {
- "autologgerSettings": {
- "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.",
- "$ref": "#/definitions/AutologgerSettings",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "codeId": {
- "description": "ARM resource ID of the code asset.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "command": {
- "description": "[Required] The command to execute on startup of the job. eg. \"python train.py\"",
- "minLength": 1,
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "distribution": {
- "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.",
- "$ref": "#/definitions/DistributionConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "environmentId": {
- "description": "[Required] The ARM resource ID of the Environment specification for the job.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "environmentVariables": {
- "description": "Environment variables included in the job.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "inputs": {
- "description": "Mapping of input data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Command job definition.",
- "$ref": "#/definitions/JobInput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the Job. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "limits": {
- "description": "Command Job limit.",
- "$ref": "#/definitions/CommandJobLimits",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "outputs": {
- "description": "Mapping of output data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Job output definition container information on where to find job output/logs.",
- "$ref": "#/definitions/JobOutput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/JobBaseResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Command Job.": {
+ "$ref": "./examples/Job/CommandJob/get.json"
},
- "parameters": {
- "description": "Input parameters.",
- "type": "object",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "Get AutoML Job.": {
+ "$ref": "./examples/Job/AutoMLJob/get.json"
},
- "queueSettings": {
- "description": "Queue settings for the job",
- "$ref": "#/definitions/QueueSettings",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "Get Sweep Job.": {
+ "$ref": "./examples/Job/SweepJob/get.json"
},
- "resources": {
- "description": "Compute Resource configuration for the job.",
- "default": "{}",
- "$ref": "#/definitions/JobResourceConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "Get Pipeline Job.": {
+ "$ref": "./examples/Job/PipelineJob/get.json"
}
- },
- "x-ms-discriminator-value": "Command",
- "additionalProperties": false
+ }
},
- "CommandJobLimits": {
- "description": "Command Job limit class.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/JobLimits"
- }
+ "patch": {
+ "tags": [
+ "Job"
],
- "x-ms-discriminator-value": "Command",
- "additionalProperties": false
- },
- "ComponentContainer": {
- "description": "Component container definition.\r\n",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetContainer"
- }
+ "summary": "Updates a Job.",
+ "operationId": "Jobs_Update",
+ "consumes": [
+ "application/json"
],
- "properties": {
- "provisioningState": {
- "description": "Provisioning state for the component container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- }
- },
- "x-ms-client-name": "ComponentContainerProperties",
- "additionalProperties": false
- },
- "ComponentContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the Job. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Job definition to apply during the operation.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PartialJobBasePartialResource"
+ }
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/ComponentContainer"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/JobBaseResource"
+ }
}
},
- "x-ms-client-name": "ComponentContainer",
- "additionalProperties": false
+ "x-ms-examples": {
+ "Update Job.": {
+ "$ref": "./examples/Job/update.json"
+ }
+ }
},
- "ComponentContainerResourceArmPaginatedResult": {
- "description": "A paginated list of ComponentContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of ComponentContainer objects. If null, there are no additional pages.",
- "type": "string"
+ "put": {
+ "tags": [
+ "Job"
+ ],
+ "summary": "Creates and executes a Job.",
+ "operationId": "Jobs_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "value": {
- "description": "An array of objects of type ComponentContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ComponentContainerResource"
- }
- }
- },
- "additionalProperties": false
- },
- "ComponentVersion": {
- "description": "Definition of a component version: defines resources that span component types.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/AssetBase"
- }
- ],
- "properties": {
- "componentSpec": {
- "description": "Defines Component definition details.\r\n",
- "type": "object",
- "example": {
- "name": "Hello_Python_World",
- "display_name": "Hello_Python_World",
- "version": 1,
- "type": "command",
- "code": "azureml:/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/mycode/versions/1",
- "environment": "azureml:/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/AzureML-Tutorial/versions/1",
- "command": "python hello.py"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "provisioningState": {
- "description": "Provisioning state for the component version.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- }
- },
- "x-ms-client-name": "ComponentVersionProperties",
- "additionalProperties": false
- },
- "ComponentVersionResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the Job. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Job definition object.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/JobBaseResource"
+ }
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/ComponentVersion"
- }
- },
- "x-ms-client-name": "ComponentVersion",
- "additionalProperties": false
- },
- "ComponentVersionResourceArmPaginatedResult": {
- "description": "A paginated list of ComponentVersion entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of ComponentVersion objects. If null, there are no additional pages.",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type ComponentVersion.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ComponentVersionResource"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/JobBaseResource"
}
- }
- },
- "additionalProperties": false
- },
- "MaterializationComputeResource": {
- "description": "Dto object representing compute resource",
- "type": "object",
- "properties": {
- "instanceType": {
- "description": "Specifies the instance type",
- "type": "string",
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "ContainerResourceRequirements": {
- "description": "Resource requirements for each container instance within an online deployment.",
- "type": "object",
- "properties": {
- "containerResourceLimits": {
- "description": "Container resource limit info:",
- "$ref": "#/definitions/ContainerResourceSettings",
- "x-nullable": true
},
- "containerResourceRequests": {
- "description": "Container resource request info:",
- "$ref": "#/definitions/ContainerResourceSettings",
- "x-nullable": true
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/JobBaseResource"
+ }
}
},
- "additionalProperties": false
- },
- "ContainerResourceSettings": {
- "type": "object",
- "properties": {
- "cpu": {
- "description": "Number of vCPUs request/limit for container. More info:\r\nhttps://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/",
- "type": "string",
- "example": "1",
- "x-nullable": true
+ "x-ms-examples": {
+ "CreateOrUpdate Command Job.": {
+ "$ref": "./examples/Job/CommandJob/createOrUpdate.json"
},
- "gpu": {
- "description": "Number of Nvidia GPU cards request/limit for container. More info:\r\nhttps://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/",
- "type": "string",
- "example": "1",
- "x-nullable": true
+ "CreateOrUpdate AutoML Job.": {
+ "$ref": "./examples/Job/AutoMLJob/createOrUpdate.json"
},
- "memory": {
- "description": "Memory size request/limit for container. More info:\r\nhttps://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/",
- "type": "string",
- "example": "2Gi",
- "x-nullable": true
+ "CreateOrUpdate Sweep Job.": {
+ "$ref": "./examples/Job/SweepJob/createOrUpdate.json"
+ },
+ "CreateOrUpdate Pipeline Job.": {
+ "$ref": "./examples/Job/PipelineJob/createOrUpdate.json"
}
- },
- "additionalProperties": false
- },
- "ContainerType": {
- "description": "The type of container to retrieve logs from.",
- "enum": [
- "StorageInitializer",
- "InferenceServer",
- "ModelDataCollector"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}/cancel": {
+ "post": {
+ "tags": [
+ "Job"
],
- "type": "string",
- "x-ms-enum": {
- "name": "ContainerType",
- "modelAsString": true,
- "values": [
- {
- "value": "StorageInitializer",
- "description": "The container used to download models and score script."
- },
- {
- "value": "InferenceServer",
- "description": "The container used to serve user's request."
- },
- {
- "value": "ModelDataCollector",
- "description": "The container used to collect payload and custom logging when mdc is enabled."
- }
- ]
- },
- "additionalProperties": false
- },
- "CredentialsType": {
- "description": "Enum to determine the datastore credentials type.",
- "enum": [
- "AccountKey",
- "Certificate",
- "None",
- "Sas",
- "ServicePrincipal",
- "KerberosKeytab",
- "KerberosPassword"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "CredentialsType",
- "modelAsString": true,
- "values": [
- {
- "value": "AccountKey"
- },
- {
- "value": "Certificate"
- },
- {
- "value": "None"
- },
- {
- "value": "Sas"
- },
- {
- "value": "ServicePrincipal"
- },
- {
- "value": "KerberosKeytab"
- },
- {
- "value": "KerberosPassword"
- }
- ]
- },
- "additionalProperties": false
- },
- "CronTrigger": {
- "required": [
- "expression"
+ "summary": "Cancels a Job (asynchronous).",
+ "operationId": "Jobs_Cancel",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/TriggerBase"
- }
- ],
- "properties": {
- "expression": {
- "description": "[Required] Specifies cron expression of schedule.\r\nThe expression should follow NCronTab format.",
- "pattern": "[a-zA-Z0-9_]",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the Job. This is case-sensitive.",
+ "required": true,
"type": "string"
- }
- },
- "x-ms-discriminator-value": "Cron",
- "additionalProperties": false
- },
- "CsvExportSummary": {
- "type": "object",
- "allOf": [
+ },
{
- "$ref": "#/definitions/ExportSummary"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "containerName": {
- "description": "The container name to which the labels will be exported.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "snapshotPath": {
- "description": "The output path where the labels will be exported.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
+ },
+ "200": {
+ "description": "Success"
}
},
- "x-ms-discriminator-value": "CSV",
- "additionalProperties": false
- },
- "CustomForecastHorizon": {
- "description": "The desired maximum forecast horizon in units of time-series frequency.",
- "required": [
- "value"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ForecastHorizon"
- }
- ],
- "properties": {
- "value": {
- "format": "int32",
- "description": "[Required] Forecast horizon value.",
- "type": "integer"
+ "x-ms-examples": {
+ "Cancel Job.": {
+ "$ref": "./examples/Job/cancel.json"
}
},
- "x-ms-discriminator-value": "Custom",
- "additionalProperties": false
- },
- "CustomInferencingServer": {
- "description": "Custom inference server configurations.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/InferencingServer"
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs": {
+ "get": {
+ "tags": [
+ "LabelingJob"
],
- "properties": {
- "inferenceConfiguration": {
- "description": "Inference configuration for custom inferencing.",
- "$ref": "#/definitions/OnlineInferenceConfiguration",
- "x-nullable": true
- }
- },
- "x-ms-discriminator-value": "Custom",
- "additionalProperties": false
- },
- "CustomModelJobInput": {
- "type": "object",
- "allOf": [
+ "summary": "Lists labeling jobs in the workspace.",
+ "operationId": "LabelingJobs_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
{
- "$ref": "#/definitions/AssetJobInput"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
{
- "$ref": "#/definitions/JobInput"
- }
- ],
- "x-ms-discriminator-value": "custom_model",
- "additionalProperties": false
- },
- "CustomModelJobOutput": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetJobOutput"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
{
- "$ref": "#/definitions/JobOutput"
- }
- ],
- "x-ms-discriminator-value": "custom_model",
- "additionalProperties": false
- },
- "CustomNCrossValidations": {
- "description": "N-Cross validations are specified by user.",
- "required": [
- "value"
- ],
- "type": "object",
- "allOf": [
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
{
- "$ref": "#/definitions/NCrossValidations"
- }
- ],
- "properties": {
- "value": {
- "format": "int32",
- "description": "[Required] N-Cross validations value.",
- "type": "integer"
- }
- },
- "x-ms-discriminator-value": "Custom",
- "additionalProperties": false
- },
- "CustomSeasonality": {
- "required": [
- "value"
- ],
- "type": "object",
- "allOf": [
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
{
- "$ref": "#/definitions/Seasonality"
- }
- ],
- "properties": {
- "value": {
- "format": "int32",
- "description": "[Required] Seasonality value.",
- "type": "integer"
- }
- },
- "x-ms-discriminator-value": "Custom",
- "additionalProperties": false
- },
- "CustomTargetLags": {
- "required": [
- "values"
- ],
- "type": "object",
- "allOf": [
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
{
- "$ref": "#/definitions/TargetLags"
+ "in": "query",
+ "name": "$top",
+ "description": "Number of labeling jobs to return.",
+ "type": "integer",
+ "format": "int32"
}
],
- "properties": {
- "values": {
- "description": "[Required] Set target lags values.",
- "type": "array",
- "items": {
- "format": "int32",
- "type": "integer"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/LabelingJobResourceArmPaginatedResult"
}
}
},
- "x-ms-discriminator-value": "Custom",
- "additionalProperties": false
- },
- "CustomTargetRollingWindowSize": {
- "required": [
- "value"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/TargetRollingWindowSize"
- }
- ],
- "properties": {
- "value": {
- "format": "int32",
- "description": "[Required] TargetRollingWindowSize value.",
- "type": "integer"
+ "x-ms-examples": {
+ "List Labeling Job.": {
+ "$ref": "./examples/LabelingJob/list.json"
}
},
- "x-ms-discriminator-value": "Custom",
- "additionalProperties": false
- },
- "DataContainer": {
- "description": "Container for data asset versions.",
- "required": [
- "dataType"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetContainer"
- }
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}": {
+ "delete": {
+ "tags": [
+ "LabelingJob"
],
- "properties": {
- "dataType": {
- "description": "[Required] Specifies the type of data.",
- "$ref": "#/definitions/DataType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "x-ms-client-name": "DataContainerProperties",
- "additionalProperties": false
- },
- "DataContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "summary": "Delete a labeling job.",
+ "operationId": "LabelingJobs_Delete",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
- ],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/DataContainer"
- }
- },
- "x-ms-client-name": "DataContainer",
- "additionalProperties": false
- },
- "DataContainerResourceArmPaginatedResult": {
- "description": "A paginated list of DataContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of DataContainer objects. If null, there are no additional pages.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the LabelingJob.",
+ "required": true,
"type": "string"
},
- "value": {
- "description": "An array of objects of type DataContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/DataContainerResource"
- }
- }
- },
- "additionalProperties": false
- },
- "DataPathAssetReference": {
- "description": "Reference to an asset via its path in a datastore.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/AssetReferenceBase"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "datastoreId": {
- "description": "ARM resource ID of the datastore where the asset is located.",
- "type": "string",
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "path": {
- "description": "The path of the file/directory in the datastore.",
- "type": "string",
- "x-nullable": true
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
}
},
- "x-ms-discriminator-value": "DataPath",
- "additionalProperties": false
- },
- "DatasetExportSummary": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ExportSummary"
- }
- ],
- "properties": {
- "labeledAssetName": {
- "description": "The unique name of the labeled data asset.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "x-ms-examples": {
+ "Delete Labeling Job.": {
+ "$ref": "./examples/LabelingJob/delete.json"
}
- },
- "x-ms-discriminator-value": "Dataset",
- "additionalProperties": false
+ }
},
- "Datastore": {
- "description": "Base definition for datastore contents configuration.",
- "required": [
- "credentials",
- "datastoreType"
+ "get": {
+ "tags": [
+ "LabelingJob"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ResourceBase"
- }
+ "summary": "Gets a labeling job by name/id.",
+ "operationId": "LabelingJobs_Get",
+ "produces": [
+ "application/json"
],
- "properties": {
- "credentials": {
- "description": "[Required] Account credentials.",
- "$ref": "#/definitions/DatastoreCredentials"
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "datastoreType": {
- "description": "[Required] Storage type backing the datastore.",
- "$ref": "#/definitions/DatastoreType"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the LabelingJob.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "includeJobInstructions",
+ "description": "Boolean value to indicate whether to include JobInstructions in response.",
+ "type": "boolean",
+ "default": false
},
- "isDefault": {
- "description": "Readonly property to indicate if datastore is the workspace default datastore",
+ {
+ "in": "query",
+ "name": "includeLabelCategories",
+ "description": "Boolean value to indicate Whether to include LabelCategories in response.",
"type": "boolean",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "default": false
}
- },
- "discriminator": "datastoreType",
- "x-ms-client-name": "DatastoreProperties"
- },
- "DatastoreCredentials": {
- "description": "Base definition for datastore credentials.",
- "required": [
- "credentialsType"
],
- "type": "object",
- "properties": {
- "credentialsType": {
- "description": "[Required] Credential type used to authentication with storage.",
- "$ref": "#/definitions/CredentialsType"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/LabelingJobResource"
+ }
}
},
- "discriminator": "credentialsType"
+ "x-ms-examples": {
+ "Get Labeling Job.": {
+ "$ref": "./examples/LabelingJob/get.json"
+ }
+ }
},
- "DatastoreResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "put": {
+ "tags": [
+ "LabelingJob"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
+ "summary": "Creates or updates a labeling job (asynchronous).",
+ "operationId": "LabelingJobs_CreateOrUpdate",
+ "consumes": [
+ "application/json"
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/Datastore"
- }
- },
- "x-ms-client-name": "Datastore",
- "additionalProperties": false
- },
- "DatastoreResourceArmPaginatedResult": {
- "description": "A paginated list of Datastore entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of Datastore objects. If null, there are no additional pages.",
- "type": "string"
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "value": {
- "description": "An array of objects of type Datastore.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/DatastoreResource"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the LabelingJob.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "LabelingJob definition object.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/LabelingJobResource"
}
}
- },
- "additionalProperties": false
- },
- "DatastoreSecrets": {
- "description": "Base definition for datastore secrets.",
- "required": [
- "secretsType"
],
- "type": "object",
- "properties": {
- "secretsType": {
- "description": "[Required] Credential type used to authentication with storage.",
- "$ref": "#/definitions/SecretsType"
- }
- },
- "discriminator": "secretsType"
- },
- "DatastoreType": {
- "description": "Enum to determine the datastore contents type.",
- "enum": [
- "AzureBlob",
- "AzureDataLakeGen1",
- "AzureDataLakeGen2",
- "AzureFile",
- "Hdfs"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "DatastoreType",
- "modelAsString": true,
- "values": [
- {
- "value": "AzureBlob"
- },
- {
- "value": "AzureDataLakeGen1"
- },
- {
- "value": "AzureDataLakeGen2"
- },
- {
- "value": "AzureFile"
- },
- {
- "value": "Hdfs"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
- },
- "additionalProperties": false
- },
- "DataType": {
- "description": "Enum to determine the type of data.",
- "enum": [
- "uri_file",
- "uri_folder",
- "mltable"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "DataType",
- "modelAsString": true,
- "values": [
- {
- "value": "uri_file"
- },
- {
- "value": "uri_folder"
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/LabelingJobResource"
},
- {
- "value": "mltable"
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/LabelingJobResource"
}
- ]
- },
- "additionalProperties": false
- },
- "DataVersionBase": {
- "description": "Data version base definition",
- "required": [
- "dataType",
- "dataUri"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetBase"
}
- ],
- "properties": {
- "dataType": {
- "description": "[Required] Specifies the type of data.",
- "$ref": "#/definitions/DataType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "dataUri": {
- "description": "[Required] Uri of the data. Example: https://go.microsoft.com/fwlink/?linkid=2202330",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Labeling Job.": {
+ "$ref": "./examples/LabelingJob/createOrUpdate.json"
}
},
- "discriminator": "dataType",
- "x-ms-client-name": "DataVersionBaseProperties"
- },
- "DataVersionBaseResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}/exportLabels": {
+ "post": {
+ "tags": [
+ "LabelingJob"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
+ "summary": "Export labels from a labeling job (asynchronous).",
+ "operationId": "LabelingJobs_ExportLabels",
+ "consumes": [
+ "application/json"
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/DataVersionBase"
- }
- },
- "x-ms-client-name": "DataVersionBase",
- "additionalProperties": false
- },
- "DataVersionBaseResourceArmPaginatedResult": {
- "description": "A paginated list of DataVersionBase entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of DataVersionBase objects. If null, there are no additional pages.",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the LabelingJob.",
+ "required": true,
"type": "string"
},
- "value": {
- "description": "An array of objects of type DataVersionBase.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/DataVersionBaseResource"
- }
- }
- },
- "additionalProperties": false
- },
- "DefaultScaleSettings": {
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/OnlineScaleSettings"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "The export summary.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ExportSummary"
+ }
}
],
- "x-ms-discriminator-value": "Default",
- "additionalProperties": false
- },
- "DeploymentLogs": {
- "type": "object",
- "properties": {
- "content": {
- "description": "The retrieved online deployment logs.",
- "type": "string",
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "DeploymentLogsRequest": {
- "type": "object",
- "properties": {
- "containerType": {
- "description": "The type of container to retrieve logs from.",
- "default": "InferenceServer",
- "$ref": "#/definitions/ContainerType"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "tail": {
- "format": "int32",
- "description": "The maximum number of lines to tail.",
- "type": "integer",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ExportSummary"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
}
},
- "additionalProperties": false
- },
- "DeploymentProvisioningState": {
- "description": "Possible values for DeploymentProvisioningState.",
- "enum": [
- "Creating",
- "Deleting",
- "Scaling",
- "Updating",
- "Succeeded",
- "Failed",
- "Canceled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "DeploymentProvisioningState",
- "modelAsString": true,
- "values": [
- {
- "value": "Creating"
- },
- {
- "value": "Deleting"
- },
- {
- "value": "Scaling"
- },
- {
- "value": "Updating"
- },
- {
- "value": "Succeeded"
- },
- {
- "value": "Failed"
- },
- {
- "value": "Canceled"
- }
- ]
+ "x-ms-examples": {
+ "ExportLabels Labeling Job.": {
+ "$ref": "./examples/LabelingJob/exportLabels.json"
+ }
},
- "additionalProperties": false
- },
- "DeploymentResourceConfiguration": {
- "type": "object",
- "allOf": [
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}/pause": {
+ "post": {
+ "tags": [
+ "LabelingJob"
+ ],
+ "summary": "Pause a labeling job.",
+ "operationId": "LabelingJobs_Pause",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the LabelingJob.",
+ "required": true,
+ "type": "string"
+ },
{
- "$ref": "#/definitions/ResourceConfiguration"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "additionalProperties": false
- },
- "DistributionConfiguration": {
- "description": "Base definition for job distribution configuration.",
- "required": [
- "distributionType"
- ],
- "type": "object",
- "properties": {
- "distributionType": {
- "description": "[Required] Specifies the type of distribution framework.",
- "$ref": "#/definitions/DistributionType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "distributionType"
- },
- "DistributionType": {
- "description": "Enum to determine the job distribution type.",
- "enum": [
- "PyTorch",
- "TensorFlow",
- "Mpi"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "DistributionType",
- "modelAsString": true,
- "values": [
- {
- "value": "PyTorch"
- },
- {
- "value": "TensorFlow"
- },
- {
- "value": "Mpi"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
+ },
+ "200": {
+ "description": "Success"
+ }
},
- "additionalProperties": false
- },
- "EarlyTerminationPolicy": {
- "description": "Early termination policies enable canceling poor-performing runs before they complete",
- "required": [
- "policyType"
+ "x-ms-examples": {
+ "Pause Labeling Job.": {
+ "$ref": "./examples/LabelingJob/pause.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/labelingJobs/{id}/resume": {
+ "post": {
+ "tags": [
+ "LabelingJob"
],
- "type": "object",
- "properties": {
- "delayEvaluation": {
- "format": "int32",
- "description": "Number of intervals by which to delay the first evaluation.",
- "default": 0,
- "type": "integer"
+ "summary": "Resume a labeling job (asynchronous).",
+ "operationId": "LabelingJobs_Resume",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "evaluationInterval": {
- "format": "int32",
- "description": "Interval (number of runs) between policy evaluations.",
- "default": 0,
- "type": "integer"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "policyType": {
- "description": "[Required] Name of policy configuration",
- "$ref": "#/definitions/EarlyTerminationPolicyType"
+ {
+ "in": "path",
+ "name": "id",
+ "description": "The name and identifier for the LabelingJob.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "discriminator": "policyType"
- },
- "EarlyTerminationPolicyType": {
- "enum": [
- "Bandit",
- "MedianStopping",
- "TruncationSelection"
],
- "type": "string",
- "x-ms-enum": {
- "name": "EarlyTerminationPolicyType",
- "modelAsString": true,
- "values": [
- {
- "value": "Bandit"
- },
- {
- "value": "MedianStopping"
- },
- {
- "value": "TruncationSelection"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
- },
- "additionalProperties": false
- },
- "EgressPublicNetworkAccessType": {
- "description": "Enum to determine whether PublicNetworkAccess is Enabled or Disabled for egress of a deployment.",
- "enum": [
- "Enabled",
- "Disabled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "EgressPublicNetworkAccessType",
- "modelAsString": true,
- "values": [
- {
- "value": "Enabled"
- },
- {
- "value": "Disabled"
+ },
+ "200": {
+ "description": "Success"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
}
- ]
+ }
},
- "additionalProperties": false
- },
- "EmailNotificationEnableType": {
- "description": "Enum to determine the email notification type.",
- "enum": [
- "JobCompleted",
- "JobFailed",
- "JobCancelled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "EmailNotificationEnableType",
- "modelAsString": true,
- "values": [
- {
- "value": "JobCompleted"
- },
- {
- "value": "JobFailed"
- },
- {
- "value": "JobCancelled"
- }
- ]
+ "x-ms-examples": {
+ "Resume Labeling Job.": {
+ "$ref": "./examples/LabelingJob/resume.json"
+ }
},
- "additionalProperties": false
- },
- "EndpointAuthKeys": {
- "description": "Keys for endpoint authentication.",
- "type": "object",
- "properties": {
- "primaryKey": {
- "description": "The primary key.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models": {
+ "get": {
+ "tags": [
+ "ModelContainer"
+ ],
+ "summary": "List model containers.",
+ "operationId": "ModelContainers_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "count",
+ "description": "Maximum number of results to return.",
+ "type": "integer",
+ "format": "int32"
},
- "secondaryKey": {
- "description": "The secondary key.",
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
"type": "string",
- "x-ms-mutability": [
- "create",
- "read"
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
],
- "x-nullable": true
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
+ }
}
- },
- "additionalProperties": false
- },
- "EndpointAuthMode": {
- "description": "Enum to determine endpoint authentication mode.",
- "enum": [
- "AMLToken",
- "Key",
- "AADToken"
],
- "type": "string",
- "x-ms-enum": {
- "name": "EndpointAuthMode",
- "modelAsString": true,
- "values": [
- {
- "value": "AMLToken"
- },
- {
- "value": "Key"
- },
- {
- "value": "AADToken"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResourceArmPaginatedResult"
+ }
+ }
},
- "additionalProperties": false
- },
- "EndpointAuthToken": {
- "description": "Service Token",
- "type": "object",
- "properties": {
- "accessToken": {
- "description": "Access token for endpoint authentication.",
- "type": "string",
- "x-nullable": true
+ "x-ms-examples": {
+ "List Workspace Model Container.": {
+ "$ref": "./examples/Workspace/ModelContainer/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}": {
+ "delete": {
+ "tags": [
+ "ModelContainer"
+ ],
+ "summary": "Delete container.",
+ "operationId": "ModelContainers_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "expiryTimeUtc": {
- "format": "int64",
- "description": "Access token expiry time (UTC).",
- "default": 0,
- "type": "integer"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "refreshAfterTimeUtc": {
- "format": "int64",
- "description": "Refresh access token after time (UTC).",
- "default": 0,
- "type": "integer"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "tokenType": {
- "description": "Access token type.",
- "type": "string",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "additionalProperties": false
- },
- "EndpointComputeType": {
- "description": "Enum to determine endpoint compute type.",
- "enum": [
- "Managed",
- "Kubernetes",
- "AzureMLCompute"
],
- "type": "string",
- "x-ms-enum": {
- "name": "EndpointComputeType",
- "modelAsString": true,
- "values": [
- {
- "value": "Managed"
- },
- {
- "value": "Kubernetes"
- },
- {
- "value": "AzureMLCompute"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
- },
- "additionalProperties": false
- },
- "EndpointDeploymentPropertiesBase": {
- "description": "Base definition for endpoint deployment.",
- "type": "object",
- "properties": {
- "codeConfiguration": {
- "description": "Code configuration for the endpoint deployment.",
- "$ref": "#/definitions/CodeConfiguration",
- "x-nullable": true
- },
- "description": {
- "description": "Description of the endpoint deployment.",
- "type": "string",
- "x-nullable": true
},
- "environmentId": {
- "description": "ARM resource ID of the environment specification for the endpoint deployment.",
- "type": "string",
- "x-nullable": true
- },
- "environmentVariables": {
- "description": "Environment variables configuration for the deployment.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "200": {
+ "description": "Success"
},
- "properties": {
- "description": "Property dictionary. Properties can be added, but not removed or altered.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "204": {
+ "description": "No Content"
}
},
- "additionalProperties": false
+ "x-ms-examples": {
+ "Delete Workspace Model Container.": {
+ "$ref": "./examples/Workspace/ModelContainer/delete.json"
+ }
+ }
},
- "EndpointPropertiesBase": {
- "description": "Inference Endpoint base definition",
- "required": [
- "authMode"
+ "get": {
+ "tags": [
+ "ModelContainer"
],
- "type": "object",
- "properties": {
- "authMode": {
- "description": "[Required] Use 'Key' for key based authentication and 'AMLToken' for Azure Machine Learning token-based authentication. 'Key' doesn't expire but 'AMLToken' does.",
- "$ref": "#/definitions/EndpointAuthMode"
+ "summary": "Get container.",
+ "operationId": "ModelContainers_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "description": {
- "description": "Description of the inference endpoint.",
- "type": "string",
- "x-nullable": true
- },
- "keys": {
- "description": "EndpointAuthKeys to set initially on an Endpoint.\r\nThis property will always be returned as null. AuthKey values must be retrieved using the ListKeys API.",
- "$ref": "#/definitions/EndpointAuthKeys",
- "x-ms-mutability": [
- "create"
- ],
- "x-ms-secret": true,
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "properties": {
- "description": "Property dictionary. Properties can be added, but not removed or altered.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "scoringUri": {
- "format": "uri",
- "description": "Endpoint URI.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "swaggerUri": {
- "format": "uri",
- "description": "Endpoint Swagger URI.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "EndpointProvisioningState": {
- "description": "State of endpoint provisioning.",
- "enum": [
- "Creating",
- "Deleting",
- "Succeeded",
- "Failed",
- "Updating",
- "Canceled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "EndpointProvisioningState",
- "modelAsString": true,
- "values": [
- {
- "value": "Creating"
- },
- {
- "value": "Deleting"
- },
- {
- "value": "Succeeded"
- },
- {
- "value": "Failed"
- },
- {
- "value": "Updating"
- },
- {
- "value": "Canceled"
- }
- ]
- },
- "additionalProperties": false
- },
- "EndpointScheduleAction": {
- "required": [
- "actionType",
- "endpointInvocationDefinition"
- ],
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/ScheduleActionBase"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "endpointInvocationDefinition": {
- "description": "[Required] Defines Schedule action definition details.\r\n",
- "type": "object",
- "example": {
- "endpoint": "azureml:/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/batchEndpoints/hello-pipeline",
- "inputs": {
- "create_time": "${{creation_context.trigger_time}}"
- }
- },
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
+ }
}
},
- "x-ms-discriminator-value": "InvokeBatchEndpoint",
- "additionalProperties": false
- },
- "EnvironmentContainer": {
- "description": "Container for environment specification versions.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetContainer"
- }
- ],
- "properties": {
- "provisioningState": {
- "description": "Provisioning state for the environment container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "x-ms-examples": {
+ "Get Workspace Model Container.": {
+ "$ref": "./examples/Workspace/ModelContainer/get.json"
}
- },
- "x-ms-client-name": "EnvironmentContainerProperties",
- "additionalProperties": false
+ }
},
- "EnvironmentContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "put": {
+ "tags": [
+ "ModelContainer"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
+ "summary": "Create or update container.",
+ "operationId": "ModelContainers_CreateOrUpdate",
+ "consumes": [
+ "application/json"
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/EnvironmentContainer"
- }
- },
- "x-ms-client-name": "EnvironmentContainer",
- "additionalProperties": false
- },
- "EnvironmentContainerResourceArmPaginatedResult": {
- "description": "A paginated list of EnvironmentContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of EnvironmentContainer objects. If null, there are no additional pages.",
- "type": "string"
- },
- "value": {
- "description": "An array of objects of type EnvironmentContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/EnvironmentContainerResource"
- }
- }
- },
- "additionalProperties": false
- },
- "EnvironmentType": {
- "description": "Environment type is either user created or curated by Azure ML service",
- "enum": [
- "Curated",
- "UserCreated"
+ "produces": [
+ "application/json"
],
- "type": "string",
- "x-ms-enum": {
- "name": "EnvironmentType",
- "modelAsString": true,
- "values": [
- {
- "value": "Curated"
- },
- {
- "value": "UserCreated"
- }
- ]
- },
- "additionalProperties": false
- },
- "EnvironmentVersion": {
- "description": "Environment version details.",
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/AssetBase"
- }
- ],
- "properties": {
- "autoRebuild": {
- "description": "Defines if image needs to be rebuilt based on base image changes.",
- "default": "Disabled",
- "$ref": "#/definitions/AutoRebuildSetting",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "build": {
- "description": "Configuration settings for Docker build context.",
- "$ref": "#/definitions/BuildContext",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "condaFile": {
- "description": "Standard configuration file used by Conda that lets you install any kind of package, including Python, R, and C/C++ packages.\r\n",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
- "$ref": "#/definitions/EnvironmentType",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
"type": "string",
- "example": "docker.io/tensorflow/serving:latest",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "inferenceConfig": {
- "description": "Defines configuration specific to inference.",
- "$ref": "#/definitions/InferenceContainerProperties",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "osType": {
- "description": "The OS type of the environment.",
- "default": "Linux",
- "$ref": "#/definitions/OperatingSystemType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "provisioningState": {
- "description": "Provisioning state for the environment version.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- }
- },
- "x-ms-client-name": "EnvironmentVersionProperties",
- "additionalProperties": false
- },
- "EnvironmentVersionResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Container entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
+ }
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/EnvironmentVersion"
- }
- },
- "x-ms-client-name": "EnvironmentVersion",
- "additionalProperties": false
- },
- "EnvironmentVersionResourceArmPaginatedResult": {
- "description": "A paginated list of EnvironmentVersion entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of EnvironmentVersion objects. If null, there are no additional pages.",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type EnvironmentVersion.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/EnvironmentVersionResource"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
+ }
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ModelContainerResource"
}
}
},
- "additionalProperties": false
- },
- "ExportFormatType": {
- "description": "The format of exported labels.",
- "enum": [
- "Dataset",
- "Coco",
- "CSV"
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Model Container.": {
+ "$ref": "./examples/Workspace/ModelContainer/createOrUpdate.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}/versions": {
+ "get": {
+ "tags": [
+ "ModelVersion"
],
- "type": "string",
- "x-ms-enum": {
- "name": "ExportFormatType",
- "modelAsString": true,
- "values": [
- {
- "value": "Dataset"
- },
- {
- "value": "Coco"
- },
- {
- "value": "CSV"
- }
- ]
- },
- "additionalProperties": false
- },
- "ExportSummary": {
- "required": [
- "format"
+ "summary": "List model versions.",
+ "operationId": "ModelVersions_List",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "properties": {
- "endDateTime": {
- "format": "date-time",
- "description": "The time when the export was completed.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Model name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
},
- "exportedRowCount": {
- "format": "int64",
- "description": "The total number of labeled datapoints exported.",
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Maximum number of records to return.",
"type": "integer",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "format": "int32"
},
- "format": {
- "description": "[Required] The format of exported labels, also as the discriminator.",
- "$ref": "#/definitions/ExportFormatType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "in": "query",
+ "name": "version",
+ "description": "Model version.",
+ "type": "string"
},
- "labelingJobId": {
- "description": "Name and identifier of the job containing exported labels.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "in": "query",
+ "name": "description",
+ "description": "Model description.",
+ "type": "string"
},
- "startDateTime": {
- "format": "date-time",
- "description": "The time when the export was requested.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- }
- },
- "discriminator": "format"
- },
- "Feature": {
- "description": "Dto object representing feature",
- "type": "object",
- "properties": {
- "dataType": {
- "description": "Specifies type",
- "default": "String",
- "$ref": "#/definitions/FeatureDataType"
+ {
+ "in": "query",
+ "name": "offset",
+ "description": "Number of initial results to skip.",
+ "type": "integer",
+ "format": "int32"
},
- "description": {
- "description": "Specifies description",
- "type": "string",
- "x-nullable": true
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "Comma-separated list of tag names (and optionally values). Example: tag1,tag2=value2",
+ "type": "string"
},
- "featureName": {
- "description": "Specifies name",
- "type": "string",
- "x-nullable": true
+ {
+ "in": "query",
+ "name": "properties",
+ "description": "Comma-separated list of property names (and optionally values). Example: prop1,prop2=value2",
+ "type": "string"
},
- "tags": {
- "description": "Specifies tags",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "FeatureArmPaginatedResult": {
- "description": "A paginated list of Feature entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of Feature objects. If null, there are no additional pages.",
+ {
+ "in": "query",
+ "name": "feed",
+ "description": "Name of the feed.",
"type": "string"
},
- "value": {
- "description": "An array of objects of type Feature.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/Feature"
- },
- "x-ms-identifiers": []
+ {
+ "in": "query",
+ "name": "stage",
+ "description": "Model stage",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "View type for including/excluding (for example) archived entities.",
+ "type": "string",
+ "default": "ActiveOnly",
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
+ },
+ {
+ "value": "ArchivedOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
+ }
}
- },
- "additionalProperties": false
- },
- "FeatureDataType": {
- "enum": [
- "String",
- "Integer",
- "Long",
- "Float",
- "Double",
- "Binary",
- "Datetime",
- "Boolean"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "FeatureDataType",
- "modelAsString": true,
- "values": [
- {
- "value": "String"
- },
- {
- "value": "Integer"
- },
- {
- "value": "Long"
- },
- {
- "value": "Float"
- },
- {
- "value": "Double"
- },
- {
- "value": "Binary"
- },
- {
- "value": "Datetime"
- },
- {
- "value": "Boolean"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
- },
- "additionalProperties": false
- },
- "FeatureLags": {
- "description": "Flag for generating lags for the numeric features.",
- "enum": [
- "None",
- "Auto"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "FeatureLags",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No feature lags generated."
- },
- {
- "value": "Auto",
- "description": "System auto-generates feature lags."
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResourceArmPaginatedResult"
}
- ]
- },
- "additionalProperties": false
- },
- "FeaturesetContainer": {
- "description": "Dto object representing feature set",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetContainer"
}
- ],
- "properties": {
- "provisioningState": {
- "description": "Provisioning state for the featureset container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ },
+ "x-ms-examples": {
+ "List Workspace Model Version.": {
+ "$ref": "./examples/Workspace/ModelVersion/list.json"
}
},
- "x-ms-client-name": "FeaturesetContainerProperties",
- "additionalProperties": false
- },
- "FeaturesetContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}/versions/{version}": {
+ "delete": {
+ "tags": [
+ "ModelVersion"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
+ "summary": "Delete version.",
+ "operationId": "ModelVersions_Delete",
+ "produces": [
+ "application/json"
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/FeaturesetContainer"
- }
- },
- "x-ms-client-name": "FeaturesetContainer",
- "additionalProperties": false
- },
- "FeaturesetContainerResourceArmPaginatedResult": {
- "description": "A paginated list of FeaturesetContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of FeaturesetContainer objects. If null, there are no additional pages.",
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
"type": "string"
},
- "value": {
- "description": "An array of objects of type FeaturesetContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/FeaturesetContainerResource"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
+ },
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
}
},
- "additionalProperties": false
+ "x-ms-examples": {
+ "Delete Workspace Model Version.": {
+ "$ref": "./examples/Workspace/ModelVersion/delete.json"
+ }
+ }
},
- "FeaturesetJob": {
- "description": "Dto object representing the feature set job",
- "type": "object",
- "properties": {
- "createdDate": {
- "format": "date-time",
- "description": "Specifies the created date",
- "type": "string",
- "x-nullable": true
- },
- "displayName": {
- "description": "Specifies the display name",
- "type": "string",
- "x-nullable": true
- },
- "duration": {
- "format": "duration",
- "description": "Specifies the duration",
- "type": "string",
- "x-nullable": true
+ "get": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "Get version.",
+ "operationId": "ModelVersions_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "experimentId": {
- "description": "Specifies the experiment id",
- "type": "string",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "featureWindow": {
- "description": "Specifies the backfill feature window to be materialized",
- "$ref": "#/definitions/FeatureWindow",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "jobId": {
- "description": "Specifies the job id",
- "type": "string",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "status": {
- "description": "Specifies the job status",
- "default": "Unknown",
- "$ref": "#/definitions/JobStatus"
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
},
- "tags": {
- "description": "Specifies the tags if any",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
- },
- "type": {
- "description": "Specifies the feature store job type",
- "default": "RecurrentMaterialization",
- "$ref": "#/definitions/FeaturestoreJobType"
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "additionalProperties": false
- },
- "FeaturesetJobArmPaginatedResult": {
- "description": "A paginated list of FeaturesetJob entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of FeaturesetJob objects. If null, there are no additional pages.",
- "type": "string"
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type FeaturesetJob.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/FeaturesetJob"
- },
- "x-ms-identifiers": []
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
+ }
}
},
- "additionalProperties": false
- },
- "FeaturesetSpecification": {
- "description": "Dto object representing specification",
- "type": "object",
- "properties": {
- "path": {
- "description": "Specifies the spec path",
- "type": "string",
- "x-nullable": true
+ "x-ms-examples": {
+ "Get Workspace Model Version.": {
+ "$ref": "./examples/Workspace/ModelVersion/get.json"
}
- },
- "additionalProperties": false
+ }
},
- "FeaturesetVersion": {
- "description": "Dto object representing feature set version",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetBase"
- }
+ "put": {
+ "tags": [
+ "ModelVersion"
],
- "properties": {
- "entities": {
- "description": "Specifies list of entities",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-nullable": true
+ "summary": "Create or update version.",
+ "operationId": "ModelVersions_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "materializationSettings": {
- "description": "Specifies the materialization settings",
- "$ref": "#/definitions/MaterializationSettings",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "provisioningState": {
- "description": "Provisioning state for the featureset version container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "specification": {
- "description": "Specifies the feature spec details",
- "$ref": "#/definitions/FeaturesetSpecification",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "stage": {
- "description": "Specifies the asset stage",
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
"type": "string",
- "x-nullable": true
- }
- },
- "x-ms-client-name": "FeaturesetVersionProperties",
- "additionalProperties": false
- },
- "FeaturesetVersionBackfillRequest": {
- "description": "Request payload for creating a backfill request for a given feature set version",
- "type": "object",
- "properties": {
- "description": {
- "description": "Specifies description",
- "type": "string"
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "displayName": {
- "description": "Specifies description",
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
"type": "string"
},
- "featureWindow": {
- "description": "Specifies the backfill feature window to be materialized",
- "$ref": "#/definitions/FeatureWindow",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "resource": {
- "description": "Specifies the compute resource settings",
- "$ref": "#/definitions/MaterializationComputeResource"
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Version entity to create or update.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
+ }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "sparkConfiguration": {
- "description": "Specifies the spark compute settings",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
}
},
- "tags": {
- "description": "Specifies the tags",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ModelVersionResource"
}
}
},
- "additionalProperties": false
- },
- "FeaturesetVersionBackfillResponse": {
- "description": "Response payload for creating a backfill request for a given feature set version",
- "type": "object",
- "properties": {
- "jobId": {
- "description": "Job id created as part of request",
- "type": "string",
- "x-nullable": true
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Model Version.": {
+ "$ref": "./examples/Workspace/ModelVersion/createOrUpdate.json"
}
- },
- "additionalProperties": false
- },
- "FeaturesetVersionResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/models/{name}/versions/{version}/package": {
+ "post": {
+ "tags": [
+ "ModelVersion"
+ ],
+ "summary": "Model Version Package operation.",
+ "operationId": "ModelVersions_Package",
+ "consumes": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Container name. This is case-sensitive.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "in": "path",
+ "name": "version",
+ "description": "Version identifier. This is case-sensitive.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "in": "body",
+ "name": "body",
+ "description": "Package operation request body.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PackageRequest"
+ }
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/FeaturesetVersion"
- }
- },
- "x-ms-client-name": "FeaturesetVersion",
- "additionalProperties": false
- },
- "FeaturesetVersionResourceArmPaginatedResult": {
- "description": "A paginated list of FeaturesetVersion entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of FeaturesetVersion objects. If null, there are no additional pages.",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type FeaturesetVersion.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/FeaturesetVersionResource"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/PackageResponse"
+ }
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
}
}
},
- "additionalProperties": false
- },
- "FeaturestoreEntityContainer": {
- "description": "Dto object representing feature entity",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetContainer"
- }
- ],
- "properties": {
- "provisioningState": {
- "description": "Provisioning state for the featurestore entity container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "x-ms-examples": {
+ "Package Workspace Model Version.": {
+ "$ref": "./examples/Workspace/ModelVersion/package.json"
}
},
- "x-ms-client-name": "FeaturestoreEntityContainerProperties",
- "additionalProperties": false
- },
- "FeaturestoreEntityContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints": {
+ "get": {
+ "tags": [
+ "OnlineEndpoint"
],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
+ "summary": "List Online Endpoints.",
+ "operationId": "OnlineEndpoints_List",
+ "produces": [
+ "application/json"
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/FeaturestoreEntityContainer"
- }
- },
- "x-ms-client-name": "FeaturestoreEntityContainer",
- "additionalProperties": false
- },
- "FeaturestoreEntityContainerResourceArmPaginatedResult": {
- "description": "A paginated list of FeaturestoreEntityContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of FeaturestoreEntityContainer objects. If null, there are no additional pages.",
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "query",
+ "name": "name",
+ "description": "Name of the endpoint.",
"type": "string"
},
- "value": {
- "description": "An array of objects of type FeaturestoreEntityContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/FeaturestoreEntityContainerResource"
+ {
+ "in": "query",
+ "name": "count",
+ "description": "Number of endpoints to be retrieved in a page of results.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "in": "query",
+ "name": "computeType",
+ "description": "EndpointComputeType to be filtered by.",
+ "type": "string",
+ "enum": [
+ "Managed",
+ "Kubernetes",
+ "AzureMLCompute"
+ ],
+ "x-ms-enum": {
+ "name": "EndpointComputeType",
+ "modelAsString": true
}
- }
- },
- "additionalProperties": false
- },
- "FeaturestoreEntityVersion": {
- "description": "Dto object representing feature entity version",
- "type": "object",
- "allOf": [
+ },
{
- "$ref": "#/definitions/AssetBase"
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "tags",
+ "description": "A set of tags with which to filter the returned models. It is a comma separated string of tags key or tags key=value. Example: tagKey1,tagKey2,tagKey3=value3 .",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "properties",
+ "description": "A set of properties with which to filter the returned models. It is a comma separated string of properties key and/or properties key=value Example: propKey1,propKey2,propKey3=value3 .",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "orderBy",
+ "description": "The option to order the response.",
+ "type": "string",
+ "enum": [
+ "CreatedAtDesc",
+ "CreatedAtAsc",
+ "UpdatedAtDesc",
+ "UpdatedAtAsc"
+ ],
+ "x-ms-enum": {
+ "name": "OrderString",
+ "modelAsString": true
+ }
}
],
- "properties": {
- "indexColumns": {
- "description": "Specifies index columns",
- "type": "array",
- "items": {
- "$ref": "#/definitions/IndexColumn"
- },
- "x-nullable": true,
- "x-ms-identifiers": []
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "provisioningState": {
- "description": "Provisioning state for the featurestore entity version.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResourceArmPaginatedResult"
+ }
}
},
- "x-ms-client-name": "FeaturestoreEntityVersionProperties",
- "additionalProperties": false
- },
- "FeaturestoreEntityVersionResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
+ "x-ms-examples": {
+ "List Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}": {
+ "delete": {
+ "tags": [
+ "OnlineEndpoint"
],
- "type": "object",
- "allOf": [
+ "summary": "Delete Online Endpoint (asynchronous).",
+ "operationId": "OnlineEndpoints_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
+ "type": "string"
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/FeaturestoreEntityVersion"
- }
- },
- "x-ms-client-name": "FeaturestoreEntityVersion",
- "additionalProperties": false
- },
- "FeaturestoreEntityVersionResourceArmPaginatedResult": {
- "description": "A paginated list of FeaturestoreEntityVersion entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of FeaturestoreEntityVersion objects. If null, there are no additional pages.",
- "type": "string"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "value": {
- "description": "An array of objects of type FeaturestoreEntityVersion.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/FeaturestoreEntityVersionResource"
+ "204": {
+ "description": "No Content"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
}
+ },
+ "200": {
+ "description": "Success"
}
},
- "additionalProperties": false
- },
- "FeaturestoreJobType": {
- "enum": [
- "RecurrentMaterialization",
- "BackfillMaterialization"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "FeaturestoreJobType",
- "modelAsString": true,
- "values": [
- {
- "value": "RecurrentMaterialization"
- },
- {
- "value": "BackfillMaterialization"
- }
- ]
+ "x-ms-examples": {
+ "Delete Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/delete.json"
+ }
},
- "additionalProperties": false
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
},
- "FeatureWindow": {
- "description": "Specifies the feature window",
- "type": "object",
- "properties": {
- "featureWindowEnd": {
- "format": "date-time",
- "description": "Specifies the feature window end time",
- "type": "string",
- "x-nullable": true
+ "get": {
+ "tags": [
+ "OnlineEndpoint"
+ ],
+ "summary": "Get Online Endpoint.",
+ "operationId": "OnlineEndpoints_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "featureWindowStart": {
- "format": "date-time",
- "description": "Specifies the feature window start time",
- "type": "string",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
- },
- "additionalProperties": false
- },
- "FeaturizationMode": {
- "description": "Featurization mode - determines data featurization mode.",
- "enum": [
- "Auto",
- "Custom",
- "Off"
],
- "type": "string",
- "x-ms-enum": {
- "name": "FeaturizationMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Auto mode, system performs featurization without any custom featurization inputs."
- },
- {
- "value": "Custom",
- "description": "Custom featurization."
- },
- {
- "value": "Off",
- "description": "Featurization off. 'Forecasting' task cannot use this value."
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResource"
}
- ]
- },
- "additionalProperties": false
- },
- "FeaturizationSettings": {
- "description": "Featurization Configuration.",
- "type": "object",
- "properties": {
- "datasetLanguage": {
- "description": "Dataset language, useful for the text data.",
- "type": "string",
- "x-nullable": true
}
},
- "additionalProperties": false
- },
- "FlavorData": {
- "type": "object",
- "properties": {
- "data": {
- "description": "Model flavor-specific data.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "x-ms-examples": {
+ "Get Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/get.json"
}
- },
- "additionalProperties": false
+ }
},
- "ForecastHorizon": {
- "description": "The desired maximum forecast horizon in units of time-series frequency.",
- "required": [
- "mode"
+ "patch": {
+ "tags": [
+ "OnlineEndpoint"
],
- "type": "object",
- "properties": {
- "mode": {
- "description": "[Required] Set forecast horizon value selection mode.",
- "$ref": "#/definitions/ForecastHorizonMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "mode"
- },
- "ForecastHorizonMode": {
- "description": "Enum to determine forecast horizon selection mode.",
- "enum": [
- "Auto",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ForecastHorizonMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Forecast horizon to be determined automatically."
- },
- {
- "value": "Custom",
- "description": "Use the custom forecast horizon."
- }
- ]
- },
- "additionalProperties": false
- },
- "Forecasting": {
- "description": "Forecasting task in AutoML Table vertical.",
- "type": "object",
- "allOf": [
+ "summary": "Update Online Endpoint (asynchronous).",
+ "operationId": "OnlineEndpoints_Update",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
{
- "$ref": "#/definitions/TableVertical"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
{
- "$ref": "#/definitions/AutoMLVertical"
- }
- ],
- "properties": {
- "forecastingSettings": {
- "description": "Forecasting task specific inputs.",
- "$ref": "#/definitions/ForecastingSettings",
- "x-nullable": true
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "primaryMetric": {
- "description": "Primary metric for forecasting task.",
- "default": "NormalizedRootMeanSquaredError",
- "$ref": "#/definitions/ForecastingPrimaryMetrics"
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "trainingSettings": {
- "description": "Inputs for training phase for an AutoML Job.",
- "$ref": "#/definitions/ForecastingTrainingSettings",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Online Endpoint entity to apply during operation.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PartialMinimalTrackedResourceWithIdentity"
+ }
}
- },
- "x-ms-discriminator-value": "Forecasting",
- "additionalProperties": false
- },
- "ForecastingModels": {
- "description": "Enum for all forecasting models supported by AutoML.",
- "enum": [
- "AutoArima",
- "Prophet",
- "Naive",
- "SeasonalNaive",
- "Average",
- "SeasonalAverage",
- "ExponentialSmoothing",
- "Arimax",
- "TCNForecaster",
- "ElasticNet",
- "GradientBoosting",
- "DecisionTree",
- "KNN",
- "LassoLars",
- "SGD",
- "RandomForest",
- "ExtremeRandomTrees",
- "LightGBM",
- "XGBoostRegressor"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ForecastingModels",
- "modelAsString": true,
- "values": [
- {
- "value": "AutoArima",
- "description": "Auto-Autoregressive Integrated Moving Average (ARIMA) model uses time-series data and statistical analysis to interpret the data and make future predictions.\nThis model aims to explain data by using time series data on its past values and uses linear regression to make predictions."
- },
- {
- "value": "Prophet",
- "description": "Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.\nIt works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well."
- },
- {
- "value": "Naive",
- "description": "The Naive forecasting model makes predictions by carrying forward the latest target value for each time-series in the training data."
- },
- {
- "value": "SeasonalNaive",
- "description": "The Seasonal Naive forecasting model makes predictions by carrying forward the latest season of target values for each time-series in the training data."
- },
- {
- "value": "Average",
- "description": "The Average forecasting model makes predictions by carrying forward the average of the target values for each time-series in the training data."
- },
- {
- "value": "SeasonalAverage",
- "description": "The Seasonal Average forecasting model makes predictions by carrying forward the average value of the latest season of data for each time-series in the training data."
- },
- {
- "value": "ExponentialSmoothing",
- "description": "Exponential smoothing is a time series forecasting method for univariate data that can be extended to support data with a systematic trend or seasonal component."
- },
- {
- "value": "Arimax",
- "description": "An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be viewed as a multiple regression model with one or more autoregressive (AR) terms and/or one or more moving average (MA) terms.\nThis method is suitable for forecasting when data is stationary/non stationary, and multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity."
- },
- {
- "value": "TCNForecaster",
- "description": "TCNForecaster: Temporal Convolutional Networks Forecaster. //TODO: Ask forecasting team for brief intro."
- },
- {
- "value": "ElasticNet",
- "description": "Elastic net is a popular type of regularized linear regression that combines two popular penalties, specifically the L1 and L2 penalty functions."
- },
- {
- "value": "GradientBoosting",
- "description": "The technique of transiting week learners into a strong learner is called Boosting. The gradient boosting algorithm process works on this theory of execution."
- },
- {
- "value": "DecisionTree",
- "description": "Decision Trees are a non-parametric supervised learning method used for both classification and regression tasks.\nThe goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features."
- },
- {
- "value": "KNN",
- "description": "K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new datapoints\nwhich further means that the new data point will be assigned a value based on how closely it matches the points in the training set."
- },
- {
- "value": "LassoLars",
- "description": "Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an L1 prior as regularizer."
- },
- {
- "value": "SGD",
- "description": "SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning applications\nto find the model parameters that correspond to the best fit between predicted and actual outputs.\nIt's an inexact but powerful technique."
- },
- {
- "value": "RandomForest",
- "description": "Random forest is a supervised learning algorithm.\nThe \"forest\" it builds, is an ensemble of decision trees, usually trained with the 'bagging' method.\nThe general idea of the bagging method is that a combination of learning models increases the overall result."
- },
- {
- "value": "ExtremeRandomTrees",
- "description": "Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many decision trees. It is related to the widely used random forest algorithm."
- },
- {
- "value": "LightGBM",
- "description": "LightGBM is a gradient boosting framework that uses tree based learning algorithms."
- },
- {
- "value": "XGBoostRegressor",
- "description": "XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model using ensemble of base learners."
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
}
- ]
- },
- "additionalProperties": false
- },
- "ForecastingPrimaryMetrics": {
- "description": "Primary metrics for Forecasting task.",
- "enum": [
- "SpearmanCorrelation",
- "NormalizedRootMeanSquaredError",
- "R2Score",
- "NormalizedMeanAbsoluteError"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ForecastingPrimaryMetrics",
- "modelAsString": true,
- "values": [
- {
- "value": "SpearmanCorrelation",
- "description": "The Spearman's rank coefficient of correlation is a non-parametric measure of rank correlation."
- },
- {
- "value": "NormalizedRootMeanSquaredError",
- "description": "The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between models with different scales."
- },
- {
- "value": "R2Score",
- "description": "The R2 score is one of the performance evaluation measures for forecasting-based machine learning models."
- },
- {
- "value": "NormalizedMeanAbsoluteError",
- "description": "The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute Error (MAE) of (time) series with different scales."
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResource"
}
- ]
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Update Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/update.json"
+ }
},
- "additionalProperties": false
+ "x-ms-long-running-operation": true
},
- "ForecastingSettings": {
- "description": "Forecasting specific parameters.",
- "type": "object",
- "properties": {
- "countryOrRegionForHolidays": {
- "description": "Country or region for holidays for forecasting tasks.\r\nThese should be ISO 3166 two-letter country/region codes, for example 'US' or 'GB'.",
- "type": "string",
- "x-nullable": true
- },
- "cvStepSize": {
- "format": "int32",
- "description": "Number of periods between the origin time of one CV fold and the next fold. For\r\nexample, if `CVStepSize` = 3 for daily data, the origin time for each fold will be\r\nthree days apart.",
- "type": "integer",
- "x-nullable": true
- },
- "featureLags": {
- "description": "Flag for generating lags for the numeric features with 'auto' or null.",
- "default": "None",
- "$ref": "#/definitions/FeatureLags"
- },
- "forecastHorizon": {
- "description": "The desired maximum forecast horizon in units of time-series frequency.",
- "default": "{\"Mode\": \"Custom\", \"Value\": 1}",
- "$ref": "#/definitions/ForecastHorizon"
- },
- "frequency": {
- "description": "When forecasting, this parameter represents the period with which the forecast is desired, for example daily, weekly, yearly, etc. The forecast frequency is dataset frequency by default.",
- "type": "string",
- "x-nullable": true
- },
- "seasonality": {
- "description": "Set time series seasonality as an integer multiple of the series frequency.\r\nIf seasonality is set to 'auto', it will be inferred.",
- "default": "{\"Mode\": \"Auto\"}",
- "$ref": "#/definitions/Seasonality"
- },
- "shortSeriesHandlingConfig": {
- "description": "The parameter defining how if AutoML should handle short time series.",
- "default": "Auto",
- "$ref": "#/definitions/ShortSeriesHandlingConfiguration"
- },
- "targetAggregateFunction": {
- "description": "The function to be used to aggregate the time series target column to conform to a user specified frequency.\r\nIf the TargetAggregateFunction is set i.e. not 'None', but the freq parameter is not set, the error is raised. The possible target aggregation functions are: \"sum\", \"max\", \"min\" and \"mean\".",
- "default": "None",
- "$ref": "#/definitions/TargetAggregationFunction"
+ "put": {
+ "tags": [
+ "OnlineEndpoint"
+ ],
+ "summary": "Create or update Online Endpoint (asynchronous).",
+ "operationId": "OnlineEndpoints_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "targetLags": {
- "description": "The number of past periods to lag from the target column.",
- "$ref": "#/definitions/TargetLags",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "targetRollingWindowSize": {
- "description": "The number of past periods used to create a rolling window average of the target column.",
- "$ref": "#/definitions/TargetRollingWindowSize",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "timeColumnName": {
- "description": "The name of the time column. This parameter is required when forecasting to specify the datetime column in the input data used for building the time series and inferring its frequency.",
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
"type": "string",
- "x-nullable": true
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "timeSeriesIdColumnNames": {
- "description": "The names of columns used to group a timeseries. It can be used to create multiple series.\r\nIf grain is not defined, the data set is assumed to be one time-series. This parameter is used with task type forecasting.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "useStl": {
- "description": "Configure STL Decomposition of the time-series target column.",
- "default": "None",
- "$ref": "#/definitions/UseStl"
- }
- },
- "additionalProperties": false
- },
- "ForecastingTrainingSettings": {
- "description": "Forecasting Training related configuration.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/TrainingSettings"
+ "in": "body",
+ "name": "body",
+ "description": "Online Endpoint entity to apply during operation.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResource"
+ }
}
],
- "properties": {
- "allowedTrainingAlgorithms": {
- "description": "Allowed models for forecasting task.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ForecastingModels"
- },
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "blockedTrainingAlgorithms": {
- "description": "Blocked models for forecasting task.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ForecastingModels"
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResource"
+ }
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResource"
},
- "x-nullable": true
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
+ }
}
},
- "additionalProperties": false
- },
- "GetFeatureRequest": {
- "description": "Request payload to retrieve feature information from a given feature set version",
- "type": "object",
- "properties": {
- "featureName": {
- "description": "Specifies name of the feature.",
- "type": "string",
- "x-nullable": true
+ "x-ms-examples": {
+ "CreateOrUpdate Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/createOrUpdate.json"
}
},
- "additionalProperties": false
- },
- "Goal": {
- "description": "Defines supported metric goals for hyperparameter tuning",
- "enum": [
- "Minimize",
- "Maximize"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "Goal",
- "modelAsString": true,
- "values": [
- {
- "value": "Minimize"
- },
- {
- "value": "Maximize"
- }
- ]
- },
- "additionalProperties": false
- },
- "GridSamplingAlgorithm": {
- "description": "Defines a Sampling Algorithm that exhaustively generates every value combination in the space",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/SamplingAlgorithm"
- }
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments": {
+ "get": {
+ "tags": [
+ "OnlineDeployment"
],
- "x-ms-discriminator-value": "Grid",
- "additionalProperties": false
- },
- "HdfsDatastore": {
- "required": [
- "nameNodeAddress"
+ "summary": "List Inference Endpoint Deployments.",
+ "operationId": "OnlineDeployments_List",
+ "produces": [
+ "application/json"
],
- "type": "object",
- "allOf": [
+ "parameters": [
{
- "$ref": "#/definitions/Datastore"
- }
- ],
- "properties": {
- "hdfsServerCertificate": {
- "description": "The TLS cert of the HDFS server. Needs to be a base64 encoded string. Required if \"Https\" protocol is selected.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "nameNodeAddress": {
- "description": "[Required] IP Address or DNS HostName.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "protocol": {
- "description": "Protocol used to communicate with the storage account (Https/Http).",
- "default": "http",
- "type": "string",
- "example": "https",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "x-ms-discriminator-value": "Hdfs",
- "additionalProperties": false
- },
- "IdAssetReference": {
- "description": "Reference to an asset via its ARM resource ID.",
- "required": [
- "assetId"
- ],
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/AssetReferenceBase"
- }
- ],
- "properties": {
- "assetId": {
- "description": "[Required] ARM resource ID of the asset.",
- "pattern": "[a-zA-Z0-9_]",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name.",
+ "required": true,
"type": "string"
- }
- },
- "x-ms-discriminator-value": "Id",
- "additionalProperties": false
- },
- "IdentityConfiguration": {
- "description": "Base definition for identity configuration.",
- "required": [
- "identityType"
- ],
- "type": "object",
- "properties": {
- "identityType": {
- "description": "[Required] Specifies the type of identity framework.",
- "$ref": "#/definitions/IdentityConfigurationType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "identityType"
- },
- "IdentityConfigurationType": {
- "description": "Enum to determine identity framework.",
- "enum": [
- "Managed",
- "AMLToken",
- "UserIdentity"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "IdentityConfigurationType",
- "modelAsString": true,
- "values": [
- {
- "value": "Managed"
- },
- {
- "value": "AMLToken"
- },
- {
- "value": "UserIdentity"
- }
- ]
- },
- "additionalProperties": false
- },
- "ImageAnnotationType": {
- "description": "Annotation type of image data.",
- "enum": [
- "Classification",
- "BoundingBox",
- "InstanceSegmentation"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ImageAnnotationType",
- "modelAsString": true,
- "values": [
- {
- "value": "Classification"
- },
- {
- "value": "BoundingBox"
- },
- {
- "value": "InstanceSegmentation"
- }
- ]
- },
- "additionalProperties": false
- },
- "ImageClassification": {
- "description": "Image Classification. Multi-class image classification is used when an image is classified with only a single label\r\nfrom a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog' or a 'duck'.",
- "type": "object",
- "allOf": [
+ },
{
- "$ref": "#/definitions/ImageClassificationBase"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
{
- "$ref": "#/definitions/AutoMLVertical"
+ "in": "query",
+ "name": "$orderBy",
+ "description": "Ordering of list.",
+ "type": "string"
+ },
+ {
+ "in": "query",
+ "name": "$top",
+ "description": "Top of list.",
+ "type": "integer",
+ "format": "int32"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
}
],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric to optimize for this task.",
- "default": "Accuracy",
- "$ref": "#/definitions/ClassificationPrimaryMetrics"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResourceArmPaginatedResult"
+ }
}
},
- "x-ms-discriminator-value": "ImageClassification",
- "additionalProperties": false
- },
- "ImageClassificationBase": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ImageVertical"
+ "x-ms-examples": {
+ "List Online Deployments.": {
+ "$ref": "./examples/OnlineDeployment/list.json"
}
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}": {
+ "delete": {
+ "tags": [
+ "OnlineDeployment"
],
- "properties": {
- "modelSettings": {
- "description": "Settings used for training the model.",
- "$ref": "#/definitions/ImageModelSettingsClassification",
- "x-nullable": true
+ "summary": "Delete Inference Endpoint Deployment (asynchronous).",
+ "operationId": "OnlineDeployments_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name.",
+ "required": true,
+ "type": "string"
},
- "searchSpace": {
- "description": "Search space for sampling different combinations of models and their hyperparameters.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ImageModelDistributionSettingsClassification"
- },
- "x-nullable": true,
- "x-ms-identifiers": []
- }
- },
- "additionalProperties": false
- },
- "ImageClassificationMultilabel": {
- "description": "Image Classification Multilabel. Multi-label image classification is used when an image could have one or more labels\r\nfrom a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/ImageClassificationBase"
+ "in": "path",
+ "name": "deploymentName",
+ "description": "Inference Endpoint Deployment name.",
+ "required": true,
+ "type": "string"
},
{
- "$ref": "#/definitions/AutoMLVertical"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric to optimize for this task.",
- "default": "IOU",
- "$ref": "#/definitions/ClassificationMultilabelPrimaryMetrics"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success"
+ },
+ "204": {
+ "description": "No Content"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
}
},
- "x-ms-discriminator-value": "ImageClassificationMultilabel",
- "additionalProperties": false
+ "x-ms-examples": {
+ "Delete Workspace Online Deployment.": {
+ "$ref": "./examples/Workspace/OnlineDeployment/delete.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
},
- "ImageInstanceSegmentation": {
- "description": "Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level,\r\ndrawing a polygon around each object in the image.",
- "type": "object",
- "allOf": [
+ "get": {
+ "tags": [
+ "OnlineDeployment"
+ ],
+ "summary": "Get Inference Deployment Deployment.",
+ "operationId": "OnlineDeployments_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name.",
+ "required": true,
+ "type": "string"
+ },
{
- "$ref": "#/definitions/ImageObjectDetectionBase"
+ "in": "path",
+ "name": "deploymentName",
+ "description": "Inference Endpoint Deployment name.",
+ "required": true,
+ "type": "string"
},
{
- "$ref": "#/definitions/AutoMLVertical"
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
}
],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric to optimize for this task.",
- "default": "MeanAveragePrecision",
- "$ref": "#/definitions/InstanceSegmentationPrimaryMetrics"
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResource"
+ }
}
},
- "x-ms-discriminator-value": "ImageInstanceSegmentation",
- "additionalProperties": false
- },
- "ImageLimitSettings": {
- "description": "Limit settings for the AutoML job.",
- "type": "object",
- "properties": {
- "maxConcurrentTrials": {
- "format": "int32",
- "description": "Maximum number of concurrent AutoML iterations.",
- "default": 1,
- "type": "integer"
- },
- "maxTrials": {
- "format": "int32",
- "description": "Maximum number of AutoML iterations.",
- "default": 1,
- "type": "integer"
+ "x-ms-examples": {
+ "Get Managed Online Deployment.": {
+ "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/get.json"
},
- "timeout": {
- "format": "duration",
- "description": "AutoML job timeout.",
- "default": "P7D",
- "type": "string"
+ "Get Kubernetes Online Deployment.": {
+ "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/get.json"
}
- },
- "additionalProperties": false
+ }
},
- "ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "object",
- "properties": {
- "amsGradient": {
- "description": "Enable AMSGrad when optimizer is 'adam' or 'adamw'.",
- "type": "string",
- "example": "choice(true, false)",
- "x-nullable": true
- },
- "augmentations": {
- "description": "Settings for using Augmentations.",
- "type": "string",
- "example": "choice('hflip;mosaic;random_crop', 'mosaic')",
- "x-nullable": true
+ "patch": {
+ "tags": [
+ "OnlineDeployment"
+ ],
+ "summary": "Update Online Deployment (asynchronous).",
+ "operationId": "OnlineDeployments_Update",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "beta1": {
- "description": "Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
- "type": "string",
- "example": "uniform(0, 1)",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "beta2": {
- "description": "Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
- "type": "string",
- "example": "uniform(0, 1)",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "distributed": {
- "description": "Whether to use distributer training.",
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
"type": "string",
- "example": "choice(true, false)",
- "x-nullable": true
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "earlyStopping": {
- "description": "Enable early stopping logic during training.",
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "Inference Endpoint Deployment name.",
+ "required": true,
"type": "string",
- "example": "choice(true, false)",
- "x-nullable": true
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "earlyStoppingDelay": {
- "description": "Minimum number of epochs or validation evaluations to wait before primary metric improvement\r\nis tracked for early stopping. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 5)",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "earlyStoppingPatience": {
- "description": "Minimum number of epochs or validation evaluations with no primary metric improvement before\r\nthe run is stopped. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 5)",
- "x-nullable": true
- },
- "enableOnnxNormalization": {
- "description": "Enable normalization when exporting ONNX model.",
- "type": "string",
- "example": "choice(true, false)",
- "x-nullable": true
- },
- "evaluationFrequency": {
- "description": "Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 5)",
- "x-nullable": true
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Online Endpoint entity to apply during operation.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/PartialMinimalTrackedResourceWithSku"
+ }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "gradientAccumulationStep": {
- "description": "Gradient accumulation means running a configured number of \"GradAccumulationStep\" steps without\r\nupdating the model weights while accumulating the gradients of those steps, and then using\r\nthe accumulated gradients to compute the weight updates. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 5)",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResource"
+ }
},
- "layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "string",
- "example": "choice(1, 2)",
- "x-nullable": true
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Update Managed Online Deployment.": {
+ "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/update.json"
},
- "learningRate": {
- "description": "Initial learning rate. Must be a float in the range [0, 1].",
- "type": "string",
- "example": "uniform(0.0005, 0.005)",
- "x-nullable": true
+ "Update Kubernetes Online Deployment.": {
+ "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/update.json"
+ }
+ },
+ "x-ms-long-running-operation": true
+ },
+ "put": {
+ "tags": [
+ "OnlineDeployment"
+ ],
+ "summary": "Create or update Inference Endpoint Deployment (asynchronous).",
+ "operationId": "OnlineDeployments_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "learningRateScheduler": {
- "description": "Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.",
- "type": "string",
- "example": "choice('warmup_cosine', 'step')",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "string",
- "example": "choice('seresnext', 'resnest50')",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "momentum": {
- "description": "Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].",
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name.",
+ "required": true,
"type": "string",
- "example": "quniform(0, 1)",
- "x-nullable": true
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "nesterov": {
- "description": "Enable nesterov when optimizer is 'sgd'.",
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "Inference Endpoint Deployment name.",
+ "required": true,
"type": "string",
- "example": "choice(true, false)",
- "x-nullable": true
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
},
- "numberOfEpochs": {
- "description": "Number of training epochs. Must be a positive integer.",
- "type": "string",
- "example": "choice(15, 30)",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "numberOfWorkers": {
- "description": "Number of data loader workers. Must be a non-negative integer.",
- "type": "string",
- "example": "uniform(8, 16)",
- "x-nullable": true
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Inference Endpoint entity to apply during operation.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResource"
+ }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "optimizer": {
- "description": "Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.",
- "type": "string",
- "example": "choice('sgd', 'adam', 'adamw')",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResource"
+ }
},
- "randomSeed": {
- "description": "Random seed to be used when using deterministic training.",
- "type": "string",
- "example": "loguniform(0, 1)",
- "x-nullable": true
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResource"
+ },
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
+ }
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Managed Online Deployment.": {
+ "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/createOrUpdate.json"
},
- "stepLRGamma": {
- "description": "Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1].",
- "type": "string",
- "example": "choice(0.1, 0.2, 0.25)",
- "x-nullable": true
+ "CreateOrUpdate Kubernetes Online Deployment.": {
+ "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}/getLogs": {
+ "post": {
+ "tags": [
+ "OnlineDeployment"
+ ],
+ "summary": "Polls an Endpoint operation.",
+ "operationId": "OnlineDeployments_GetLogs",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "stepLRStepSize": {
- "description": "Value of step size when learning rate scheduler is 'step'. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 2, 3)",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "trainingBatchSize": {
- "description": "Training batch size. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 2, 3)",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "validationBatchSize": {
- "description": "Validation batch size. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 2, 3)",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name.",
+ "required": true,
+ "type": "string"
},
- "warmupCosineLRCycles": {
- "description": "Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1].",
- "type": "string",
- "example": "uniform(0, 1)",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "The name and identifier for the endpoint.",
+ "required": true,
+ "type": "string"
},
- "warmupCosineLRWarmupEpochs": {
- "description": "Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.",
- "type": "string",
- "example": "choice(1, 2, 3)",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "weightDecay": {
- "description": "Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1].",
- "type": "string",
- "example": "uniform(0, 1)",
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/ImageModelDistributionSettings"
+ "in": "body",
+ "name": "body",
+ "description": "The request containing parameters for retrieving logs.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/DeploymentLogsRequest"
+ }
}
],
- "properties": {
- "trainingCropSize": {
- "description": "Image crop size that is input to the neural network for the training dataset. Must be a positive integer.",
- "type": "string",
- "example": "choice(224, 360)",
- "x-nullable": true
- },
- "validationCropSize": {
- "description": "Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.",
- "type": "string",
- "example": "choice(224, 360)",
- "x-nullable": true
- },
- "validationResizeSize": {
- "description": "Image size to which to resize before cropping for validation dataset. Must be a positive integer.",
- "type": "string",
- "example": "choice(128, 256)",
- "x-nullable": true
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "weightedLoss": {
- "description": "Weighted loss. The accepted values are 0 for no weighted loss.\r\n1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be 0 or 1 or 2.",
- "type": "string",
- "example": "choice(0, 1, 2)",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/DeploymentLogs"
+ }
}
},
- "additionalProperties": false
- },
- "ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ImageModelDistributionSettings"
+ "x-ms-examples": {
+ "Get Online Deployment Logs.": {
+ "$ref": "./examples/OnlineDeployment/getLogs.json"
}
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/deployments/{deploymentName}/skus": {
+ "get": {
+ "tags": [
+ "OnlineDeployment"
],
- "properties": {
- "boxDetectionsPerImage": {
- "description": "Maximum number of detections per image, for all classes. Must be a positive integer.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice(50, 100)",
- "x-nullable": true
- },
- "boxScoreThreshold": {
- "description": "During inference, only return proposals with a classification score greater than\r\nBoxScoreThreshold. Must be a float in the range[0, 1].",
- "type": "string",
- "example": "uniform(0.1, 0.2)",
- "x-nullable": true
- },
- "imageSize": {
- "description": "Image size for train and validation. Must be a positive integer.\r\nNote: The training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice(224, 640)",
- "x-nullable": true
- },
- "maxSize": {
- "description": "Maximum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice(640, 1333)",
- "x-nullable": true
+ "summary": "List Inference Endpoint Deployment Skus.",
+ "operationId": "OnlineDeployments_ListSkus",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "minSize": {
- "description": "Minimum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice(300, 600)",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "modelSize": {
- "description": "Model size. Must be 'small', 'medium', 'large', or 'xlarge'.\r\nNote: training run may get into CUDA OOM if the model size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice('small', 'medium', 'large', 'xlarge')",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "multiScale": {
- "description": "Enable multi-scale image by varying image size by +/- 50%.\r\nNote: training run may get into CUDA OOM if no sufficient GPU memory.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice(true, false)",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Inference endpoint name.",
+ "required": true,
+ "type": "string"
},
- "nmsIouThreshold": {
- "description": "IOU threshold used during inference in NMS post processing. Must be float in the range [0, 1].",
- "type": "string",
- "example": "uniform(0.1, 0.2)",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "deploymentName",
+ "description": "Inference Endpoint Deployment name.",
+ "required": true,
+ "type": "string"
},
- "tileGridSize": {
- "description": "The grid size to use for tiling each image. Note: TileGridSize must not be\r\nNone to enable small object detection logic. A string containing two integers in mxn format.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "choice('3x2', '2x2')",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "tileOverlapRatio": {
- "description": "Overlap ratio between adjacent tiles in each dimension. Must be float in the range [0, 1).\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "string",
- "example": "uniform(0.1, 0.2)",
- "x-nullable": true
+ {
+ "in": "query",
+ "name": "count",
+ "description": "Number of Skus to be retrieved in a page of results.",
+ "type": "integer",
+ "format": "int32"
},
- "tilePredictionsNmsThreshold": {
- "description": "The IOU threshold to use to perform NMS while merging predictions from tiles and image.\r\nUsed in validation/ inference. Must be float in the range [0, 1].\r\nNote: This settings is not supported for the 'yolov5' algorithm.\r\nNMS: Non-maximum suppression",
- "type": "string",
- "example": "uniform(0.2, 0.3)",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "validationIouThreshold": {
- "description": "IOU threshold to use when computing validation metric. Must be float in the range [0, 1].",
- "type": "string",
- "example": "uniform(0.2, 0.3)",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/SkuResourceArmPaginatedResult"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "List Managed Online Deployment Skus.": {
+ "$ref": "./examples/OnlineDeployment/ManagedOnlineDeployment/listSkus.json"
},
- "validationMetricType": {
- "description": "Metric computation method to use for validation metrics. Must be 'none', 'coco', 'voc', or 'coco_voc'.",
- "type": "string",
- "example": "choice('none', 'coco', 'voc', 'coco_voc')",
- "x-nullable": true
+ "List Kubernetes Online Deployment Skus.": {
+ "$ref": "./examples/OnlineDeployment/KubernetesOnlineDeployment/listSkus.json"
}
},
- "additionalProperties": false
- },
- "ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "object",
- "properties": {
- "advancedSettings": {
- "description": "Settings for advanced scenarios.",
- "type": "string",
- "example": "key1:val1;key2;key3:val3;key4",
- "x-nullable": true
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/listKeys": {
+ "post": {
+ "tags": [
+ "OnlineEndpoint"
+ ],
+ "summary": "List EndpointAuthKeys for an Endpoint using Key-based authentication.",
+ "operationId": "OnlineEndpoints_ListKeys",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "amsGradient": {
- "description": "Enable AMSGrad when optimizer is 'adam' or 'adamw'.",
- "type": "boolean",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "augmentations": {
- "description": "Settings for using Augmentations.",
- "type": "string",
- "example": "hflip;mosaic;random_crop",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "beta1": {
- "format": "float",
- "description": "Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
+ "type": "string"
},
- "beta2": {
- "format": "float",
- "description": "Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "checkpointFrequency": {
- "format": "int32",
- "description": "Frequency to store model checkpoints. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EndpointAuthKeys"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "ListKeys Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/listKeys.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/regenerateKeys": {
+ "post": {
+ "tags": [
+ "OnlineEndpoint"
+ ],
+ "summary": "Regenerate EndpointAuthKeys for an Endpoint using Key-based authentication (asynchronous).",
+ "operationId": "OnlineEndpoints_RegenerateKeys",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "checkpointModel": {
- "description": "The pretrained checkpoint model for incremental training.",
- "$ref": "#/definitions/MLFlowModelJobInput",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "checkpointRunId": {
- "description": "The id of a previous run that has a pretrained checkpoint for incremental training.",
- "type": "string",
- "x-nullable": true
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
},
- "distributed": {
- "description": "Whether to use distributed training.",
- "type": "boolean",
- "x-nullable": true
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
+ "type": "string"
},
- "earlyStopping": {
- "description": "Enable early stopping logic during training.",
- "type": "boolean",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
},
- "earlyStoppingDelay": {
- "format": "int32",
- "description": "Minimum number of epochs or validation evaluations to wait before primary metric improvement\r\nis tracked for early stopping. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "in": "body",
+ "name": "body",
+ "description": "RegenerateKeys request .",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/RegenerateEndpointKeysRequest"
+ }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
},
- "earlyStoppingPatience": {
- "format": "int32",
- "description": "Minimum number of epochs or validation evaluations with no primary metric improvement before\r\nthe run is stopped. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ "200": {
+ "description": "Success"
},
- "enableOnnxNormalization": {
- "description": "Enable normalization when exporting ONNX model.",
- "type": "boolean",
- "x-nullable": true
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
+ }
+ },
+ "x-ms-examples": {
+ "RegenerateKeys Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/regenerateKeys.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/onlineEndpoints/{endpointName}/token": {
+ "post": {
+ "tags": [
+ "OnlineEndpoint"
+ ],
+ "summary": "Retrieve a valid AML token for an Endpoint using AMLToken-based authentication.",
+ "operationId": "OnlineEndpoints_GetToken",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
},
- "evaluationFrequency": {
- "format": "int32",
- "description": "Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
},
- "gradientAccumulationStep": {
- "format": "int32",
- "description": "Gradient accumulation means running a configured number of \"GradAccumulationStep\" steps without\r\nupdating the model weights while accumulating the gradients of those steps, and then using\r\nthe accumulated gradients to compute the weight updates. Must be a positive integer.",
- "type": "integer",
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "endpointName",
+ "description": "Online Endpoint name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/EndpointAuthToken"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "GetToken Workspace Online Endpoint.": {
+ "$ref": "./examples/Workspace/OnlineEndpoint/getToken.json"
+ }
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/schedules": {
+ "get": {
+ "tags": [
+ "Schedule"
+ ],
+ "summary": "List schedules in specified workspace.",
+ "operationId": "Schedules_List",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/PaginationParameter"
+ },
+ {
+ "in": "query",
+ "name": "listViewType",
+ "description": "Status filter for schedule.",
+ "type": "string",
+ "default": "EnabledOnly",
+ "enum": [
+ "EnabledOnly",
+ "DisabledOnly",
+ "All"
+ ],
+ "x-ms-enum": {
+ "name": "ScheduleListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "EnabledOnly"
+ },
+ {
+ "value": "DisabledOnly"
+ },
+ {
+ "value": "All"
+ }
+ ]
+ }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ScheduleResourceArmPaginatedResult"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "List Schedules.": {
+ "$ref": "./examples/Schedule/list.json"
+ }
+ },
+ "x-ms-pageable": {
+ "nextLinkName": "nextLink"
+ }
+ }
+ },
+ "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/schedules/{name}": {
+ "delete": {
+ "tags": [
+ "Schedule"
+ ],
+ "summary": "Delete schedule.",
+ "operationId": "Schedules_Delete",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Schedule name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success"
+ },
+ "202": {
+ "description": "Accepted",
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Location": {
+ "description": "URI to poll for asynchronous operation result.",
+ "type": "string"
+ },
+ "Retry-After": {
+ "description": "Duration the client should wait between requests, in seconds.",
+ "type": "integer",
+ "format": "int32",
+ "maximum": 600,
+ "minimum": 10
+ }
+ }
+ },
+ "204": {
+ "description": "No Content"
+ }
+ },
+ "x-ms-examples": {
+ "Delete Schedule.": {
+ "$ref": "./examples/Schedule/delete.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "location"
+ }
+ },
+ "get": {
+ "tags": [
+ "Schedule"
+ ],
+ "summary": "Get schedule.",
+ "operationId": "Schedules_Get",
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Schedule name.",
+ "required": true,
+ "type": "string"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ScheduleResource"
+ }
+ }
+ },
+ "x-ms-examples": {
+ "Get Schedule.": {
+ "$ref": "./examples/Schedule/get.json"
+ }
+ }
+ },
+ "put": {
+ "tags": [
+ "Schedule"
+ ],
+ "summary": "Create or update schedule.",
+ "operationId": "Schedules_CreateOrUpdate",
+ "consumes": [
+ "application/json"
+ ],
+ "produces": [
+ "application/json"
+ ],
+ "parameters": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/SubscriptionIdParameter"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ResourceGroupNameParameter"
+ },
+ {
+ "$ref": "machineLearningServices.json#/parameters/WorkspaceNameParameter"
+ },
+ {
+ "in": "path",
+ "name": "name",
+ "description": "Schedule name.",
+ "required": true,
+ "type": "string",
+ "pattern": "^[a-zA-Z0-9][a-zA-Z0-9\\-_]{0,254}$"
+ },
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/parameters/ApiVersionParameter"
+ },
+ {
+ "in": "body",
+ "name": "body",
+ "description": "Schedule definition.",
+ "required": true,
+ "schema": {
+ "$ref": "#/definitions/ScheduleResource"
+ }
+ }
+ ],
+ "responses": {
+ "default": {
+ "description": "Error",
+ "schema": {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/ErrorResponse"
+ }
+ },
+ "200": {
+ "description": "Success",
+ "schema": {
+ "$ref": "#/definitions/ScheduleResource"
+ }
+ },
+ "201": {
+ "description": "Created",
+ "schema": {
+ "$ref": "#/definitions/ScheduleResource"
+ },
+ "headers": {
+ "x-ms-async-operation-timeout": {
+ "description": "Timeout for the client to use when polling the asynchronous operation.",
+ "type": "string",
+ "format": "duration"
+ },
+ "Azure-AsyncOperation": {
+ "description": "URI to poll for asynchronous operation status.",
+ "type": "string"
+ }
+ }
+ }
+ },
+ "x-ms-examples": {
+ "CreateOrUpdate Schedule.": {
+ "$ref": "./examples/Schedule/createOrUpdate.json"
+ }
+ },
+ "x-ms-long-running-operation": true,
+ "x-ms-long-running-operation-options": {
+ "final-state-via": "original-uri"
+ }
+ }
+ }
+ },
+ "definitions": {
+ "AccountKeyDatastoreCredentials": {
+ "description": "Account key datastore credentials configuration.",
+ "required": [
+ "secrets"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "properties": {
+ "secrets": {
+ "description": "[Required] Storage account secrets.",
+ "$ref": "#/definitions/AccountKeyDatastoreSecrets",
+ "x-ms-mutability": [
+ "create",
+ "update"
+ ],
+ "x-ms-secret": true
+ }
+ },
+ "x-ms-discriminator-value": "AccountKey",
+ "additionalProperties": false
+ },
+ "AccountKeyDatastoreSecrets": {
+ "description": "Datastore account key secrets.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreSecrets"
+ }
+ ],
+ "properties": {
+ "key": {
+ "description": "Storage account key.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "AccountKey",
+ "additionalProperties": false
+ },
+ "AllFeatures": {
+ "required": [
+ "filterType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringFeatureFilterBase"
+ }
+ ],
+ "x-ms-discriminator-value": "AllFeatures",
+ "additionalProperties": false
+ },
+ "AllNodes": {
+ "description": "All nodes means the service will be running on all of the nodes of the job",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/Nodes"
+ }
+ ],
+ "x-ms-discriminator-value": "All",
+ "additionalProperties": false
+ },
+ "AmlToken": {
+ "description": "AML Token identity configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/IdentityConfiguration"
+ }
+ ],
+ "x-ms-discriminator-value": "AMLToken",
+ "additionalProperties": false
+ },
+ "AssetBase": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceBase"
+ }
+ ],
+ "properties": {
+ "autoDeleteSetting": {
+ "description": "Specifies the lifecycle setting of managed data asset.",
+ "$ref": "#/definitions/AutoDeleteSetting",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ },
+ "isAnonymous": {
+ "description": "If the name version are system generated (anonymous registration). For types where Stage is defined, when Stage is provided it will be used to populate IsAnonymous",
+ "default": false,
+ "type": "boolean",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "isArchived": {
+ "description": "Is the asset archived? For types where Stage is defined, when Stage is provided it will be used to populate IsArchived",
+ "default": false,
+ "type": "boolean",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "AssetContainer": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceBase"
+ }
+ ],
+ "properties": {
+ "isArchived": {
+ "description": "Is the asset archived?",
+ "default": false,
+ "type": "boolean",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ },
+ "latestVersion": {
+ "description": "The latest version inside this container.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "nextVersion": {
+ "description": "The next auto incremental version",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "AssetJobInput": {
+ "description": "Asset input type.",
+ "required": [
+ "uri"
+ ],
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "Input Asset Delivery Mode.",
+ "default": "ReadOnlyMount",
+ "$ref": "#/definitions/InputDeliveryMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "uri": {
+ "description": "[Required] Input Asset URI.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ },
+ "AssetJobOutput": {
+ "description": "Asset output type.",
+ "type": "object",
+ "properties": {
+ "assetName": {
+ "description": "Output Asset Name.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "assetVersion": {
+ "description": "Output Asset Version.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "autoDeleteSetting": {
+ "description": "Auto delete setting of output data asset.",
+ "$ref": "#/definitions/AutoDeleteSetting",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ },
+ "mode": {
+ "description": "Output Asset Delivery Mode.",
+ "default": "ReadWriteMount",
+ "$ref": "#/definitions/OutputDeliveryMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "uri": {
+ "description": "Output Asset URI.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "AssetProvisioningState": {
+ "description": "Provisioning state of registry asset.",
+ "enum": [
+ "Succeeded",
+ "Failed",
+ "Canceled",
+ "Creating",
+ "Updating",
+ "Deleting"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "AssetProvisioningState",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Succeeded"
+ },
+ {
+ "value": "Failed"
+ },
+ {
+ "value": "Canceled"
+ },
+ {
+ "value": "Creating"
+ },
+ {
+ "value": "Updating"
+ },
+ {
+ "value": "Deleting"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "AssetReferenceBase": {
+ "description": "Base definition for asset references.",
+ "required": [
+ "referenceType"
+ ],
+ "type": "object",
+ "properties": {
+ "referenceType": {
+ "description": "[Required] Specifies the type of asset reference.",
+ "$ref": "#/definitions/ReferenceType"
+ }
+ },
+ "discriminator": "referenceType"
+ },
+ "AutoDeleteCondition": {
+ "enum": [
+ "CreatedGreaterThan",
+ "LastAccessedGreaterThan"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "AutoDeleteCondition",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "CreatedGreaterThan"
+ },
+ {
+ "value": "LastAccessedGreaterThan"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "AutoDeleteSetting": {
+ "type": "object",
+ "properties": {
+ "condition": {
+ "description": "When to check if an asset is expired",
+ "default": "CreatedGreaterThan",
+ "$ref": "#/definitions/AutoDeleteCondition",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ },
+ "value": {
+ "description": "Expiration condition value.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "AutoForecastHorizon": {
+ "description": "Forecast horizon determined automatically by system.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ForecastHorizon"
+ }
+ ],
+ "x-ms-discriminator-value": "Auto",
+ "additionalProperties": false
+ },
+ "AutoMLJob": {
+ "description": "AutoMLJob class.\r\nUse this class for executing AutoML tasks like Classification/Regression etc.\r\nSee TaskType enum for all the tasks supported.",
+ "required": [
+ "taskDetails"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobBase"
+ }
+ ],
+ "properties": {
+ "environmentId": {
+ "description": "The ARM resource ID of the Environment specification for the job.\r\nThis is optional value to provide, if not provided, AutoML will default this to Production AutoML curated environment version when running the job.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "environmentVariables": {
+ "description": "Environment variables included in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "outputs": {
+ "description": "Mapping of output data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Job output definition container information on where to find job output/logs.",
+ "$ref": "#/definitions/JobOutput",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "queueSettings": {
+ "description": "Queue settings for the job",
+ "$ref": "#/definitions/QueueSettings",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "resources": {
+ "description": "Compute Resource configuration for the job.",
+ "default": "{}",
+ "$ref": "#/definitions/JobResourceConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "taskDetails": {
+ "description": "[Required] This represents scenario which can be one of Tables/NLP/Image",
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ },
+ "x-ms-discriminator-value": "AutoML",
+ "additionalProperties": false
+ },
+ "AutoMLVertical": {
+ "description": "AutoML vertical class.\r\nBase class for AutoML verticals - TableVertical/ImageVertical/NLPVertical",
+ "required": [
+ "taskType",
+ "trainingData"
+ ],
+ "type": "object",
+ "properties": {
+ "logVerbosity": {
+ "description": "Log verbosity for the job.",
+ "default": "Info",
+ "$ref": "#/definitions/LogVerbosity"
+ },
+ "targetColumnName": {
+ "description": "Target column name: This is prediction values column.\r\nAlso known as label column name in context of classification tasks.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "taskType": {
+ "description": "[Required] Task type for AutoMLJob.",
+ "$ref": "#/definitions/TaskType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "trainingData": {
+ "description": "[Required] Training data input.",
+ "$ref": "#/definitions/MLTableJobInput"
+ }
+ },
+ "discriminator": "taskType"
+ },
+ "AutoNCrossValidations": {
+ "description": "N-Cross validations determined automatically.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/NCrossValidations"
+ }
+ ],
+ "x-ms-discriminator-value": "Auto",
+ "additionalProperties": false
+ },
+ "AutoRebuildSetting": {
+ "description": "AutoRebuild setting for the derived image",
+ "enum": [
+ "Disabled",
+ "OnBaseImageUpdate"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "AutoRebuildSetting",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Disabled"
+ },
+ {
+ "value": "OnBaseImageUpdate"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "AutoSeasonality": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/Seasonality"
+ }
+ ],
+ "x-ms-discriminator-value": "Auto",
+ "additionalProperties": false
+ },
+ "AutoTargetLags": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TargetLags"
+ }
+ ],
+ "x-ms-discriminator-value": "Auto",
+ "additionalProperties": false
+ },
+ "AutoTargetRollingWindowSize": {
+ "description": "Target lags rolling window determined automatically.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TargetRollingWindowSize"
+ }
+ ],
+ "x-ms-discriminator-value": "Auto",
+ "additionalProperties": false
+ },
+ "AutologgerSettings": {
+ "description": "Settings for Autologger.",
+ "required": [
+ "mlflowAutologger"
+ ],
+ "type": "object",
+ "properties": {
+ "mlflowAutologger": {
+ "description": "[Required] Indicates whether mlflow autologger is enabled.",
+ "$ref": "#/definitions/MLFlowAutologgerState",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "AzureBlobDatastore": {
+ "description": "Azure Blob datastore configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AzureDatastore"
+ },
+ {
+ "$ref": "#/definitions/Datastore"
+ }
+ ],
+ "properties": {
+ "accountName": {
+ "description": "Storage account name.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "containerName": {
+ "description": "Storage account container name.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "endpoint": {
+ "description": "Azure cloud endpoint for the storage account.",
+ "type": "string",
+ "example": "core.windows.net",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "protocol": {
+ "description": "Protocol used to communicate with the storage account.",
+ "type": "string",
+ "example": "https",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "serviceDataAccessAuthIdentity": {
+ "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
+ "default": "None",
+ "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "AzureBlob",
+ "additionalProperties": false
+ },
+ "AzureDataLakeGen1Datastore": {
+ "description": "Azure Data Lake Gen1 datastore configuration.",
+ "required": [
+ "storeName"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AzureDatastore"
+ },
+ {
+ "$ref": "#/definitions/Datastore"
+ }
+ ],
+ "properties": {
+ "serviceDataAccessAuthIdentity": {
+ "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
+ "default": "None",
+ "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "storeName": {
+ "description": "[Required] Azure Data Lake store name.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "AzureDataLakeGen1",
+ "additionalProperties": false
+ },
+ "AzureDataLakeGen2Datastore": {
+ "description": "Azure Data Lake Gen2 datastore configuration.",
+ "required": [
+ "accountName",
+ "filesystem"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AzureDatastore"
+ },
+ {
+ "$ref": "#/definitions/Datastore"
+ }
+ ],
+ "properties": {
+ "accountName": {
+ "description": "[Required] Storage account name.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "endpoint": {
+ "description": "Azure cloud endpoint for the storage account.",
+ "type": "string",
+ "example": "core.windows.net",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "filesystem": {
+ "description": "[Required] The name of the Data Lake Gen2 filesystem.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "protocol": {
+ "description": "Protocol used to communicate with the storage account.",
+ "type": "string",
+ "example": "https",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "serviceDataAccessAuthIdentity": {
+ "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
+ "default": "None",
+ "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "AzureDataLakeGen2",
+ "additionalProperties": false
+ },
+ "AzureDatastore": {
+ "description": "Base definition for Azure datastore contents configuration.",
+ "type": "object",
+ "properties": {
+ "resourceGroup": {
+ "description": "Azure Resource Group name",
+ "type": "string",
+ "x-nullable": true
+ },
+ "subscriptionId": {
+ "description": "Azure Subscription Id",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "AzureDevOpsWebhook": {
+ "description": "Webhook details specific for Azure DevOps",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/Webhook"
+ }
+ ],
+ "x-ms-discriminator-value": "AzureDevOps",
+ "additionalProperties": false
+ },
+ "AzureFileDatastore": {
+ "description": "Azure File datastore configuration.",
+ "required": [
+ "accountName",
+ "fileShareName"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AzureDatastore"
+ },
+ {
+ "$ref": "#/definitions/Datastore"
+ }
+ ],
+ "properties": {
+ "accountName": {
+ "description": "[Required] Storage account name.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "endpoint": {
+ "description": "Azure cloud endpoint for the storage account.",
+ "type": "string",
+ "example": "core.windows.net",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "fileShareName": {
+ "description": "[Required] The name of the Azure file share that the datastore points to.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "protocol": {
+ "description": "Protocol used to communicate with the storage account.",
+ "type": "string",
+ "example": "https",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "serviceDataAccessAuthIdentity": {
+ "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
+ "default": "None",
+ "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "AzureFile",
+ "additionalProperties": false
+ },
+ "AzureMLBatchInferencingServer": {
+ "description": "Azure ML batch inferencing server configurations.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/InferencingServer"
+ }
+ ],
+ "properties": {
+ "codeConfiguration": {
+ "description": "Code configuration for AML batch inferencing server.",
+ "$ref": "#/definitions/CodeConfiguration",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "AzureMLBatch",
+ "additionalProperties": false
+ },
+ "AzureMLOnlineInferencingServer": {
+ "description": "Azure ML online inferencing configurations.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/InferencingServer"
+ }
+ ],
+ "properties": {
+ "codeConfiguration": {
+ "description": "Code configuration for AML inferencing server.",
+ "$ref": "#/definitions/CodeConfiguration",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "AzureMLOnline",
+ "additionalProperties": false
+ },
+ "BanditPolicy": {
+ "description": "Defines an early termination policy based on slack criteria, and a frequency and delay interval for evaluation",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EarlyTerminationPolicy"
+ }
+ ],
+ "properties": {
+ "slackAmount": {
+ "format": "float",
+ "description": "Absolute distance allowed from the best performing run.",
+ "default": 0,
+ "type": "number"
+ },
+ "slackFactor": {
+ "format": "float",
+ "description": "Ratio of the allowed distance from the best performing run.",
+ "default": 0,
+ "type": "number"
+ }
+ },
+ "x-ms-discriminator-value": "Bandit",
+ "additionalProperties": false
+ },
+ "BaseEnvironmentId": {
+ "description": "Base environment type.",
+ "required": [
+ "resourceId"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/BaseEnvironmentSource"
+ }
+ ],
+ "properties": {
+ "resourceId": {
+ "description": "[Required] Resource id accepting ArmId or AzureMlId.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
+ },
+ "x-ms-discriminator-value": "EnvironmentAsset",
+ "additionalProperties": false
+ },
+ "BaseEnvironmentSource": {
+ "required": [
+ "baseEnvironmentSourceType"
+ ],
+ "type": "object",
+ "properties": {
+ "baseEnvironmentSourceType": {
+ "description": "[Required] Base environment type.",
+ "$ref": "#/definitions/BaseEnvironmentSourceType"
+ }
+ },
+ "discriminator": "baseEnvironmentSourceType"
+ },
+ "BaseEnvironmentSourceType": {
+ "description": "Base environment type.",
+ "enum": [
+ "EnvironmentAsset"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "BaseEnvironmentSourceType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "EnvironmentAsset"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "BatchDeployment": {
+ "description": "Batch inference settings per deployment.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EndpointDeploymentPropertiesBase"
+ }
+ ],
+ "properties": {
+ "compute": {
+ "description": "Compute target for batch inference operation.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "deploymentConfiguration": {
+ "description": "Properties relevant to different deployment types.",
+ "$ref": "#/definitions/BatchDeploymentConfiguration",
+ "x-nullable": true
+ },
+ "errorThreshold": {
+ "format": "int32",
+ "description": "Error threshold, if the error count for the entire input goes above this value,\r\nthe batch inference will be aborted. Range is [-1, int.MaxValue].\r\nFor FileDataset, this value is the count of file failures.\r\nFor TabularDataset, this value is the count of record failures.\r\nIf set to -1 (the lower bound), all failures during batch inference will be ignored.",
+ "default": -1,
+ "type": "integer"
+ },
+ "loggingLevel": {
+ "description": "Logging level for batch inference operation.",
+ "default": "Info",
+ "$ref": "#/definitions/BatchLoggingLevel"
+ },
+ "maxConcurrencyPerInstance": {
+ "format": "int32",
+ "description": "Indicates maximum number of parallelism per instance.",
+ "default": 1,
+ "type": "integer"
+ },
+ "miniBatchSize": {
+ "format": "int64",
+ "description": "Size of the mini-batch passed to each batch invocation.\r\nFor FileDataset, this is the number of files per mini-batch.\r\nFor TabularDataset, this is the size of the records in bytes, per mini-batch.",
+ "default": 10,
+ "type": "integer"
+ },
+ "model": {
+ "description": "Reference to the model asset for the endpoint deployment.",
+ "$ref": "#/definitions/AssetReferenceBase",
+ "x-nullable": true
+ },
+ "outputAction": {
+ "description": "Indicates how the output will be organized.",
+ "default": "AppendRow",
+ "$ref": "#/definitions/BatchOutputAction"
+ },
+ "outputFileName": {
+ "description": "Customized output file name for append_row output action.",
+ "default": "predictions.csv",
+ "type": "string"
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the endpoint deployment.",
+ "$ref": "#/definitions/DeploymentProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ },
+ "resources": {
+ "description": "Indicates compute configuration for the job.\r\nIf not provided, will default to the defaults defined in ResourceConfiguration.",
+ "$ref": "#/definitions/DeploymentResourceConfiguration",
+ "x-nullable": true
+ },
+ "retrySettings": {
+ "description": "Retry Settings for the batch inference operation.\r\nIf not provided, will default to the defaults defined in BatchRetrySettings.",
+ "$ref": "#/definitions/BatchRetrySettings",
+ "x-nullable": true
+ }
+ },
+ "x-ms-client-name": "BatchDeploymentProperties",
+ "additionalProperties": false
+ },
+ "BatchDeploymentConfiguration": {
+ "description": "Properties relevant to different deployment types.",
+ "required": [
+ "deploymentConfigurationType"
+ ],
+ "type": "object",
+ "properties": {
+ "deploymentConfigurationType": {
+ "description": "[Required] The type of the deployment",
+ "$ref": "#/definitions/BatchDeploymentConfigurationType"
+ }
+ },
+ "discriminator": "deploymentConfigurationType"
+ },
+ "BatchDeploymentConfigurationType": {
+ "description": "The enumerated property types for batch deployments.",
+ "enum": [
+ "Model",
+ "PipelineComponent"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "BatchDeploymentConfigurationType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Model"
+ },
+ {
+ "value": "PipelineComponent"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "BatchDeploymentTrackedResource": {
+ "required": [
+ "location",
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
+ }
+ ],
+ "properties": {
+ "identity": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ },
+ "kind": {
+ "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
+ "type": "string"
+ },
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/BatchDeployment"
+ },
+ "sku": {
+ "description": "Sku details required for ARM contract for Autoscaling.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
+ }
+ },
+ "x-ms-client-name": "BatchDeployment",
+ "additionalProperties": false
+ },
+ "BatchDeploymentTrackedResourceArmPaginatedResult": {
+ "description": "A paginated list of BatchDeployment entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of BatchDeployment objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type BatchDeployment.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/BatchDeploymentTrackedResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "BatchEndpoint": {
+ "description": "Batch endpoint configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EndpointPropertiesBase"
+ }
+ ],
+ "properties": {
+ "defaults": {
+ "description": "Default values for Batch Endpoint.",
+ "$ref": "#/definitions/BatchEndpointDefaults",
+ "x-nullable": true
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the endpoint.",
+ "$ref": "#/definitions/EndpointProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "BatchEndpointProperties",
+ "additionalProperties": false
+ },
+ "BatchEndpointDefaults": {
+ "description": "Batch endpoint default values",
+ "type": "object",
+ "properties": {
+ "deploymentName": {
+ "description": "Name of the deployment that will be default for the endpoint.\r\nThis deployment will end up getting 100% traffic when the endpoint scoring URL is invoked.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "BatchEndpointTrackedResource": {
+ "required": [
+ "location",
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
+ }
+ ],
+ "properties": {
+ "identity": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ },
+ "kind": {
+ "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
+ "type": "string"
+ },
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/BatchEndpoint"
+ },
+ "sku": {
+ "description": "Sku details required for ARM contract for Autoscaling.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
+ }
+ },
+ "x-ms-client-name": "BatchEndpoint",
+ "additionalProperties": false
+ },
+ "BatchEndpointTrackedResourceArmPaginatedResult": {
+ "description": "A paginated list of BatchEndpoint entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of BatchEndpoint objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type BatchEndpoint.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/BatchEndpointTrackedResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "BatchLoggingLevel": {
+ "description": "Log verbosity for batch inferencing.\r\nIncreasing verbosity order for logging is : Warning, Info and Debug.\r\nThe default value is Info.",
+ "enum": [
+ "Info",
+ "Warning",
+ "Debug"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "BatchLoggingLevel",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Info"
+ },
+ {
+ "value": "Warning"
+ },
+ {
+ "value": "Debug"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "BatchOutputAction": {
+ "description": "Enum to determine how batch inferencing will handle output",
+ "enum": [
+ "SummaryOnly",
+ "AppendRow"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "BatchOutputAction",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "SummaryOnly"
+ },
+ {
+ "value": "AppendRow"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "BatchPipelineComponentDeploymentConfiguration": {
+ "description": "Properties for a Batch Pipeline Component Deployment.",
+ "required": [
+ "deploymentConfigurationType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/BatchDeploymentConfiguration"
+ }
+ ],
+ "properties": {
+ "componentId": {
+ "description": "The ARM id of the component to be run.",
+ "$ref": "#/definitions/IdAssetReference",
+ "x-nullable": true
+ },
+ "description": {
+ "description": "The description which will be applied to the job.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "settings": {
+ "description": "Run-time settings for the pipeline job.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
+ },
+ "x-nullable": true
+ },
+ "tags": {
+ "description": "The tags which will be applied to the job.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
+ },
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "PipelineComponent",
+ "additionalProperties": false
+ },
+ "BatchRetrySettings": {
+ "description": "Retry settings for a batch inference operation.",
+ "type": "object",
+ "properties": {
+ "maxRetries": {
+ "format": "int32",
+ "description": "Maximum retry count for a mini-batch",
+ "default": 3,
+ "type": "integer"
+ },
+ "timeout": {
+ "format": "duration",
+ "description": "Invocation timeout for a mini-batch, in ISO 8601 format.",
+ "default": "PT30S",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ },
+ "BayesianSamplingAlgorithm": {
+ "description": "Defines a Sampling Algorithm that generates values based on previous values",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/SamplingAlgorithm"
+ }
+ ],
+ "x-ms-discriminator-value": "Bayesian",
+ "additionalProperties": false
+ },
+ "BlobReferenceForConsumptionDto": {
+ "type": "object",
+ "properties": {
+ "blobUri": {
+ "format": "uri",
+ "description": "Blob URI path for client to upload data.\r\nExample: https://blob.windows.core.net/Container/Path",
+ "type": "string",
+ "x-nullable": true
+ },
+ "credential": {
+ "description": "Credential info to access storage account",
+ "$ref": "#/definitions/PendingUploadCredentialDto",
+ "x-nullable": true
+ },
+ "storageAccountArmId": {
+ "description": "Arm ID of the storage account to use",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "BlockedTransformers": {
+ "description": "Enum for all classification models supported by AutoML.",
+ "enum": [
+ "TextTargetEncoder",
+ "OneHotEncoder",
+ "CatTargetEncoder",
+ "TfIdf",
+ "WoETargetEncoder",
+ "LabelEncoder",
+ "WordEmbedding",
+ "NaiveBayes",
+ "CountVectorizer",
+ "HashOneHotEncoder"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "BlockedTransformers",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "TextTargetEncoder",
+ "description": "Target encoding for text data."
+ },
+ {
+ "value": "OneHotEncoder",
+ "description": "Ohe hot encoding creates a binary feature transformation."
+ },
+ {
+ "value": "CatTargetEncoder",
+ "description": "Target encoding for categorical data."
+ },
+ {
+ "value": "TfIdf",
+ "description": "Tf-Idf stands for, term-frequency times inverse document-frequency. This is a common term weighting scheme for identifying information from documents."
+ },
+ {
+ "value": "WoETargetEncoder",
+ "description": "Weight of Evidence encoding is a technique used to encode categorical variables. It uses the natural log of the P(1)/P(0) to create weights."
+ },
+ {
+ "value": "LabelEncoder",
+ "description": "Label encoder converts labels/categorical variables in a numerical form."
+ },
+ {
+ "value": "WordEmbedding",
+ "description": "Word embedding helps represents words or phrases as a vector, or a series of numbers."
+ },
+ {
+ "value": "NaiveBayes",
+ "description": "Naive Bayes is a classified that is used for classification of discrete features that are categorically distributed."
+ },
+ {
+ "value": "CountVectorizer",
+ "description": "Count Vectorizer converts a collection of text documents to a matrix of token counts."
+ },
+ {
+ "value": "HashOneHotEncoder",
+ "description": "Hashing One Hot Encoder can turn categorical variables into a limited number of new features. This is often used for high-cardinality categorical features."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "BuildContext": {
+ "description": "Configuration settings for Docker build context",
+ "required": [
+ "contextUri"
+ ],
+ "type": "object",
+ "properties": {
+ "contextUri": {
+ "description": "[Required] URI of the Docker build context used to build the image. Supports blob URIs on environment creation and may return blob or Git URIs.\r\n",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "example": "https://storage-account.blob.core.windows.net/azureml/DockerBuildContext/95ddede6b9b8c4e90472db3acd0a8d28/",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "dockerfilePath": {
+ "description": "Path to the Dockerfile in the build context.\r\n",
+ "default": "Dockerfile",
+ "type": "string",
+ "example": "prod/Dockerfile",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "CategoricalDataDriftMetric": {
+ "enum": [
+ "JensenShannonDistance",
+ "PopulationStabilityIndex",
+ "PearsonsChiSquaredTest"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "CategoricalDataDriftMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "JensenShannonDistance",
+ "description": "The Jensen Shannon Distance (JSD) metric."
+ },
+ {
+ "value": "PopulationStabilityIndex",
+ "description": "The Population Stability Index (PSI) metric."
+ },
+ {
+ "value": "PearsonsChiSquaredTest",
+ "description": "The Pearsons Chi Squared Test metric."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "CategoricalDataDriftMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataDriftMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The categorical data drift metric to calculate.",
+ "$ref": "#/definitions/CategoricalDataDriftMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Categorical",
+ "additionalProperties": false
+ },
+ "CategoricalDataQualityMetric": {
+ "enum": [
+ "NullValueRate",
+ "DataTypeErrorRate",
+ "OutOfBoundsRate"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "CategoricalDataQualityMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "NullValueRate",
+ "description": "Calculates the rate of null values."
+ },
+ {
+ "value": "DataTypeErrorRate",
+ "description": "Calculates the rate of data type errors."
+ },
+ {
+ "value": "OutOfBoundsRate",
+ "description": "Calculates the rate values are out of bounds."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "CategoricalDataQualityMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataQualityMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The categorical data quality metric to calculate.",
+ "$ref": "#/definitions/CategoricalDataQualityMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Categorical",
+ "additionalProperties": false
+ },
+ "CategoricalPredictionDriftMetric": {
+ "enum": [
+ "JensenShannonDistance",
+ "PopulationStabilityIndex",
+ "PearsonsChiSquaredTest"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "CategoricalPredictionDriftMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "JensenShannonDistance",
+ "description": "The Jensen Shannon Distance (JSD) metric."
+ },
+ {
+ "value": "PopulationStabilityIndex",
+ "description": "The Population Stability Index (PSI) metric."
+ },
+ {
+ "value": "PearsonsChiSquaredTest",
+ "description": "The Pearsons Chi Squared Test metric."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "CategoricalPredictionDriftMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PredictionDriftMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The categorical prediction drift metric to calculate.",
+ "$ref": "#/definitions/CategoricalPredictionDriftMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Categorical",
+ "additionalProperties": false
+ },
+ "CertificateDatastoreCredentials": {
+ "description": "Certificate datastore credentials configuration.",
+ "required": [
+ "clientId",
+ "secrets",
+ "tenantId",
+ "thumbprint"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "properties": {
+ "authorityUrl": {
+ "description": "Authority URL used for authentication.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "clientId": {
+ "format": "uuid",
+ "description": "[Required] Service principal client ID.",
+ "type": "string"
+ },
+ "resourceUrl": {
+ "description": "Resource the service principal has access to.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "secrets": {
+ "description": "[Required] Service principal secrets.",
+ "$ref": "#/definitions/CertificateDatastoreSecrets",
+ "x-ms-mutability": [
+ "create",
+ "update"
+ ],
+ "x-ms-secret": true
+ },
+ "tenantId": {
+ "format": "uuid",
+ "description": "[Required] ID of the tenant to which the service principal belongs.",
+ "type": "string"
+ },
+ "thumbprint": {
+ "description": "[Required] Thumbprint of the certificate used for authentication.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
+ },
+ "x-ms-discriminator-value": "Certificate",
+ "additionalProperties": false
+ },
+ "CertificateDatastoreSecrets": {
+ "description": "Datastore certificate secrets.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreSecrets"
+ }
+ ],
+ "properties": {
+ "certificate": {
+ "description": "Service principal certificate.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Certificate",
+ "additionalProperties": false
+ },
+ "Classification": {
+ "description": "Classification task in AutoML Table vertical.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TableVertical"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "positiveLabel": {
+ "description": "Positive label for binary metrics calculation.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "primaryMetric": {
+ "description": "Primary metric for the task.",
+ "default": "AUCWeighted",
+ "$ref": "#/definitions/ClassificationPrimaryMetrics"
+ },
+ "trainingSettings": {
+ "description": "Inputs for training phase for an AutoML Job.",
+ "$ref": "#/definitions/ClassificationTrainingSettings",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Classification",
+ "additionalProperties": false
+ },
+ "ClassificationModelPerformanceMetric": {
+ "enum": [
+ "Accuracy",
+ "Precision",
+ "Recall",
+ "F1Score"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ClassificationModelPerformanceMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Accuracy",
+ "description": "Calculates the accuracy of the model predictions."
+ },
+ {
+ "value": "Precision",
+ "description": "Calculates the precision of the model predictions."
+ },
+ {
+ "value": "Recall",
+ "description": "Calculates the recall of the model predictions."
+ },
+ {
+ "value": "F1Score",
+ "description": "Calculates the F1 score of the model predictions."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ClassificationModelPerformanceMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ModelPerformanceMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The classification model performance to calculate.",
+ "$ref": "#/definitions/ClassificationModelPerformanceMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Classification",
+ "additionalProperties": false
+ },
+ "ClassificationModels": {
+ "description": "Enum for all classification models supported by AutoML.",
+ "enum": [
+ "LogisticRegression",
+ "SGD",
+ "MultinomialNaiveBayes",
+ "BernoulliNaiveBayes",
+ "SVM",
+ "LinearSVM",
+ "KNN",
+ "DecisionTree",
+ "RandomForest",
+ "ExtremeRandomTrees",
+ "LightGBM",
+ "GradientBoosting",
+ "XGBoostClassifier"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ClassificationModels",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "LogisticRegression",
+ "description": "Logistic regression is a fundamental classification technique.\nIt belongs to the group of linear classifiers and is somewhat similar to polynomial and linear regression.\nLogistic regression is fast and relatively uncomplicated, and it's convenient for you to interpret the results.\nAlthough it's essentially a method for binary classification, it can also be applied to multiclass problems."
+ },
+ {
+ "value": "SGD",
+ "description": "SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning applications\nto find the model parameters that correspond to the best fit between predicted and actual outputs."
+ },
+ {
+ "value": "MultinomialNaiveBayes",
+ "description": "The multinomial Naive Bayes classifier is suitable for classification with discrete features (e.g., word counts for text classification).\nThe multinomial distribution normally requires integer feature counts. However, in practice, fractional counts such as tf-idf may also work."
+ },
+ {
+ "value": "BernoulliNaiveBayes",
+ "description": "Naive Bayes classifier for multivariate Bernoulli models."
+ },
+ {
+ "value": "SVM",
+ "description": "A support vector machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems.\nAfter giving an SVM model sets of labeled training data for each category, they're able to categorize new text."
+ },
+ {
+ "value": "LinearSVM",
+ "description": "A support vector machine (SVM) is a supervised machine learning model that uses classification algorithms for two-group classification problems.\nAfter giving an SVM model sets of labeled training data for each category, they're able to categorize new text.\nLinear SVM performs best when input data is linear, i.e., data can be easily classified by drawing the straight line between classified values on a plotted graph."
+ },
+ {
+ "value": "KNN",
+ "description": "K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new datapoints\nwhich further means that the new data point will be assigned a value based on how closely it matches the points in the training set."
+ },
+ {
+ "value": "DecisionTree",
+ "description": "Decision Trees are a non-parametric supervised learning method used for both classification and regression tasks.\nThe goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features."
+ },
+ {
+ "value": "RandomForest",
+ "description": "Random forest is a supervised learning algorithm.\nThe \"forest\" it builds, is an ensemble of decision trees, usually trained with the “bagging†method.\nThe general idea of the bagging method is that a combination of learning models increases the overall result."
+ },
+ {
+ "value": "ExtremeRandomTrees",
+ "description": "Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many decision trees. It is related to the widely used random forest algorithm."
+ },
+ {
+ "value": "LightGBM",
+ "description": "LightGBM is a gradient boosting framework that uses tree based learning algorithms."
+ },
+ {
+ "value": "GradientBoosting",
+ "description": "The technique of transiting week learners into a strong learner is called Boosting. The gradient boosting algorithm process works on this theory of execution."
+ },
+ {
+ "value": "XGBoostClassifier",
+ "description": "XGBoost: Extreme Gradient Boosting Algorithm. This algorithm is used for structured data where target column values can be divided into distinct class values."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ClassificationMultilabelPrimaryMetrics": {
+ "description": "Primary metrics for classification multilabel tasks.",
+ "enum": [
+ "AUCWeighted",
+ "Accuracy",
+ "NormMacroRecall",
+ "AveragePrecisionScoreWeighted",
+ "PrecisionScoreWeighted",
+ "IOU"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ClassificationMultilabelPrimaryMetrics",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AUCWeighted",
+ "description": "AUC is the Area under the curve.\nThis metric represents arithmetic mean of the score for each class,\nweighted by the number of true instances in each class."
+ },
+ {
+ "value": "Accuracy",
+ "description": "Accuracy is the ratio of predictions that exactly match the true class labels."
+ },
+ {
+ "value": "NormMacroRecall",
+ "description": "Normalized macro recall is recall macro-averaged and normalized, so that random\nperformance has a score of 0, and perfect performance has a score of 1."
+ },
+ {
+ "value": "AveragePrecisionScoreWeighted",
+ "description": "The arithmetic mean of the average precision score for each class, weighted by\nthe number of true instances in each class."
+ },
+ {
+ "value": "PrecisionScoreWeighted",
+ "description": "The arithmetic mean of precision for each class, weighted by number of true instances in each class."
+ },
+ {
+ "value": "IOU",
+ "description": "Intersection Over Union. Intersection of predictions divided by union of predictions."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ClassificationPrimaryMetrics": {
+ "description": "Primary metrics for classification tasks.",
+ "enum": [
+ "AUCWeighted",
+ "Accuracy",
+ "NormMacroRecall",
+ "AveragePrecisionScoreWeighted",
+ "PrecisionScoreWeighted"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ClassificationPrimaryMetrics",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AUCWeighted",
+ "description": "AUC is the Area under the curve.\nThis metric represents arithmetic mean of the score for each class,\nweighted by the number of true instances in each class."
+ },
+ {
+ "value": "Accuracy",
+ "description": "Accuracy is the ratio of predictions that exactly match the true class labels."
+ },
+ {
+ "value": "NormMacroRecall",
+ "description": "Normalized macro recall is recall macro-averaged and normalized, so that random\nperformance has a score of 0, and perfect performance has a score of 1."
+ },
+ {
+ "value": "AveragePrecisionScoreWeighted",
+ "description": "The arithmetic mean of the average precision score for each class, weighted by\nthe number of true instances in each class."
+ },
+ {
+ "value": "PrecisionScoreWeighted",
+ "description": "The arithmetic mean of precision for each class, weighted by number of true instances in each class."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ClassificationTrainingSettings": {
+ "description": "Classification Training related configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TrainingSettings"
+ }
+ ],
+ "properties": {
+ "allowedTrainingAlgorithms": {
+ "description": "Allowed models for classification task.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ClassificationModels"
+ },
+ "x-nullable": true
+ },
+ "blockedTrainingAlgorithms": {
+ "description": "Blocked models for classification task.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ClassificationModels"
+ },
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "CocoExportSummary": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ExportSummary"
+ }
+ ],
+ "properties": {
+ "containerName": {
+ "description": "The container name to which the labels will be exported.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "snapshotPath": {
+ "description": "The output path where the labels will be exported.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Coco",
+ "additionalProperties": false
+ },
+ "CodeConfiguration": {
+ "description": "Configuration for a scoring code asset.",
+ "required": [
+ "scoringScript"
+ ],
+ "type": "object",
+ "properties": {
+ "codeId": {
+ "description": "ARM resource ID of the code asset.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "scoringScript": {
+ "description": "[Required] The script to execute on startup. eg. \"score.py\"",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "CodeContainer": {
+ "description": "Container for code asset versions.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "provisioningState": {
+ "description": "Provisioning state for the code container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "CodeContainerProperties",
+ "additionalProperties": false
+ },
+ "CodeContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/CodeContainer"
+ }
+ },
+ "x-ms-client-name": "CodeContainer",
+ "additionalProperties": false
+ },
+ "CodeContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of CodeContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of CodeContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type CodeContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/CodeContainerResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "CodeVersion": {
+ "description": "Code asset version details.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "codeUri": {
+ "description": "Uri where code is located",
+ "type": "string",
+ "example": "https://blobStorage/folderName",
+ "x-nullable": true
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the code version.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "CodeVersionProperties",
+ "additionalProperties": false
+ },
+ "CodeVersionResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/CodeVersion"
+ }
+ },
+ "x-ms-client-name": "CodeVersion",
+ "additionalProperties": false
+ },
+ "CodeVersionResourceArmPaginatedResult": {
+ "description": "A paginated list of CodeVersion entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of CodeVersion objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type CodeVersion.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/CodeVersionResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "Collection": {
+ "type": "object",
+ "properties": {
+ "clientId": {
+ "description": "The msi client id used to collect logging to blob storage. If it's null,backend will pick a registered endpoint identity to auth.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "dataCollectionMode": {
+ "description": "Enable or disable data collection.",
+ "default": "Disabled",
+ "$ref": "#/definitions/DataCollectionMode"
+ },
+ "dataId": {
+ "description": "The data asset arm resource id. Client side will ensure data asset is pointing to the blob storage, and backend will collect data to the blob storage.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "samplingRate": {
+ "format": "double",
+ "description": "The sampling rate for collection. Sampling rate 1.0 means we collect 100% of data by default.",
+ "default": 1,
+ "type": "number"
+ }
+ },
+ "additionalProperties": false
+ },
+ "ColumnTransformer": {
+ "description": "Column transformer parameters.",
+ "type": "object",
+ "properties": {
+ "fields": {
+ "description": "Fields to apply transformer logic on.",
+ "type": "array",
+ "items": {
+ "type": "string"
+ },
+ "x-nullable": true
+ },
+ "parameters": {
+ "description": "Different properties to be passed to transformer.\r\nInput expected is dictionary of key,value pairs in JSON format.",
+ "type": "object",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "CommandJob": {
+ "description": "Command job definition.",
+ "required": [
+ "command",
+ "environmentId"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobBase"
+ }
+ ],
+ "properties": {
+ "autologgerSettings": {
+ "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.",
+ "$ref": "#/definitions/AutologgerSettings",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "codeId": {
+ "description": "ARM resource ID of the code asset.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "command": {
+ "description": "[Required] The command to execute on startup of the job. eg. \"python train.py\"",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "distribution": {
+ "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, Ray, or null.",
+ "$ref": "#/definitions/DistributionConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "environmentId": {
+ "description": "[Required] The ARM resource ID of the Environment specification for the job.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "environmentVariables": {
+ "description": "Environment variables included in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
"x-nullable": true
},
- "layersToFreeze": {
- "format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "inputs": {
+ "description": "Mapping of input data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Command job definition.",
+ "$ref": "#/definitions/JobInput",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "limits": {
+ "description": "Command Job limit.",
+ "$ref": "#/definitions/CommandJobLimits",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "outputs": {
+ "description": "Mapping of output data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Job output definition container information on where to find job output/logs.",
+ "$ref": "#/definitions/JobOutput",
"x-nullable": true
},
- "learningRate": {
- "format": "float",
- "description": "Initial learning rate. Must be a float in the range [0, 1].",
- "type": "number",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "parameters": {
+ "description": "Input parameters.",
+ "type": "object",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "queueSettings": {
+ "description": "Queue settings for the job",
+ "$ref": "#/definitions/QueueSettings",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "resources": {
+ "description": "Compute Resource configuration for the job.",
+ "default": "{}",
+ "$ref": "#/definitions/JobResourceConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Command",
+ "additionalProperties": false
+ },
+ "CommandJobLimits": {
+ "description": "Command Job limit class.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobLimits"
+ }
+ ],
+ "x-ms-discriminator-value": "Command",
+ "additionalProperties": false
+ },
+ "ComponentContainer": {
+ "description": "Component container definition.\r\n",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "provisioningState": {
+ "description": "Provisioning state for the component container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "ComponentContainerProperties",
+ "additionalProperties": false
+ },
+ "ComponentContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/ComponentContainer"
+ }
+ },
+ "x-ms-client-name": "ComponentContainer",
+ "additionalProperties": false
+ },
+ "ComponentContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of ComponentContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of ComponentContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type ComponentContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ComponentContainerResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "ComponentVersion": {
+ "description": "Definition of a component version: defines resources that span component types.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "componentSpec": {
+ "description": "Defines Component definition details.\r\n",
+ "type": "object",
+ "example": {
+ "name": "Hello_Python_World",
+ "display_name": "Hello_Python_World",
+ "version": 1,
+ "type": "command",
+ "code": "azureml:/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/codes/mycode/versions/1",
+ "environment": "azureml:/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/environments/AzureML-Tutorial/versions/1",
+ "command": "python hello.py"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the component version.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ },
+ "stage": {
+ "description": "Stage in the component lifecycle",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-client-name": "ComponentVersionProperties",
+ "additionalProperties": false
+ },
+ "ComponentVersionResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/ComponentVersion"
+ }
+ },
+ "x-ms-client-name": "ComponentVersion",
+ "additionalProperties": false
+ },
+ "ComponentVersionResourceArmPaginatedResult": {
+ "description": "A paginated list of ComponentVersion entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of ComponentVersion objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type ComponentVersion.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ComponentVersionResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "ContainerResourceRequirements": {
+ "description": "Resource requirements for each container instance within an online deployment.",
+ "type": "object",
+ "properties": {
+ "containerResourceLimits": {
+ "description": "Container resource limit info:",
+ "$ref": "#/definitions/ContainerResourceSettings",
+ "x-nullable": true
+ },
+ "containerResourceRequests": {
+ "description": "Container resource request info:",
+ "$ref": "#/definitions/ContainerResourceSettings",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ContainerResourceSettings": {
+ "type": "object",
+ "properties": {
+ "cpu": {
+ "description": "Number of vCPUs request/limit for container. More info:\r\nhttps://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/",
+ "type": "string",
+ "example": "1",
+ "x-nullable": true
+ },
+ "gpu": {
+ "description": "Number of Nvidia GPU cards request/limit for container. More info:\r\nhttps://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/",
+ "type": "string",
+ "example": "1",
+ "x-nullable": true
+ },
+ "memory": {
+ "description": "Memory size request/limit for container. More info:\r\nhttps://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/",
+ "type": "string",
+ "example": "2Gi",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ContainerType": {
+ "description": "The type of container to retrieve logs from.",
+ "enum": [
+ "StorageInitializer",
+ "InferenceServer",
+ "ModelDataCollector"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ContainerType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "StorageInitializer",
+ "description": "The container used to download models and score script."
+ },
+ {
+ "value": "InferenceServer",
+ "description": "The container used to serve user's request."
+ },
+ {
+ "value": "ModelDataCollector",
+ "description": "The container used to collect payload and custom logging when mdc is enabled."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "CreateMonitorAction": {
+ "required": [
+ "monitorDefinition"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ScheduleActionBase"
+ }
+ ],
+ "properties": {
+ "monitorDefinition": {
+ "description": "[Required] Defines the monitor.",
+ "$ref": "#/definitions/MonitorDefinition",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "CreateMonitor",
+ "additionalProperties": false
+ },
+ "CredentialsType": {
+ "description": "Enum to determine the datastore credentials type.",
+ "enum": [
+ "AccountKey",
+ "Certificate",
+ "None",
+ "Sas",
+ "ServicePrincipal",
+ "KerberosKeytab",
+ "KerberosPassword"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "CredentialsType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AccountKey"
+ },
+ {
+ "value": "Certificate"
+ },
+ {
+ "value": "None"
+ },
+ {
+ "value": "Sas"
+ },
+ {
+ "value": "ServicePrincipal"
+ },
+ {
+ "value": "KerberosKeytab"
+ },
+ {
+ "value": "KerberosPassword"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "CronTrigger": {
+ "required": [
+ "expression"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TriggerBase"
+ }
+ ],
+ "properties": {
+ "expression": {
+ "description": "[Required] Specifies cron expression of schedule.\r\nThe expression should follow NCronTab format.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
+ },
+ "x-ms-discriminator-value": "Cron",
+ "additionalProperties": false
+ },
+ "CsvExportSummary": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ExportSummary"
+ }
+ ],
+ "properties": {
+ "containerName": {
+ "description": "The container name to which the labels will be exported.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "snapshotPath": {
+ "description": "The output path where the labels will be exported.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "CSV",
+ "additionalProperties": false
+ },
+ "CustomForecastHorizon": {
+ "description": "The desired maximum forecast horizon in units of time-series frequency.",
+ "required": [
+ "value"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ForecastHorizon"
+ }
+ ],
+ "properties": {
+ "value": {
+ "format": "int32",
+ "description": "[Required] Forecast horizon value.",
+ "type": "integer"
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "CustomInferencingServer": {
+ "description": "Custom inference server configurations.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/InferencingServer"
+ }
+ ],
+ "properties": {
+ "inferenceConfiguration": {
+ "description": "Inference configuration for custom inferencing.",
+ "$ref": "#/definitions/OnlineInferenceConfiguration",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "CustomMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "properties": {
+ "metric": {
+ "description": "[Required] The user-defined metric to calculate.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "threshold": {
+ "description": "The threshold value. If null, a default value will be set depending on the selected metric.",
+ "$ref": "#/definitions/MonitoringThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "CustomModelJobInput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobInput"
+ },
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "x-ms-discriminator-value": "custom_model",
+ "additionalProperties": false
+ },
+ "CustomModelJobOutput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobOutput"
+ },
+ {
+ "$ref": "#/definitions/JobOutput"
+ }
+ ],
+ "x-ms-discriminator-value": "custom_model",
+ "additionalProperties": false
+ },
+ "CustomMonitoringSignal": {
+ "required": [
+ "componentId",
+ "metricThresholds"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringSignalBase"
+ }
+ ],
+ "properties": {
+ "componentId": {
+ "description": "[Required] ARM resource ID of the component resource used to calculate the custom metrics.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "inputAssets": {
+ "description": "Monitoring assets to take as input. Key is the component input port name, value is the data asset.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/MonitoringInputData",
"x-nullable": true
},
- "learningRateScheduler": {
- "description": "Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.",
- "default": "None",
- "$ref": "#/definitions/LearningRateScheduler"
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "metricThresholds": {
+ "description": "[Required] A list of metrics to calculate and their associated thresholds.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/CustomMetricThreshold"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-ms-identifiers": []
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "CustomNCrossValidations": {
+ "description": "N-Cross validations are specified by user.",
+ "required": [
+ "value"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/NCrossValidations"
+ }
+ ],
+ "properties": {
+ "value": {
+ "format": "int32",
+ "description": "[Required] N-Cross validations value.",
+ "type": "integer"
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "CustomSeasonality": {
+ "required": [
+ "value"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/Seasonality"
+ }
+ ],
+ "properties": {
+ "value": {
+ "format": "int32",
+ "description": "[Required] Seasonality value.",
+ "type": "integer"
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "CustomTargetLags": {
+ "required": [
+ "values"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TargetLags"
+ }
+ ],
+ "properties": {
+ "values": {
+ "description": "[Required] Set target lags values.",
+ "type": "array",
+ "items": {
+ "format": "int32",
+ "type": "integer"
+ }
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "CustomTargetRollingWindowSize": {
+ "required": [
+ "value"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TargetRollingWindowSize"
+ }
+ ],
+ "properties": {
+ "value": {
+ "format": "int32",
+ "description": "[Required] TargetRollingWindowSize value.",
+ "type": "integer"
+ }
+ },
+ "x-ms-discriminator-value": "Custom",
+ "additionalProperties": false
+ },
+ "DataCollectionMode": {
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "DataCollectionMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Enabled"
+ },
+ {
+ "value": "Disabled"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "DataCollector": {
+ "required": [
+ "collections"
+ ],
+ "type": "object",
+ "properties": {
+ "collections": {
+ "description": "[Required] The collection configuration. Each collection has it own configuration to collect model data and the name of collection can be arbitrary string.\r\nModel data collector can be used for either payload logging or custom logging or both of them. Collection request and response are reserved for payload logging, others are for custom logging.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/Collection",
+ "x-nullable": true
+ }
+ },
+ "requestLogging": {
+ "description": "The request logging configuration for mdc, it includes advanced logging settings for all collections. It's optional.",
+ "$ref": "#/definitions/RequestLogging",
+ "x-nullable": true
+ },
+ "rollingRate": {
+ "description": "When model data is collected to blob storage, we need to roll the data to different path to avoid logging all of them in a single blob file.\r\nIf the rolling rate is hour, all data will be collected in the blob path /yyyy/MM/dd/HH/.\r\nIf it's day, all data will be collected in blob path /yyyy/MM/dd/.\r\nThe other benefit of rolling path is that model monitoring ui is able to select a time range of data very quickly.",
+ "default": "Hour",
+ "$ref": "#/definitions/RollingRateType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "DataContainer": {
+ "description": "Container for data asset versions.",
+ "required": [
+ "dataType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "dataType": {
+ "description": "[Required] Specifies the type of data.",
+ "$ref": "#/definitions/DataType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "DataContainerProperties",
+ "additionalProperties": false
+ },
+ "DataContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/DataContainer"
+ }
+ },
+ "x-ms-client-name": "DataContainer",
+ "additionalProperties": false
+ },
+ "DataContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of DataContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of DataContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type DataContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/DataContainerResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "DataDriftMetricThresholdBase": {
+ "required": [
+ "dataType"
+ ],
+ "type": "object",
+ "properties": {
+ "dataType": {
+ "description": "[Required] Specifies the data type of the metric threshold.",
+ "$ref": "#/definitions/MonitoringFeatureDataType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "threshold": {
+ "description": "The threshold value. If null, a default value will be set depending on the selected metric.",
+ "$ref": "#/definitions/MonitoringThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "discriminator": "dataType"
+ },
+ "DataDriftMonitoringSignal": {
+ "required": [
+ "baselineData",
+ "metricThresholds",
+ "targetData"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringSignalBase"
+ }
+ ],
+ "properties": {
+ "baselineData": {
+ "description": "[Required] The data to calculate drift against.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "dataSegment": {
+ "description": "The data segment used for scoping on a subset of the data population.",
+ "$ref": "#/definitions/MonitoringDataSegment",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "features": {
+ "description": "The feature filter which identifies which feature to calculate drift over.",
+ "$ref": "#/definitions/MonitoringFeatureFilterBase",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "metricThresholds": {
+ "description": "[Required] A list of metrics to calculate and their associated thresholds.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/DataDriftMetricThresholdBase"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-ms-identifiers": []
+ },
+ "targetData": {
+ "description": "[Required] The data which drift will be calculated for.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "DataDrift",
+ "additionalProperties": false
+ },
+ "DataImport": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataVersionBase"
+ }
+ ],
+ "properties": {
+ "assetName": {
+ "description": "Name of the asset for data import job to create",
+ "type": "string",
+ "x-nullable": true
+ },
+ "source": {
+ "description": "Source data of the asset to import from",
+ "$ref": "#/definitions/DataImportSource",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "uri_folder",
+ "additionalProperties": false
+ },
+ "DataImportSource": {
+ "required": [
+ "sourceType"
+ ],
+ "type": "object",
+ "properties": {
+ "connection": {
+ "description": "Workspace connection for data import source storage",
+ "type": "string",
+ "x-nullable": true
+ },
+ "sourceType": {
+ "description": "[Required] Specifies the type of data.",
+ "$ref": "#/definitions/DataImportSourceType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "sourceType"
+ },
+ "DataImportSourceType": {
+ "description": "Enum to determine the type of data.",
+ "enum": [
+ "database",
+ "file_system"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "DataImportSourceType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "database"
+ },
+ {
+ "value": "file_system"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "DataPathAssetReference": {
+ "description": "Reference to an asset via its path in a datastore.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetReferenceBase"
+ }
+ ],
+ "properties": {
+ "datastoreId": {
+ "description": "ARM resource ID of the datastore where the asset is located.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "path": {
+ "description": "The path of the file/directory in the datastore.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "DataPath",
+ "additionalProperties": false
+ },
+ "DataQualityMetricThresholdBase": {
+ "required": [
+ "dataType"
+ ],
+ "type": "object",
+ "properties": {
+ "dataType": {
+ "description": "[Required] Specifies the data type of the metric threshold.",
+ "$ref": "#/definitions/MonitoringFeatureDataType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "threshold": {
+ "description": "The threshold value. If null, a default value will be set depending on the selected metric.",
+ "$ref": "#/definitions/MonitoringThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "discriminator": "dataType"
+ },
+ "DataQualityMonitoringSignal": {
+ "required": [
+ "baselineData",
+ "metricThresholds",
+ "targetData"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringSignalBase"
+ }
+ ],
+ "properties": {
+ "baselineData": {
+ "description": "[Required] The data to calculate drift against.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "features": {
+ "description": "The features to calculate drift over.",
+ "$ref": "#/definitions/MonitoringFeatureFilterBase",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "metricThresholds": {
+ "description": "[Required] A list of metrics to calculate and their associated thresholds.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/DataQualityMetricThresholdBase"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-ms-identifiers": []
+ },
+ "targetData": {
+ "description": "[Required] The data produced by the production service which drift will be calculated for.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "DataQuality",
+ "additionalProperties": false
+ },
+ "DataType": {
+ "description": "Enum to determine the type of data.",
+ "enum": [
+ "uri_file",
+ "uri_folder",
+ "mltable"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "DataType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "uri_file"
+ },
+ {
+ "value": "uri_folder"
+ },
+ {
+ "value": "mltable"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "DataVersionBase": {
+ "description": "Data version base definition",
+ "required": [
+ "dataType",
+ "dataUri"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "dataType": {
+ "description": "[Required] Specifies the type of data.",
+ "$ref": "#/definitions/DataType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "dataUri": {
+ "description": "[Required] Uri of the data. Example: https://go.microsoft.com/fwlink/?linkid=2202330",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "intellectualProperty": {
+ "description": "Intellectual Property details. Used if data is an Intellectual Property.",
+ "$ref": "#/definitions/IntellectualProperty",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "stage": {
+ "description": "Stage in the data lifecycle assigned to this data asset",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "discriminator": "dataType",
+ "x-ms-client-name": "DataVersionBaseProperties"
+ },
+ "DataVersionBaseResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/DataVersionBase"
+ }
+ },
+ "x-ms-client-name": "DataVersionBase",
+ "additionalProperties": false
+ },
+ "DataVersionBaseResourceArmPaginatedResult": {
+ "description": "A paginated list of DataVersionBase entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of DataVersionBase objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type DataVersionBase.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/DataVersionBaseResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "DatabaseSource": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataImportSource"
+ }
+ ],
+ "properties": {
+ "query": {
+ "description": "SQL Query statement for data import Database source",
+ "type": "string",
+ "x-nullable": true
+ },
+ "storedProcedure": {
+ "description": "SQL StoredProcedure on data import Database source",
+ "type": "string",
+ "x-nullable": true
+ },
+ "storedProcedureParams": {
+ "description": "SQL StoredProcedure parameters",
+ "type": "array",
+ "items": {
+ "type": "object",
+ "additionalProperties": {
+ "type": "string"
+ }
+ },
+ "x-nullable": true
+ },
+ "tableName": {
+ "description": "Name of the table on data import Database source",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "database",
+ "additionalProperties": false
+ },
+ "DatasetExportSummary": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ExportSummary"
+ }
+ ],
+ "properties": {
+ "labeledAssetName": {
+ "description": "The unique name of the labeled data asset.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Dataset",
+ "additionalProperties": false
+ },
+ "Datastore": {
+ "description": "Base definition for datastore contents configuration.",
+ "required": [
+ "credentials",
+ "datastoreType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceBase"
+ }
+ ],
+ "properties": {
+ "credentials": {
+ "description": "[Required] Account credentials.",
+ "$ref": "#/definitions/DatastoreCredentials"
+ },
+ "datastoreType": {
+ "description": "[Required] Storage type backing the datastore.",
+ "$ref": "#/definitions/DatastoreType"
+ },
+ "intellectualProperty": {
+ "description": "Intellectual Property details.",
+ "$ref": "#/definitions/IntellectualProperty",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "isDefault": {
+ "description": "Readonly property to indicate if datastore is the workspace default datastore",
+ "type": "boolean",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "discriminator": "datastoreType",
+ "x-ms-client-name": "DatastoreProperties"
+ },
+ "DatastoreCredentials": {
+ "description": "Base definition for datastore credentials.",
+ "required": [
+ "credentialsType"
+ ],
+ "type": "object",
+ "properties": {
+ "credentialsType": {
+ "description": "[Required] Credential type used to authentication with storage.",
+ "$ref": "#/definitions/CredentialsType"
+ }
+ },
+ "discriminator": "credentialsType"
+ },
+ "DatastoreResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/Datastore"
+ }
+ },
+ "x-ms-client-name": "Datastore",
+ "additionalProperties": false
+ },
+ "DatastoreResourceArmPaginatedResult": {
+ "description": "A paginated list of Datastore entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of Datastore objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type Datastore.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/DatastoreResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "DatastoreSecrets": {
+ "description": "Base definition for datastore secrets.",
+ "required": [
+ "secretsType"
+ ],
+ "type": "object",
+ "properties": {
+ "secretsType": {
+ "description": "[Required] Credential type used to authentication with storage.",
+ "$ref": "#/definitions/SecretsType"
+ }
+ },
+ "discriminator": "secretsType"
+ },
+ "DatastoreType": {
+ "description": "Enum to determine the datastore contents type.",
+ "enum": [
+ "AzureBlob",
+ "AzureDataLakeGen1",
+ "AzureDataLakeGen2",
+ "AzureFile",
+ "Hdfs",
+ "OneLake"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "DatastoreType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AzureBlob"
},
- "modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "AzureDataLakeGen1"
},
- "momentum": {
- "format": "float",
- "description": "Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "AzureDataLakeGen2"
},
- "nesterov": {
- "description": "Enable nesterov when optimizer is 'sgd'.",
- "type": "boolean",
- "x-nullable": true
+ {
+ "value": "AzureFile"
},
- "numberOfEpochs": {
- "format": "int32",
- "description": "Number of training epochs. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Hdfs"
},
- "numberOfWorkers": {
- "format": "int32",
- "description": "Number of data loader workers. Must be a non-negative integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "OneLake"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "DefaultScaleSettings": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/OnlineScaleSettings"
+ }
+ ],
+ "x-ms-discriminator-value": "Default",
+ "additionalProperties": false
+ },
+ "DeploymentLogs": {
+ "type": "object",
+ "properties": {
+ "content": {
+ "description": "The retrieved online deployment logs.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "DeploymentLogsRequest": {
+ "type": "object",
+ "properties": {
+ "containerType": {
+ "description": "The type of container to retrieve logs from.",
+ "default": "InferenceServer",
+ "$ref": "#/definitions/ContainerType"
+ },
+ "tail": {
+ "format": "int32",
+ "description": "The maximum number of lines to tail.",
+ "type": "integer",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "DeploymentProvisioningState": {
+ "description": "Possible values for DeploymentProvisioningState.",
+ "enum": [
+ "Creating",
+ "Deleting",
+ "Scaling",
+ "Updating",
+ "Succeeded",
+ "Failed",
+ "Canceled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "DeploymentProvisioningState",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Creating"
},
- "optimizer": {
- "description": "Type of optimizer.",
- "default": "None",
- "$ref": "#/definitions/StochasticOptimizer"
+ {
+ "value": "Deleting"
},
- "randomSeed": {
- "format": "int32",
- "description": "Random seed to be used when using deterministic training.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Scaling"
},
- "stepLRGamma": {
- "format": "float",
- "description": "Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "Updating"
},
- "stepLRStepSize": {
- "format": "int32",
- "description": "Value of step size when learning rate scheduler is 'step'. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Succeeded"
},
- "trainingBatchSize": {
- "format": "int32",
- "description": "Training batch size. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Failed"
},
- "validationBatchSize": {
- "format": "int32",
- "description": "Validation batch size. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Canceled"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "DeploymentResourceConfiguration": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceConfiguration"
+ }
+ ],
+ "additionalProperties": false
+ },
+ "DistributionConfiguration": {
+ "description": "Base definition for job distribution configuration.",
+ "required": [
+ "distributionType"
+ ],
+ "type": "object",
+ "properties": {
+ "distributionType": {
+ "description": "[Required] Specifies the type of distribution framework.",
+ "$ref": "#/definitions/DistributionType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "distributionType"
+ },
+ "DistributionType": {
+ "description": "Enum to determine the job distribution type.",
+ "enum": [
+ "PyTorch",
+ "TensorFlow",
+ "Mpi",
+ "Ray"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "DistributionType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "PyTorch"
},
- "warmupCosineLRCycles": {
- "format": "float",
- "description": "Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "TensorFlow"
},
- "warmupCosineLRWarmupEpochs": {
- "format": "int32",
- "description": "Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Mpi"
},
- "weightDecay": {
- "format": "float",
- "description": "Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "Ray"
}
- },
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EarlyTerminationPolicy": {
+ "description": "Early termination policies enable canceling poor-performing runs before they complete",
+ "required": [
+ "policyType"
+ ],
+ "type": "object",
+ "properties": {
+ "delayEvaluation": {
+ "format": "int32",
+ "description": "Number of intervals by which to delay the first evaluation.",
+ "default": 0,
+ "type": "integer"
+ },
+ "evaluationInterval": {
+ "format": "int32",
+ "description": "Interval (number of runs) between policy evaluations.",
+ "default": 0,
+ "type": "integer"
+ },
+ "policyType": {
+ "description": "[Required] Name of policy configuration",
+ "$ref": "#/definitions/EarlyTerminationPolicyType"
+ }
},
- "ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "object",
- "allOf": [
+ "discriminator": "policyType"
+ },
+ "EarlyTerminationPolicyType": {
+ "enum": [
+ "Bandit",
+ "MedianStopping",
+ "TruncationSelection"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EarlyTerminationPolicyType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/ImageModelSettings"
- }
- ],
- "properties": {
- "trainingCropSize": {
- "format": "int32",
- "description": "Image crop size that is input to the neural network for the training dataset. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
- },
- "validationCropSize": {
- "format": "int32",
- "description": "Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ "value": "Bandit"
},
- "validationResizeSize": {
- "format": "int32",
- "description": "Image size to which to resize before cropping for validation dataset. Must be a positive integer.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "MedianStopping"
},
- "weightedLoss": {
- "format": "int32",
- "description": "Weighted loss. The accepted values are 0 for no weighted loss.\r\n1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be 0 or 1 or 2.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "TruncationSelection"
}
- },
- "additionalProperties": false
+ ]
},
- "ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "EgressPublicNetworkAccessType": {
+ "description": "Enum to determine whether PublicNetworkAccess is Enabled or Disabled for egress of a deployment.",
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EgressPublicNetworkAccessType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Enabled"
+ },
{
- "$ref": "#/definitions/ImageModelSettings"
+ "value": "Disabled"
}
- ],
- "properties": {
- "boxDetectionsPerImage": {
- "format": "int32",
- "description": "Maximum number of detections per image, for all classes. Must be a positive integer.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "integer",
- "x-nullable": true
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EmailNotificationEnableType": {
+ "description": "Enum to determine the email notification type.",
+ "enum": [
+ "JobCompleted",
+ "JobFailed",
+ "JobCancelled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EmailNotificationEnableType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "JobCompleted"
},
- "boxScoreThreshold": {
- "format": "float",
- "description": "During inference, only return proposals with a classification score greater than\r\nBoxScoreThreshold. Must be a float in the range[0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "JobFailed"
},
- "imageSize": {
- "format": "int32",
- "description": "Image size for train and validation. Must be a positive integer.\r\nNote: The training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "JobCancelled"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EndpointAuthKeys": {
+ "description": "Keys for endpoint authentication.",
+ "type": "object",
+ "properties": {
+ "primaryKey": {
+ "description": "The primary key.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "secondaryKey": {
+ "description": "The secondary key.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "EndpointAuthMode": {
+ "description": "Enum to determine endpoint authentication mode.",
+ "enum": [
+ "AMLToken",
+ "Key",
+ "AADToken"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EndpointAuthMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AMLToken"
},
- "maxSize": {
- "format": "int32",
- "description": "Maximum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Key"
},
- "minSize": {
- "format": "int32",
- "description": "Minimum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "AADToken"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EndpointAuthToken": {
+ "description": "Service Token",
+ "type": "object",
+ "properties": {
+ "accessToken": {
+ "description": "Access token for endpoint authentication.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "expiryTimeUtc": {
+ "format": "int64",
+ "description": "Access token expiry time (UTC).",
+ "default": 0,
+ "type": "integer"
+ },
+ "refreshAfterTimeUtc": {
+ "format": "int64",
+ "description": "Refresh access token after time (UTC).",
+ "default": 0,
+ "type": "integer"
+ },
+ "tokenType": {
+ "description": "Access token type.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "EndpointComputeType": {
+ "description": "Enum to determine endpoint compute type.",
+ "enum": [
+ "Managed",
+ "Kubernetes",
+ "AzureMLCompute"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EndpointComputeType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Managed"
},
- "modelSize": {
- "description": "Model size. Must be 'small', 'medium', 'large', or 'xlarge'.\r\nNote: training run may get into CUDA OOM if the model size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
- "default": "None",
- "$ref": "#/definitions/ModelSize"
+ {
+ "value": "Kubernetes"
},
- "multiScale": {
- "description": "Enable multi-scale image by varying image size by +/- 50%.\r\nNote: training run may get into CUDA OOM if no sufficient GPU memory.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
- "type": "boolean",
+ {
+ "value": "AzureMLCompute"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EndpointDeploymentPropertiesBase": {
+ "description": "Base definition for endpoint deployment.",
+ "type": "object",
+ "properties": {
+ "codeConfiguration": {
+ "description": "Code configuration for the endpoint deployment.",
+ "$ref": "#/definitions/CodeConfiguration",
+ "x-nullable": true
+ },
+ "description": {
+ "description": "Description of the endpoint deployment.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "environmentId": {
+ "description": "ARM resource ID of the environment specification for the endpoint deployment.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "environmentVariables": {
+ "description": "Environment variables configuration for the deployment.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
"x-nullable": true
},
- "nmsIouThreshold": {
- "format": "float",
- "description": "IOU threshold used during inference in NMS post processing. Must be a float in the range [0, 1].",
- "type": "number",
+ "x-nullable": true
+ },
+ "properties": {
+ "description": "Property dictionary. Properties can be added, but not removed or altered.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
"x-nullable": true
},
- "tileGridSize": {
- "description": "The grid size to use for tiling each image. Note: TileGridSize must not be\r\nNone to enable small object detection logic. A string containing two integers in mxn format.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "EndpointPropertiesBase": {
+ "description": "Inference Endpoint base definition",
+ "required": [
+ "authMode"
+ ],
+ "type": "object",
+ "properties": {
+ "authMode": {
+ "description": "[Required] Use 'Key' for key based authentication and 'AMLToken' for Azure Machine Learning token-based authentication. 'Key' doesn't expire but 'AMLToken' does.",
+ "$ref": "#/definitions/EndpointAuthMode"
+ },
+ "description": {
+ "description": "Description of the inference endpoint.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "keys": {
+ "description": "EndpointAuthKeys to set initially on an Endpoint.\r\nThis property will always be returned as null. AuthKey values must be retrieved using the ListKeys API.",
+ "$ref": "#/definitions/EndpointAuthKeys",
+ "x-ms-mutability": [
+ "create"
+ ],
+ "x-ms-secret": true,
+ "x-nullable": true
+ },
+ "properties": {
+ "description": "Property dictionary. Properties can be added, but not removed or altered.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
- "example": "3x2",
"x-nullable": true
},
- "tileOverlapRatio": {
- "format": "float",
- "description": "Overlap ratio between adjacent tiles in each dimension. Must be float in the range [0, 1).\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "number",
- "x-nullable": true
+ "x-nullable": true
+ },
+ "scoringUri": {
+ "format": "uri",
+ "description": "Endpoint URI.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "swaggerUri": {
+ "format": "uri",
+ "description": "Endpoint Swagger URI.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "EndpointProvisioningState": {
+ "description": "State of endpoint provisioning.",
+ "enum": [
+ "Creating",
+ "Deleting",
+ "Succeeded",
+ "Failed",
+ "Updating",
+ "Canceled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EndpointProvisioningState",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Creating"
},
- "tilePredictionsNmsThreshold": {
- "format": "float",
- "description": "The IOU threshold to use to perform NMS while merging predictions from tiles and image.\r\nUsed in validation/ inference. Must be float in the range [0, 1].\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "Deleting"
},
- "validationIouThreshold": {
- "format": "float",
- "description": "IOU threshold to use when computing validation metric. Must be float in the range [0, 1].",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "Succeeded"
+ },
+ {
+ "value": "Failed"
},
- "validationMetricType": {
- "description": "Metric computation method to use for validation metrics.",
- "default": "None",
- "$ref": "#/definitions/ValidationMetricType"
- }
- },
- "additionalProperties": false
- },
- "ImageObjectDetection": {
- "description": "Image Object Detection. Object detection is used to identify objects in an image and locate each object with a\r\nbounding box e.g. locate all dogs and cats in an image and draw a bounding box around each.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/ImageObjectDetectionBase"
+ "value": "Updating"
},
{
- "$ref": "#/definitions/AutoMLVertical"
+ "value": "Canceled"
}
- ],
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EndpointScheduleAction": {
+ "required": [
+ "actionType",
+ "endpointInvocationDefinition"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ScheduleActionBase"
+ }
+ ],
+ "properties": {
+ "endpointInvocationDefinition": {
+ "description": "[Required] Defines Schedule action definition details.\r\n",
+ "type": "object",
+ "example": {
+ "endpoint": "azureml:/subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/resourceGroup-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/batchEndpoints/hello-pipeline",
+ "inputs": {
+ "create_time": "${{creation_context.trigger_time}}"
+ }
+ },
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "InvokeBatchEndpoint",
+ "additionalProperties": false
+ },
+ "EnvironmentContainer": {
+ "description": "Container for environment specification versions.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "provisioningState": {
+ "description": "Provisioning state for the environment container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "EnvironmentContainerProperties",
+ "additionalProperties": false
+ },
+ "EnvironmentContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "primaryMetric": {
- "description": "Primary metric to optimize for this task.",
- "default": "MeanAveragePrecision",
- "$ref": "#/definitions/ObjectDetectionPrimaryMetrics"
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/EnvironmentContainer"
+ }
+ },
+ "x-ms-client-name": "EnvironmentContainer",
+ "additionalProperties": false
+ },
+ "EnvironmentContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of EnvironmentContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of EnvironmentContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type EnvironmentContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/EnvironmentContainerResource"
}
- },
- "x-ms-discriminator-value": "ImageObjectDetection",
- "additionalProperties": false
+ }
},
- "ImageObjectDetectionBase": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "EnvironmentType": {
+ "description": "Environment type is either user created or curated by Azure ML service",
+ "enum": [
+ "Curated",
+ "UserCreated"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "EnvironmentType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/ImageVertical"
- }
- ],
- "properties": {
- "modelSettings": {
- "description": "Settings used for training the model.",
- "$ref": "#/definitions/ImageModelSettingsObjectDetection",
- "x-nullable": true
+ "value": "Curated"
},
- "searchSpace": {
- "description": "Search space for sampling different combinations of models and their hyperparameters.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ImageModelDistributionSettingsObjectDetection"
- },
- "x-nullable": true,
- "x-ms-identifiers": []
+ {
+ "value": "UserCreated"
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "EnvironmentVersion": {
+ "description": "Environment version details.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "autoRebuild": {
+ "description": "Defines if image needs to be rebuilt based on base image changes.",
+ "default": "Disabled",
+ "$ref": "#/definitions/AutoRebuildSetting",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "build": {
+ "description": "Configuration settings for Docker build context.",
+ "$ref": "#/definitions/BuildContext",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "condaFile": {
+ "description": "Standard configuration file used by Conda that lets you install any kind of package, including Python, R, and C/C++ packages.\r\n",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "environmentType": {
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "$ref": "#/definitions/EnvironmentType",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ },
+ "image": {
+ "description": "Name of the image that will be used for the environment.\r\n",
+ "type": "string",
+ "example": "docker.io/tensorflow/serving:latest",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "inferenceConfig": {
+ "description": "Defines configuration specific to inference.",
+ "$ref": "#/definitions/InferenceContainerProperties",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "intellectualProperty": {
+ "description": "Intellectual Property details. Used if environment is an Intellectual Property.",
+ "$ref": "#/definitions/IntellectualProperty",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "osType": {
+ "description": "The OS type of the environment.",
+ "default": "Linux",
+ "$ref": "#/definitions/OperatingSystemType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the environment version.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
},
- "additionalProperties": false
+ "stage": {
+ "description": "Stage in the environment lifecycle assigned to this environment",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "ImageSweepSettings": {
- "description": "Model sweeping and hyperparameter sweeping related settings.",
- "required": [
- "samplingAlgorithm"
- ],
- "type": "object",
+ "x-ms-client-name": "EnvironmentVersionProperties",
+ "additionalProperties": false
+ },
+ "EnvironmentVersionResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "earlyTermination": {
- "description": "Type of early termination policy.",
- "$ref": "#/definitions/EarlyTerminationPolicy",
- "x-nullable": true
- },
- "samplingAlgorithm": {
- "description": "[Required] Type of the hyperparameter sampling algorithms.",
- "$ref": "#/definitions/SamplingAlgorithmType"
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/EnvironmentVersion"
+ }
+ },
+ "x-ms-client-name": "EnvironmentVersion",
+ "additionalProperties": false
+ },
+ "EnvironmentVersionResourceArmPaginatedResult": {
+ "description": "A paginated list of EnvironmentVersion entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of EnvironmentVersion objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type EnvironmentVersion.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/EnvironmentVersionResource"
}
- },
- "additionalProperties": false
+ }
},
- "ImageVertical": {
- "description": "Abstract class for AutoML tasks that train image (computer vision) models -\r\nsuch as Image Classification / Image Classification Multilabel / Image Object Detection / Image Instance Segmentation.",
- "required": [
- "limitSettings"
- ],
- "type": "object",
- "properties": {
- "limitSettings": {
- "description": "[Required] Limit settings for the AutoML job.",
- "$ref": "#/definitions/ImageLimitSettings"
- },
- "sweepSettings": {
- "description": "Model sweeping and hyperparameter sweeping related settings.",
- "$ref": "#/definitions/ImageSweepSettings",
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "ExportFormatType": {
+ "description": "The format of exported labels.",
+ "enum": [
+ "Dataset",
+ "Coco",
+ "CSV"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ExportFormatType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Dataset"
},
- "validationData": {
- "description": "Validation data inputs.",
- "$ref": "#/definitions/MLTableJobInput",
- "x-nullable": true
+ {
+ "value": "Coco"
},
- "validationDataSize": {
- "format": "double",
- "description": "The fraction of training dataset that needs to be set aside for validation purpose.\r\nValues between (0.0 , 1.0)\r\nApplied when validation dataset is not provided.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "CSV"
}
- },
- "additionalProperties": false
+ ]
},
- "IncrementalDataRefresh": {
- "description": "Whether IncrementalDataRefresh is enabled",
- "enum": [
- "Enabled",
- "Disabled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "IncrementalDataRefresh",
- "modelAsString": true,
- "values": [
- {
- "value": "Enabled"
- },
- {
- "value": "Disabled"
- }
+ "additionalProperties": false
+ },
+ "ExportSummary": {
+ "required": [
+ "format"
+ ],
+ "type": "object",
+ "properties": {
+ "endDateTime": {
+ "format": "date-time",
+ "description": "The time when the export was completed.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "exportedRowCount": {
+ "format": "int64",
+ "description": "The total number of labeled datapoints exported.",
+ "type": "integer",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "format": {
+ "description": "[Required] The format of exported labels, also as the discriminator.",
+ "$ref": "#/definitions/ExportFormatType",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "labelingJobId": {
+ "description": "Name and identifier of the job containing exported labels.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "startDateTime": {
+ "format": "date-time",
+ "description": "The time when the export was requested.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "IndexColumn": {
- "description": "Dto object representing index column",
- "type": "object",
- "properties": {
- "columnName": {
- "description": "Specifies the column name",
+ "discriminator": "format"
+ },
+ "Feature": {
+ "description": "Dto object representing feature",
+ "type": "object",
+ "properties": {
+ "dataType": {
+ "description": "Specifies type",
+ "default": "String",
+ "$ref": "#/definitions/FeatureDataType"
+ },
+ "description": {
+ "description": "Specifies description",
+ "type": "string",
+ "x-nullable": true
+ },
+ "featureName": {
+ "description": "Specifies name",
+ "type": "string",
+ "x-nullable": true
+ },
+ "tags": {
+ "description": "Specifies tags",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "dataType": {
- "description": "Specifies the data type",
- "default": "String",
- "$ref": "#/definitions/FeatureDataType"
- }
- },
- "additionalProperties": false
+ "x-nullable": true
+ }
},
- "InferenceContainerProperties": {
- "type": "object",
- "properties": {
- "livenessRoute": {
- "description": "The route to check the liveness of the inference server container.",
- "$ref": "#/definitions/Route"
- },
- "readinessRoute": {
- "description": "The route to check the readiness of the inference server container.",
- "$ref": "#/definitions/Route"
- },
- "scoringRoute": {
- "description": "The port to send the scoring requests to, within the inference server container.",
- "$ref": "#/definitions/Route"
- }
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "FeatureArmPaginatedResult": {
+ "description": "A paginated list of Feature entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of Feature objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type Feature.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/Feature"
+ },
+ "x-ms-identifiers": []
+ }
},
- "InferencingServer": {
- "required": [
- "serverType"
- ],
- "type": "object",
- "properties": {
- "serverType": {
- "description": "[Required] Inferencing server type for various targets.",
- "$ref": "#/definitions/InferencingServerType"
- }
- },
- "discriminator": "serverType"
- },
- "InferencingServerType": {
- "description": "Inferencing server type for various targets.",
- "enum": [
- "AzureMLOnline",
- "AzureMLBatch",
- "Triton",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "InferencingServerType",
- "modelAsString": true,
- "values": [
- {
- "value": "AzureMLOnline"
- },
- {
- "value": "AzureMLBatch"
- },
- {
- "value": "Triton"
- },
- {
- "value": "Custom"
- }
+ "additionalProperties": false
+ },
+ "FeatureAttributionDriftMonitoringSignal": {
+ "required": [
+ "baselineData",
+ "metricThreshold",
+ "targetData"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringSignalBase"
+ }
+ ],
+ "properties": {
+ "baselineData": {
+ "description": "[Required] The data to calculate drift against.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
- },
- "InputDeliveryMode": {
- "description": "Enum to determine the input data delivery mode.",
- "enum": [
- "ReadOnlyMount",
- "ReadWriteMount",
- "Download",
- "Direct",
- "EvalMount",
- "EvalDownload"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "InputDeliveryMode",
- "modelAsString": true,
- "values": [
- {
- "value": "ReadOnlyMount"
- },
- {
- "value": "ReadWriteMount"
- },
- {
- "value": "Download"
- },
- {
- "value": "Direct"
- },
- {
- "value": "EvalMount"
- },
- {
- "value": "EvalDownload"
- }
+ "metricThreshold": {
+ "description": "[Required] A list of metrics to calculate and their associated thresholds.",
+ "$ref": "#/definitions/FeatureAttributionMetricThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
- },
- "InputPathType": {
- "description": "Input path type for package inputs.",
- "enum": [
- "Url",
- "PathId",
- "PathVersion"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "InputPathType",
- "modelAsString": true,
- "values": [
- {
- "value": "Url"
- },
- {
- "value": "PathId"
- },
- {
- "value": "PathVersion"
- }
+ "targetData": {
+ "description": "[Required] The data which drift will be calculated for.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "InstanceSegmentationPrimaryMetrics": {
- "description": "Primary metrics for InstanceSegmentation tasks.",
- "enum": [
- "MeanAveragePrecision"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "InstanceSegmentationPrimaryMetrics",
- "modelAsString": true,
- "values": [
- {
- "value": "MeanAveragePrecision",
- "description": "Mean Average Precision (MAP) is the average of AP (Average Precision).\nAP is calculated for each class and averaged to get the MAP."
- }
+ "x-ms-discriminator-value": "FeatureAttributionDrift",
+ "additionalProperties": false
+ },
+ "FeatureAttributionMetric": {
+ "enum": [
+ "NormalizedDiscountedCumulativeGain"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "FeatureAttributionMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "NormalizedDiscountedCumulativeGain",
+ "description": "The Normalized Discounted Cumulative Gain metric."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "FeatureAttributionMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "properties": {
+ "metric": {
+ "description": "[Required] The feature attribution metric to calculate.",
+ "$ref": "#/definitions/FeatureAttributionMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "threshold": {
+ "description": "The threshold value. If null, a default value will be set depending on the selected metric.",
+ "$ref": "#/definitions/MonitoringThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "JobBase": {
- "description": "Base definition for a job.",
- "required": [
- "jobType"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "FeatureDataType": {
+ "enum": [
+ "String",
+ "Integer",
+ "Long",
+ "Float",
+ "Double",
+ "Binary",
+ "Datetime",
+ "Boolean"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "FeatureDataType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/ResourceBase"
- }
- ],
- "properties": {
- "componentId": {
- "description": "ARM resource ID of the component resource.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "value": "String"
},
- "computeId": {
- "description": "ARM resource ID of the compute resource.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Integer"
},
- "displayName": {
- "description": "Display name of job.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Long"
},
- "experimentName": {
- "description": "The name of the experiment the job belongs to. If not set, the job is placed in the \"Default\" experiment.",
- "default": "Default",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "identity": {
- "description": "Identity configuration. If set, this should be one of AmlToken, ManagedIdentity, UserIdentity or null.\r\nDefaults to AmlToken if null.",
- "$ref": "#/definitions/IdentityConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Float"
},
- "isArchived": {
- "description": "Is the asset archived?",
- "default": false,
- "type": "boolean",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- },
- "jobType": {
- "description": "[Required] Specifies the type of job.",
- "$ref": "#/definitions/JobType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "notificationSetting": {
- "description": "Notification setting for the job",
- "$ref": "#/definitions/NotificationSetting",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Double"
},
- "services": {
- "description": "List of JobEndpoints.\r\nFor local jobs, a job endpoint will have an endpoint value of FileStreamObject.",
- "type": "object",
- "additionalProperties": {
- "$ref": "#/definitions/JobService",
- "x-nullable": true
- },
- "x-nullable": true
+ {
+ "value": "Binary"
},
- "status": {
- "description": "Status of the job.",
- "$ref": "#/definitions/JobStatus",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- }
- },
- "discriminator": "jobType",
- "x-ms-client-name": "JobBaseProperties"
- },
- "JobBaseResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
- ],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/JobBase"
+ "value": "Datetime"
+ },
+ {
+ "value": "Boolean"
}
- },
- "x-ms-client-name": "JobBase",
- "additionalProperties": false
+ ]
},
- "JobBaseResourceArmPaginatedResult": {
- "description": "A paginated list of JobBase entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of JobBase objects. If null, there are no additional pages.",
- "type": "string"
+ "additionalProperties": false
+ },
+ "FeatureLags": {
+ "description": "Flag for generating lags for the numeric features.",
+ "enum": [
+ "None",
+ "Auto"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "FeatureLags",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None",
+ "description": "No feature lags generated."
},
- "value": {
- "description": "An array of objects of type JobBase.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/JobBaseResource"
- }
+ {
+ "value": "Auto",
+ "description": "System auto-generates feature lags."
}
- },
- "additionalProperties": false
+ ]
},
- "JobInput": {
- "description": "Command job definition.",
- "required": [
- "jobInputType"
- ],
- "type": "object",
- "properties": {
- "description": {
- "description": "Description for the input.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "FeatureSubset": {
+ "required": [
+ "features",
+ "filterType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringFeatureFilterBase"
+ }
+ ],
+ "properties": {
+ "features": {
+ "description": "[Required] The list of features to include.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "jobInputType": {
- "description": "[Required] Specifies the type of job.",
- "$ref": "#/definitions/JobInputType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "jobInputType"
- },
- "JobInputType": {
- "description": "Enum to determine the Job Input Type.",
- "enum": [
- "literal",
- "uri_file",
- "uri_folder",
- "mltable",
- "custom_model",
- "mlflow_model",
- "triton_model"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobInputType",
- "modelAsString": true,
- "values": [
- {
- "value": "literal"
- },
- {
- "value": "uri_file"
- },
- {
- "value": "uri_folder"
- },
- {
- "value": "mltable"
- },
- {
- "value": "custom_model"
- },
- {
- "value": "mlflow_model"
- },
- {
- "value": "triton_model"
- }
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "JobLimits": {
- "required": [
- "jobLimitsType"
- ],
- "type": "object",
- "properties": {
- "jobLimitsType": {
- "description": "[Required] JobLimit type.",
- "$ref": "#/definitions/JobLimitsType"
- },
- "timeout": {
- "format": "duration",
- "description": "The max run duration in ISO 8601 format, after which the job will be cancelled. Only supports duration with precision as low as Seconds.",
- "type": "string",
- "x-nullable": true
- }
- },
- "discriminator": "jobLimitsType"
+ "x-ms-discriminator-value": "FeatureSubset",
+ "additionalProperties": false
+ },
+ "FeatureWindow": {
+ "description": "Specifies the feature window",
+ "type": "object",
+ "properties": {
+ "featureWindowEnd": {
+ "format": "date-time",
+ "description": "Specifies the feature window end time",
+ "type": "string",
+ "x-nullable": true
+ },
+ "featureWindowStart": {
+ "format": "date-time",
+ "description": "Specifies the feature window start time",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "JobLimitsType": {
- "enum": [
- "Command",
- "Sweep"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobLimitsType",
- "modelAsString": true,
- "values": [
- {
- "value": "Command"
- },
- {
- "value": "Sweep"
- }
+ "additionalProperties": false
+ },
+ "FeaturesetContainer": {
+ "description": "Dto object representing feature set",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "provisioningState": {
+ "description": "Provisioning state for the featureset container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "JobOutput": {
- "description": "Job output definition container information on where to find job output/logs.",
- "required": [
- "jobOutputType"
- ],
- "type": "object",
+ "x-ms-client-name": "FeaturesetContainerProperties",
+ "additionalProperties": false
+ },
+ "FeaturesetContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "description": {
- "description": "Description for the output.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "jobOutputType": {
- "description": "[Required] Specifies the type of job.",
- "$ref": "#/definitions/JobOutputType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "jobOutputType"
- },
- "JobOutputType": {
- "description": "Enum to determine the Job Output Type.",
- "enum": [
- "uri_file",
- "uri_folder",
- "mltable",
- "custom_model",
- "mlflow_model",
- "triton_model"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobOutputType",
- "modelAsString": true,
- "values": [
- {
- "value": "uri_file"
- },
- {
- "value": "uri_folder"
- },
- {
- "value": "mltable"
- },
- {
- "value": "custom_model"
- },
- {
- "value": "mlflow_model"
- },
- {
- "value": "triton_model"
- }
- ]
- },
- "additionalProperties": false
- },
- "JobProvisioningState": {
- "description": "Enum to determine the job provisioning state.",
- "enum": [
- "Succeeded",
- "Failed",
- "Canceled",
- "InProgress"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobProvisioningState",
- "modelAsString": true,
- "values": [
- {
- "value": "Succeeded"
- },
- {
- "value": "Failed"
- },
- {
- "value": "Canceled"
- },
- {
- "value": "InProgress"
- }
- ]
- },
- "additionalProperties": false
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/FeaturesetContainer"
+ }
},
- "JobResourceConfiguration": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ResourceConfiguration"
+ "x-ms-client-name": "FeaturesetContainer",
+ "additionalProperties": false
+ },
+ "FeaturesetContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of FeaturesetContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of FeaturesetContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type FeaturesetContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/FeaturesetContainerResource"
}
- ],
- "properties": {
- "dockerArgs": {
- "description": "Extra arguments to pass to the Docker run command. This would override any parameters that have already been set by the system, or in this section. This parameter is only supported for Azure ML compute types.",
+ }
+ },
+ "additionalProperties": false
+ },
+ "FeaturesetJob": {
+ "description": "Dto object representing the feature set job",
+ "type": "object",
+ "properties": {
+ "createdDate": {
+ "format": "date-time",
+ "description": "Specifies the created date",
+ "type": "string",
+ "x-nullable": true
+ },
+ "displayName": {
+ "description": "Specifies the display name",
+ "type": "string",
+ "x-nullable": true
+ },
+ "duration": {
+ "format": "duration",
+ "description": "Specifies the duration",
+ "type": "string",
+ "x-nullable": true
+ },
+ "experimentId": {
+ "description": "Specifies the experiment id",
+ "type": "string",
+ "x-nullable": true
+ },
+ "featureWindow": {
+ "description": "Specifies the backfill feature window to be materialized",
+ "$ref": "#/definitions/FeatureWindow",
+ "x-nullable": true
+ },
+ "jobId": {
+ "description": "Specifies the job id",
+ "type": "string",
+ "x-nullable": true
+ },
+ "status": {
+ "description": "Specifies the job status",
+ "default": "Unknown",
+ "$ref": "#/definitions/JobStatus"
+ },
+ "tags": {
+ "description": "Specifies the tags if any",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
"x-nullable": true
},
- "shmSize": {
- "description": "Size of the docker container's shared memory block. This should be in the format of (number)(unit) where number as to be greater than 0 and the unit can be one of b(bytes), k(kilobytes), m(megabytes), or g(gigabytes).",
- "default": "2g",
- "pattern": "\\d+[bBkKmMgG]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
+ "x-nullable": true
},
- "additionalProperties": false
+ "type": {
+ "description": "Specifies the feature store job type",
+ "default": "RecurrentMaterialization",
+ "$ref": "#/definitions/FeaturestoreJobType"
+ }
},
- "JobScheduleAction": {
- "required": [
- "actionType",
- "jobDefinition"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/ScheduleActionBase"
- }
- ],
- "properties": {
- "jobDefinition": {
- "description": "[Required] Defines Schedule action definition details.",
- "$ref": "#/definitions/JobBase",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "x-ms-discriminator-value": "CreateJob",
- "additionalProperties": false
- },
- "JobService": {
- "description": "Job endpoint definition",
- "type": "object",
- "properties": {
- "endpoint": {
- "description": "Url for endpoint.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "errorMessage": {
- "description": "Any error in the service.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- },
- "jobServiceType": {
- "description": "Endpoint type.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "nodes": {
- "description": "Nodes that user would like to start the service on.\r\nIf Nodes is not set or set to null, the service will only be started on leader node.",
- "$ref": "#/definitions/Nodes",
- "x-nullable": true
- },
- "port": {
- "format": "int32",
- "description": "Port for endpoint set by user.",
- "type": "integer",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "properties": {
- "description": "Additional properties to set on the endpoint.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "FeaturesetJobArmPaginatedResult": {
+ "description": "A paginated list of FeaturesetJob entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of FeaturesetJob objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type FeaturesetJob.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/FeaturesetJob"
+ },
+ "x-ms-identifiers": []
+ }
+ },
+ "additionalProperties": false
+ },
+ "FeaturesetSpecification": {
+ "description": "Dto object representing specification",
+ "type": "object",
+ "properties": {
+ "path": {
+ "description": "Specifies the spec path",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "FeaturesetVersion": {
+ "description": "Dto object representing feature set version",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "entities": {
+ "description": "Specifies list of entities",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "status": {
- "description": "Status of endpoint.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "JobStatus": {
- "description": "The status of a job.",
- "enum": [
- "NotStarted",
- "Starting",
- "Provisioning",
- "Preparing",
- "Queued",
- "Running",
- "Finalizing",
- "CancelRequested",
- "Completed",
- "Failed",
- "Canceled",
- "NotResponding",
- "Paused",
- "Unknown",
- "Scheduled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobStatus",
- "modelAsString": true,
- "values": [
- {
- "value": "NotStarted",
- "description": "Run hasn't started yet."
- },
- {
- "value": "Starting",
- "description": "Run has started. The user has a run ID."
- },
- {
- "value": "Provisioning",
- "description": "(Not used currently) It will be used if ES is creating the compute target."
- },
- {
- "value": "Preparing",
- "description": "The run environment is being prepared."
- },
- {
- "value": "Queued",
- "description": "The job is queued in the compute target. For example, in BatchAI the job is in queued state, while waiting for all required nodes to be ready."
- },
- {
- "value": "Running",
- "description": "The job started to run in the compute target."
- },
- {
- "value": "Finalizing",
- "description": "Job is completed in the target. It is in output collection state now."
- },
- {
- "value": "CancelRequested",
- "description": "Cancellation has been requested for the job."
- },
- {
- "value": "Completed",
- "description": "Job completed successfully. This reflects that both the job itself and output collection states completed successfully"
- },
- {
- "value": "Failed",
- "description": "Job failed."
- },
- {
- "value": "Canceled",
- "description": "Following cancellation request, the job is now successfully canceled."
- },
- {
- "value": "NotResponding",
- "description": "When heartbeat is enabled, if the run isn't updating any information to RunHistory then the run goes to NotResponding state.\nNotResponding is the only state that is exempt from strict transition orders. A run can go from NotResponding to any of the previous states."
- },
- {
- "value": "Paused",
- "description": "The job is paused by users. Some adjustment to labeling jobs can be made only in paused state."
- },
- {
- "value": "Unknown",
- "description": "Default job status if not mapped to all other statuses"
- },
- {
- "value": "Scheduled",
- "description": "The job is in a scheduled state. Job is not in any active state."
- }
- ]
- },
- "additionalProperties": false
- },
- "JobTier": {
- "description": "Enum to determine the job tier.",
- "enum": [
- "Spot",
- "Basic",
- "Standard",
- "Premium"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobTier",
- "modelAsString": true,
- "values": [
- {
- "value": "Spot"
- },
- {
- "value": "Basic"
- },
- {
- "value": "Standard"
- },
- {
- "value": "Premium"
- }
- ]
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "JobType": {
- "description": "Enum to determine the type of job.",
- "enum": [
- "AutoML",
- "Command",
- "Labeling",
- "Sweep",
- "Pipeline",
- "Spark"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "JobType",
- "modelAsString": true,
- "values": [
- {
- "value": "AutoML"
- },
- {
- "value": "Command"
- },
- {
- "value": "Labeling"
- },
- {
- "value": "Sweep"
- },
- {
- "value": "Pipeline"
- },
- {
- "value": "Spark"
- }
+ "materializationSettings": {
+ "description": "Specifies the materialization settings",
+ "$ref": "#/definitions/MaterializationSettings",
+ "x-nullable": true
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the featureset version container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
]
},
- "additionalProperties": false
+ "specification": {
+ "description": "Specifies the feature spec details",
+ "$ref": "#/definitions/FeaturesetSpecification",
+ "x-nullable": true
+ },
+ "stage": {
+ "description": "Specifies the asset stage",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "KerberosCredentials": {
- "required": [
- "kerberosKdcAddress",
- "kerberosPrincipal",
- "kerberosRealm"
- ],
- "type": "object",
- "properties": {
- "kerberosKdcAddress": {
- "description": "[Required] IP Address or DNS HostName.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "kerberosPrincipal": {
- "description": "[Required] Kerberos Username",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "kerberosRealm": {
- "description": "[Required] Domain over which a Kerberos authentication server has the authority to authenticate a user, host or service.",
- "pattern": "[a-zA-Z0-9_]",
+ "x-ms-client-name": "FeaturesetVersionProperties",
+ "additionalProperties": false
+ },
+ "FeaturesetVersionBackfillRequest": {
+ "description": "Request payload for creating a backfill request for a given feature set version",
+ "type": "object",
+ "properties": {
+ "description": {
+ "description": "Specifies description",
+ "type": "string"
+ },
+ "displayName": {
+ "description": "Specifies description",
+ "type": "string"
+ },
+ "featureWindow": {
+ "description": "Specifies the backfill feature window to be materialized",
+ "$ref": "#/definitions/FeatureWindow",
+ "x-nullable": true
+ },
+ "resource": {
+ "description": "Specifies the compute resource settings",
+ "$ref": "#/definitions/MaterializationComputeResource"
+ },
+ "sparkConfiguration": {
+ "description": "Specifies the spark compute settings",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "x-nullable": true
}
},
- "additionalProperties": false
+ "tags": {
+ "description": "Specifies the tags",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
+ }
+ }
},
- "KerberosKeytabCredentials": {
- "required": [
- "secrets"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/KerberosCredentials"
- },
- {
- "$ref": "#/definitions/DatastoreCredentials"
+ "additionalProperties": false
+ },
+ "FeaturesetVersionResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/FeaturesetVersion"
+ }
+ },
+ "x-ms-client-name": "FeaturesetVersion",
+ "additionalProperties": false
+ },
+ "FeaturesetVersionResourceArmPaginatedResult": {
+ "description": "A paginated list of FeaturesetVersion entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of FeaturesetVersion objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type FeaturesetVersion.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/FeaturesetVersionResource"
}
- ],
+ }
+ },
+ "additionalProperties": false
+ },
+ "FeaturestoreEntityContainer": {
+ "description": "Dto object representing feature entity",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "provisioningState": {
+ "description": "Provisioning state for the featurestore entity container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
+ },
+ "x-ms-client-name": "FeaturestoreEntityContainerProperties",
+ "additionalProperties": false
+ },
+ "FeaturestoreEntityContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "secrets": {
- "description": "[Required] Keytab secrets.",
- "$ref": "#/definitions/KerberosKeytabSecrets",
- "x-ms-mutability": [
- "create",
- "update"
- ],
- "x-ms-secret": true
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/FeaturestoreEntityContainer"
+ }
+ },
+ "x-ms-client-name": "FeaturestoreEntityContainer",
+ "additionalProperties": false
+ },
+ "FeaturestoreEntityContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of FeaturestoreEntityContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of FeaturestoreEntityContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type FeaturestoreEntityContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/FeaturestoreEntityContainerResource"
}
+ }
+ },
+ "additionalProperties": false
+ },
+ "FeaturestoreEntityVersion": {
+ "description": "Dto object representing feature entity version",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "indexColumns": {
+ "description": "Specifies index columns",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/IndexColumn"
+ },
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the featurestore entity version.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
},
- "x-ms-discriminator-value": "KerberosKeytab",
- "additionalProperties": false
+ "stage": {
+ "description": "Specifies the asset stage",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "KerberosKeytabSecrets": {
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/DatastoreSecrets"
- }
- ],
+ "x-ms-client-name": "FeaturestoreEntityVersionProperties",
+ "additionalProperties": false
+ },
+ "FeaturestoreEntityVersionResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "kerberosKeytab": {
- "description": "Kerberos keytab secret.",
- "type": "string",
- "x-nullable": true
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/FeaturestoreEntityVersion"
+ }
+ },
+ "x-ms-client-name": "FeaturestoreEntityVersion",
+ "additionalProperties": false
+ },
+ "FeaturestoreEntityVersionResourceArmPaginatedResult": {
+ "description": "A paginated list of FeaturestoreEntityVersion entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of FeaturestoreEntityVersion objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type FeaturestoreEntityVersion.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/FeaturestoreEntityVersionResource"
}
- },
- "x-ms-discriminator-value": "KerberosKeytab",
- "additionalProperties": false
+ }
},
- "KerberosPasswordCredentials": {
- "required": [
- "secrets"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "FeaturestoreJobType": {
+ "enum": [
+ "RecurrentMaterialization",
+ "BackfillMaterialization"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "FeaturestoreJobType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/KerberosCredentials"
+ "value": "RecurrentMaterialization"
},
{
- "$ref": "#/definitions/DatastoreCredentials"
- }
- ],
- "properties": {
- "secrets": {
- "description": "[Required] Kerberos password secrets.",
- "$ref": "#/definitions/KerberosPasswordSecrets",
- "x-ms-mutability": [
- "create",
- "update"
- ],
- "x-ms-secret": true
+ "value": "BackfillMaterialization"
}
- },
- "x-ms-discriminator-value": "KerberosPassword",
- "additionalProperties": false
+ ]
},
- "KerberosPasswordSecrets": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "FeaturizationMode": {
+ "description": "Featurization mode - determines data featurization mode.",
+ "enum": [
+ "Auto",
+ "Custom",
+ "Off"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "FeaturizationMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Auto",
+ "description": "Auto mode, system performs featurization without any custom featurization inputs."
+ },
+ {
+ "value": "Custom",
+ "description": "Custom featurization."
+ },
{
- "$ref": "#/definitions/DatastoreSecrets"
+ "value": "Off",
+ "description": "Featurization off. 'Forecasting' task cannot use this value."
}
- ],
- "properties": {
- "kerberosPassword": {
- "description": "Kerberos password secret.",
+ ]
+ },
+ "additionalProperties": false
+ },
+ "FeaturizationSettings": {
+ "description": "Featurization Configuration.",
+ "type": "object",
+ "properties": {
+ "datasetLanguage": {
+ "description": "Dataset language, useful for the text data.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "FileSystemSource": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataImportSource"
+ }
+ ],
+ "properties": {
+ "path": {
+ "description": "Path on data import FileSystem source",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "file_system",
+ "additionalProperties": false
+ },
+ "FlavorData": {
+ "type": "object",
+ "properties": {
+ "data": {
+ "description": "Model flavor-specific data.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
- }
- },
- "x-ms-discriminator-value": "KerberosPassword",
- "additionalProperties": false
+ },
+ "x-nullable": true
+ }
},
- "KeyType": {
- "enum": [
- "Primary",
- "Secondary"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "KeyType",
- "modelAsString": true,
- "values": [
- {
- "value": "Primary"
- },
- {
- "value": "Secondary"
- }
+ "additionalProperties": false
+ },
+ "ForecastHorizon": {
+ "description": "The desired maximum forecast horizon in units of time-series frequency.",
+ "required": [
+ "mode"
+ ],
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "[Required] Set forecast horizon value selection mode.",
+ "$ref": "#/definitions/ForecastHorizonMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "KubernetesOnlineDeployment": {
- "description": "Properties specific to a KubernetesOnlineDeployment.",
- "type": "object",
- "allOf": [
+ "discriminator": "mode"
+ },
+ "ForecastHorizonMode": {
+ "description": "Enum to determine forecast horizon selection mode.",
+ "enum": [
+ "Auto",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ForecastHorizonMode",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/OnlineDeployment"
- }
- ],
- "properties": {
- "containerResourceRequirements": {
- "description": "The resource requirements for the container (cpu and memory).",
- "$ref": "#/definitions/ContainerResourceRequirements",
- "x-nullable": true
+ "value": "Auto",
+ "description": "Forecast horizon to be determined automatically."
+ },
+ {
+ "value": "Custom",
+ "description": "Use the custom forecast horizon."
}
- },
- "x-ms-discriminator-value": "Kubernetes",
- "additionalProperties": false
+ ]
},
- "LabelCategory": {
- "description": "Label category definition",
- "type": "object",
- "properties": {
- "classes": {
- "description": "Dictionary of label classes in this category.",
- "type": "object",
- "additionalProperties": {
- "$ref": "#/definitions/LabelClass",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ],
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "Forecasting": {
+ "description": "Forecasting task in AutoML Table vertical.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TableVertical"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "forecastingSettings": {
+ "description": "Forecasting task specific inputs.",
+ "$ref": "#/definitions/ForecastingSettings",
+ "x-nullable": true
+ },
+ "primaryMetric": {
+ "description": "Primary metric for forecasting task.",
+ "default": "NormalizedRootMeanSquaredError",
+ "$ref": "#/definitions/ForecastingPrimaryMetrics"
+ },
+ "trainingSettings": {
+ "description": "Inputs for training phase for an AutoML Job.",
+ "$ref": "#/definitions/ForecastingTrainingSettings",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Forecasting",
+ "additionalProperties": false
+ },
+ "ForecastingModels": {
+ "description": "Enum for all forecasting models supported by AutoML.",
+ "enum": [
+ "AutoArima",
+ "Prophet",
+ "Naive",
+ "SeasonalNaive",
+ "Average",
+ "SeasonalAverage",
+ "ExponentialSmoothing",
+ "Arimax",
+ "TCNForecaster",
+ "ElasticNet",
+ "GradientBoosting",
+ "DecisionTree",
+ "KNN",
+ "LassoLars",
+ "SGD",
+ "RandomForest",
+ "ExtremeRandomTrees",
+ "LightGBM",
+ "XGBoostRegressor"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ForecastingModels",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AutoArima",
+ "description": "Auto-Autoregressive Integrated Moving Average (ARIMA) model uses time-series data and statistical analysis to interpret the data and make future predictions.\nThis model aims to explain data by using time series data on its past values and uses linear regression to make predictions."
},
- "displayName": {
- "description": "Display name of the label category.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Prophet",
+ "description": "Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.\nIt works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well."
},
- "multiSelect": {
- "description": "Indicates whether it is allowed to select multiple classes in this category.",
- "default": "Disabled",
- "$ref": "#/definitions/MultiSelect",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "additionalProperties": false
- },
- "LabelClass": {
- "description": "Label class definition",
- "type": "object",
- "properties": {
- "displayName": {
- "description": "Display name of the label class.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Naive",
+ "description": "The Naive forecasting model makes predictions by carrying forward the latest target value for each time-series in the training data."
},
- "subclasses": {
- "description": "Dictionary of subclasses of the label class.",
- "type": "object",
- "additionalProperties": {
- "$ref": "#/definitions/LabelClass",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ],
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "LabelingDataConfiguration": {
- "description": "Labeling data configuration definition",
- "type": "object",
- "properties": {
- "dataId": {
- "description": "Resource Id of the data asset to perform labeling.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "SeasonalNaive",
+ "description": "The Seasonal Naive forecasting model makes predictions by carrying forward the latest season of target values for each time-series in the training data."
},
- "incrementalDataRefresh": {
- "description": "Indicates whether to enable incremental data refresh.",
- "default": "Disabled",
- "$ref": "#/definitions/IncrementalDataRefresh",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "additionalProperties": false
- },
- "LabelingJob": {
- "description": "Labeling job definition",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/JobBase"
- }
- ],
- "properties": {
- "createdDateTime": {
- "format": "date-time",
- "description": "Created time of the job in UTC timezone.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "value": "Average",
+ "description": "The Average forecasting model makes predictions by carrying forward the average of the target values for each time-series in the training data."
},
- "dataConfiguration": {
- "description": "Configuration of data used in the job.",
- "$ref": "#/definitions/LabelingDataConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "SeasonalAverage",
+ "description": "The Seasonal Average forecasting model makes predictions by carrying forward the average value of the latest season of data for each time-series in the training data."
},
- "jobInstructions": {
- "description": "Labeling instructions of the job.",
- "$ref": "#/definitions/LabelingJobInstructions",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ],
- "x-nullable": true
+ {
+ "value": "ExponentialSmoothing",
+ "description": "Exponential smoothing is a time series forecasting method for univariate data that can be extended to support data with a systematic trend or seasonal component."
},
- "labelCategories": {
- "description": "Label categories of the job.",
- "type": "object",
- "additionalProperties": {
- "$ref": "#/definitions/LabelCategory",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ],
- "x-nullable": true
+ {
+ "value": "Arimax",
+ "description": "An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be viewed as a multiple regression model with one or more autoregressive (AR) terms and/or one or more moving average (MA) terms.\nThis method is suitable for forecasting when data is stationary/non stationary, and multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity."
},
- "labelingJobMediaProperties": {
- "description": "Media type specific properties in the job.",
- "$ref": "#/definitions/LabelingJobMediaProperties",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "TCNForecaster",
+ "description": "TCNForecaster: Temporal Convolutional Networks Forecaster. //TODO: Ask forecasting team for brief intro."
},
- "mlAssistConfiguration": {
- "description": "Configuration of MLAssist feature in the job.",
- "default": "{\"MLAssist\":\"Disabled\"}",
- "$ref": "#/definitions/MLAssistConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "progressMetrics": {
- "description": "Progress metrics of the job.",
- "$ref": "#/definitions/ProgressMetrics",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "ElasticNet",
+ "description": "Elastic net is a popular type of regularized linear regression that combines two popular penalties, specifically the L1 and L2 penalty functions."
},
- "projectId": {
- "format": "uuid",
- "description": "Internal id of the job(Previously called project).",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "provisioningState": {
- "description": "Specifies the labeling job provisioning state.",
- "$ref": "#/definitions/JobProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "statusMessages": {
- "description": "Status messages of the job.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/StatusMessage"
- },
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true,
- "x-ms-identifiers": []
- }
- },
- "x-ms-discriminator-value": "Labeling",
- "x-ms-client-name": "LabelingJobProperties",
- "additionalProperties": false
- },
- "LabelingJobImageProperties": {
- "description": "Properties of a labeling job for image data",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/LabelingJobMediaProperties"
- }
- ],
- "properties": {
- "annotationType": {
- "description": "Annotation type of image labeling job.",
- "default": "Classification",
- "$ref": "#/definitions/ImageAnnotationType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "x-ms-discriminator-value": "Image",
- "additionalProperties": false
- },
- "LabelingJobInstructions": {
- "description": "Instructions for labeling job",
- "type": "object",
- "properties": {
- "uri": {
- "description": "The link to a page with detailed labeling instructions for labelers.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ],
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "LabelingJobMediaProperties": {
- "description": "Properties of a labeling job",
- "required": [
- "mediaType"
- ],
- "type": "object",
- "properties": {
- "mediaType": {
- "description": "[Required] Media type of the job.",
- "$ref": "#/definitions/MediaType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "mediaType"
- },
- "LabelingJobResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
+ "value": "GradientBoosting",
+ "description": "The technique of transiting week learners into a strong learner is called Boosting. The gradient boosting algorithm process works on this theory of execution."
+ },
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
- ],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/LabelingJob"
- }
- },
- "x-ms-client-name": "LabelingJob",
- "additionalProperties": false
- },
- "LabelingJobResourceArmPaginatedResult": {
- "description": "A paginated list of LabelingJob entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of LabelingJob objects. If null, there are no additional pages.",
- "type": "string"
+ "value": "DecisionTree",
+ "description": "Decision Trees are a non-parametric supervised learning method used for both classification and regression tasks.\nThe goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features."
},
- "value": {
- "description": "An array of objects of type LabelingJob.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/LabelingJobResource"
- }
- }
- },
- "additionalProperties": false
- },
- "LabelingJobTextProperties": {
- "description": "Properties of a labeling job for text data",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/LabelingJobMediaProperties"
- }
- ],
- "properties": {
- "annotationType": {
- "description": "Annotation type of text labeling job.",
- "default": "Classification",
- "$ref": "#/definitions/TextAnnotationType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "x-ms-discriminator-value": "Text",
- "additionalProperties": false
- },
- "LearningRateScheduler": {
- "description": "Learning rate scheduler enum.",
- "enum": [
- "None",
- "WarmupCosine",
- "Step"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "LearningRateScheduler",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No learning rate scheduler selected."
- },
- {
- "value": "WarmupCosine",
- "description": "Cosine Annealing With Warmup."
- },
- {
- "value": "Step",
- "description": "Step learning rate scheduler."
- }
- ]
- },
- "additionalProperties": false
- },
- "ListViewType": {
- "enum": [
- "ActiveOnly",
- "ArchivedOnly",
- "All"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "ActiveOnly"
- },
- {
- "value": "ArchivedOnly"
- },
- {
- "value": "All"
- }
- ]
- },
- "additionalProperties": false
- },
- "LiteralJobInput": {
- "description": "Literal input type.",
- "required": [
- "value"
- ],
- "type": "object",
- "allOf": [
+ "value": "KNN",
+ "description": "K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new datapoints\nwhich further means that the new data point will be assigned a value based on how closely it matches the points in the training set."
+ },
{
- "$ref": "#/definitions/JobInput"
- }
- ],
- "properties": {
- "value": {
- "description": "[Required] Literal value for the input.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string"
- }
- },
- "x-ms-discriminator-value": "literal",
- "additionalProperties": false
- },
- "LogVerbosity": {
- "description": "Enum for setting log verbosity.",
- "enum": [
- "NotSet",
- "Debug",
- "Info",
- "Warning",
- "Error",
- "Critical"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "LogVerbosity",
- "modelAsString": true,
- "values": [
- {
- "value": "NotSet",
- "description": "No logs emitted."
- },
- {
- "value": "Debug",
- "description": "Debug and above log statements logged."
- },
- {
- "value": "Info",
- "description": "Info and above log statements logged."
- },
- {
- "value": "Warning",
- "description": "Warning and above log statements logged."
- },
- {
- "value": "Error",
- "description": "Error and above log statements logged."
- },
- {
- "value": "Critical",
- "description": "Only critical statements logged."
- }
- ]
- },
- "additionalProperties": false
- },
- "ManagedIdentity": {
- "description": "Managed identity configuration.",
- "type": "object",
- "allOf": [
+ "value": "LassoLars",
+ "description": "Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an L1 prior as regularizer."
+ },
{
- "$ref": "#/definitions/IdentityConfiguration"
- }
- ],
- "properties": {
- "clientId": {
- "format": "uuid",
- "description": "Specifies a user-assigned identity by client ID. For system-assigned, do not set this field.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "value": "SGD",
+ "description": "SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning applications\nto find the model parameters that correspond to the best fit between predicted and actual outputs.\nIt's an inexact but powerful technique."
},
- "objectId": {
- "format": "uuid",
- "description": "Specifies a user-assigned identity by object ID. For system-assigned, do not set this field.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "RandomForest",
+ "description": "Random forest is a supervised learning algorithm.\nThe \"forest\" it builds, is an ensemble of decision trees, usually trained with the “bagging†method.\nThe general idea of the bagging method is that a combination of learning models increases the overall result."
},
- "resourceId": {
- "description": "Specifies a user-assigned identity by ARM resource ID. For system-assigned, do not set this field.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "ExtremeRandomTrees",
+ "description": "Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many decision trees. It is related to the widely used random forest algorithm."
+ },
+ {
+ "value": "LightGBM",
+ "description": "LightGBM is a gradient boosting framework that uses tree based learning algorithms."
+ },
+ {
+ "value": "XGBoostRegressor",
+ "description": "XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model using ensemble of base learners."
}
- },
- "x-ms-discriminator-value": "Managed",
- "additionalProperties": false
+ ]
},
- "ManagedOnlineDeployment": {
- "description": "Properties specific to a ManagedOnlineDeployment.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "ForecastingPrimaryMetrics": {
+ "description": "Primary metrics for Forecasting task.",
+ "enum": [
+ "SpearmanCorrelation",
+ "NormalizedRootMeanSquaredError",
+ "R2Score",
+ "NormalizedMeanAbsoluteError"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ForecastingPrimaryMetrics",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "SpearmanCorrelation",
+ "description": "The Spearman's rank coefficient of correlation is a non-parametric measure of rank correlation."
+ },
{
- "$ref": "#/definitions/OnlineDeployment"
- }
- ],
- "x-ms-discriminator-value": "Managed",
- "additionalProperties": false
- },
- "MaterializationSettings": {
- "type": "object",
- "properties": {
- "notification": {
- "description": "Specifies the notification details",
- "$ref": "#/definitions/NotificationSetting",
- "x-nullable": true
+ "value": "NormalizedRootMeanSquaredError",
+ "description": "The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between models with different scales."
},
- "resource": {
- "description": "Specifies the compute resource settings",
- "$ref": "#/definitions/MaterializationComputeResource",
- "x-nullable": true
+ {
+ "value": "R2Score",
+ "description": "The R2 score is one of the performance evaluation measures for forecasting-based machine learning models."
},
- "schedule": {
- "description": "Specifies the schedule details",
- "$ref": "#/definitions/RecurrenceTrigger",
- "x-nullable": true
+ {
+ "value": "NormalizedMeanAbsoluteError",
+ "description": "The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute Error (MAE) of (time) series with different scales."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ForecastingSettings": {
+ "description": "Forecasting specific parameters.",
+ "type": "object",
+ "properties": {
+ "countryOrRegionForHolidays": {
+ "description": "Country or region for holidays for forecasting tasks.\r\nThese should be ISO 3166 two-letter country/region codes, for example 'US' or 'GB'.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "cvStepSize": {
+ "format": "int32",
+ "description": "Number of periods between the origin time of one CV fold and the next fold. For\r\nexample, if `CVStepSize` = 3 for daily data, the origin time for each fold will be\r\nthree days apart.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "featureLags": {
+ "description": "Flag for generating lags for the numeric features with 'auto' or null.",
+ "default": "None",
+ "$ref": "#/definitions/FeatureLags"
+ },
+ "featuresUnknownAtForecastTime": {
+ "description": "The feature columns that are available for training but unknown at the time of forecast/inference.\r\nIf features_unknown_at_forecast_time is not set, it is assumed that all the feature columns in the dataset are known at inference time.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "sparkConfiguration": {
- "description": "Specifies the spark compute settings",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "x-nullable": true
+ },
+ "forecastHorizon": {
+ "description": "The desired maximum forecast horizon in units of time-series frequency.",
+ "default": "{\"Mode\": \"Custom\", \"Value\": 1}",
+ "$ref": "#/definitions/ForecastHorizon"
+ },
+ "frequency": {
+ "description": "When forecasting, this parameter represents the period with which the forecast is desired, for example daily, weekly, yearly, etc. The forecast frequency is dataset frequency by default.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "seasonality": {
+ "description": "Set time series seasonality as an integer multiple of the series frequency.\r\nIf seasonality is set to 'auto', it will be inferred.",
+ "default": "{\"Mode\": \"Auto\"}",
+ "$ref": "#/definitions/Seasonality"
+ },
+ "shortSeriesHandlingConfig": {
+ "description": "The parameter defining how if AutoML should handle short time series.",
+ "default": "Auto",
+ "$ref": "#/definitions/ShortSeriesHandlingConfiguration"
+ },
+ "targetAggregateFunction": {
+ "description": "The function to be used to aggregate the time series target column to conform to a user specified frequency.\r\nIf the TargetAggregateFunction is set i.e. not 'None', but the freq parameter is not set, the error is raised. The possible target aggregation functions are: \"sum\", \"max\", \"min\" and \"mean\".",
+ "default": "None",
+ "$ref": "#/definitions/TargetAggregationFunction"
+ },
+ "targetLags": {
+ "description": "The number of past periods to lag from the target column.",
+ "$ref": "#/definitions/TargetLags",
+ "x-nullable": true
+ },
+ "targetRollingWindowSize": {
+ "description": "The number of past periods used to create a rolling window average of the target column.",
+ "$ref": "#/definitions/TargetRollingWindowSize",
+ "x-nullable": true
+ },
+ "timeColumnName": {
+ "description": "The name of the time column. This parameter is required when forecasting to specify the datetime column in the input data used for building the time series and inferring its frequency.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "timeSeriesIdColumnNames": {
+ "description": "The names of columns used to group a timeseries. It can be used to create multiple series.\r\nIf grain is not defined, the data set is assumed to be one time-series. This parameter is used with task type forecasting.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "storeType": {
- "description": "Specifies the stores to which materialization should happen",
- "default": "None",
- "$ref": "#/definitions/MaterializationStoreType"
- }
+ "x-nullable": true
},
- "additionalProperties": false
+ "useStl": {
+ "description": "Configure STL Decomposition of the time-series target column.",
+ "default": "None",
+ "$ref": "#/definitions/UseStl"
+ }
},
- "MaterializationStoreType": {
- "enum": [
- "None",
- "Online",
- "Offline",
- "OnlineAndOffline"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "MaterializationStoreType",
- "modelAsString": true,
- "values": [
- {
- "value": "None"
- },
- {
- "value": "Online"
- },
- {
- "value": "Offline"
- },
- {
- "value": "OnlineAndOffline"
- }
- ]
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "ForecastingTrainingSettings": {
+ "description": "Forecasting Training related configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TrainingSettings"
+ }
+ ],
+ "properties": {
+ "allowedTrainingAlgorithms": {
+ "description": "Allowed models for forecasting task.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ForecastingModels"
+ },
+ "x-nullable": true
+ },
+ "blockedTrainingAlgorithms": {
+ "description": "Blocked models for forecasting task.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ForecastingModels"
+ },
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "GetFeatureRequest": {
+ "description": "Request payload to retrieve feature information from a given feature set version",
+ "type": "object",
+ "properties": {
+ "featureName": {
+ "description": "Specifies name of the feature.",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "MedianStoppingPolicy": {
- "description": "Defines an early termination policy based on running averages of the primary metric of all runs",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "Goal": {
+ "description": "Defines supported metric goals for hyperparameter tuning",
+ "enum": [
+ "Minimize",
+ "Maximize"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "Goal",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Minimize"
+ },
{
- "$ref": "#/definitions/EarlyTerminationPolicy"
+ "value": "Maximize"
}
- ],
- "x-ms-discriminator-value": "MedianStopping",
- "additionalProperties": false
+ ]
},
- "MediaType": {
- "description": "Media type of data asset.",
- "enum": [
- "Image",
- "Text"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "MediaType",
- "modelAsString": true,
- "values": [
- {
- "value": "Image"
- },
- {
- "value": "Text"
- }
+ "additionalProperties": false
+ },
+ "GridSamplingAlgorithm": {
+ "description": "Defines a Sampling Algorithm that exhaustively generates every value combination in the space",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/SamplingAlgorithm"
+ }
+ ],
+ "x-ms-discriminator-value": "Grid",
+ "additionalProperties": false
+ },
+ "HdfsDatastore": {
+ "required": [
+ "nameNodeAddress"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/Datastore"
+ }
+ ],
+ "properties": {
+ "hdfsServerCertificate": {
+ "description": "The TLS cert of the HDFS server. Needs to be a base64 encoded string. Required if \"Https\" protocol is selected.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "nameNodeAddress": {
+ "description": "[Required] IP Address or DNS HostName.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "protocol": {
+ "description": "Protocol used to communicate with the storage account (Https/Http).",
+ "default": "http",
+ "type": "string",
+ "example": "https",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "MLAssistConfiguration": {
- "description": "Labeling MLAssist configuration definition",
- "required": [
- "mlAssist"
- ],
- "type": "object",
- "properties": {
- "mlAssist": {
- "description": "[Required] Indicates whether MLAssist feature is enabled.",
- "$ref": "#/definitions/MLAssistConfigurationType",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "discriminator": "mlAssist"
+ "x-ms-discriminator-value": "Hdfs",
+ "additionalProperties": false
+ },
+ "IdAssetReference": {
+ "description": "Reference to an asset via its ARM resource ID.",
+ "required": [
+ "assetId"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetReferenceBase"
+ }
+ ],
+ "properties": {
+ "assetId": {
+ "description": "[Required] ARM resource ID of the asset.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
+ },
+ "x-ms-discriminator-value": "Id",
+ "additionalProperties": false
+ },
+ "IdentityConfiguration": {
+ "description": "Base definition for identity configuration.",
+ "required": [
+ "identityType"
+ ],
+ "type": "object",
+ "properties": {
+ "identityType": {
+ "description": "[Required] Specifies the type of identity framework.",
+ "$ref": "#/definitions/IdentityConfigurationType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "MLAssistConfigurationDisabled": {
- "description": "Labeling MLAssist configuration definition when MLAssist is disabled",
- "type": "object",
- "allOf": [
+ "discriminator": "identityType"
+ },
+ "IdentityConfigurationType": {
+ "description": "Enum to determine identity framework.",
+ "enum": [
+ "Managed",
+ "AMLToken",
+ "UserIdentity"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "IdentityConfigurationType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Managed"
+ },
{
- "$ref": "#/definitions/MLAssistConfiguration"
+ "value": "AMLToken"
+ },
+ {
+ "value": "UserIdentity"
}
- ],
- "x-ms-discriminator-value": "Disabled",
- "additionalProperties": false
+ ]
},
- "MLAssistConfigurationEnabled": {
- "description": "Labeling MLAssist configuration definition when MLAssist is enabled",
- "required": [
- "inferencingComputeBinding",
- "trainingComputeBinding"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "ImageAnnotationType": {
+ "description": "Annotation type of image data.",
+ "enum": [
+ "Classification",
+ "BoundingBox",
+ "InstanceSegmentation"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ImageAnnotationType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Classification"
+ },
+ {
+ "value": "BoundingBox"
+ },
{
- "$ref": "#/definitions/MLAssistConfiguration"
+ "value": "InstanceSegmentation"
}
- ],
- "properties": {
- "inferencingComputeBinding": {
- "description": "[Required] AML compute binding used in inferencing.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- },
- "trainingComputeBinding": {
- "description": "[Required] AML compute binding used in training.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "x-ms-discriminator-value": "Enabled",
- "additionalProperties": false
- },
- "MLAssistConfigurationType": {
- "enum": [
- "Enabled",
- "Disabled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "MLAssistConfigurationType",
- "modelAsString": true,
- "values": [
- {
- "value": "Enabled"
- },
- {
- "value": "Disabled"
- }
- ]
- },
- "additionalProperties": false
- },
- "MLFlowAutologgerState": {
- "description": "Enum to determine the state of mlflow autologger.",
- "enum": [
- "Enabled",
- "Disabled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "MLFlowAutologgerState",
- "modelAsString": true,
- "values": [
- {
- "value": "Enabled"
- },
- {
- "value": "Disabled"
- }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ImageClassification": {
+ "description": "Image Classification. Multi-class image classification is used when an image is classified with only a single label\r\nfrom a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog' or a 'duck'.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageClassificationBase"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric to optimize for this task.",
+ "default": "Accuracy",
+ "$ref": "#/definitions/ClassificationPrimaryMetrics"
+ }
+ },
+ "x-ms-discriminator-value": "ImageClassification",
+ "additionalProperties": false
+ },
+ "ImageClassificationBase": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageVertical"
+ }
+ ],
+ "properties": {
+ "modelSettings": {
+ "description": "Settings used for training the model.",
+ "$ref": "#/definitions/ImageModelSettingsClassification",
+ "x-nullable": true
+ },
+ "searchSpace": {
+ "description": "Search space for sampling different combinations of models and their hyperparameters.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ImageModelDistributionSettingsClassification"
+ },
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageClassificationMultilabel": {
+ "description": "Image Classification Multilabel. Multi-label image classification is used when an image could have one or more labels\r\nfrom a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageClassificationBase"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric to optimize for this task.",
+ "default": "IOU",
+ "$ref": "#/definitions/ClassificationMultilabelPrimaryMetrics"
+ }
+ },
+ "x-ms-discriminator-value": "ImageClassificationMultilabel",
+ "additionalProperties": false
+ },
+ "ImageInstanceSegmentation": {
+ "description": "Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level,\r\ndrawing a polygon around each object in the image.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageObjectDetectionBase"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric to optimize for this task.",
+ "default": "MeanAveragePrecision",
+ "$ref": "#/definitions/InstanceSegmentationPrimaryMetrics"
+ }
+ },
+ "x-ms-discriminator-value": "ImageInstanceSegmentation",
+ "additionalProperties": false
+ },
+ "ImageLimitSettings": {
+ "description": "Limit settings for the AutoML job.",
+ "type": "object",
+ "properties": {
+ "maxConcurrentTrials": {
+ "format": "int32",
+ "description": "Maximum number of concurrent AutoML iterations.",
+ "default": 1,
+ "type": "integer"
+ },
+ "maxTrials": {
+ "format": "int32",
+ "description": "Maximum number of AutoML iterations.",
+ "default": 1,
+ "type": "integer"
+ },
+ "timeout": {
+ "format": "duration",
+ "description": "AutoML job timeout.",
+ "default": "P7D",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageModelDistributionSettings": {
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "object",
+ "properties": {
+ "amsGradient": {
+ "description": "Enable AMSGrad when optimizer is 'adam' or 'adamw'.",
+ "type": "string",
+ "example": "choice(true, false)",
+ "x-nullable": true
+ },
+ "augmentations": {
+ "description": "Settings for using Augmentations.",
+ "type": "string",
+ "example": "choice('hflip;mosaic;random_crop', 'mosaic')",
+ "x-nullable": true
+ },
+ "beta1": {
+ "description": "Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
+ "type": "string",
+ "example": "uniform(0, 1)",
+ "x-nullable": true
+ },
+ "beta2": {
+ "description": "Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
+ "type": "string",
+ "example": "uniform(0, 1)",
+ "x-nullable": true
+ },
+ "distributed": {
+ "description": "Whether to use distributer training.",
+ "type": "string",
+ "example": "choice(true, false)",
+ "x-nullable": true
+ },
+ "earlyStopping": {
+ "description": "Enable early stopping logic during training.",
+ "type": "string",
+ "example": "choice(true, false)",
+ "x-nullable": true
+ },
+ "earlyStoppingDelay": {
+ "description": "Minimum number of epochs or validation evaluations to wait before primary metric improvement\r\nis tracked for early stopping. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 5)",
+ "x-nullable": true
+ },
+ "earlyStoppingPatience": {
+ "description": "Minimum number of epochs or validation evaluations with no primary metric improvement before\r\nthe run is stopped. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 5)",
+ "x-nullable": true
+ },
+ "enableOnnxNormalization": {
+ "description": "Enable normalization when exporting ONNX model.",
+ "type": "string",
+ "example": "choice(true, false)",
+ "x-nullable": true
+ },
+ "evaluationFrequency": {
+ "description": "Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 5)",
+ "x-nullable": true
+ },
+ "gradientAccumulationStep": {
+ "description": "Gradient accumulation means running a configured number of \"GradAccumulationStep\" steps without\r\nupdating the model weights while accumulating the gradients of those steps, and then using\r\nthe accumulated gradients to compute the weight updates. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 5)",
+ "x-nullable": true
+ },
+ "layersToFreeze": {
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "string",
+ "example": "choice(1, 2)",
+ "x-nullable": true
+ },
+ "learningRate": {
+ "description": "Initial learning rate. Must be a float in the range [0, 1].",
+ "type": "string",
+ "example": "uniform(0.0005, 0.005)",
+ "x-nullable": true
+ },
+ "learningRateScheduler": {
+ "description": "Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.",
+ "type": "string",
+ "example": "choice('warmup_cosine', 'step')",
+ "x-nullable": true
+ },
+ "modelName": {
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "string",
+ "example": "choice('seresnext', 'resnest50')",
+ "x-nullable": true
+ },
+ "momentum": {
+ "description": "Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].",
+ "type": "string",
+ "example": "quniform(0, 1)",
+ "x-nullable": true
+ },
+ "nesterov": {
+ "description": "Enable nesterov when optimizer is 'sgd'.",
+ "type": "string",
+ "example": "choice(true, false)",
+ "x-nullable": true
+ },
+ "numberOfEpochs": {
+ "description": "Number of training epochs. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(15, 30)",
+ "x-nullable": true
+ },
+ "numberOfWorkers": {
+ "description": "Number of data loader workers. Must be a non-negative integer.",
+ "type": "string",
+ "example": "uniform(8, 16)",
+ "x-nullable": true
+ },
+ "optimizer": {
+ "description": "Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.",
+ "type": "string",
+ "example": "choice('sgd', 'adam', 'adamw')",
+ "x-nullable": true
+ },
+ "randomSeed": {
+ "description": "Random seed to be used when using deterministic training.",
+ "type": "string",
+ "example": "loguniform(0, 1)",
+ "x-nullable": true
+ },
+ "stepLRGamma": {
+ "description": "Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1].",
+ "type": "string",
+ "example": "choice(0.1, 0.2, 0.25)",
+ "x-nullable": true
+ },
+ "stepLRStepSize": {
+ "description": "Value of step size when learning rate scheduler is 'step'. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 2, 3)",
+ "x-nullable": true
+ },
+ "trainingBatchSize": {
+ "description": "Training batch size. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 2, 3)",
+ "x-nullable": true
+ },
+ "validationBatchSize": {
+ "description": "Validation batch size. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 2, 3)",
+ "x-nullable": true
+ },
+ "warmupCosineLRCycles": {
+ "description": "Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1].",
+ "type": "string",
+ "example": "uniform(0, 1)",
+ "x-nullable": true
+ },
+ "warmupCosineLRWarmupEpochs": {
+ "description": "Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(1, 2, 3)",
+ "x-nullable": true
+ },
+ "weightDecay": {
+ "description": "Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1].",
+ "type": "string",
+ "example": "uniform(0, 1)",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageModelDistributionSettingsClassification": {
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageModelDistributionSettings"
+ }
+ ],
+ "properties": {
+ "trainingCropSize": {
+ "description": "Image crop size that is input to the neural network for the training dataset. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(224, 360)",
+ "x-nullable": true
+ },
+ "validationCropSize": {
+ "description": "Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(224, 360)",
+ "x-nullable": true
+ },
+ "validationResizeSize": {
+ "description": "Image size to which to resize before cropping for validation dataset. Must be a positive integer.",
+ "type": "string",
+ "example": "choice(128, 256)",
+ "x-nullable": true
+ },
+ "weightedLoss": {
+ "description": "Weighted loss. The accepted values are 0 for no weighted loss.\r\n1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be 0 or 1 or 2.",
+ "type": "string",
+ "example": "choice(0, 1, 2)",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageModelDistributionSettingsObjectDetection": {
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageModelDistributionSettings"
+ }
+ ],
+ "properties": {
+ "boxDetectionsPerImage": {
+ "description": "Maximum number of detections per image, for all classes. Must be a positive integer.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice(50, 100)",
+ "x-nullable": true
+ },
+ "boxScoreThreshold": {
+ "description": "During inference, only return proposals with a classification score greater than\r\nBoxScoreThreshold. Must be a float in the range[0, 1].",
+ "type": "string",
+ "example": "uniform(0.1, 0.2)",
+ "x-nullable": true
+ },
+ "imageSize": {
+ "description": "Image size for train and validation. Must be a positive integer.\r\nNote: The training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice(224, 640)",
+ "x-nullable": true
+ },
+ "maxSize": {
+ "description": "Maximum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice(640, 1333)",
+ "x-nullable": true
+ },
+ "minSize": {
+ "description": "Minimum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice(300, 600)",
+ "x-nullable": true
+ },
+ "modelSize": {
+ "description": "Model size. Must be 'small', 'medium', 'large', or 'xlarge'.\r\nNote: training run may get into CUDA OOM if the model size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice('small', 'medium', 'large', 'xlarge')",
+ "x-nullable": true
+ },
+ "multiScale": {
+ "description": "Enable multi-scale image by varying image size by +/- 50%.\r\nNote: training run may get into CUDA OOM if no sufficient GPU memory.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice(true, false)",
+ "x-nullable": true
+ },
+ "nmsIouThreshold": {
+ "description": "IOU threshold used during inference in NMS post processing. Must be float in the range [0, 1].",
+ "type": "string",
+ "example": "uniform(0.1, 0.2)",
+ "x-nullable": true
+ },
+ "tileGridSize": {
+ "description": "The grid size to use for tiling each image. Note: TileGridSize must not be\r\nNone to enable small object detection logic. A string containing two integers in mxn format.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "choice('3x2', '2x2')",
+ "x-nullable": true
+ },
+ "tileOverlapRatio": {
+ "description": "Overlap ratio between adjacent tiles in each dimension. Must be float in the range [0, 1).\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "uniform(0.1, 0.2)",
+ "x-nullable": true
+ },
+ "tilePredictionsNmsThreshold": {
+ "description": "The IOU threshold to use to perform NMS while merging predictions from tiles and image.\r\nUsed in validation/ inference. Must be float in the range [0, 1].\r\nNote: This settings is not supported for the 'yolov5' algorithm.\r\nNMS: Non-maximum suppression",
+ "type": "string",
+ "example": "uniform(0.2, 0.3)",
+ "x-nullable": true
+ },
+ "validationIouThreshold": {
+ "description": "IOU threshold to use when computing validation metric. Must be float in the range [0, 1].",
+ "type": "string",
+ "example": "uniform(0.2, 0.3)",
+ "x-nullable": true
+ },
+ "validationMetricType": {
+ "description": "Metric computation method to use for validation metrics. Must be 'none', 'coco', 'voc', or 'coco_voc'.",
+ "type": "string",
+ "example": "choice('none', 'coco', 'voc', 'coco_voc')",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageModelSettings": {
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "object",
+ "properties": {
+ "advancedSettings": {
+ "description": "Settings for advanced scenarios.",
+ "type": "string",
+ "example": "key1:val1;key2;key3:val3;key4",
+ "x-nullable": true
+ },
+ "amsGradient": {
+ "description": "Enable AMSGrad when optimizer is 'adam' or 'adamw'.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "augmentations": {
+ "description": "Settings for using Augmentations.",
+ "type": "string",
+ "example": "hflip;mosaic;random_crop",
+ "x-nullable": true
+ },
+ "beta1": {
+ "format": "float",
+ "description": "Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "beta2": {
+ "format": "float",
+ "description": "Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "checkpointFrequency": {
+ "format": "int32",
+ "description": "Frequency to store model checkpoints. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "checkpointModel": {
+ "description": "The pretrained checkpoint model for incremental training.",
+ "$ref": "#/definitions/MLFlowModelJobInput",
+ "x-nullable": true
+ },
+ "checkpointRunId": {
+ "description": "The id of a previous run that has a pretrained checkpoint for incremental training.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "distributed": {
+ "description": "Whether to use distributed training.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "earlyStopping": {
+ "description": "Enable early stopping logic during training.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "earlyStoppingDelay": {
+ "format": "int32",
+ "description": "Minimum number of epochs or validation evaluations to wait before primary metric improvement\r\nis tracked for early stopping. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "earlyStoppingPatience": {
+ "format": "int32",
+ "description": "Minimum number of epochs or validation evaluations with no primary metric improvement before\r\nthe run is stopped. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "enableOnnxNormalization": {
+ "description": "Enable normalization when exporting ONNX model.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "evaluationFrequency": {
+ "format": "int32",
+ "description": "Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "gradientAccumulationStep": {
+ "format": "int32",
+ "description": "Gradient accumulation means running a configured number of \"GradAccumulationStep\" steps without\r\nupdating the model weights while accumulating the gradients of those steps, and then using\r\nthe accumulated gradients to compute the weight updates. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "layersToFreeze": {
+ "format": "int32",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "learningRate": {
+ "format": "float",
+ "description": "Initial learning rate. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "learningRateScheduler": {
+ "description": "Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.",
+ "default": "None",
+ "$ref": "#/definitions/LearningRateScheduler"
+ },
+ "modelName": {
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "momentum": {
+ "format": "float",
+ "description": "Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "nesterov": {
+ "description": "Enable nesterov when optimizer is 'sgd'.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "numberOfEpochs": {
+ "format": "int32",
+ "description": "Number of training epochs. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "numberOfWorkers": {
+ "format": "int32",
+ "description": "Number of data loader workers. Must be a non-negative integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "optimizer": {
+ "description": "Type of optimizer.",
+ "default": "None",
+ "$ref": "#/definitions/StochasticOptimizer"
+ },
+ "randomSeed": {
+ "format": "int32",
+ "description": "Random seed to be used when using deterministic training.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "stepLRGamma": {
+ "format": "float",
+ "description": "Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "stepLRStepSize": {
+ "format": "int32",
+ "description": "Value of step size when learning rate scheduler is 'step'. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "trainingBatchSize": {
+ "format": "int32",
+ "description": "Training batch size. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "validationBatchSize": {
+ "format": "int32",
+ "description": "Validation batch size. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "warmupCosineLRCycles": {
+ "format": "float",
+ "description": "Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "warmupCosineLRWarmupEpochs": {
+ "format": "int32",
+ "description": "Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "weightDecay": {
+ "format": "float",
+ "description": "Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1].",
+ "type": "number",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageModelSettingsClassification": {
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageModelSettings"
+ }
+ ],
+ "properties": {
+ "trainingCropSize": {
+ "format": "int32",
+ "description": "Image crop size that is input to the neural network for the training dataset. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "validationCropSize": {
+ "format": "int32",
+ "description": "Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "validationResizeSize": {
+ "format": "int32",
+ "description": "Image size to which to resize before cropping for validation dataset. Must be a positive integer.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "weightedLoss": {
+ "format": "int32",
+ "description": "Weighted loss. The accepted values are 0 for no weighted loss.\r\n1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be 0 or 1 or 2.",
+ "type": "integer",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageModelSettingsObjectDetection": {
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageModelSettings"
+ }
+ ],
+ "properties": {
+ "boxDetectionsPerImage": {
+ "format": "int32",
+ "description": "Maximum number of detections per image, for all classes. Must be a positive integer.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "boxScoreThreshold": {
+ "format": "float",
+ "description": "During inference, only return proposals with a classification score greater than\r\nBoxScoreThreshold. Must be a float in the range[0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "imageSize": {
+ "format": "int32",
+ "description": "Image size for train and validation. Must be a positive integer.\r\nNote: The training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "logTrainingMetrics": {
+ "description": "Enable computing and logging training metrics.",
+ "default": "Enable",
+ "$ref": "#/definitions/LogTrainingMetrics"
+ },
+ "logValidationLoss": {
+ "description": "Enable computing and logging validation loss.",
+ "default": "Disable",
+ "$ref": "#/definitions/LogValidationLoss"
+ },
+ "maxSize": {
+ "format": "int32",
+ "description": "Maximum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "minSize": {
+ "format": "int32",
+ "description": "Minimum size of the image to be rescaled before feeding it to the backbone.\r\nMust be a positive integer. Note: training run may get into CUDA OOM if the size is too big.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "modelSize": {
+ "description": "Model size. Must be 'small', 'medium', 'large', or 'xlarge'.\r\nNote: training run may get into CUDA OOM if the model size is too big.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
+ "default": "None",
+ "$ref": "#/definitions/ModelSize"
+ },
+ "multiScale": {
+ "description": "Enable multi-scale image by varying image size by +/- 50%.\r\nNote: training run may get into CUDA OOM if no sufficient GPU memory.\r\nNote: This settings is only supported for the 'yolov5' algorithm.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "nmsIouThreshold": {
+ "format": "float",
+ "description": "IOU threshold used during inference in NMS post processing. Must be a float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "tileGridSize": {
+ "description": "The grid size to use for tiling each image. Note: TileGridSize must not be\r\nNone to enable small object detection logic. A string containing two integers in mxn format.\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "string",
+ "example": "3x2",
+ "x-nullable": true
+ },
+ "tileOverlapRatio": {
+ "format": "float",
+ "description": "Overlap ratio between adjacent tiles in each dimension. Must be float in the range [0, 1).\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "tilePredictionsNmsThreshold": {
+ "format": "float",
+ "description": "The IOU threshold to use to perform NMS while merging predictions from tiles and image.\r\nUsed in validation/ inference. Must be float in the range [0, 1].\r\nNote: This settings is not supported for the 'yolov5' algorithm.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "validationIouThreshold": {
+ "format": "float",
+ "description": "IOU threshold to use when computing validation metric. Must be float in the range [0, 1].",
+ "type": "number",
+ "x-nullable": true
+ },
+ "validationMetricType": {
+ "description": "Metric computation method to use for validation metrics.",
+ "default": "None",
+ "$ref": "#/definitions/ValidationMetricType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageObjectDetection": {
+ "description": "Image Object Detection. Object detection is used to identify objects in an image and locate each object with a\r\nbounding box e.g. locate all dogs and cats in an image and draw a bounding box around each.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageObjectDetectionBase"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric to optimize for this task.",
+ "default": "MeanAveragePrecision",
+ "$ref": "#/definitions/ObjectDetectionPrimaryMetrics"
+ }
+ },
+ "x-ms-discriminator-value": "ImageObjectDetection",
+ "additionalProperties": false
+ },
+ "ImageObjectDetectionBase": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ImageVertical"
+ }
+ ],
+ "properties": {
+ "modelSettings": {
+ "description": "Settings used for training the model.",
+ "$ref": "#/definitions/ImageModelSettingsObjectDetection",
+ "x-nullable": true
+ },
+ "searchSpace": {
+ "description": "Search space for sampling different combinations of models and their hyperparameters.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ImageModelDistributionSettingsObjectDetection"
+ },
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageSweepSettings": {
+ "description": "Model sweeping and hyperparameter sweeping related settings.",
+ "required": [
+ "samplingAlgorithm"
+ ],
+ "type": "object",
+ "properties": {
+ "earlyTermination": {
+ "description": "Type of early termination policy.",
+ "$ref": "#/definitions/EarlyTerminationPolicy",
+ "x-nullable": true
+ },
+ "samplingAlgorithm": {
+ "description": "[Required] Type of the hyperparameter sampling algorithms.",
+ "$ref": "#/definitions/SamplingAlgorithmType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImageVertical": {
+ "description": "Abstract class for AutoML tasks that train image (computer vision) models -\r\nsuch as Image Classification / Image Classification Multilabel / Image Object Detection / Image Instance Segmentation.",
+ "required": [
+ "limitSettings"
+ ],
+ "type": "object",
+ "properties": {
+ "limitSettings": {
+ "description": "[Required] Limit settings for the AutoML job.",
+ "$ref": "#/definitions/ImageLimitSettings"
+ },
+ "sweepSettings": {
+ "description": "Model sweeping and hyperparameter sweeping related settings.",
+ "$ref": "#/definitions/ImageSweepSettings",
+ "x-nullable": true
+ },
+ "validationData": {
+ "description": "Validation data inputs.",
+ "$ref": "#/definitions/MLTableJobInput",
+ "x-nullable": true
+ },
+ "validationDataSize": {
+ "format": "double",
+ "description": "The fraction of training dataset that needs to be set aside for validation purpose.\r\nValues between (0.0 , 1.0)\r\nApplied when validation dataset is not provided.",
+ "type": "number",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ImportDataAction": {
+ "required": [
+ "actionType",
+ "dataImportDefinition"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ScheduleActionBase"
+ }
+ ],
+ "properties": {
+ "dataImportDefinition": {
+ "description": "[Required] Defines Schedule action definition details.",
+ "$ref": "#/definitions/DataImport",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
]
- },
- "additionalProperties": false
+ }
},
- "MLFlowModelJobInput": {
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "ImportData",
+ "additionalProperties": false
+ },
+ "IncrementalDataRefresh": {
+ "description": "Whether IncrementalDataRefresh is enabled",
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "IncrementalDataRefresh",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobInput"
+ "value": "Enabled"
},
{
- "$ref": "#/definitions/JobInput"
+ "value": "Disabled"
}
- ],
- "x-ms-discriminator-value": "mlflow_model",
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "IndexColumn": {
+ "description": "Dto object representing index column",
+ "type": "object",
+ "properties": {
+ "columnName": {
+ "description": "Specifies the column name",
+ "type": "string",
+ "x-nullable": true
+ },
+ "dataType": {
+ "description": "Specifies the data type",
+ "default": "String",
+ "$ref": "#/definitions/FeatureDataType"
+ }
},
- "MLFlowModelJobOutput": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "InferenceContainerProperties": {
+ "type": "object",
+ "properties": {
+ "livenessRoute": {
+ "description": "The route to check the liveness of the inference server container.",
+ "$ref": "#/definitions/Route"
+ },
+ "readinessRoute": {
+ "description": "The route to check the readiness of the inference server container.",
+ "$ref": "#/definitions/Route"
+ },
+ "scoringRoute": {
+ "description": "The port to send the scoring requests to, within the inference server container.",
+ "$ref": "#/definitions/Route"
+ }
+ },
+ "additionalProperties": false
+ },
+ "InferencingServer": {
+ "required": [
+ "serverType"
+ ],
+ "type": "object",
+ "properties": {
+ "serverType": {
+ "description": "[Required] Inferencing server type for various targets.",
+ "$ref": "#/definitions/InferencingServerType"
+ }
+ },
+ "discriminator": "serverType"
+ },
+ "InferencingServerType": {
+ "description": "Inferencing server type for various targets.",
+ "enum": [
+ "AzureMLOnline",
+ "AzureMLBatch",
+ "Triton",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "InferencingServerType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobOutput"
+ "value": "AzureMLOnline"
},
{
- "$ref": "#/definitions/JobOutput"
- }
- ],
- "x-ms-discriminator-value": "mlflow_model",
- "additionalProperties": false
- },
- "MLTableData": {
- "description": "MLTable data definition",
- "type": "object",
- "allOf": [
+ "value": "AzureMLBatch"
+ },
{
- "$ref": "#/definitions/DataVersionBase"
- }
- ],
- "properties": {
- "referencedUris": {
- "description": "Uris referenced in the MLTable definition (required for lineage)",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "value": "Triton"
+ },
+ {
+ "value": "Custom"
}
- },
- "x-ms-discriminator-value": "mltable",
- "additionalProperties": false
+ ]
},
- "MLTableJobInput": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "InputDeliveryMode": {
+ "description": "Enum to determine the input data delivery mode.",
+ "enum": [
+ "ReadOnlyMount",
+ "ReadWriteMount",
+ "Download",
+ "Direct",
+ "EvalMount",
+ "EvalDownload"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "InputDeliveryMode",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobInput"
+ "value": "ReadOnlyMount"
},
{
- "$ref": "#/definitions/JobInput"
- }
- ],
- "x-ms-discriminator-value": "mltable",
- "additionalProperties": false
- },
- "MLTableJobOutput": {
- "type": "object",
- "allOf": [
+ "value": "ReadWriteMount"
+ },
{
- "$ref": "#/definitions/AssetJobOutput"
+ "value": "Download"
},
{
- "$ref": "#/definitions/JobOutput"
- }
- ],
- "x-ms-discriminator-value": "mltable",
- "additionalProperties": false
- },
- "ModelConfiguration": {
- "description": "Model configuration options.",
- "type": "object",
- "properties": {
- "mode": {
- "description": "Input delivery mode for the model.",
- "default": "Download",
- "$ref": "#/definitions/PackageInputDeliveryMode"
+ "value": "Direct"
},
- "mountPath": {
- "description": "Relative mounting path of the model in the target image.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "EvalMount"
+ },
+ {
+ "value": "EvalDownload"
}
- },
- "additionalProperties": false
+ ]
},
- "ModelContainer": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "InputPathType": {
+ "description": "Input path type for package inputs.",
+ "enum": [
+ "Url",
+ "PathId",
+ "PathVersion"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "InputPathType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetContainer"
- }
- ],
- "properties": {
- "provisioningState": {
- "description": "Provisioning state for the model container.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ "value": "Url"
+ },
+ {
+ "value": "PathId"
+ },
+ {
+ "value": "PathVersion"
}
- },
- "x-ms-client-name": "ModelContainerProperties",
- "additionalProperties": false
+ ]
},
- "ModelContainerResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "InstanceSegmentationPrimaryMetrics": {
+ "description": "Primary metrics for InstanceSegmentation tasks.",
+ "enum": [
+ "MeanAveragePrecision"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "InstanceSegmentationPrimaryMetrics",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
- ],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/ModelContainer"
+ "value": "MeanAveragePrecision",
+ "description": "Mean Average Precision (MAP) is the average of AP (Average Precision).\nAP is calculated for each class and averaged to get the MAP."
}
- },
- "x-ms-client-name": "ModelContainer",
- "additionalProperties": false
+ ]
},
- "ModelContainerResourceArmPaginatedResult": {
- "description": "A paginated list of ModelContainer entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of ModelContainer objects. If null, there are no additional pages.",
- "type": "string"
- },
- "value": {
- "description": "An array of objects of type ModelContainer.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ModelContainerResource"
- }
- }
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "IntellectualProperty": {
+ "description": "Intellectual Property details for a resource.",
+ "required": [
+ "publisher"
+ ],
+ "type": "object",
+ "properties": {
+ "protectionLevel": {
+ "description": "Protection level of the Intellectual Property.",
+ "default": "All",
+ "$ref": "#/definitions/ProtectionLevel"
+ },
+ "publisher": {
+ "description": "[Required] Publisher of the Intellectual Property. Must be the same as Registry publisher name.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
},
- "ModelPackageInput": {
- "description": "Model package input options.",
- "required": [
- "inputType",
- "path"
- ],
- "type": "object",
- "properties": {
- "inputType": {
- "description": "[Required] Type of the input included in the target image.",
- "$ref": "#/definitions/PackageInputType"
- },
- "mode": {
- "description": "Input delivery mode of the input.",
- "default": "ReadOnlyMount",
- "$ref": "#/definitions/PackageInputDeliveryMode"
+ "additionalProperties": false
+ },
+ "JobBase": {
+ "description": "Base definition for a job.",
+ "required": [
+ "jobType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceBase"
+ }
+ ],
+ "properties": {
+ "componentId": {
+ "description": "ARM resource ID of the component resource.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "computeId": {
+ "description": "ARM resource ID of the compute resource.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "displayName": {
+ "description": "Display name of job.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "experimentName": {
+ "description": "The name of the experiment the job belongs to. If not set, the job is placed in the \"Default\" experiment.",
+ "default": "Default",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "identity": {
+ "description": "Identity configuration. If set, this should be one of AmlToken, ManagedIdentity, UserIdentity or null.\r\nDefaults to AmlToken if null.",
+ "$ref": "#/definitions/IdentityConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "isArchived": {
+ "description": "Is the asset archived?",
+ "default": false,
+ "type": "boolean",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ },
+ "jobType": {
+ "description": "[Required] Specifies the type of job.",
+ "$ref": "#/definitions/JobType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "notificationSetting": {
+ "description": "Notification setting for the job",
+ "$ref": "#/definitions/NotificationSetting",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ },
+ "secretsConfiguration": {
+ "description": "Configuration for secrets to be made available during runtime.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/SecretConfiguration",
+ "x-nullable": true
},
- "mountPath": {
- "description": "Relative mount path of the input in the target image.",
- "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "services": {
+ "description": "List of JobEndpoints.\r\nFor local jobs, a job endpoint will have an endpoint value of FileStreamObject.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/JobService",
"x-nullable": true
},
- "path": {
- "description": "[Required] Location of the input.",
- "$ref": "#/definitions/PackageInputPathBase"
- }
- },
- "additionalProperties": false
- },
- "ModelSize": {
- "description": "Image model size.",
- "enum": [
- "None",
- "Small",
- "Medium",
- "Large",
- "ExtraLarge"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ModelSize",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No value selected."
- },
- {
- "value": "Small",
- "description": "Small size."
- },
- {
- "value": "Medium",
- "description": "Medium size."
- },
- {
- "value": "Large",
- "description": "Large size."
- },
- {
- "value": "ExtraLarge",
- "description": "Extra large size."
- }
- ]
+ "x-nullable": true
},
- "additionalProperties": false
+ "status": {
+ "description": "Status of the job.",
+ "$ref": "#/definitions/JobStatus",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ }
},
- "ModelVersion": {
- "description": "Model asset version details.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetBase"
- }
- ],
+ "discriminator": "jobType",
+ "x-ms-client-name": "JobBaseProperties"
+ },
+ "JobBaseResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "flavors": {
- "description": "Mapping of model flavors to their properties.",
- "type": "object",
- "additionalProperties": {
- "$ref": "#/definitions/FlavorData",
- "x-nullable": true
- },
- "x-nullable": true
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/JobBase"
+ }
+ },
+ "x-ms-client-name": "JobBase",
+ "additionalProperties": false
+ },
+ "JobBaseResourceArmPaginatedResult": {
+ "description": "A paginated list of JobBase entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of JobBase objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type JobBase.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/JobBaseResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "JobInput": {
+ "description": "Command job definition.",
+ "required": [
+ "jobInputType"
+ ],
+ "type": "object",
+ "properties": {
+ "description": {
+ "description": "Description for the input.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jobInputType": {
+ "description": "[Required] Specifies the type of job.",
+ "$ref": "#/definitions/JobInputType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "jobInputType"
+ },
+ "JobInputType": {
+ "description": "Enum to determine the Job Input Type.",
+ "enum": [
+ "literal",
+ "uri_file",
+ "uri_folder",
+ "mltable",
+ "custom_model",
+ "mlflow_model",
+ "triton_model"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobInputType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "literal"
+ },
+ {
+ "value": "uri_file"
},
- "jobName": {
- "description": "Name of the training job which produced this model",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "uri_folder"
},
- "modelType": {
- "description": "The storage format for this entity. Used for NCD.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "mltable"
},
- "modelUri": {
- "description": "The URI path to the model contents.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "custom_model"
+ },
+ {
+ "value": "mlflow_model"
},
- "provisioningState": {
- "description": "Provisioning state for the model version.",
- "$ref": "#/definitions/AssetProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ {
+ "value": "triton_model"
}
- },
- "x-ms-client-name": "ModelVersionProperties",
- "additionalProperties": false
+ ]
},
- "ModelVersionResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "JobLimits": {
+ "required": [
+ "jobLimitsType"
+ ],
+ "type": "object",
+ "properties": {
+ "jobLimitsType": {
+ "description": "[Required] JobLimit type.",
+ "$ref": "#/definitions/JobLimitsType"
+ },
+ "timeout": {
+ "format": "duration",
+ "description": "The max run duration in ISO 8601 format, after which the job will be cancelled. Only supports duration with precision as low as Seconds.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "discriminator": "jobLimitsType"
+ },
+ "JobLimitsType": {
+ "enum": [
+ "Command",
+ "Sweep"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobLimitsType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
- ],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/ModelVersion"
+ "value": "Command"
+ },
+ {
+ "value": "Sweep"
}
- },
- "x-ms-client-name": "ModelVersion",
- "additionalProperties": false
+ ]
},
- "ModelVersionResourceArmPaginatedResult": {
- "description": "A paginated list of ModelVersion entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of ModelVersion objects. If null, there are no additional pages.",
- "type": "string"
+ "additionalProperties": false
+ },
+ "JobOutput": {
+ "description": "Job output definition container information on where to find job output/logs.",
+ "required": [
+ "jobOutputType"
+ ],
+ "type": "object",
+ "properties": {
+ "description": {
+ "description": "Description for the output.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jobOutputType": {
+ "description": "[Required] Specifies the type of job.",
+ "$ref": "#/definitions/JobOutputType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "jobOutputType"
+ },
+ "JobOutputType": {
+ "description": "Enum to determine the Job Output Type.",
+ "enum": [
+ "uri_file",
+ "uri_folder",
+ "mltable",
+ "custom_model",
+ "mlflow_model",
+ "triton_model"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobOutputType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "uri_file"
},
- "value": {
- "description": "An array of objects of type ModelVersion.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ModelVersionResource"
- }
+ {
+ "value": "uri_folder"
+ },
+ {
+ "value": "mltable"
+ },
+ {
+ "value": "custom_model"
+ },
+ {
+ "value": "mlflow_model"
+ },
+ {
+ "value": "triton_model"
}
- },
- "additionalProperties": false
+ ]
},
- "Mpi": {
- "description": "MPI distribution configuration.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "JobProvisioningState": {
+ "description": "Enum to determine the job provisioning state.",
+ "enum": [
+ "Succeeded",
+ "Failed",
+ "Canceled",
+ "InProgress"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobProvisioningState",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/DistributionConfiguration"
- }
- ],
- "properties": {
- "processCountPerInstance": {
- "format": "int32",
- "description": "Number of processes per MPI node.",
- "type": "integer",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "value": "Succeeded"
+ },
+ {
+ "value": "Failed"
+ },
+ {
+ "value": "Canceled"
+ },
+ {
+ "value": "InProgress"
}
- },
- "x-ms-discriminator-value": "Mpi",
- "additionalProperties": false
+ ]
},
- "MultiSelect": {
- "description": "Whether multiSelect is enabled",
- "enum": [
- "Enabled",
- "Disabled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "MultiSelect",
- "modelAsString": true,
- "values": [
- {
- "value": "Enabled"
- },
- {
- "value": "Disabled"
- }
+ "additionalProperties": false
+ },
+ "JobResourceConfiguration": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceConfiguration"
+ }
+ ],
+ "properties": {
+ "dockerArgs": {
+ "description": "Extra arguments to pass to the Docker run command. This would override any parameters that have already been set by the system, or in this section. This parameter is only supported for Azure ML compute types.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "shmSize": {
+ "description": "Size of the docker container's shared memory block. This should be in the format of (number)(unit) where number as to be greater than 0 and the unit can be one of b(bytes), k(kilobytes), m(megabytes), or g(gigabytes).",
+ "default": "2g",
+ "pattern": "\\d+[bBkKmMgG]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "NCrossValidations": {
- "description": "N-Cross validations value.",
- "required": [
- "mode"
- ],
- "type": "object",
- "properties": {
- "mode": {
- "description": "[Required] Mode for determining N-Cross validations.",
- "$ref": "#/definitions/NCrossValidationsMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "mode"
- },
- "NCrossValidationsMode": {
- "description": "Determines how N-Cross validations value is determined.",
- "enum": [
- "Auto",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "NCrossValidationsMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Determine N-Cross validations value automatically. Supported only for 'Forecasting' AutoML task."
- },
- {
- "value": "Custom",
- "description": "Use custom N-Cross validations value."
- }
+ "additionalProperties": false
+ },
+ "JobScheduleAction": {
+ "required": [
+ "actionType",
+ "jobDefinition"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ScheduleActionBase"
+ }
+ ],
+ "properties": {
+ "jobDefinition": {
+ "description": "[Required] Defines Schedule action definition details.",
+ "$ref": "#/definitions/JobBase",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
]
- },
- "additionalProperties": false
+ }
},
- "NlpFixedParameters": {
- "description": "Fixed training parameters that won't be swept over during AutoML NLP training.",
- "type": "object",
- "properties": {
- "gradientAccumulationSteps": {
- "format": "int32",
- "description": "Number of steps to accumulate gradients over before running a backward pass.",
- "type": "integer",
+ "x-ms-discriminator-value": "CreateJob",
+ "additionalProperties": false
+ },
+ "JobService": {
+ "description": "Job endpoint definition",
+ "type": "object",
+ "properties": {
+ "endpoint": {
+ "description": "Url for endpoint.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "errorMessage": {
+ "description": "Any error in the service.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jobServiceType": {
+ "description": "Endpoint type.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "nodes": {
+ "description": "Nodes that user would like to start the service on.\r\nIf Nodes is not set or set to null, the service will only be started on leader node.",
+ "$ref": "#/definitions/Nodes",
+ "x-nullable": true
+ },
+ "port": {
+ "format": "int32",
+ "description": "Port for endpoint set by user.",
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "properties": {
+ "description": "Additional properties to set on the endpoint.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
"x-nullable": true
},
- "learningRate": {
- "format": "float",
- "description": "The learning rate for the training procedure.",
- "type": "number",
- "x-nullable": true
+ "x-nullable": true
+ },
+ "status": {
+ "description": "Status of endpoint.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "JobStatus": {
+ "description": "The status of a job.",
+ "enum": [
+ "NotStarted",
+ "Starting",
+ "Provisioning",
+ "Preparing",
+ "Queued",
+ "Running",
+ "Finalizing",
+ "CancelRequested",
+ "Completed",
+ "Failed",
+ "Canceled",
+ "NotResponding",
+ "Paused",
+ "Unknown",
+ "Scheduled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobStatus",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "NotStarted",
+ "description": "Run hasn't started yet."
},
- "learningRateScheduler": {
- "description": "The type of learning rate schedule to use during the training procedure.",
- "default": "None",
- "$ref": "#/definitions/NlpLearningRateScheduler"
+ {
+ "value": "Starting",
+ "description": "Run has started. The user has a run ID."
},
- "modelName": {
- "description": "The name of the model to train.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Provisioning",
+ "description": "(Not used currently) It will be used if ES is creating the compute target."
},
- "numberOfEpochs": {
- "format": "int32",
- "description": "Number of training epochs.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Preparing",
+ "description": "The run environment is being prepared."
},
- "trainingBatchSize": {
- "format": "int32",
- "description": "The batch size for the training procedure.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Queued",
+ "description": "The job is queued in the compute target. For example, in BatchAI the job is in queued state, while waiting for all required nodes to be ready."
},
- "validationBatchSize": {
- "format": "int32",
- "description": "The batch size to be used during evaluation.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Running",
+ "description": "The job started to run in the compute target."
},
- "warmupRatio": {
- "format": "float",
- "description": "The warmup ratio, used alongside LrSchedulerType.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "Finalizing",
+ "description": "Job is completed in the target. It is in output collection state now."
},
- "weightDecay": {
- "format": "float",
- "description": "The weight decay for the training procedure.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "CancelRequested",
+ "description": "Cancellation has been requested for the job."
+ },
+ {
+ "value": "Completed",
+ "description": "Job completed successfully. This reflects that both the job itself and output collection states completed successfully"
+ },
+ {
+ "value": "Failed",
+ "description": "Job failed."
+ },
+ {
+ "value": "Canceled",
+ "description": "Following cancellation request, the job is now successfully canceled."
+ },
+ {
+ "value": "NotResponding",
+ "description": "When heartbeat is enabled, if the run isn't updating any information to RunHistory then the run goes to NotResponding state.\nNotResponding is the only state that is exempt from strict transition orders. A run can go from NotResponding to any of the previous states."
+ },
+ {
+ "value": "Paused",
+ "description": "The job is paused by users. Some adjustment to labeling jobs can be made only in paused state."
+ },
+ {
+ "value": "Unknown",
+ "description": "Default job status if not mapped to all other statuses"
+ },
+ {
+ "value": "Scheduled",
+ "description": "The job is in a scheduled state. Job is not in any active state."
}
- },
- "additionalProperties": false
- },
- "NlpLearningRateScheduler": {
- "description": "Enum of learning rate schedulers that aligns with those supported by HF",
- "enum": [
- "None",
- "Linear",
- "Cosine",
- "CosineWithRestarts",
- "Polynomial",
- "Constant",
- "ConstantWithWarmup"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "NlpLearningRateScheduler",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No learning rate schedule."
- },
- {
- "value": "Linear",
- "description": "Linear warmup and decay."
- },
- {
- "value": "Cosine",
- "description": "Linear warmup then cosine decay."
- },
- {
- "value": "CosineWithRestarts",
- "description": "Linear warmup, cosine decay, then restart to initial LR."
- },
- {
- "value": "Polynomial",
- "description": "Increase linearly then polynomially decay."
- },
- {
- "value": "Constant",
- "description": "Constant learning rate."
- },
- {
- "value": "ConstantWithWarmup",
- "description": "Linear warmup followed by constant value."
- }
- ]
- },
- "additionalProperties": false
+ ]
},
- "NlpParameterSubspace": {
- "description": "Stringified search spaces for each parameter. See below examples.",
- "type": "object",
- "properties": {
- "gradientAccumulationSteps": {
- "description": "Number of steps to accumulate gradients over before running a backward pass.",
- "type": "string",
- "example": "choice(1, 2)",
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "JobTier": {
+ "description": "Enum to determine the job tier.",
+ "enum": [
+ "Spot",
+ "Basic",
+ "Standard",
+ "Premium"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobTier",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Spot"
},
- "learningRate": {
- "description": "The learning rate for the training procedure.",
- "type": "string",
- "example": "uniform(5e-6, 5e-5)",
- "x-nullable": true
+ {
+ "value": "Basic"
},
- "learningRateScheduler": {
- "description": "The type of learning rate schedule to use during the training procedure.",
- "type": "string",
- "example": "choice('linear', 'cosine')",
- "x-nullable": true
+ {
+ "value": "Standard"
},
- "modelName": {
- "description": "The name of the model to train.",
- "type": "string",
- "example": "choice('bert-base-cased', 'roberta-base')",
- "x-nullable": true
+ {
+ "value": "Premium"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "JobType": {
+ "description": "Enum to determine the type of job.",
+ "enum": [
+ "AutoML",
+ "Command",
+ "Labeling",
+ "Sweep",
+ "Pipeline",
+ "Spark"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "JobType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AutoML"
},
- "numberOfEpochs": {
- "description": "Number of training epochs.",
- "type": "string",
- "example": "choice(3, 4)",
- "x-nullable": true
+ {
+ "value": "Command"
},
- "trainingBatchSize": {
- "description": "The batch size for the training procedure.",
- "type": "string",
- "example": "choice(16, 32)",
- "x-nullable": true
+ {
+ "value": "Labeling"
},
- "validationBatchSize": {
- "description": "The batch size to be used during evaluation.",
- "type": "string",
- "example": "choice(16, 32)",
- "x-nullable": true
+ {
+ "value": "Sweep"
},
- "warmupRatio": {
- "description": "The warmup ratio, used alongside LrSchedulerType.",
- "type": "string",
- "example": "uniform(0.01, 0.1)",
- "x-nullable": true
+ {
+ "value": "Pipeline"
},
- "weightDecay": {
- "description": "The weight decay for the training procedure.",
- "type": "string",
- "example": "uniform(0.01, 0.1)",
- "x-nullable": true
+ {
+ "value": "Spark"
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "KerberosCredentials": {
+ "required": [
+ "kerberosKdcAddress",
+ "kerberosPrincipal",
+ "kerberosRealm"
+ ],
+ "type": "object",
+ "properties": {
+ "kerberosKdcAddress": {
+ "description": "[Required] IP Address or DNS HostName.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
},
- "additionalProperties": false
+ "kerberosPrincipal": {
+ "description": "[Required] Kerberos Username",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "kerberosRealm": {
+ "description": "[Required] Domain over which a Kerberos authentication server has the authority to authenticate a user, host or service.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "NlpSweepSettings": {
- "description": "Model sweeping and hyperparameter tuning related settings.",
- "required": [
- "samplingAlgorithm"
- ],
- "type": "object",
- "properties": {
- "earlyTermination": {
- "description": "Type of early termination policy for the sweeping job.",
- "$ref": "#/definitions/EarlyTerminationPolicy",
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "KerberosKeytabCredentials": {
+ "required": [
+ "secrets"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/KerberosCredentials"
+ },
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "properties": {
+ "secrets": {
+ "description": "[Required] Keytab secrets.",
+ "$ref": "#/definitions/KerberosKeytabSecrets",
+ "x-ms-mutability": [
+ "create",
+ "update"
+ ],
+ "x-ms-secret": true
+ }
+ },
+ "x-ms-discriminator-value": "KerberosKeytab",
+ "additionalProperties": false
+ },
+ "KerberosKeytabSecrets": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreSecrets"
+ }
+ ],
+ "properties": {
+ "kerberosKeytab": {
+ "description": "Kerberos keytab secret.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "KerberosKeytab",
+ "additionalProperties": false
+ },
+ "KerberosPasswordCredentials": {
+ "required": [
+ "secrets"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/KerberosCredentials"
+ },
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "properties": {
+ "secrets": {
+ "description": "[Required] Kerberos password secrets.",
+ "$ref": "#/definitions/KerberosPasswordSecrets",
+ "x-ms-mutability": [
+ "create",
+ "update"
+ ],
+ "x-ms-secret": true
+ }
+ },
+ "x-ms-discriminator-value": "KerberosPassword",
+ "additionalProperties": false
+ },
+ "KerberosPasswordSecrets": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreSecrets"
+ }
+ ],
+ "properties": {
+ "kerberosPassword": {
+ "description": "Kerberos password secret.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "KerberosPassword",
+ "additionalProperties": false
+ },
+ "KeyType": {
+ "enum": [
+ "Primary",
+ "Secondary"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "KeyType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Primary"
},
- "samplingAlgorithm": {
- "description": "[Required] Type of sampling algorithm.",
- "$ref": "#/definitions/SamplingAlgorithmType"
+ {
+ "value": "Secondary"
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "KubernetesOnlineDeployment": {
+ "description": "Properties specific to a KubernetesOnlineDeployment.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/OnlineDeployment"
+ }
+ ],
+ "properties": {
+ "containerResourceRequirements": {
+ "description": "The resource requirements for the container (cpu and memory).",
+ "$ref": "#/definitions/ContainerResourceRequirements",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Kubernetes",
+ "additionalProperties": false
+ },
+ "LabelCategory": {
+ "description": "Label category definition",
+ "type": "object",
+ "properties": {
+ "classes": {
+ "description": "Dictionary of label classes in this category.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/LabelClass",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ },
+ "displayName": {
+ "description": "Display name of the label category.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "multiSelect": {
+ "description": "Indicates whether it is allowed to select multiple classes in this category.",
+ "default": "Disabled",
+ "$ref": "#/definitions/MultiSelect",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "LabelClass": {
+ "description": "Label class definition",
+ "type": "object",
+ "properties": {
+ "displayName": {
+ "description": "Display name of the label class.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "subclasses": {
+ "description": "Dictionary of subclasses of the label class.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/LabelClass",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "LabelingDataConfiguration": {
+ "description": "Labeling data configuration definition",
+ "type": "object",
+ "properties": {
+ "dataId": {
+ "description": "Resource Id of the data asset to perform labeling.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "incrementalDataRefresh": {
+ "description": "Indicates whether to enable incremental data refresh.",
+ "default": "Disabled",
+ "$ref": "#/definitions/IncrementalDataRefresh",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "LabelingJob": {
+ "description": "Labeling job definition",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobBase"
+ }
+ ],
+ "properties": {
+ "createdDateTime": {
+ "format": "date-time",
+ "description": "Created time of the job in UTC timezone.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "dataConfiguration": {
+ "description": "Configuration of data used in the job.",
+ "$ref": "#/definitions/LabelingDataConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jobInstructions": {
+ "description": "Labeling instructions of the job.",
+ "$ref": "#/definitions/LabelingJobInstructions",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ },
+ "labelCategories": {
+ "description": "Label categories of the job.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/LabelCategory",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ },
+ "labelingJobMediaProperties": {
+ "description": "Media type specific properties in the job.",
+ "$ref": "#/definitions/LabelingJobMediaProperties",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "mlAssistConfiguration": {
+ "description": "Configuration of MLAssist feature in the job.",
+ "default": "{\"MLAssist\":\"Disabled\"}",
+ "$ref": "#/definitions/MLAssistConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "progressMetrics": {
+ "description": "Progress metrics of the job.",
+ "$ref": "#/definitions/ProgressMetrics",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "projectId": {
+ "format": "uuid",
+ "description": "Internal id of the job(Previously called project).",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ },
+ "provisioningState": {
+ "description": "Specifies the labeling job provisioning state.",
+ "$ref": "#/definitions/JobProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
},
- "additionalProperties": false
+ "statusMessages": {
+ "description": "Status messages of the job.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/StatusMessage"
+ },
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ }
+ },
+ "x-ms-discriminator-value": "Labeling",
+ "x-ms-client-name": "LabelingJobProperties",
+ "additionalProperties": false
+ },
+ "LabelingJobImageProperties": {
+ "description": "Properties of a labeling job for image data",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/LabelingJobMediaProperties"
+ }
+ ],
+ "properties": {
+ "annotationType": {
+ "description": "Annotation type of image labeling job.",
+ "default": "Classification",
+ "$ref": "#/definitions/ImageAnnotationType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Image",
+ "additionalProperties": false
+ },
+ "LabelingJobInstructions": {
+ "description": "Instructions for labeling job",
+ "type": "object",
+ "properties": {
+ "uri": {
+ "description": "The link to a page with detailed labeling instructions for labelers.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "LabelingJobMediaProperties": {
+ "description": "Properties of a labeling job",
+ "required": [
+ "mediaType"
+ ],
+ "type": "object",
+ "properties": {
+ "mediaType": {
+ "description": "[Required] Media type of the job.",
+ "$ref": "#/definitions/MediaType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "NlpVertical": {
- "description": "Abstract class for NLP related AutoML tasks.\r\nNLP - Natural Language Processing.",
- "type": "object",
+ "discriminator": "mediaType"
+ },
+ "LabelingJobResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "featurizationSettings": {
- "description": "Featurization inputs needed for AutoML job.",
- "$ref": "#/definitions/NlpVerticalFeaturizationSettings",
- "x-nullable": true
- },
- "fixedParameters": {
- "description": "Model/training parameters that will remain constant throughout training.",
- "$ref": "#/definitions/NlpFixedParameters",
- "x-nullable": true
- },
- "limitSettings": {
- "description": "Execution constraints for AutoMLJob.",
- "$ref": "#/definitions/NlpVerticalLimitSettings",
- "x-nullable": true
- },
- "searchSpace": {
- "description": "Search space for sampling different combinations of models and their hyperparameters.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/NlpParameterSubspace"
- },
- "x-nullable": true,
- "x-ms-identifiers": []
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/LabelingJob"
+ }
+ },
+ "x-ms-client-name": "LabelingJob",
+ "additionalProperties": false
+ },
+ "LabelingJobResourceArmPaginatedResult": {
+ "description": "A paginated list of LabelingJob entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of LabelingJob objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type LabelingJob.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/LabelingJobResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "LabelingJobTextProperties": {
+ "description": "Properties of a labeling job for text data",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/LabelingJobMediaProperties"
+ }
+ ],
+ "properties": {
+ "annotationType": {
+ "description": "Annotation type of text labeling job.",
+ "default": "Classification",
+ "$ref": "#/definitions/TextAnnotationType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Text",
+ "additionalProperties": false
+ },
+ "LakehouseArtifact": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/OneLakeArtifact"
+ }
+ ],
+ "x-ms-discriminator-value": "Lakehouse",
+ "additionalProperties": false
+ },
+ "LearningRateScheduler": {
+ "description": "Learning rate scheduler enum.",
+ "enum": [
+ "None",
+ "WarmupCosine",
+ "Step"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "LearningRateScheduler",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None",
+ "description": "No learning rate scheduler selected."
},
- "sweepSettings": {
- "description": "Settings for model sweeping and hyperparameter tuning.",
- "$ref": "#/definitions/NlpSweepSettings",
- "x-nullable": true
+ {
+ "value": "WarmupCosine",
+ "description": "Cosine Annealing With Warmup."
},
- "validationData": {
- "description": "Validation data inputs.",
- "$ref": "#/definitions/MLTableJobInput",
- "x-nullable": true
- }
- },
- "additionalProperties": false
- },
- "NlpVerticalFeaturizationSettings": {
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/FeaturizationSettings"
+ "value": "Step",
+ "description": "Step learning rate scheduler."
}
- ],
- "additionalProperties": false
+ ]
},
- "NlpVerticalLimitSettings": {
- "description": "Job execution constraints.",
- "type": "object",
- "properties": {
- "maxConcurrentTrials": {
- "format": "int32",
- "description": "Maximum Concurrent AutoML iterations.",
- "default": 1,
- "type": "integer"
- },
- "maxNodes": {
- "format": "int32",
- "description": "Maximum nodes to use for the experiment.",
- "default": 1,
- "type": "integer"
- },
- "maxTrials": {
- "format": "int32",
- "description": "Number of AutoML iterations.",
- "default": 1,
- "type": "integer"
+ "additionalProperties": false
+ },
+ "ListViewType": {
+ "enum": [
+ "ActiveOnly",
+ "ArchivedOnly",
+ "All"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ActiveOnly"
},
- "timeout": {
- "format": "duration",
- "description": "AutoML job timeout.",
- "default": "P7D",
- "type": "string"
+ {
+ "value": "ArchivedOnly"
},
- "trialTimeout": {
- "format": "duration",
- "description": "Timeout for individual HD trials.",
- "type": "string"
+ {
+ "value": "All"
}
- },
- "additionalProperties": false
+ ]
},
- "Nodes": {
- "description": "Abstract Nodes definition",
- "required": [
- "nodesValueType"
- ],
- "type": "object",
- "properties": {
- "nodesValueType": {
- "description": "[Required] Type of the Nodes value",
- "$ref": "#/definitions/NodesValueType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "nodesValueType"
- },
- "NodesValueType": {
- "description": "The enumerated types for the nodes value",
- "enum": [
- "All",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "NodesValueType",
- "modelAsString": true,
- "values": [
- {
- "value": "All"
- },
- {
- "value": "Custom"
- }
- ]
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "LiteralJobInput": {
+ "description": "Literal input type.",
+ "required": [
+ "value"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "properties": {
+ "value": {
+ "description": "[Required] Literal value for the input.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
},
- "NoneDatastoreCredentials": {
- "description": "Empty/none datastore credentials.",
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "literal",
+ "additionalProperties": false
+ },
+ "LogTrainingMetrics": {
+ "enum": [
+ "Enable",
+ "Disable"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "LogTrainingMetrics",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/DatastoreCredentials"
- }
- ],
- "x-ms-discriminator-value": "None",
- "additionalProperties": false
- },
- "NotificationSetting": {
- "description": "Configuration for notification.",
- "type": "object",
- "properties": {
- "emailOn": {
- "description": "Send email notification to user on specified notification type",
- "type": "array",
- "items": {
- "$ref": "#/definitions/EmailNotificationEnableType"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "value": "Enable",
+ "description": "Enable compute and log training metrics."
},
- "emails": {
- "description": "This is the email recipient list which has a limitation of 499 characters in total concat with comma separator",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Disable",
+ "description": "Disable compute and log training metrics."
}
- },
- "additionalProperties": false
- },
- "ObjectDetectionPrimaryMetrics": {
- "description": "Primary metrics for Image ObjectDetection task.",
- "enum": [
- "MeanAveragePrecision"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ObjectDetectionPrimaryMetrics",
- "modelAsString": true,
- "values": [
- {
- "value": "MeanAveragePrecision",
- "description": "Mean Average Precision (MAP) is the average of AP (Average Precision).\nAP is calculated for each class and averaged to get the MAP."
- }
- ]
- },
- "additionalProperties": false
+ ]
},
- "Objective": {
- "description": "Optimization objective.",
- "required": [
- "goal",
- "primaryMetric"
- ],
- "type": "object",
- "properties": {
- "goal": {
- "description": "[Required] Defines supported metric goals for hyperparameter tuning",
- "$ref": "#/definitions/Goal"
+ "additionalProperties": false
+ },
+ "LogValidationLoss": {
+ "enum": [
+ "Enable",
+ "Disable"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "LogValidationLoss",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Enable",
+ "description": "Enable compute and log validation metrics."
},
- "primaryMetric": {
- "description": "[Required] Name of the metric to optimize.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string"
+ {
+ "value": "Disable",
+ "description": "Disable compute and log validation metrics."
}
- },
- "additionalProperties": false
+ ]
},
- "OnlineDeployment": {
- "required": [
- "endpointComputeType"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "LogVerbosity": {
+ "description": "Enum for setting log verbosity.",
+ "enum": [
+ "NotSet",
+ "Debug",
+ "Info",
+ "Warning",
+ "Error",
+ "Critical"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "LogVerbosity",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/EndpointDeploymentPropertiesBase"
- }
- ],
- "properties": {
- "appInsightsEnabled": {
- "description": "If true, enables Application Insights logging.",
- "default": false,
- "type": "boolean"
- },
- "egressPublicNetworkAccess": {
- "description": "If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.",
- "default": "Enabled",
- "$ref": "#/definitions/EgressPublicNetworkAccessType"
- },
- "endpointComputeType": {
- "description": "[Required] The compute type of the endpoint.",
- "$ref": "#/definitions/EndpointComputeType"
- },
- "instanceType": {
- "description": "Compute instance type.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "livenessProbe": {
- "description": "Liveness probe monitors the health of the container regularly.",
- "$ref": "#/definitions/ProbeSettings",
- "x-nullable": true
+ "value": "NotSet",
+ "description": "No logs emitted."
},
- "model": {
- "description": "The URI path to the model.",
- "type": "string",
- "x-nullable": true
- },
- "modelMountPath": {
- "description": "The path to mount the model in custom container.",
- "type": "string",
- "x-nullable": true
- },
- "provisioningState": {
- "description": "Provisioning state for the endpoint deployment.",
- "$ref": "#/definitions/DeploymentProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "readinessProbe": {
- "description": "Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.",
- "$ref": "#/definitions/ProbeSettings",
- "x-nullable": true
- },
- "requestSettings": {
- "description": "Request settings for the deployment.",
- "$ref": "#/definitions/OnlineRequestSettings",
- "x-nullable": true
+ {
+ "value": "Debug",
+ "description": "Debug and above log statements logged."
},
- "scaleSettings": {
- "description": "Scale settings for the deployment.\r\nIf it is null or not provided,\r\nit defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment\r\nand to DefaultScaleSettings for ManagedOnlineDeployment.",
- "$ref": "#/definitions/OnlineScaleSettings",
- "x-nullable": true
- }
- },
- "discriminator": "endpointComputeType",
- "x-ms-client-name": "OnlineDeploymentProperties"
- },
- "OnlineDeploymentTrackedResource": {
- "required": [
- "location",
- "properties"
- ],
- "type": "object",
- "allOf": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
- }
- ],
- "properties": {
- "identity": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ "value": "Info",
+ "description": "Info and above log statements logged."
},
- "kind": {
- "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
- "type": "string"
+ {
+ "value": "Warning",
+ "description": "Warning and above log statements logged."
},
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/OnlineDeployment"
+ {
+ "value": "Error",
+ "description": "Error and above log statements logged."
},
- "sku": {
- "description": "Sku details required for ARM contract for Autoscaling.",
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
+ {
+ "value": "Critical",
+ "description": "Only critical statements logged."
}
- },
- "x-ms-client-name": "OnlineDeployment",
- "additionalProperties": false
+ ]
},
- "OnlineDeploymentTrackedResourceArmPaginatedResult": {
- "description": "A paginated list of OnlineDeployment entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of OnlineDeployment objects. If null, there are no additional pages.",
- "type": "string"
- },
- "value": {
- "description": "An array of objects of type OnlineDeployment.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/OnlineDeploymentTrackedResource"
- }
- }
+ "additionalProperties": false
+ },
+ "MLAssistConfiguration": {
+ "description": "Labeling MLAssist configuration definition",
+ "required": [
+ "mlAssist"
+ ],
+ "type": "object",
+ "properties": {
+ "mlAssist": {
+ "description": "[Required] Indicates whether MLAssist feature is enabled.",
+ "$ref": "#/definitions/MLAssistConfigurationType",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "discriminator": "mlAssist"
+ },
+ "MLAssistConfigurationDisabled": {
+ "description": "Labeling MLAssist configuration definition when MLAssist is disabled",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MLAssistConfiguration"
+ }
+ ],
+ "x-ms-discriminator-value": "Disabled",
+ "additionalProperties": false
+ },
+ "MLAssistConfigurationEnabled": {
+ "description": "Labeling MLAssist configuration definition when MLAssist is enabled",
+ "required": [
+ "inferencingComputeBinding",
+ "trainingComputeBinding"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MLAssistConfiguration"
+ }
+ ],
+ "properties": {
+ "inferencingComputeBinding": {
+ "description": "[Required] AML compute binding used in inferencing.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
},
- "additionalProperties": false
+ "trainingComputeBinding": {
+ "description": "[Required] AML compute binding used in training.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
},
- "OnlineEndpoint": {
- "description": "Online endpoint configuration",
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "Enabled",
+ "additionalProperties": false
+ },
+ "MLAssistConfigurationType": {
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MLAssistConfigurationType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/EndpointPropertiesBase"
- }
- ],
- "properties": {
- "compute": {
- "description": "ARM resource ID of the compute if it exists.\r\noptional",
- "type": "string",
- "x-nullable": true
+ "value": "Enabled"
},
- "mirrorTraffic": {
- "description": "Percentage of traffic to be mirrored to each deployment without using returned scoring. Traffic values need to sum to utmost 50.",
- "type": "object",
- "additionalProperties": {
- "format": "int32",
- "type": "integer"
- },
- "x-nullable": true
- },
- "provisioningState": {
- "description": "Provisioning state for the endpoint.",
- "$ref": "#/definitions/EndpointProvisioningState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "publicNetworkAccess": {
- "description": "Set to \"Enabled\" for endpoints that should allow public access when Private Link is enabled.",
- "default": "Enabled",
- "$ref": "#/definitions/PublicNetworkAccessType"
- },
- "traffic": {
- "description": "Percentage of traffic from endpoint to divert to each deployment. Traffic values need to sum to 100.",
- "type": "object",
- "additionalProperties": {
- "format": "int32",
- "type": "integer"
- },
- "x-nullable": true
+ {
+ "value": "Disabled"
}
- },
- "x-ms-client-name": "OnlineEndpointProperties",
- "additionalProperties": false
+ ]
},
- "OnlineEndpointTrackedResource": {
- "required": [
- "location",
- "properties"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "MLFlowAutologgerState": {
+ "description": "Enum to determine the state of mlflow autologger.",
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MLFlowAutologgerState",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
- }
- ],
- "properties": {
- "identity": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ "value": "Enabled"
},
- "kind": {
- "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
- "type": "string"
- },
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/OnlineEndpoint"
- },
- "sku": {
- "description": "Sku details required for ARM contract for Autoscaling.",
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
+ {
+ "value": "Disabled"
}
- },
- "x-ms-client-name": "OnlineEndpoint",
- "additionalProperties": false
+ ]
},
- "OnlineEndpointTrackedResourceArmPaginatedResult": {
- "description": "A paginated list of OnlineEndpoint entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of OnlineEndpoint objects. If null, there are no additional pages.",
+ "additionalProperties": false
+ },
+ "MLFlowModelJobInput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobInput"
+ },
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "x-ms-discriminator-value": "mlflow_model",
+ "additionalProperties": false
+ },
+ "MLFlowModelJobOutput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobOutput"
+ },
+ {
+ "$ref": "#/definitions/JobOutput"
+ }
+ ],
+ "x-ms-discriminator-value": "mlflow_model",
+ "additionalProperties": false
+ },
+ "MLTableData": {
+ "description": "MLTable data definition",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataVersionBase"
+ }
+ ],
+ "properties": {
+ "referencedUris": {
+ "description": "Uris referenced in the MLTable definition (required for lineage)",
+ "type": "array",
+ "items": {
"type": "string"
},
- "value": {
- "description": "An array of objects of type OnlineEndpoint.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/OnlineEndpointTrackedResource"
- }
- }
- },
- "additionalProperties": false
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "OnlineInferenceConfiguration": {
- "description": "Online inference configuration options.",
- "type": "object",
- "properties": {
- "configurations": {
- "description": "Additional configurations",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
- },
- "entryScript": {
- "description": "Entry script or command to invoke.",
+ "x-ms-discriminator-value": "mltable",
+ "additionalProperties": false
+ },
+ "MLTableJobInput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobInput"
+ },
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "x-ms-discriminator-value": "mltable",
+ "additionalProperties": false
+ },
+ "MLTableJobOutput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobOutput"
+ },
+ {
+ "$ref": "#/definitions/JobOutput"
+ }
+ ],
+ "x-ms-discriminator-value": "mltable",
+ "additionalProperties": false
+ },
+ "ManagedIdentity": {
+ "description": "Managed identity configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/IdentityConfiguration"
+ }
+ ],
+ "properties": {
+ "clientId": {
+ "format": "uuid",
+ "description": "Specifies a user-assigned identity by client ID. For system-assigned, do not set this field.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "objectId": {
+ "format": "uuid",
+ "description": "Specifies a user-assigned identity by object ID. For system-assigned, do not set this field.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "resourceId": {
+ "description": "Specifies a user-assigned identity by ARM resource ID. For system-assigned, do not set this field.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Managed",
+ "additionalProperties": false
+ },
+ "ManagedOnlineDeployment": {
+ "description": "Properties specific to a ManagedOnlineDeployment.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/OnlineDeployment"
+ }
+ ],
+ "x-ms-discriminator-value": "Managed",
+ "additionalProperties": false
+ },
+ "MaterializationComputeResource": {
+ "description": "Dto object representing compute resource",
+ "type": "object",
+ "properties": {
+ "instanceType": {
+ "description": "Specifies the instance type",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "MaterializationSettings": {
+ "type": "object",
+ "properties": {
+ "notification": {
+ "description": "Specifies the notification details",
+ "$ref": "#/definitions/NotificationSetting",
+ "x-nullable": true
+ },
+ "resource": {
+ "description": "Specifies the compute resource settings",
+ "$ref": "#/definitions/MaterializationComputeResource",
+ "x-nullable": true
+ },
+ "schedule": {
+ "description": "Specifies the schedule details",
+ "$ref": "#/definitions/RecurrenceTrigger",
+ "x-nullable": true
+ },
+ "sparkConfiguration": {
+ "description": "Specifies the spark compute settings",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "livenessRoute": {
- "description": "The route to check the liveness of the inference server container.",
- "$ref": "#/definitions/Route",
- "x-nullable": true
+ "x-nullable": true
+ },
+ "storeType": {
+ "description": "Specifies the stores to which materialization should happen",
+ "default": "None",
+ "$ref": "#/definitions/MaterializationStoreType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "MaterializationStoreType": {
+ "enum": [
+ "None",
+ "Online",
+ "Offline",
+ "OnlineAndOffline"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MaterializationStoreType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None"
},
- "readinessRoute": {
- "description": "The route to check the readiness of the inference server container.",
- "$ref": "#/definitions/Route",
- "x-nullable": true
+ {
+ "value": "Online"
},
- "scoringRoute": {
- "description": "The port to send the scoring requests to, within the inference server container.",
- "$ref": "#/definitions/Route",
- "x-nullable": true
+ {
+ "value": "Offline"
+ },
+ {
+ "value": "OnlineAndOffline"
}
- },
- "additionalProperties": false
+ ]
},
- "OnlineRequestSettings": {
- "description": "Online deployment scoring requests configuration.",
- "type": "object",
- "properties": {
- "maxConcurrentRequestsPerInstance": {
- "format": "int32",
- "description": "The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.",
- "default": 1,
- "type": "integer"
- },
- "maxQueueWait": {
- "format": "duration",
- "description": "The maximum amount of time a request will stay in the queue in ISO 8601 format.\r\nDefaults to 500ms.",
- "default": "PT0.5S",
- "type": "string"
+ "additionalProperties": false
+ },
+ "MediaType": {
+ "description": "Media type of data asset.",
+ "enum": [
+ "Image",
+ "Text"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MediaType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Image"
},
- "requestTimeout": {
- "format": "duration",
- "description": "The scoring timeout in ISO 8601 format.\r\nDefaults to 5000ms.",
- "default": "PT5S",
- "type": "string"
+ {
+ "value": "Text"
}
- },
- "additionalProperties": false
+ ]
},
- "OnlineScaleSettings": {
- "description": "Online deployment scaling configuration.",
- "required": [
- "scaleType"
- ],
- "type": "object",
- "properties": {
- "scaleType": {
- "description": "[Required] Type of deployment scaling algorithm",
- "$ref": "#/definitions/ScaleType"
- }
- },
- "discriminator": "scaleType"
- },
- "OperatingSystemType": {
- "description": "The type of operating system.",
- "enum": [
- "Linux",
- "Windows"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "OperatingSystemType",
- "modelAsString": true,
- "values": [
- {
- "value": "Linux"
- },
- {
- "value": "Windows"
- }
- ]
- },
- "additionalProperties": false
- },
- "OrderString": {
- "enum": [
- "CreatedAtDesc",
- "CreatedAtAsc",
- "UpdatedAtDesc",
- "UpdatedAtAsc"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "OrderString",
- "modelAsString": true,
- "values": [
- {
- "value": "CreatedAtDesc"
- },
- {
- "value": "CreatedAtAsc"
- },
- {
- "value": "UpdatedAtDesc"
- },
- {
- "value": "UpdatedAtAsc"
- }
- ]
- },
- "additionalProperties": false
- },
- "OutputDeliveryMode": {
- "description": "Output data delivery mode enums.",
- "enum": [
- "ReadWriteMount",
- "Upload",
- "Direct"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "OutputDeliveryMode",
- "modelAsString": true,
- "values": [
- {
- "value": "ReadWriteMount"
- },
- {
- "value": "Upload"
- },
- {
- "value": "Direct"
- }
+ "additionalProperties": false
+ },
+ "MedianStoppingPolicy": {
+ "description": "Defines an early termination policy based on running averages of the primary metric of all runs",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EarlyTerminationPolicy"
+ }
+ ],
+ "x-ms-discriminator-value": "MedianStopping",
+ "additionalProperties": false
+ },
+ "ModelConfiguration": {
+ "description": "Model configuration options.",
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "Input delivery mode for the model.",
+ "default": "Download",
+ "$ref": "#/definitions/PackageInputDeliveryMode"
+ },
+ "mountPath": {
+ "description": "Relative mounting path of the model in the target image.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ModelContainer": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetContainer"
+ }
+ ],
+ "properties": {
+ "provisioningState": {
+ "description": "Provisioning state for the model container.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "OutputPathAssetReference": {
- "description": "Reference to an asset via its path in a job output.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/AssetReferenceBase"
- }
- ],
+ "x-ms-client-name": "ModelContainerProperties",
+ "additionalProperties": false
+ },
+ "ModelContainerResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "jobId": {
- "description": "ARM resource ID of the job.",
- "type": "string",
- "x-nullable": true
- },
- "path": {
- "description": "The path of the file/directory in the job output.",
- "type": "string",
- "x-nullable": true
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/ModelContainer"
+ }
+ },
+ "x-ms-client-name": "ModelContainer",
+ "additionalProperties": false
+ },
+ "ModelContainerResourceArmPaginatedResult": {
+ "description": "A paginated list of ModelContainer entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of ModelContainer objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type ModelContainer.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ModelContainerResource"
}
- },
- "x-ms-discriminator-value": "OutputPath",
- "additionalProperties": false
- },
- "PackageBuildState": {
- "description": "Package build state returned in package response.",
- "enum": [
- "NotStarted",
- "Running",
- "Succeeded",
- "Failed"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "PackageBuildState",
- "modelAsString": true,
- "values": [
- {
- "value": "NotStarted"
- },
- {
- "value": "Running"
- },
- {
- "value": "Succeeded"
- },
- {
- "value": "Failed"
- }
+ }
+ },
+ "additionalProperties": false
+ },
+ "ModelPackageInput": {
+ "description": "Model package input options.",
+ "required": [
+ "inputType",
+ "path"
+ ],
+ "type": "object",
+ "properties": {
+ "inputType": {
+ "description": "[Required] Type of the input included in the target image.",
+ "$ref": "#/definitions/PackageInputType"
+ },
+ "mode": {
+ "description": "Input delivery mode of the input.",
+ "default": "ReadOnlyMount",
+ "$ref": "#/definitions/PackageInputDeliveryMode"
+ },
+ "mountPath": {
+ "description": "Relative mount path of the input in the target image.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "path": {
+ "description": "[Required] Location of the input.",
+ "$ref": "#/definitions/PackageInputPathBase"
+ }
+ },
+ "additionalProperties": false
+ },
+ "ModelPerformanceMetricThresholdBase": {
+ "required": [
+ "modelType"
+ ],
+ "type": "object",
+ "properties": {
+ "modelType": {
+ "description": "[Required] Specifies the data type of the metric threshold.",
+ "$ref": "#/definitions/MonitoringModelType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "threshold": {
+ "description": "The threshold value. If null, a default value will be set depending on the selected metric.",
+ "$ref": "#/definitions/MonitoringThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "discriminator": "modelType"
+ },
+ "ModelPerformanceSignalBase": {
+ "required": [
+ "baselineData",
+ "metricThreshold",
+ "targetData"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringSignalBase"
+ }
+ ],
+ "properties": {
+ "baselineData": {
+ "description": "[Required] The data to calculate drift against.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
- },
- "PackageInputDeliveryMode": {
- "description": "Mounting type of the model or the inputs",
- "enum": [
- "ReadOnlyMount",
- "Download"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "PackageInputDeliveryMode",
- "modelAsString": true,
- "values": [
- {
- "value": "ReadOnlyMount"
- },
- {
- "value": "Download"
- }
+ "dataSegment": {
+ "description": "The data segment.",
+ "$ref": "#/definitions/MonitoringDataSegment",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "metricThreshold": {
+ "description": "[Required] A list of metrics to calculate and their associated thresholds.",
+ "$ref": "#/definitions/ModelPerformanceMetricThresholdBase",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "targetData": {
+ "description": "[Required] The data produced by the production service which drift will be calculated for.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "PackageInputPathBase": {
- "required": [
- "inputPathType"
- ],
- "type": "object",
- "properties": {
- "inputPathType": {
- "description": "[Required] Input path type for package inputs.",
- "$ref": "#/definitions/InputPathType"
+ "additionalProperties": false
+ },
+ "ModelSize": {
+ "description": "Image model size.",
+ "enum": [
+ "None",
+ "Small",
+ "Medium",
+ "Large",
+ "ExtraLarge"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ModelSize",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None",
+ "description": "No value selected."
+ },
+ {
+ "value": "Small",
+ "description": "Small size."
+ },
+ {
+ "value": "Medium",
+ "description": "Medium size."
+ },
+ {
+ "value": "Large",
+ "description": "Large size."
+ },
+ {
+ "value": "ExtraLarge",
+ "description": "Extra large size."
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ModelVersion": {
+ "description": "Model asset version details.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetBase"
+ }
+ ],
+ "properties": {
+ "flavors": {
+ "description": "Mapping of model flavors to their properties.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/FlavorData",
+ "x-nullable": true
+ },
+ "x-nullable": true
+ },
+ "intellectualProperty": {
+ "description": "Intellectual Property details. Used if model is an Intellectual Property.",
+ "$ref": "#/definitions/IntellectualProperty",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jobName": {
+ "description": "Name of the training job which produced this model",
+ "type": "string",
+ "x-nullable": true
+ },
+ "modelType": {
+ "description": "The storage format for this entity. Used for NCD.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "modelUri": {
+ "description": "The URI path to the model contents.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the model version.",
+ "$ref": "#/definitions/AssetProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
},
- "discriminator": "inputPathType"
+ "stage": {
+ "description": "Stage in the model lifecycle assigned to this model",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "PackageInputPathId": {
- "description": "Package input path specified with a resource id.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/PackageInputPathBase"
- }
- ],
+ "x-ms-client-name": "ModelVersionProperties",
+ "additionalProperties": false
+ },
+ "ModelVersionResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "resourceId": {
- "description": "Input resource id.",
- "type": "string",
- "x-nullable": true
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/ModelVersion"
+ }
+ },
+ "x-ms-client-name": "ModelVersion",
+ "additionalProperties": false
+ },
+ "ModelVersionResourceArmPaginatedResult": {
+ "description": "A paginated list of ModelVersion entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of ModelVersion objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type ModelVersion.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ModelVersionResource"
}
+ }
+ },
+ "additionalProperties": false
+ },
+ "MonitorDefinition": {
+ "required": [
+ "computeId",
+ "signals"
+ ],
+ "type": "object",
+ "properties": {
+ "computeId": {
+ "description": "[Required] The ARM resource ID of the compute resource to run the monitoring job on.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "monitoringTarget": {
+ "description": "The ARM resource ID of either the model or deployment targeted by this monitor.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "notificationSetting": {
+ "description": "The monitor's notification settings.",
+ "$ref": "#/definitions/NotificationSetting",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "x-ms-discriminator-value": "PathId",
- "additionalProperties": false
+ "signals": {
+ "description": "[Required] The signals to monitor.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/MonitoringSignalBase",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "MonitoringDataSegment": {
+ "type": "object",
+ "properties": {
+ "feature": {
+ "description": "The feature to segment the data on.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "values": {
+ "description": "Filters for only the specified values of the given segmented feature.",
+ "type": "array",
+ "items": {
+ "type": "string"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "PackageInputPathUrl": {
- "description": "Package input path specified as an url.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "MonitoringFeatureDataType": {
+ "enum": [
+ "Numerical",
+ "Categorical"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MonitoringFeatureDataType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/PackageInputPathBase"
- }
- ],
- "properties": {
- "url": {
- "description": "Input path url.",
- "type": "string",
- "x-nullable": true
+ "value": "Numerical",
+ "description": "Used for features of numerical data type."
+ },
+ {
+ "value": "Categorical",
+ "description": "Used for features of categorical data type."
}
- },
- "x-ms-discriminator-value": "Url",
- "additionalProperties": false
+ ]
},
- "PackageInputPathVersion": {
- "description": "Package input path specified with name and version.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "MonitoringFeatureFilterBase": {
+ "required": [
+ "filterType"
+ ],
+ "type": "object",
+ "properties": {
+ "filterType": {
+ "description": "[Required] Specifies the feature filter to leverage when selecting features to calculate metrics over.",
+ "$ref": "#/definitions/MonitoringFeatureFilterType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "filterType"
+ },
+ "MonitoringFeatureFilterType": {
+ "enum": [
+ "AllFeatures",
+ "TopNByAttribution",
+ "FeatureSubset"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MonitoringFeatureFilterType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/PackageInputPathBase"
- }
- ],
- "properties": {
- "resourceName": {
- "description": "Input resource name.",
- "type": "string",
- "x-nullable": true
+ "value": "AllFeatures",
+ "description": "Includes all features."
},
- "resourceVersion": {
- "description": "Input resource version.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "TopNByAttribution",
+ "description": "Only includes the top contributing features, measured by feature attribution."
+ },
+ {
+ "value": "FeatureSubset",
+ "description": "Includes a user-defined subset of features."
}
- },
- "x-ms-discriminator-value": "PathVersion",
- "additionalProperties": false
+ ]
},
- "PackageInputType": {
- "description": "Type of the inputs.",
- "enum": [
- "UriFile",
- "UriFolder"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "PackageInputType",
- "modelAsString": true,
- "values": [
- {
- "value": "UriFile"
- },
- {
- "value": "UriFolder"
- }
+ "additionalProperties": false
+ },
+ "MonitoringInputData": {
+ "required": [
+ "dataContext"
+ ],
+ "type": "object",
+ "properties": {
+ "asset": {
+ "description": "The data asset input to be leveraged by the monitoring job..",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "dataContext": {
+ "description": "[Required] The context of the data source.",
+ "$ref": "#/definitions/MonitoringInputDataContext",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "preprocessingComponentId": {
+ "description": "The ARM resource ID of the component resource used to preprocess the data.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "PackageRequest": {
- "description": "Model package operation request properties.",
- "required": [
- "inferencingServer",
- "targetEnvironmentName"
- ],
- "type": "object",
- "properties": {
- "baseEnvironmentSource": {
- "description": "Base environment to start with.",
- "$ref": "#/definitions/BaseEnvironmentSource",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "MonitoringInputDataContext": {
+ "enum": [
+ "ModelInputs",
+ "ModelOutputs",
+ "Training",
+ "Test",
+ "Validation",
+ "GroundTruth"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MonitoringInputDataContext",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ModelInputs",
+ "description": "A dataset containing the feature input to the model."
},
- "environmentVariables": {
- "description": "Collection of environment variables.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "ModelOutputs",
+ "description": "A dataset containing the infered results of the model."
},
- "inferencingServer": {
- "description": "[Required] Inferencing server configurations.",
- "$ref": "#/definitions/InferencingServer",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "value": "Training",
+ "description": "A dataset containing the data used for training the model."
},
- "inputs": {
- "description": "Collection of inputs.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ModelPackageInput"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true,
- "x-ms-identifiers": []
+ {
+ "value": "Test",
+ "description": "A dataset leveraged to test the model."
},
- "modelConfiguration": {
- "description": "Model configuration including the mount mode.",
- "$ref": "#/definitions/ModelConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Validation",
+ "description": "A dataset leveraged for model validation."
},
- "tags": {
- "description": "Tag dictionary. Tags can be added, removed, and updated.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "GroundTruth",
+ "description": "A dataset containing the ground truth data."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "MonitoringModelType": {
+ "enum": [
+ "Classification",
+ "Regression"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MonitoringModelType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Classification",
+ "description": "A model trained for classification tasks."
},
- "targetEnvironmentName": {
- "description": "[Required] Target environment name to be generated by package.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "value": "Regression",
+ "description": "A model trained for regressions tasks."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "MonitoringNotificationMode": {
+ "enum": [
+ "Disabled",
+ "Enabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MonitoringNotificationMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Disabled",
+ "description": "Disabled notifications will not produce emails/metrics leveraged for alerting."
},
- "targetEnvironmentVersion": {
- "description": "Target environment version to be generated by package.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Enabled",
+ "description": "Enabled notification will produce emails/metrics leveraged for alerting."
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "MonitoringSignalBase": {
+ "required": [
+ "signalType"
+ ],
+ "type": "object",
+ "properties": {
+ "lookbackPeriod": {
+ "format": "duration",
+ "description": "The amount of time a single monitor should look back over the target data on a given run.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "mode": {
+ "description": "The current notification mode for this signal.",
+ "default": "Disabled",
+ "$ref": "#/definitions/MonitoringNotificationMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
},
- "additionalProperties": false
+ "signalType": {
+ "description": "[Required] Specifies the type of signal to monitor.",
+ "$ref": "#/definitions/MonitoringSignalType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "PackageResponse": {
- "description": "Package response returned after async package operation completes successfully.",
- "type": "object",
- "properties": {
- "baseEnvironmentSource": {
- "description": "Base environment to start with.",
- "$ref": "#/definitions/BaseEnvironmentSource",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- },
- "buildId": {
- "description": "Build id of the image build operation.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- },
- "buildState": {
- "description": "Build state of the image build operation.",
- "$ref": "#/definitions/PackageBuildState",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "environmentVariables": {
- "description": "Collection of environment variables.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- },
- "inferencingServer": {
- "description": "Inferencing server configurations.",
- "$ref": "#/definitions/InferencingServer",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
- },
- "inputs": {
- "description": "Collection of inputs.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ModelPackageInput"
- },
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true,
- "x-ms-identifiers": []
- },
- "logUrl": {
- "description": "Log url of the image build operation.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "discriminator": "signalType"
+ },
+ "MonitoringSignalType": {
+ "enum": [
+ "DataDrift",
+ "PredictionDrift",
+ "DataQuality",
+ "FeatureAttributionDrift",
+ "Custom",
+ "ModelPerformance"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MonitoringSignalType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "DataDrift",
+ "description": "Tracks model input data distribution change, comparing against training data or past production data."
},
- "modelConfiguration": {
- "description": "Model configuration including the mount mode.",
- "$ref": "#/definitions/ModelConfiguration",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "PredictionDrift",
+ "description": "Tracks prediction result data distribution change, comparing against validation/test label data or past production data."
},
- "tags": {
- "description": "Tag dictionary. Tags can be added, removed, and updated.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "DataQuality",
+ "description": "Tracks model input data integrity."
},
- "targetEnvironmentId": {
- "description": "Asset ID of the target environment created by package operation.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "FeatureAttributionDrift",
+ "description": "Tracks feature importance change in production, comparing against feature importance at training time."
},
- "targetEnvironmentName": {
- "description": "Target environment name to be generated by package.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Custom",
+ "description": "Tracks a custom signal provided by users."
},
- "targetEnvironmentVersion": {
- "description": "Target environment version to be generated by package.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "ModelPerformance",
+ "description": "Tracks model perforance based on ground truth data."
}
- },
- "additionalProperties": false
+ ]
},
- "PartialBatchDeployment": {
- "description": "Mutable batch inference settings per deployment.",
- "type": "object",
- "properties": {
- "description": {
- "description": "Description of the endpoint deployment.",
- "type": "string",
- "x-nullable": true
- }
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "MonitoringThreshold": {
+ "type": "object",
+ "properties": {
+ "value": {
+ "format": "double",
+ "description": "The threshold value. If null, the set default is dependent on the metric type.",
+ "type": "number",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties": {
- "description": "Strictly used in update requests.",
- "type": "object",
- "properties": {
- "properties": {
- "description": "Additional attributes of the entity.",
- "$ref": "#/definitions/PartialBatchDeployment"
+ "additionalProperties": false
+ },
+ "Mpi": {
+ "description": "MPI distribution configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DistributionConfiguration"
+ }
+ ],
+ "properties": {
+ "processCountPerInstance": {
+ "format": "int32",
+ "description": "Number of processes per MPI node.",
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Mpi",
+ "additionalProperties": false
+ },
+ "MultiSelect": {
+ "description": "Whether multiSelect is enabled",
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "MultiSelect",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Enabled"
},
- "tags": {
- "description": "Resource tags.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- }
+ {
+ "value": "Disabled"
}
- },
- "additionalProperties": false
+ ]
},
- "PartialManagedServiceIdentity": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "type": "object",
- "properties": {
- "type": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentityType"
+ "additionalProperties": false
+ },
+ "NCrossValidations": {
+ "description": "N-Cross validations value.",
+ "required": [
+ "mode"
+ ],
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "[Required] Mode for determining N-Cross validations.",
+ "$ref": "#/definitions/NCrossValidationsMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "mode"
+ },
+ "NCrossValidationsMode": {
+ "description": "Determines how N-Cross validations value is determined.",
+ "enum": [
+ "Auto",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "NCrossValidationsMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Auto",
+ "description": "Determine N-Cross validations value automatically. Supported only for 'Forecasting' AutoML task."
},
- "userAssignedIdentities": {
- "description": "The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.",
- "type": "object",
- "additionalProperties": {
- "$ref": "#/definitions/PartialUserAssignedIdentity"
- }
+ {
+ "value": "Custom",
+ "description": "Use custom N-Cross validations value."
}
- },
- "additionalProperties": false
+ ]
},
- "PartialMinimalTrackedResource": {
- "description": "Strictly used in update requests.",
- "type": "object",
- "properties": {
- "tags": {
- "description": "Resource tags.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- }
- }
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "NlpFixedParameters": {
+ "description": "Fixed training parameters that won't be swept over during AutoML NLP training.",
+ "type": "object",
+ "properties": {
+ "gradientAccumulationSteps": {
+ "format": "int32",
+ "description": "Number of steps to accumulate gradients over before running a backward pass.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "learningRate": {
+ "format": "float",
+ "description": "The learning rate for the training procedure.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "learningRateScheduler": {
+ "description": "The type of learning rate schedule to use during the training procedure.",
+ "default": "None",
+ "$ref": "#/definitions/NlpLearningRateScheduler"
+ },
+ "modelName": {
+ "description": "The name of the model to train.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "numberOfEpochs": {
+ "format": "int32",
+ "description": "Number of training epochs.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "trainingBatchSize": {
+ "format": "int32",
+ "description": "The batch size for the training procedure.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "validationBatchSize": {
+ "format": "int32",
+ "description": "The batch size to be used during evaluation.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "warmupRatio": {
+ "format": "float",
+ "description": "The warmup ratio, used alongside LrSchedulerType.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "weightDecay": {
+ "format": "float",
+ "description": "The weight decay for the training procedure.",
+ "type": "number",
+ "x-nullable": true
+ }
},
- "PartialMinimalTrackedResourceWithIdentity": {
- "description": "Strictly used in update requests.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "NlpLearningRateScheduler": {
+ "description": "Enum of learning rate schedulers that aligns with those supported by HF",
+ "enum": [
+ "None",
+ "Linear",
+ "Cosine",
+ "CosineWithRestarts",
+ "Polynomial",
+ "Constant",
+ "ConstantWithWarmup"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "NlpLearningRateScheduler",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/PartialMinimalTrackedResource"
- }
- ],
- "properties": {
- "identity": {
- "description": "Managed service identity (system assigned and/or user assigned identities)",
- "$ref": "#/definitions/PartialManagedServiceIdentity"
+ "value": "None",
+ "description": "No learning rate schedule."
+ },
+ {
+ "value": "Linear",
+ "description": "Linear warmup and decay."
+ },
+ {
+ "value": "Cosine",
+ "description": "Linear warmup then cosine decay."
+ },
+ {
+ "value": "CosineWithRestarts",
+ "description": "Linear warmup, cosine decay, then restart to initial LR."
+ },
+ {
+ "value": "Polynomial",
+ "description": "Increase linearly then polynomially decay."
+ },
+ {
+ "value": "Constant",
+ "description": "Constant learning rate."
+ },
+ {
+ "value": "ConstantWithWarmup",
+ "description": "Linear warmup followed by constant value."
}
- },
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "NlpParameterSubspace": {
+ "description": "Stringified search spaces for each parameter. See below examples.",
+ "type": "object",
+ "properties": {
+ "gradientAccumulationSteps": {
+ "description": "Number of steps to accumulate gradients over before running a backward pass.",
+ "type": "string",
+ "example": "choice(1, 2)",
+ "x-nullable": true
+ },
+ "learningRate": {
+ "description": "The learning rate for the training procedure.",
+ "type": "string",
+ "example": "uniform(5e-6, 5e-5)",
+ "x-nullable": true
+ },
+ "learningRateScheduler": {
+ "description": "The type of learning rate schedule to use during the training procedure.",
+ "type": "string",
+ "example": "choice('linear', 'cosine')",
+ "x-nullable": true
+ },
+ "modelName": {
+ "description": "The name of the model to train.",
+ "type": "string",
+ "example": "choice('bert-base-cased', 'roberta-base')",
+ "x-nullable": true
+ },
+ "numberOfEpochs": {
+ "description": "Number of training epochs.",
+ "type": "string",
+ "example": "choice(3, 4)",
+ "x-nullable": true
+ },
+ "trainingBatchSize": {
+ "description": "The batch size for the training procedure.",
+ "type": "string",
+ "example": "choice(16, 32)",
+ "x-nullable": true
+ },
+ "validationBatchSize": {
+ "description": "The batch size to be used during evaluation.",
+ "type": "string",
+ "example": "choice(16, 32)",
+ "x-nullable": true
+ },
+ "warmupRatio": {
+ "description": "The warmup ratio, used alongside LrSchedulerType.",
+ "type": "string",
+ "example": "uniform(0.01, 0.1)",
+ "x-nullable": true
+ },
+ "weightDecay": {
+ "description": "The weight decay for the training procedure.",
+ "type": "string",
+ "example": "uniform(0.01, 0.1)",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "NlpSweepSettings": {
+ "description": "Model sweeping and hyperparameter tuning related settings.",
+ "required": [
+ "samplingAlgorithm"
+ ],
+ "type": "object",
+ "properties": {
+ "earlyTermination": {
+ "description": "Type of early termination policy for the sweeping job.",
+ "$ref": "#/definitions/EarlyTerminationPolicy",
+ "x-nullable": true
+ },
+ "samplingAlgorithm": {
+ "description": "[Required] Type of sampling algorithm.",
+ "$ref": "#/definitions/SamplingAlgorithmType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "NlpVertical": {
+ "description": "Abstract class for NLP related AutoML tasks.\r\nNLP - Natural Language Processing.",
+ "type": "object",
+ "properties": {
+ "featurizationSettings": {
+ "description": "Featurization inputs needed for AutoML job.",
+ "$ref": "#/definitions/NlpVerticalFeaturizationSettings",
+ "x-nullable": true
+ },
+ "fixedParameters": {
+ "description": "Model/training parameters that will remain constant throughout training.",
+ "$ref": "#/definitions/NlpFixedParameters",
+ "x-nullable": true
+ },
+ "limitSettings": {
+ "description": "Execution constraints for AutoMLJob.",
+ "$ref": "#/definitions/NlpVerticalLimitSettings",
+ "x-nullable": true
+ },
+ "searchSpace": {
+ "description": "Search space for sampling different combinations of models and their hyperparameters.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/NlpParameterSubspace"
+ },
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ },
+ "sweepSettings": {
+ "description": "Settings for model sweeping and hyperparameter tuning.",
+ "$ref": "#/definitions/NlpSweepSettings",
+ "x-nullable": true
+ },
+ "validationData": {
+ "description": "Validation data inputs.",
+ "$ref": "#/definitions/MLTableJobInput",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "NlpVerticalFeaturizationSettings": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/FeaturizationSettings"
+ }
+ ],
+ "additionalProperties": false
+ },
+ "NlpVerticalLimitSettings": {
+ "description": "Job execution constraints.",
+ "type": "object",
+ "properties": {
+ "maxConcurrentTrials": {
+ "format": "int32",
+ "description": "Maximum Concurrent AutoML iterations.",
+ "default": 1,
+ "type": "integer"
+ },
+ "maxNodes": {
+ "format": "int32",
+ "description": "Maximum nodes to use for the experiment.",
+ "default": 1,
+ "type": "integer"
+ },
+ "maxTrials": {
+ "format": "int32",
+ "description": "Number of AutoML iterations.",
+ "default": 1,
+ "type": "integer"
+ },
+ "timeout": {
+ "format": "duration",
+ "description": "AutoML job timeout.",
+ "default": "P7D",
+ "type": "string"
+ },
+ "trialTimeout": {
+ "format": "duration",
+ "description": "Timeout for individual HD trials.",
+ "type": "string"
+ }
},
- "PartialMinimalTrackedResourceWithSku": {
- "description": "Strictly used in update requests.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "Nodes": {
+ "description": "Abstract Nodes definition",
+ "required": [
+ "nodesValueType"
+ ],
+ "type": "object",
+ "properties": {
+ "nodesValueType": {
+ "description": "[Required] Type of the Nodes value",
+ "$ref": "#/definitions/NodesValueType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "nodesValueType"
+ },
+ "NodesValueType": {
+ "description": "The enumerated types for the nodes value",
+ "enum": [
+ "All",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "NodesValueType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/PartialMinimalTrackedResource"
- }
- ],
- "properties": {
- "sku": {
- "description": "Sku details required for ARM contract for Autoscaling.",
- "$ref": "#/definitions/PartialSku"
+ "value": "All"
+ },
+ {
+ "value": "Custom"
}
- },
- "additionalProperties": false
+ ]
},
- "PartialSku": {
- "description": "Common SKU definition.",
- "type": "object",
- "properties": {
- "capacity": {
- "format": "int32",
- "description": "If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.",
- "type": "integer"
- },
- "family": {
- "description": "If the service has different generations of hardware, for the same SKU, then that can be captured here.",
- "type": "string"
- },
- "name": {
- "description": "The name of the SKU. Ex - P3. It is typically a letter+number code.",
- "type": "string"
- },
- "size": {
- "description": "The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.",
+ "additionalProperties": false
+ },
+ "NoneDatastoreCredentials": {
+ "description": "Empty/none datastore credentials.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "x-ms-discriminator-value": "None",
+ "additionalProperties": false
+ },
+ "NotificationSetting": {
+ "description": "Configuration for notification.",
+ "type": "object",
+ "properties": {
+ "emailOn": {
+ "description": "Send email notification to user on specified notfication type",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/EmailNotificationEnableType"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "emails": {
+ "description": "This is the email recipient list which has a limitation of 499 characters in total concat with comma seperator",
+ "type": "array",
+ "items": {
"type": "string"
},
- "tier": {
- "description": "This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.",
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/SkuTier"
- }
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "PartialUserAssignedIdentity": {
- "type": "object",
- "additionalProperties": false
- },
- "PipelineJob": {
- "description": "Pipeline Job definition: defines generic to MFE attributes.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/JobBase"
- }
- ],
- "properties": {
- "inputs": {
- "description": "Inputs for the pipeline job.",
- "type": "object",
- "additionalProperties": {
- "description": "Command job definition.",
- "$ref": "#/definitions/JobInput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
+ "webhooks": {
+ "description": "Send webhook callback to a service. Key is a user-provided name for the webhook.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Webhook base",
+ "$ref": "#/definitions/Webhook",
"x-nullable": true
},
- "jobs": {
- "description": "Jobs construct the Pipeline Job.",
- "type": "object",
- "additionalProperties": {
- "type": "object",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "NumericalDataDriftMetric": {
+ "enum": [
+ "JensenShannonDistance",
+ "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance",
+ "TwoSampleKolmogorovSmirnovTest"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "NumericalDataDriftMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "JensenShannonDistance",
+ "description": "The Jensen Shannon Distance (JSD) metric."
},
- "outputs": {
- "description": "Outputs for the pipeline job",
- "type": "object",
- "additionalProperties": {
- "description": "Job output definition container information on where to find job output/logs.",
- "$ref": "#/definitions/JobOutput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "PopulationStabilityIndex",
+ "description": "The Population Stability Index (PSI) metric."
},
- "settings": {
- "description": "Pipeline settings, for things like ContinueRunOnStepFailure etc.",
- "type": "object",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "NormalizedWassersteinDistance",
+ "description": "The Normalized Wasserstein Distance metric."
},
- "sourceJobId": {
- "description": "ARM resource ID of source job.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "TwoSampleKolmogorovSmirnovTest",
+ "description": "The Two Sample Kolmogorov-Smirnov Test (two-sample K–S) metric."
}
- },
- "x-ms-discriminator-value": "Pipeline",
- "additionalProperties": false
+ ]
},
- "ProbeSettings": {
- "description": "Deployment container liveness/readiness probe configuration.",
- "type": "object",
- "properties": {
- "failureThreshold": {
- "format": "int32",
- "description": "The number of failures to allow before returning an unhealthy status.",
- "default": 30,
- "type": "integer"
- },
- "initialDelay": {
- "format": "duration",
- "description": "The delay before the first probe in ISO 8601 format.",
- "type": "string",
- "x-nullable": true
- },
- "period": {
- "format": "duration",
- "description": "The length of time between probes in ISO 8601 format.",
- "default": "PT10S",
- "type": "string"
+ "additionalProperties": false
+ },
+ "NumericalDataDriftMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataDriftMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The numerical data drift metric to calculate.",
+ "$ref": "#/definitions/NumericalDataDriftMetric"
+ }
+ },
+ "x-ms-discriminator-value": "Numerical",
+ "additionalProperties": false
+ },
+ "NumericalDataQualityMetric": {
+ "enum": [
+ "NullValueRate",
+ "DataTypeErrorRate",
+ "OutOfBoundsRate"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "NumericalDataQualityMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "NullValueRate",
+ "description": "Calculates the rate of null values."
},
- "successThreshold": {
- "format": "int32",
- "description": "The number of successful probes before returning a healthy status.",
- "default": 1,
- "type": "integer"
+ {
+ "value": "DataTypeErrorRate",
+ "description": "Calculates the rate of data type errors."
},
- "timeout": {
- "format": "duration",
- "description": "The probe timeout in ISO 8601 format.",
- "default": "PT2S",
- "type": "string"
+ {
+ "value": "OutOfBoundsRate",
+ "description": "Calculates the rate values are out of bounds."
}
- },
- "additionalProperties": false
+ ]
},
- "ProgressMetrics": {
- "description": "Progress metrics definition",
- "type": "object",
- "properties": {
- "completedDatapointCount": {
- "format": "int64",
- "description": "The completed datapoint count.",
- "type": "integer",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "NumericalDataQualityMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataQualityMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The numerical data quality metric to calculate.",
+ "$ref": "#/definitions/NumericalDataQualityMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "Numerical",
+ "additionalProperties": false
+ },
+ "NumericalPredictionDriftMetric": {
+ "enum": [
+ "JensenShannonDistance",
+ "PopulationStabilityIndex",
+ "NormalizedWassersteinDistance",
+ "TwoSampleKolmogorovSmirnovTest"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "NumericalPredictionDriftMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "JensenShannonDistance",
+ "description": "The Jensen Shannon Distance (JSD) metric."
},
- "incrementalDataLastRefreshDateTime": {
- "format": "date-time",
- "description": "The time of last successful incremental data refresh in UTC.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "PopulationStabilityIndex",
+ "description": "The Population Stability Index (PSI) metric."
},
- "skippedDatapointCount": {
- "format": "int64",
- "description": "The skipped datapoint count.",
- "type": "integer",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "NormalizedWassersteinDistance",
+ "description": "The Normalized Wasserstein Distance metric."
},
- "totalDatapointCount": {
- "format": "int64",
- "description": "The total datapoint count.",
- "type": "integer",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "TwoSampleKolmogorovSmirnovTest",
+ "description": "The Two Sample Kolmogorov-Smirnov Test (two-sample K–S) metric."
}
- },
- "additionalProperties": false
+ ]
},
- "PublicNetworkAccessType": {
- "description": "Enum to determine whether PublicNetworkAccess is Enabled or Disabled.",
- "enum": [
- "Enabled",
- "Disabled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "PublicNetworkAccessType",
- "modelAsString": true,
- "values": [
- {
- "value": "Enabled"
- },
- {
- "value": "Disabled"
- }
+ "additionalProperties": false
+ },
+ "NumericalPredictionDriftMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PredictionDriftMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The numerical prediction drift metric to calculate.",
+ "$ref": "#/definitions/NumericalPredictionDriftMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "PyTorch": {
- "description": "PyTorch distribution configuration.",
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "Numerical",
+ "additionalProperties": false
+ },
+ "ObjectDetectionPrimaryMetrics": {
+ "description": "Primary metrics for Image ObjectDetection task.",
+ "enum": [
+ "MeanAveragePrecision"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ObjectDetectionPrimaryMetrics",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/DistributionConfiguration"
- }
- ],
- "properties": {
- "processCountPerInstance": {
- "format": "int32",
- "description": "Number of processes per node.",
- "type": "integer",
- "x-nullable": true
+ "value": "MeanAveragePrecision",
+ "description": "Mean Average Precision (MAP) is the average of AP (Average Precision).\nAP is calculated for each class and averaged to get the MAP."
}
- },
- "x-ms-discriminator-value": "PyTorch",
- "additionalProperties": false
+ ]
},
- "QueueSettings": {
- "type": "object",
- "properties": {
- "jobTier": {
- "description": "Enum to determine the job tier.",
- "default": "Standard",
- "$ref": "#/definitions/JobTier",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "priority": {
- "format": "int32",
- "description": "Controls the priority of the job on a compute.",
- "type": "integer",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- }
+ "additionalProperties": false
+ },
+ "Objective": {
+ "description": "Optimization objective.",
+ "required": [
+ "goal",
+ "primaryMetric"
+ ],
+ "type": "object",
+ "properties": {
+ "goal": {
+ "description": "[Required] Defines supported metric goals for hyperparameter tuning",
+ "$ref": "#/definitions/Goal"
+ },
+ "primaryMetric": {
+ "description": "[Required] Name of the metric to optimize.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ },
+ "OneLakeArtifact": {
+ "description": "OneLake artifact (data source) configuration.",
+ "required": [
+ "artifactName",
+ "artifactType"
+ ],
+ "type": "object",
+ "properties": {
+ "artifactName": {
+ "description": "[Required] OneLake artifact name",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
},
- "additionalProperties": false
+ "artifactType": {
+ "description": "[Required] OneLake artifact type",
+ "$ref": "#/definitions/OneLakeArtifactType"
+ }
},
- "RandomSamplingAlgorithm": {
- "description": "Defines a Sampling Algorithm that generates values randomly",
- "type": "object",
- "allOf": [
+ "discriminator": "artifactType"
+ },
+ "OneLakeArtifactType": {
+ "description": "Enum to determine OneLake artifact type.",
+ "enum": [
+ "Lakehouse"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "OneLakeArtifactType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/SamplingAlgorithm"
- }
- ],
- "properties": {
- "logbase": {
- "description": "An optional positive number or e in string format to be used as base for log based random sampling",
- "type": "string",
- "x-nullable": true
- },
- "rule": {
- "description": "The specific type of random algorithm",
- "default": "Random",
- "$ref": "#/definitions/RandomSamplingAlgorithmRule"
- },
- "seed": {
- "format": "int32",
- "description": "An optional integer to use as the seed for random number generation",
- "type": "integer",
- "x-nullable": true
+ "value": "Lakehouse"
}
- },
- "x-ms-discriminator-value": "Random",
- "additionalProperties": false
+ ]
},
- "RandomSamplingAlgorithmRule": {
- "description": "The specific type of random algorithm",
- "enum": [
- "Random",
- "Sobol"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "RandomSamplingAlgorithmRule",
- "modelAsString": true,
- "values": [
- {
- "value": "Random"
- },
- {
- "value": "Sobol"
- }
+ "additionalProperties": false
+ },
+ "OneLakeDatastore": {
+ "description": "OneLake (Trident) datastore configuration.",
+ "required": [
+ "artifact",
+ "oneLakeWorkspaceName"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/Datastore"
+ }
+ ],
+ "properties": {
+ "artifact": {
+ "description": "[Required] OneLake artifact backing the datastore.",
+ "$ref": "#/definitions/OneLakeArtifact",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
- },
- "RecurrenceFrequency": {
- "description": "Enum to describe the frequency of a recurrence schedule",
- "enum": [
- "Minute",
- "Hour",
- "Day",
- "Week",
- "Month"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "RecurrenceFrequency",
- "modelAsString": true,
- "values": [
- {
- "value": "Minute",
- "description": "Minute frequency"
- },
- {
- "value": "Hour",
- "description": "Hour frequency"
- },
- {
- "value": "Day",
- "description": "Day frequency"
- },
- {
- "value": "Week",
- "description": "Week frequency"
- },
- {
- "value": "Month",
- "description": "Month frequency"
- }
+ "endpoint": {
+ "description": "OneLake endpoint to use for the datastore.",
+ "type": "string",
+ "example": "data.microsoft.com",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "oneLakeWorkspaceName": {
+ "description": "[Required] OneLake workspace name.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "serviceDataAccessAuthIdentity": {
+ "description": "Indicates which identity to use to authenticate service data access to customer's storage.",
+ "default": "None",
+ "$ref": "#/definitions/ServiceDataAccessAuthIdentity",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "RecurrenceSchedule": {
- "required": [
- "hours",
- "minutes"
- ],
- "type": "object",
+ "x-ms-discriminator-value": "OneLake",
+ "additionalProperties": false
+ },
+ "OnlineDeployment": {
+ "required": [
+ "endpointComputeType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EndpointDeploymentPropertiesBase"
+ }
+ ],
+ "properties": {
+ "appInsightsEnabled": {
+ "description": "If true, enables Application Insights logging.",
+ "default": false,
+ "type": "boolean"
+ },
+ "dataCollector": {
+ "description": "The mdc configuration, we disable mdc when it's null.",
+ "$ref": "#/definitions/DataCollector",
+ "x-nullable": true
+ },
+ "egressPublicNetworkAccess": {
+ "description": "If Enabled, allow egress public network access. If Disabled, this will create secure egress. Default: Enabled.",
+ "default": "Enabled",
+ "$ref": "#/definitions/EgressPublicNetworkAccessType"
+ },
+ "endpointComputeType": {
+ "description": "[Required] The compute type of the endpoint.",
+ "$ref": "#/definitions/EndpointComputeType"
+ },
+ "instanceType": {
+ "description": "Compute instance type.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "livenessProbe": {
+ "description": "Liveness probe monitors the health of the container regularly.",
+ "$ref": "#/definitions/ProbeSettings",
+ "x-nullable": true
+ },
+ "model": {
+ "description": "The URI path to the model.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "modelMountPath": {
+ "description": "The path to mount the model in custom container.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the endpoint deployment.",
+ "$ref": "#/definitions/DeploymentProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ },
+ "readinessProbe": {
+ "description": "Readiness probe validates if the container is ready to serve traffic. The properties and defaults are the same as liveness probe.",
+ "$ref": "#/definitions/ProbeSettings",
+ "x-nullable": true
+ },
+ "requestSettings": {
+ "description": "Request settings for the deployment.",
+ "$ref": "#/definitions/OnlineRequestSettings",
+ "x-nullable": true
+ },
+ "scaleSettings": {
+ "description": "Scale settings for the deployment.\r\nIf it is null or not provided,\r\nit defaults to TargetUtilizationScaleSettings for KubernetesOnlineDeployment\r\nand to DefaultScaleSettings for ManagedOnlineDeployment.",
+ "$ref": "#/definitions/OnlineScaleSettings",
+ "x-nullable": true
+ }
+ },
+ "discriminator": "endpointComputeType",
+ "x-ms-client-name": "OnlineDeploymentProperties"
+ },
+ "OnlineDeploymentTrackedResource": {
+ "required": [
+ "location",
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
+ }
+ ],
+ "properties": {
+ "identity": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
+ },
+ "kind": {
+ "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
+ "type": "string"
+ },
"properties": {
- "hours": {
- "description": "[Required] List of hours for the schedule.",
- "type": "array",
- "items": {
- "format": "int32",
- "type": "integer"
- }
- },
- "minutes": {
- "description": "[Required] List of minutes for the schedule.",
- "type": "array",
- "items": {
- "format": "int32",
- "type": "integer"
- }
- },
- "monthDays": {
- "description": "List of month days for the schedule",
- "type": "array",
- "items": {
- "format": "int32",
- "type": "integer"
- },
- "x-nullable": true
- },
- "weekDays": {
- "description": "List of days for the schedule.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/WeekDay"
- },
- "x-nullable": true
- }
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/OnlineDeployment"
},
- "additionalProperties": false
+ "sku": {
+ "description": "Sku details required for ARM contract for Autoscaling.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
+ }
},
- "RecurrenceTrigger": {
- "required": [
- "frequency",
- "interval"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/TriggerBase"
+ "x-ms-client-name": "OnlineDeployment",
+ "additionalProperties": false
+ },
+ "OnlineDeploymentTrackedResourceArmPaginatedResult": {
+ "description": "A paginated list of OnlineDeployment entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of OnlineDeployment objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type OnlineDeployment.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/OnlineDeploymentTrackedResource"
}
- ],
- "properties": {
- "frequency": {
- "description": "[Required] The frequency to trigger schedule.",
- "$ref": "#/definitions/RecurrenceFrequency"
- },
- "interval": {
+ }
+ },
+ "additionalProperties": false
+ },
+ "OnlineEndpoint": {
+ "description": "Online endpoint configuration",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EndpointPropertiesBase"
+ }
+ ],
+ "properties": {
+ "compute": {
+ "description": "ARM resource ID of the compute if it exists.\r\noptional",
+ "type": "string",
+ "x-nullable": true
+ },
+ "mirrorTraffic": {
+ "description": "Percentage of traffic to be mirrored to each deployment without using returned scoring. Traffic values need to sum to utmost 50.",
+ "type": "object",
+ "additionalProperties": {
"format": "int32",
- "description": "[Required] Specifies schedule interval in conjunction with frequency",
"type": "integer"
},
- "schedule": {
- "description": "The recurrence schedule.",
- "$ref": "#/definitions/RecurrenceSchedule",
- "x-nullable": true
- }
+ "x-nullable": true
},
- "x-ms-discriminator-value": "Recurrence",
- "additionalProperties": false
- },
- "ReferenceType": {
- "description": "Enum to determine which reference method to use for an asset.",
- "enum": [
- "Id",
- "DataPath",
- "OutputPath"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ReferenceType",
- "modelAsString": true,
- "values": [
- {
- "value": "Id"
- },
- {
- "value": "DataPath"
- },
- {
- "value": "OutputPath"
- }
+ "provisioningState": {
+ "description": "Provisioning state for the endpoint.",
+ "$ref": "#/definitions/EndpointProvisioningState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
]
},
- "additionalProperties": false
- },
- "RegenerateEndpointKeysRequest": {
- "required": [
- "keyType"
- ],
- "type": "object",
- "properties": {
- "keyType": {
- "description": "[Required] Specification for which type of key to generate. Primary or Secondary.",
- "$ref": "#/definitions/KeyType",
- "example": "Primary"
- },
- "keyValue": {
- "description": "The value the key is set to.",
- "type": "string",
- "x-nullable": true
- }
+ "publicNetworkAccess": {
+ "description": "Set to \"Enabled\" for endpoints that should allow public access when Private Link is enabled.",
+ "default": "Enabled",
+ "$ref": "#/definitions/PublicNetworkAccessType"
},
- "additionalProperties": false
- },
- "Regression": {
- "description": "Regression task in AutoML Table vertical.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/TableVertical"
+ "traffic": {
+ "description": "Percentage of traffic from endpoint to divert to each deployment. Traffic values need to sum to 100.",
+ "type": "object",
+ "additionalProperties": {
+ "format": "int32",
+ "type": "integer"
},
- {
- "$ref": "#/definitions/AutoMLVertical"
- }
- ],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric for regression task.",
- "default": "NormalizedRootMeanSquaredError",
- "$ref": "#/definitions/RegressionPrimaryMetrics"
- },
- "trainingSettings": {
- "description": "Inputs for training phase for an AutoML Job.",
- "$ref": "#/definitions/RegressionTrainingSettings",
- "x-nullable": true
- }
+ "x-nullable": true
+ }
+ },
+ "x-ms-client-name": "OnlineEndpointProperties",
+ "additionalProperties": false
+ },
+ "OnlineEndpointTrackedResource": {
+ "required": [
+ "location",
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/TrackedResource"
+ }
+ ],
+ "properties": {
+ "identity": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentity"
},
- "x-ms-discriminator-value": "Regression",
- "additionalProperties": false
- },
- "RegressionModels": {
- "description": "Enum for all Regression models supported by AutoML.",
- "enum": [
- "ElasticNet",
- "GradientBoosting",
- "DecisionTree",
- "KNN",
- "LassoLars",
- "SGD",
- "RandomForest",
- "ExtremeRandomTrees",
- "LightGBM",
- "XGBoostRegressor"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "RegressionModels",
- "modelAsString": true,
- "values": [
- {
- "value": "ElasticNet",
- "description": "Elastic net is a popular type of regularized linear regression that combines two popular penalties, specifically the L1 and L2 penalty functions."
- },
- {
- "value": "GradientBoosting",
- "description": "The technique of transiting week learners into a strong learner is called Boosting. The gradient boosting algorithm process works on this theory of execution."
- },
- {
- "value": "DecisionTree",
- "description": "Decision Trees are a non-parametric supervised learning method used for both classification and regression tasks.\nThe goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features."
- },
- {
- "value": "KNN",
- "description": "K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new datapoints\nwhich further means that the new data point will be assigned a value based on how closely it matches the points in the training set."
- },
- {
- "value": "LassoLars",
- "description": "Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an L1 prior as regularizer."
- },
- {
- "value": "SGD",
- "description": "SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning applications\nto find the model parameters that correspond to the best fit between predicted and actual outputs.\nIt's an inexact but powerful technique."
- },
- {
- "value": "RandomForest",
- "description": "Random forest is a supervised learning algorithm.\nThe \"forest\" it builds, is an ensemble of decision trees, usually trained with the 'bagging' method.\nThe general idea of the bagging method is that a combination of learning models increases the overall result."
- },
- {
- "value": "ExtremeRandomTrees",
- "description": "Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many decision trees. It is related to the widely used random forest algorithm."
- },
- {
- "value": "LightGBM",
- "description": "LightGBM is a gradient boosting framework that uses tree based learning algorithms."
- },
- {
- "value": "XGBoostRegressor",
- "description": "XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model using ensemble of base learners."
- }
- ]
+ "kind": {
+ "description": "Metadata used by portal/tooling/etc to render different UX experiences for resources of the same type.",
+ "type": "string"
},
- "additionalProperties": false
- },
- "RegressionPrimaryMetrics": {
- "description": "Primary metrics for Regression task.",
- "enum": [
- "SpearmanCorrelation",
- "NormalizedRootMeanSquaredError",
- "R2Score",
- "NormalizedMeanAbsoluteError"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "RegressionPrimaryMetrics",
- "modelAsString": true,
- "values": [
- {
- "value": "SpearmanCorrelation",
- "description": "The Spearman's rank coefficient of correlation is a nonparametric measure of rank correlation."
- },
- {
- "value": "NormalizedRootMeanSquaredError",
- "description": "The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between models with different scales."
- },
- {
- "value": "R2Score",
- "description": "The R2 score is one of the performance evaluation measures for forecasting-based machine learning models."
- },
- {
- "value": "NormalizedMeanAbsoluteError",
- "description": "The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute Error (MAE) of (time) series with different scales."
- }
- ]
+ "properties": {
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/OnlineEndpoint"
},
- "additionalProperties": false
+ "sku": {
+ "description": "Sku details required for ARM contract for Autoscaling.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Sku"
+ }
},
- "RegressionTrainingSettings": {
- "description": "Regression Training related configuration.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/TrainingSettings"
- }
- ],
- "properties": {
- "allowedTrainingAlgorithms": {
- "description": "Allowed models for regression task.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/RegressionModels"
- },
- "x-nullable": true
- },
- "blockedTrainingAlgorithms": {
- "description": "Blocked models for regression task.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/RegressionModels"
- },
- "x-nullable": true
+ "x-ms-client-name": "OnlineEndpoint",
+ "additionalProperties": false
+ },
+ "OnlineEndpointTrackedResourceArmPaginatedResult": {
+ "description": "A paginated list of OnlineEndpoint entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of OnlineEndpoint objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type OnlineEndpoint.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/OnlineEndpointTrackedResource"
}
- },
- "additionalProperties": false
+ }
},
- "ResourceBase": {
- "type": "object",
- "properties": {
- "description": {
- "description": "The asset description text.",
+ "additionalProperties": false
+ },
+ "OnlineInferenceConfiguration": {
+ "description": "Online inference configuration options.",
+ "type": "object",
+ "properties": {
+ "configurations": {
+ "description": "Additional configurations",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "properties": {
- "description": "The asset property dictionary.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ "x-nullable": true
+ },
+ "entryScript": {
+ "description": "Entry script or command to invoke.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "livenessRoute": {
+ "description": "The route to check the liveness of the inference server container.",
+ "$ref": "#/definitions/Route",
+ "x-nullable": true
+ },
+ "readinessRoute": {
+ "description": "The route to check the readiness of the inference server container.",
+ "$ref": "#/definitions/Route",
+ "x-nullable": true
+ },
+ "scoringRoute": {
+ "description": "The port to send the scoring requests to, within the inference server container.",
+ "$ref": "#/definitions/Route",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "OnlineRequestSettings": {
+ "description": "Online deployment scoring requests configuration.",
+ "type": "object",
+ "properties": {
+ "maxConcurrentRequestsPerInstance": {
+ "format": "int32",
+ "description": "The number of maximum concurrent requests per node allowed per deployment. Defaults to 1.",
+ "default": 1,
+ "type": "integer"
+ },
+ "maxQueueWait": {
+ "format": "duration",
+ "description": "The maximum amount of time a request will stay in the queue in ISO 8601 format.\r\nDefaults to 500ms.",
+ "default": "PT0.5S",
+ "type": "string"
+ },
+ "requestTimeout": {
+ "format": "duration",
+ "description": "The scoring timeout in ISO 8601 format.\r\nDefaults to 5000ms.",
+ "default": "PT5S",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ },
+ "OnlineScaleSettings": {
+ "description": "Online deployment scaling configuration.",
+ "required": [
+ "scaleType"
+ ],
+ "type": "object",
+ "properties": {
+ "scaleType": {
+ "description": "[Required] Type of deployment scaling algorithm",
+ "$ref": "#/definitions/ScaleType"
+ }
+ },
+ "discriminator": "scaleType"
+ },
+ "OperatingSystemType": {
+ "description": "The type of operating system.",
+ "enum": [
+ "Linux",
+ "Windows"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "OperatingSystemType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Linux"
},
- "tags": {
- "description": "Tag dictionary. Tags can be added, removed, and updated.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
+ {
+ "value": "Windows"
}
- },
- "additionalProperties": false
+ ]
},
- "ResourceConfiguration": {
- "type": "object",
- "properties": {
- "instanceCount": {
- "format": "int32",
- "description": "Optional number of instances or nodes used by the compute target.",
- "default": 1,
- "type": "integer",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "additionalProperties": false
+ },
+ "OrderString": {
+ "enum": [
+ "CreatedAtDesc",
+ "CreatedAtAsc",
+ "UpdatedAtDesc",
+ "UpdatedAtAsc"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "OrderString",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "CreatedAtDesc"
},
- "instanceType": {
- "description": "Optional type of VM used as supported by the compute target.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "CreatedAtAsc"
},
- "locations": {
- "description": "Locations where the job can run.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "UpdatedAtDesc"
},
- "properties": {
- "description": "Additional properties bag.",
- "type": "object",
- "additionalProperties": {
- "type": "object",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "UpdatedAtAsc"
}
- },
- "additionalProperties": false
+ ]
},
- "Route": {
- "required": [
- "path",
- "port"
- ],
- "type": "object",
- "properties": {
- "path": {
- "description": "[Required] The path for the route.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string"
+ "additionalProperties": false
+ },
+ "OutputDeliveryMode": {
+ "description": "Output data delivery mode enums.",
+ "enum": [
+ "ReadWriteMount",
+ "Upload",
+ "Direct"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "OutputDeliveryMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "ReadWriteMount"
},
- "port": {
- "format": "int32",
- "description": "[Required] The port for the route.",
- "type": "integer"
+ {
+ "value": "Upload"
+ },
+ {
+ "value": "Direct"
}
- },
- "additionalProperties": false
+ ]
},
- "SamplingAlgorithm": {
- "description": "The Sampling Algorithm used to generate hyperparameter values, along with properties to\r\nconfigure the algorithm",
- "required": [
- "samplingAlgorithmType"
- ],
- "type": "object",
- "properties": {
- "samplingAlgorithmType": {
- "description": "[Required] The algorithm used for generating hyperparameter values, along with configuration properties",
- "$ref": "#/definitions/SamplingAlgorithmType"
- }
- },
- "discriminator": "samplingAlgorithmType"
- },
- "SamplingAlgorithmType": {
- "enum": [
- "Grid",
- "Random",
- "Bayesian"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "SamplingAlgorithmType",
- "modelAsString": true,
- "values": [
- {
- "value": "Grid"
- },
- {
- "value": "Random"
- },
- {
- "value": "Bayesian"
- }
- ]
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "OutputPathAssetReference": {
+ "description": "Reference to an asset via its path in a job output.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetReferenceBase"
+ }
+ ],
+ "properties": {
+ "jobId": {
+ "description": "ARM resource ID of the job.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "path": {
+ "description": "The path of the file/directory in the job output.",
+ "type": "string",
+ "x-nullable": true
+ }
},
- "SasDatastoreCredentials": {
- "description": "SAS datastore credentials configuration.",
- "required": [
- "secrets"
- ],
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "OutputPath",
+ "additionalProperties": false
+ },
+ "PackageBuildState": {
+ "description": "Package build state returned in package response.",
+ "enum": [
+ "NotStarted",
+ "Running",
+ "Succeeded",
+ "Failed"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "PackageBuildState",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/DatastoreCredentials"
- }
- ],
- "properties": {
- "secrets": {
- "description": "[Required] Storage container secrets.",
- "$ref": "#/definitions/SasDatastoreSecrets",
- "x-ms-mutability": [
- "create",
- "update"
- ],
- "x-ms-secret": true
+ "value": "NotStarted"
+ },
+ {
+ "value": "Running"
+ },
+ {
+ "value": "Succeeded"
+ },
+ {
+ "value": "Failed"
}
- },
- "x-ms-discriminator-value": "Sas",
- "additionalProperties": false
+ ]
},
- "SasDatastoreSecrets": {
- "description": "Datastore SAS secrets.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "PackageInputDeliveryMode": {
+ "description": "Mounting type of the model or the inputs",
+ "enum": [
+ "ReadOnlyMount",
+ "Download"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "PackageInputDeliveryMode",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/DatastoreSecrets"
- }
- ],
- "properties": {
- "sasToken": {
- "description": "Storage container SAS token.",
- "type": "string",
- "x-nullable": true
+ "value": "ReadOnlyMount"
+ },
+ {
+ "value": "Download"
}
- },
- "x-ms-discriminator-value": "Sas",
- "additionalProperties": false
+ ]
},
- "ScaleType": {
- "enum": [
- "Default",
- "TargetUtilization"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ScaleType",
- "modelAsString": true,
- "values": [
- {
- "value": "Default"
- },
- {
- "value": "TargetUtilization"
- }
- ]
- },
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "PackageInputPathBase": {
+ "required": [
+ "inputPathType"
+ ],
+ "type": "object",
+ "properties": {
+ "inputPathType": {
+ "description": "[Required] Input path type for package inputs.",
+ "$ref": "#/definitions/InputPathType"
+ }
},
- "Schedule": {
- "description": "Base definition of a schedule",
- "required": [
- "action",
- "trigger"
- ],
- "type": "object",
- "allOf": [
+ "discriminator": "inputPathType"
+ },
+ "PackageInputPathId": {
+ "description": "Package input path specified with a resource id.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PackageInputPathBase"
+ }
+ ],
+ "properties": {
+ "resourceId": {
+ "description": "Input resource id.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "PathId",
+ "additionalProperties": false
+ },
+ "PackageInputPathUrl": {
+ "description": "Package input path specified as an url.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PackageInputPathBase"
+ }
+ ],
+ "properties": {
+ "url": {
+ "description": "Input path url.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Url",
+ "additionalProperties": false
+ },
+ "PackageInputPathVersion": {
+ "description": "Package input path specified with name and version.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PackageInputPathBase"
+ }
+ ],
+ "properties": {
+ "resourceName": {
+ "description": "Input resource name.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "resourceVersion": {
+ "description": "Input resource version.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "PathVersion",
+ "additionalProperties": false
+ },
+ "PackageInputType": {
+ "description": "Type of the inputs.",
+ "enum": [
+ "UriFile",
+ "UriFolder"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "PackageInputType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "UriFile"
+ },
{
- "$ref": "#/definitions/ResourceBase"
+ "value": "UriFolder"
}
- ],
- "properties": {
- "action": {
- "description": "[Required] Specifies the action of the schedule",
- "$ref": "#/definitions/ScheduleActionBase",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- },
- "displayName": {
- "description": "Display name of schedule.",
+ ]
+ },
+ "additionalProperties": false
+ },
+ "PackageRequest": {
+ "description": "Model package operation request properties.",
+ "required": [
+ "inferencingServer",
+ "targetEnvironmentName"
+ ],
+ "type": "object",
+ "properties": {
+ "baseEnvironmentSource": {
+ "description": "Base environment to start with.",
+ "$ref": "#/definitions/BaseEnvironmentSource",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "environmentVariables": {
+ "description": "Collection of environment variables.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
"x-nullable": true
},
- "isEnabled": {
- "description": "Is the schedule enabled?",
- "default": true,
- "type": "boolean",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- },
- "provisioningState": {
- "description": "Provisioning state for the schedule.",
- "$ref": "#/definitions/ScheduleProvisioningStatus",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
- },
- "trigger": {
- "description": "[Required] Specifies the trigger details",
- "$ref": "#/definitions/TriggerBase",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "x-ms-client-name": "ScheduleProperties",
- "additionalProperties": false
- },
- "ScheduleActionBase": {
- "required": [
- "actionType"
- ],
- "type": "object",
- "properties": {
- "actionType": {
- "description": "[Required] Specifies the action type of the schedule",
- "$ref": "#/definitions/ScheduleActionType",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "discriminator": "actionType"
- },
- "ScheduleActionType": {
- "enum": [
- "CreateJob",
- "InvokeBatchEndpoint"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ScheduleActionType",
- "modelAsString": true,
- "values": [
- {
- "value": "CreateJob"
- },
- {
- "value": "InvokeBatchEndpoint"
- }
- ]
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "ScheduleListViewType": {
- "enum": [
- "EnabledOnly",
- "DisabledOnly",
- "All"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ScheduleListViewType",
- "modelAsString": true,
- "values": [
- {
- "value": "EnabledOnly"
- },
- {
- "value": "DisabledOnly"
- },
- {
- "value": "All"
- }
+ "inferencingServer": {
+ "description": "[Required] Inferencing server configurations.",
+ "$ref": "#/definitions/InferencingServer",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
- },
- "ScheduleProvisioningStatus": {
- "enum": [
- "Creating",
- "Updating",
- "Deleting",
- "Succeeded",
- "Failed",
- "Canceled"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ScheduleProvisioningStatus",
- "modelAsString": true,
- "values": [
- {
- "value": "Creating"
- },
- {
- "value": "Updating"
- },
- {
- "value": "Deleting"
- },
- {
- "value": "Succeeded"
- },
- {
- "value": "Failed"
- },
- {
- "value": "Canceled"
- }
- ]
+ "inputs": {
+ "description": "Collection of inputs.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ModelPackageInput"
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true,
+ "x-ms-identifiers": []
},
- "additionalProperties": false
- },
- "ScheduleResource": {
- "description": "Azure Resource Manager resource envelope.",
- "required": [
- "properties"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
- }
- ],
- "properties": {
- "properties": {
- "description": "[Required] Additional attributes of the entity.",
- "$ref": "#/definitions/Schedule"
- }
+ "modelConfiguration": {
+ "description": "Model configuration including the mount mode.",
+ "$ref": "#/definitions/ModelConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "x-ms-client-name": "Schedule",
- "additionalProperties": false
- },
- "ScheduleResourceArmPaginatedResult": {
- "description": "A paginated list of Schedule entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of Schedule objects. If null, there are no additional pages.",
- "type": "string"
+ "tags": {
+ "description": "Tag dictionary. Tags can be added, removed, and updated.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
},
- "value": {
- "description": "An array of objects of type Schedule.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/ScheduleResource"
- }
- }
- },
- "additionalProperties": false
- },
- "Seasonality": {
- "description": "Forecasting seasonality.",
- "required": [
- "mode"
- ],
- "type": "object",
- "properties": {
- "mode": {
- "description": "[Required] Seasonality mode.",
- "$ref": "#/definitions/SeasonalityMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "mode"
- },
- "SeasonalityMode": {
- "description": "Forecasting seasonality mode.",
- "enum": [
- "Auto",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "SeasonalityMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Seasonality to be determined automatically."
- },
- {
- "value": "Custom",
- "description": "Use the custom seasonality value."
- }
- ]
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "SecretsType": {
- "description": "Enum to determine the datastore secrets type.",
- "enum": [
- "AccountKey",
- "Certificate",
- "Sas",
- "ServicePrincipal",
- "KerberosPassword",
- "KerberosKeytab"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "SecretsType",
- "modelAsString": true,
- "values": [
- {
- "value": "AccountKey"
- },
- {
- "value": "Certificate"
- },
- {
- "value": "Sas"
- },
- {
- "value": "ServicePrincipal"
- },
- {
- "value": "KerberosPassword"
- },
- {
- "value": "KerberosKeytab"
- }
+ "targetEnvironmentName": {
+ "description": "[Required] Target environment name to be generated by package.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
- },
- "ServiceDataAccessAuthIdentity": {
- "enum": [
- "None",
- "WorkspaceSystemAssignedIdentity",
- "WorkspaceUserAssignedIdentity"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ServiceDataAccessAuthIdentity",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "Do not use any identity for service data access."
- },
- {
- "value": "WorkspaceSystemAssignedIdentity",
- "description": "Use the system assigned managed identity of the Workspace to authenticate service data access."
- },
- {
- "value": "WorkspaceUserAssignedIdentity",
- "description": "Use the user assigned managed identity of the Workspace to authenticate service data access."
- }
+ "targetEnvironmentVersion": {
+ "description": "Target environment version to be generated by package.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "PackageResponse": {
+ "description": "Package response returned after async package operation completes successfully.",
+ "type": "object",
+ "properties": {
+ "baseEnvironmentSource": {
+ "description": "Base environment to start with.",
+ "$ref": "#/definitions/BaseEnvironmentSource",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "buildId": {
+ "description": "Build id of the image build operation.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "buildState": {
+ "description": "Build state of the image build operation.",
+ "$ref": "#/definitions/PackageBuildState",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
]
},
- "additionalProperties": false
- },
- "ServicePrincipalDatastoreCredentials": {
- "description": "Service Principal datastore credentials configuration.",
- "required": [
- "clientId",
- "secrets",
- "tenantId"
- ],
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/DatastoreCredentials"
- }
- ],
- "properties": {
- "authorityUrl": {
- "description": "Authority URL used for authentication.",
+ "environmentVariables": {
+ "description": "Collection of environment variables.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "clientId": {
- "format": "uuid",
- "description": "[Required] Service principal client ID.",
- "type": "string"
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "inferencingServer": {
+ "description": "Inferencing server configurations.",
+ "$ref": "#/definitions/InferencingServer",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "inputs": {
+ "description": "Collection of inputs.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ModelPackageInput"
},
- "resourceUrl": {
- "description": "Resource the service principal has access to.",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ },
+ "logUrl": {
+ "description": "Log url of the image build operation.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "modelConfiguration": {
+ "description": "Model configuration including the mount mode.",
+ "$ref": "#/definitions/ModelConfiguration",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "tags": {
+ "description": "Tag dictionary. Tags can be added, removed, and updated.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "secrets": {
- "description": "[Required] Service principal secrets.",
- "$ref": "#/definitions/ServicePrincipalDatastoreSecrets",
- "x-ms-mutability": [
- "create",
- "update"
- ],
- "x-ms-secret": true
- },
- "tenantId": {
- "format": "uuid",
- "description": "[Required] ID of the tenant to which the service principal belongs.",
- "type": "string"
- }
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "targetEnvironmentId": {
+ "description": "Asset ID of the target environment created by package operation.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "targetEnvironmentName": {
+ "description": "Target environment name to be generated by package.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
},
- "x-ms-discriminator-value": "ServicePrincipal",
- "additionalProperties": false
+ "targetEnvironmentVersion": {
+ "description": "Target environment version to be generated by package.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "ServicePrincipalDatastoreSecrets": {
- "description": "Datastore Service Principal secrets.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/DatastoreSecrets"
+ "additionalProperties": false
+ },
+ "PartialBatchDeployment": {
+ "description": "Mutable batch inference settings per deployment.",
+ "type": "object",
+ "properties": {
+ "description": {
+ "description": "Description of the endpoint deployment.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialBatchDeploymentPartialMinimalTrackedResourceWithProperties": {
+ "description": "Strictly used in update requests.",
+ "type": "object",
+ "properties": {
+ "properties": {
+ "description": "Additional attributes of the entity.",
+ "$ref": "#/definitions/PartialBatchDeployment"
+ },
+ "tags": {
+ "description": "Resource tags.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
}
- ],
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialJobBase": {
+ "description": "Mutable base definition for a job.",
+ "type": "object",
+ "properties": {
+ "partialNotificationSetting": {
+ "description": "Mutable notification setting for the job",
+ "$ref": "#/definitions/PartialNotificationSetting",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialJobBasePartialResource": {
+ "description": "Azure Resource Manager resource envelope strictly used in update requests.",
+ "type": "object",
+ "properties": {
"properties": {
- "clientSecret": {
- "description": "Service principal secret.",
+ "description": "Additional attributes of the entity.",
+ "$ref": "#/definitions/PartialJobBase"
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialManagedServiceIdentity": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "type": "object",
+ "properties": {
+ "type": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "$ref": "../../../../../common-types/resource-management/v3/managedidentity.json#/definitions/ManagedServiceIdentityType"
+ },
+ "userAssignedIdentities": {
+ "description": "The set of user assigned identities associated with the resource. The userAssignedIdentities dictionary keys will be ARM resource ids in the form: '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identityName}. The dictionary values can be empty objects ({}) in requests.",
+ "type": "object",
+ "additionalProperties": {
+ "$ref": "#/definitions/PartialUserAssignedIdentity"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialMinimalTrackedResource": {
+ "description": "Strictly used in update requests.",
+ "type": "object",
+ "properties": {
+ "tags": {
+ "description": "Resource tags.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
}
- },
- "x-ms-discriminator-value": "ServicePrincipal",
- "additionalProperties": false
- },
- "ShortSeriesHandlingConfiguration": {
- "description": "The parameter defining how if AutoML should handle short time series.",
- "enum": [
- "None",
- "Auto",
- "Pad",
- "Drop"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ShortSeriesHandlingConfiguration",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "Represents no/null value."
- },
- {
- "value": "Auto",
- "description": "Short series will be padded if there are no long series, otherwise short series will be dropped."
- },
- {
- "value": "Pad",
- "description": "All the short series will be padded."
- },
- {
- "value": "Drop",
- "description": "All the short series will be dropped."
- }
- ]
- },
- "additionalProperties": false
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialMinimalTrackedResourceWithIdentity": {
+ "description": "Strictly used in update requests.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PartialMinimalTrackedResource"
+ }
+ ],
+ "properties": {
+ "identity": {
+ "description": "Managed service identity (system assigned and/or user assigned identities)",
+ "$ref": "#/definitions/PartialManagedServiceIdentity"
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialMinimalTrackedResourceWithSku": {
+ "description": "Strictly used in update requests.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PartialMinimalTrackedResource"
+ }
+ ],
+ "properties": {
+ "sku": {
+ "description": "Sku details required for ARM contract for Autoscaling.",
+ "$ref": "#/definitions/PartialSku"
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialNotificationSetting": {
+ "description": "Mutable configuration for notification.",
+ "type": "object",
+ "properties": {
+ "webhooks": {
+ "description": "Send webhook callback to a service. Key is a user-provided name for the webhook.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Webhook base",
+ "$ref": "#/definitions/Webhook",
+ "x-nullable": true
+ },
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialSku": {
+ "description": "Common SKU definition.",
+ "type": "object",
+ "properties": {
+ "capacity": {
+ "format": "int32",
+ "description": "If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.",
+ "type": "integer"
+ },
+ "family": {
+ "description": "If the service has different generations of hardware, for the same SKU, then that can be captured here.",
+ "type": "string"
+ },
+ "name": {
+ "description": "The name of the SKU. Ex - P3. It is typically a letter+number code.",
+ "type": "string"
+ },
+ "size": {
+ "description": "The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.",
+ "type": "string"
+ },
+ "tier": {
+ "description": "This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/SkuTier"
+ }
+ },
+ "additionalProperties": false
+ },
+ "PartialUserAssignedIdentity": {
+ "type": "object",
+ "additionalProperties": false
+ },
+ "PendingUploadCredentialDto": {
+ "required": [
+ "credentialType"
+ ],
+ "type": "object",
+ "properties": {
+ "credentialType": {
+ "description": "[Required] Credential type used to authentication with storage.",
+ "$ref": "#/definitions/PendingUploadCredentialType"
+ }
+ },
+ "discriminator": "credentialType"
+ },
+ "PendingUploadCredentialType": {
+ "description": "Enum to determine the PendingUpload credentials type.",
+ "enum": [
+ "SAS"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "PendingUploadCredentialType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "SAS"
+ }
+ ]
},
- "SkuCapacity": {
- "description": "SKU capacity information",
- "type": "object",
- "properties": {
- "default": {
- "format": "int32",
- "description": "Gets or sets the default capacity.",
- "default": 0,
- "type": "integer"
- },
- "maximum": {
- "format": "int32",
- "description": "Gets or sets the maximum.",
- "default": 0,
- "type": "integer"
- },
- "minimum": {
- "format": "int32",
- "description": "Gets or sets the minimum.",
- "default": 0,
- "type": "integer"
+ "additionalProperties": false
+ },
+ "PendingUploadRequestDto": {
+ "type": "object",
+ "properties": {
+ "pendingUploadId": {
+ "description": "If PendingUploadId = null then random guid will be used.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "pendingUploadType": {
+ "description": "TemporaryBlobReference is the only supported type",
+ "default": "TemporaryBlobReference",
+ "$ref": "#/definitions/PendingUploadType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "PendingUploadResponseDto": {
+ "type": "object",
+ "properties": {
+ "blobReferenceForConsumption": {
+ "description": "Container level read, write, list SAS",
+ "$ref": "#/definitions/BlobReferenceForConsumptionDto",
+ "x-nullable": true
+ },
+ "pendingUploadId": {
+ "description": "ID for this upload request",
+ "type": "string",
+ "x-nullable": true
+ },
+ "pendingUploadType": {
+ "description": "TemporaryBlobReference is the only supported type",
+ "default": "TemporaryBlobReference",
+ "$ref": "#/definitions/PendingUploadType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "PendingUploadType": {
+ "description": "Type of storage to use for the pending upload location",
+ "enum": [
+ "None",
+ "TemporaryBlobReference"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "PendingUploadType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None"
},
- "scaleType": {
- "description": "Gets or sets the type of the scale.",
- "default": "Automatic",
- "$ref": "#/definitions/SkuScaleType"
+ {
+ "value": "TemporaryBlobReference"
}
- },
- "additionalProperties": false
+ ]
},
- "SkuResource": {
- "description": "Fulfills ARM Contract requirement to list all available SKUS for a resource.",
- "type": "object",
- "properties": {
- "capacity": {
- "description": "Gets or sets the Sku Capacity.",
- "$ref": "#/definitions/SkuCapacity",
+ "additionalProperties": false
+ },
+ "PipelineJob": {
+ "description": "Pipeline Job definition: defines generic to MFE attributes.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobBase"
+ }
+ ],
+ "properties": {
+ "inputs": {
+ "description": "Inputs for the pipeline job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Command job definition.",
+ "$ref": "#/definitions/JobInput",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jobs": {
+ "description": "Jobs construct the Pipeline Job.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "object",
"x-nullable": true
},
- "resourceType": {
- "description": "The resource type name.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "outputs": {
+ "description": "Outputs for the pipeline job",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Job output definition container information on where to find job output/logs.",
+ "$ref": "#/definitions/JobOutput",
"x-nullable": true
},
- "sku": {
- "description": "Gets or sets the Sku.",
- "$ref": "#/definitions/SkuSetting",
- "x-nullable": true
- }
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "SkuResourceArmPaginatedResult": {
- "description": "A paginated list of SkuResource entities.",
- "type": "object",
- "properties": {
- "nextLink": {
- "description": "The link to the next page of SkuResource objects. If null, there are no additional pages.",
- "type": "string"
- },
- "value": {
- "description": "An array of objects of type SkuResource.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/SkuResource"
- },
- "x-ms-identifiers": []
- }
+ "settings": {
+ "description": "Pipeline settings, for things like ContinueRunOnStepFailure etc.",
+ "type": "object",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
+ "sourceJobId": {
+ "description": "ARM resource ID of source job.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "SkuScaleType": {
- "description": "Node scaling setting for the compute sku.",
- "enum": [
- "Automatic",
- "Manual",
- "None"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "SkuScaleType",
- "modelAsString": true,
- "values": [
- {
- "value": "Automatic",
- "description": "Automatically scales node count."
- },
- {
- "value": "Manual",
- "description": "Node count scaled upon user request."
- },
- {
- "value": "None",
- "description": "Fixed set of nodes."
- }
+ "x-ms-discriminator-value": "Pipeline",
+ "additionalProperties": false
+ },
+ "PredictionDriftMetricThresholdBase": {
+ "required": [
+ "dataType"
+ ],
+ "type": "object",
+ "properties": {
+ "dataType": {
+ "description": "[Required] Specifies the data type of the metric threshold.",
+ "$ref": "#/definitions/MonitoringFeatureDataType",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "threshold": {
+ "description": "The threshold value. If null, a default value will be set depending on the selected metric.",
+ "$ref": "#/definitions/MonitoringThreshold",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "SkuSetting": {
- "description": "SkuSetting fulfills the need for stripped down SKU info in ARM contract.",
- "required": [
- "name"
- ],
- "type": "object",
- "properties": {
- "name": {
- "description": "[Required] The name of the SKU. Ex - P3. It is typically a letter+number code.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string"
+ "discriminator": "dataType"
+ },
+ "PredictionDriftMonitoringSignal": {
+ "required": [
+ "baselineData",
+ "metricThresholds",
+ "modelType",
+ "targetData"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringSignalBase"
+ }
+ ],
+ "properties": {
+ "baselineData": {
+ "description": "[Required] The data to calculate drift against.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "metricThresholds": {
+ "description": "[Required] A list of metrics to calculate and their associated thresholds.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/PredictionDriftMetricThresholdBase"
},
- "tier": {
- "description": "This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.",
- "default": "Basic",
- "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/SkuTier"
- }
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-ms-identifiers": []
+ },
+ "modelType": {
+ "description": "[Required] The type of the model monitored.",
+ "$ref": "#/definitions/MonitoringModelType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
},
- "additionalProperties": false
+ "targetData": {
+ "description": "[Required] The data which drift will be calculatd for.",
+ "$ref": "#/definitions/MonitoringInputData",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "SparkJob": {
- "description": "Spark job definition.",
- "required": [
- "codeId",
- "entry"
- ],
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "PredictionDrift",
+ "additionalProperties": false
+ },
+ "ProbeSettings": {
+ "description": "Deployment container liveness/readiness probe configuration.",
+ "type": "object",
+ "properties": {
+ "failureThreshold": {
+ "format": "int32",
+ "description": "The number of failures to allow before returning an unhealthy status.",
+ "default": 30,
+ "type": "integer"
+ },
+ "initialDelay": {
+ "format": "duration",
+ "description": "The delay before the first probe in ISO 8601 format.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "period": {
+ "format": "duration",
+ "description": "The length of time between probes in ISO 8601 format.",
+ "default": "PT10S",
+ "type": "string"
+ },
+ "successThreshold": {
+ "format": "int32",
+ "description": "The number of successful probes before returning a healthy status.",
+ "default": 1,
+ "type": "integer"
+ },
+ "timeout": {
+ "format": "duration",
+ "description": "The probe timeout in ISO 8601 format.",
+ "default": "PT2S",
+ "type": "string"
+ }
+ },
+ "additionalProperties": false
+ },
+ "ProgressMetrics": {
+ "description": "Progress metrics definition",
+ "type": "object",
+ "properties": {
+ "completedDatapointCount": {
+ "format": "int64",
+ "description": "The completed datapoint count.",
+ "type": "integer",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "incrementalDataLastRefreshDateTime": {
+ "format": "date-time",
+ "description": "The time of last successful incremental data refresh in UTC.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "skippedDatapointCount": {
+ "format": "int64",
+ "description": "The skipped datapoint count.",
+ "type": "integer",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "totalDatapointCount": {
+ "format": "int64",
+ "description": "The total datapoint count.",
+ "type": "integer",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ProtectionLevel": {
+ "description": "Protection level associated with the Intellectual Property.",
+ "enum": [
+ "All",
+ "None"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ProtectionLevel",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/JobBase"
- }
- ],
- "properties": {
- "archives": {
- "description": "Archive files used in the job.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "args": {
- "description": "Arguments for the job.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "codeId": {
- "description": "[Required] ARM resource ID of the code asset.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "conf": {
- "description": "Spark configured properties.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "entry": {
- "description": "[Required] The entry to execute on startup of the job.",
- "$ref": "#/definitions/SparkJobEntry",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "environmentId": {
- "description": "The ARM resource ID of the Environment specification for the job.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "files": {
- "description": "Files used in the job.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "inputs": {
- "description": "Mapping of input data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Command job definition.",
- "$ref": "#/definitions/JobInput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "jars": {
- "description": "Jar files used in the job.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "outputs": {
- "description": "Mapping of output data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Job output definition container information on where to find job output/logs.",
- "$ref": "#/definitions/JobOutput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "pyFiles": {
- "description": "Python files used in the job.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "value": "All",
+ "description": "All means Intellectual Property is fully protected."
},
- "queueSettings": {
- "description": "Queue settings for the job",
- "$ref": "#/definitions/QueueSettings",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "None",
+ "description": "None means it is not an Intellectual Property."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "PublicNetworkAccessType": {
+ "description": "Enum to determine whether PublicNetworkAccess is Enabled or Disabled.",
+ "enum": [
+ "Enabled",
+ "Disabled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "PublicNetworkAccessType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Enabled"
},
- "resources": {
- "description": "Compute Resource configuration for the job.",
- "$ref": "#/definitions/SparkResourceConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Disabled"
}
- },
- "x-ms-discriminator-value": "Spark",
- "additionalProperties": false
+ ]
},
- "SparkJobEntry": {
- "description": "Spark job entry point definition.",
- "required": [
- "sparkJobEntryType"
- ],
- "type": "object",
- "properties": {
- "sparkJobEntryType": {
- "description": "[Required] Type of the job's entry point.",
- "$ref": "#/definitions/SparkJobEntryType",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "sparkJobEntryType"
- },
- "SparkJobEntryType": {
- "enum": [
- "SparkJobPythonEntry",
- "SparkJobScalaEntry"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "SparkJobEntryType",
- "modelAsString": true,
- "values": [
- {
- "value": "SparkJobPythonEntry"
- },
- {
- "value": "SparkJobScalaEntry"
- }
+ "additionalProperties": false
+ },
+ "PyTorch": {
+ "description": "PyTorch distribution configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DistributionConfiguration"
+ }
+ ],
+ "properties": {
+ "processCountPerInstance": {
+ "format": "int32",
+ "description": "Number of processes per node.",
+ "type": "integer",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "PyTorch",
+ "additionalProperties": false
+ },
+ "QueueSettings": {
+ "type": "object",
+ "properties": {
+ "jobTier": {
+ "description": "Enum to determine the job tier.",
+ "default": "Standard",
+ "$ref": "#/definitions/JobTier",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
},
- "additionalProperties": false
+ "priority": {
+ "format": "int32",
+ "description": "Controls the priority of the job on a compute.",
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "SparkJobPythonEntry": {
- "required": [
- "file"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "RandomSamplingAlgorithm": {
+ "description": "Defines a Sampling Algorithm that generates values randomly",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/SamplingAlgorithm"
+ }
+ ],
+ "properties": {
+ "logbase": {
+ "description": "An optional positive number or e in string format to be used as base for log based random sampling",
+ "type": "string",
+ "x-nullable": true
+ },
+ "rule": {
+ "description": "The specific type of random algorithm",
+ "default": "Random",
+ "$ref": "#/definitions/RandomSamplingAlgorithmRule"
+ },
+ "seed": {
+ "format": "int32",
+ "description": "An optional integer to use as the seed for random number generation",
+ "type": "integer",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Random",
+ "additionalProperties": false
+ },
+ "RandomSamplingAlgorithmRule": {
+ "description": "The specific type of random algorithm",
+ "enum": [
+ "Random",
+ "Sobol"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "RandomSamplingAlgorithmRule",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/SparkJobEntry"
- }
- ],
- "properties": {
- "file": {
- "description": "[Required] Relative python file path for job entry point.",
- "minLength": 1,
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "example": "train.py",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "value": "Random"
+ },
+ {
+ "value": "Sobol"
}
- },
- "x-ms-discriminator-value": "SparkJobPythonEntry",
- "additionalProperties": false
+ ]
},
- "SparkJobScalaEntry": {
- "required": [
- "className"
- ],
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "Ray": {
+ "description": "Ray distribution configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DistributionConfiguration"
+ }
+ ],
+ "properties": {
+ "address": {
+ "description": "The address of Ray head node.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "dashboardPort": {
+ "format": "int32",
+ "description": "The port to bind the dashboard server to.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "headNodeAdditionalArgs": {
+ "description": "Additional arguments passed to ray start in head node.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "includeDashboard": {
+ "description": "Provide this argument to start the Ray dashboard GUI.",
+ "type": "boolean",
+ "x-nullable": true
+ },
+ "port": {
+ "format": "int32",
+ "description": "The port of the head ray process.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "workerNodeAdditionalArgs": {
+ "description": "Additional arguments passed to ray start in worker node.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Ray",
+ "additionalProperties": false
+ },
+ "RecurrenceFrequency": {
+ "description": "Enum to describe the frequency of a recurrence schedule",
+ "enum": [
+ "Minute",
+ "Hour",
+ "Day",
+ "Week",
+ "Month"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "RecurrenceFrequency",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Minute",
+ "description": "Minute frequency"
+ },
+ {
+ "value": "Hour",
+ "description": "Hour frequency"
+ },
+ {
+ "value": "Day",
+ "description": "Day frequency"
+ },
+ {
+ "value": "Week",
+ "description": "Week frequency"
+ },
{
- "$ref": "#/definitions/SparkJobEntry"
+ "value": "Month",
+ "description": "Month frequency"
}
- ],
- "properties": {
- "className": {
- "description": "[Required] Scala class name used as entry point.",
- "minLength": 1,
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "example": "microsoft.aml.sample.myapp",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ ]
+ },
+ "additionalProperties": false
+ },
+ "RecurrenceSchedule": {
+ "required": [
+ "hours",
+ "minutes"
+ ],
+ "type": "object",
+ "properties": {
+ "hours": {
+ "description": "[Required] List of hours for the schedule.",
+ "type": "array",
+ "items": {
+ "format": "int32",
+ "type": "integer"
}
},
- "x-ms-discriminator-value": "SparkJobScalaEntry",
- "additionalProperties": false
- },
- "SparkResourceConfiguration": {
- "type": "object",
- "properties": {
- "instanceType": {
- "description": "Optional type of VM used as supported by the compute target.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "runtimeVersion": {
- "description": "Version of spark runtime used for the job.",
- "default": "3.1",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "minutes": {
+ "description": "[Required] List of minutes for the schedule.",
+ "type": "array",
+ "items": {
+ "format": "int32",
+ "type": "integer"
}
},
- "additionalProperties": false
- },
- "StackEnsembleSettings": {
- "description": "Advances setting to customize StackEnsemble run.",
- "type": "object",
- "properties": {
- "stackMetaLearnerKWargs": {
- "description": "Optional parameters to pass to the initializer of the meta-learner.",
- "type": "object",
- "x-nullable": true
+ "monthDays": {
+ "description": "List of month days for the schedule",
+ "type": "array",
+ "items": {
+ "format": "int32",
+ "type": "integer"
},
- "stackMetaLearnerTrainPercentage": {
- "format": "double",
- "description": "Specifies the proportion of the training set (when choosing train and validation type of training) to be reserved for training the meta-learner. Default value is 0.2.",
- "default": 0.2,
- "type": "number"
- },
- "stackMetaLearnerType": {
- "description": "The meta-learner is a model trained on the output of the individual heterogeneous models.",
- "default": "None",
- "$ref": "#/definitions/StackMetaLearnerType"
- }
- },
- "additionalProperties": false
- },
- "StackMetaLearnerType": {
- "description": "The meta-learner is a model trained on the output of the individual heterogeneous models.\r\nDefault meta-learners are LogisticRegression for classification tasks (or LogisticRegressionCV if cross-validation is enabled) and ElasticNet for regression/forecasting tasks (or ElasticNetCV if cross-validation is enabled).\r\nThis parameter can be one of the following strings: LogisticRegression, LogisticRegressionCV, LightGBMClassifier, ElasticNet, ElasticNetCV, LightGBMRegressor, or LinearRegression",
- "enum": [
- "None",
- "LogisticRegression",
- "LogisticRegressionCV",
- "LightGBMClassifier",
- "ElasticNet",
- "ElasticNetCV",
- "LightGBMRegressor",
- "LinearRegression"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "StackMetaLearnerType",
- "modelAsString": true,
- "values": [
- {
- "value": "None"
- },
- {
- "value": "LogisticRegression",
- "description": "Default meta-learners are LogisticRegression for classification tasks."
- },
- {
- "value": "LogisticRegressionCV",
- "description": "Default meta-learners are LogisticRegression for classification task when CV is on."
- },
- {
- "value": "LightGBMClassifier"
- },
- {
- "value": "ElasticNet",
- "description": "Default meta-learners are LogisticRegression for regression task."
- },
- {
- "value": "ElasticNetCV",
- "description": "Default meta-learners are LogisticRegression for regression task when CV is on."
- },
- {
- "value": "LightGBMRegressor"
- },
- {
- "value": "LinearRegression"
- }
- ]
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "StatusMessage": {
- "description": "Active message associated with project",
- "type": "object",
- "properties": {
- "code": {
- "description": "Service-defined message code.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "weekDays": {
+ "description": "List of days for the schedule.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/WeekDay"
},
- "createdDateTime": {
- "format": "date-time",
- "description": "Time in UTC at which the message was created.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "RecurrenceTrigger": {
+ "required": [
+ "frequency",
+ "interval"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TriggerBase"
+ }
+ ],
+ "properties": {
+ "frequency": {
+ "description": "[Required] The frequency to trigger schedule.",
+ "$ref": "#/definitions/RecurrenceFrequency"
+ },
+ "interval": {
+ "format": "int32",
+ "description": "[Required] Specifies schedule interval in conjunction with frequency",
+ "type": "integer"
+ },
+ "schedule": {
+ "description": "The recurrence schedule.",
+ "$ref": "#/definitions/RecurrenceSchedule",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Recurrence",
+ "additionalProperties": false
+ },
+ "ReferenceType": {
+ "description": "Enum to determine which reference method to use for an asset.",
+ "enum": [
+ "Id",
+ "DataPath",
+ "OutputPath"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ReferenceType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Id"
},
- "level": {
- "description": "Severity level of message.",
- "$ref": "#/definitions/StatusMessageLevel",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ]
+ {
+ "value": "DataPath"
},
- "message": {
- "description": "A human-readable representation of the message code.",
- "type": "string",
- "readOnly": true,
- "x-ms-mutability": [
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "OutputPath"
}
- },
- "additionalProperties": false
+ ]
},
- "StatusMessageLevel": {
- "enum": [
- "Error",
- "Information",
- "Warning"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "StatusMessageLevel",
- "modelAsString": true,
- "values": [
- {
- "value": "Error"
- },
- {
- "value": "Information"
- },
- {
- "value": "Warning"
- }
- ]
- },
- "additionalProperties": false
- },
- "StochasticOptimizer": {
- "description": "Stochastic optimizer for image models.",
- "enum": [
- "None",
- "Sgd",
- "Adam",
- "Adamw"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "StochasticOptimizer",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No optimizer selected."
- },
- {
- "value": "Sgd",
- "description": "Stochastic Gradient Descent optimizer."
- },
- {
- "value": "Adam",
- "description": "Adam is algorithm the optimizes stochastic objective functions based on adaptive estimates of moments"
- },
- {
- "value": "Adamw",
- "description": "AdamW is a variant of the optimizer Adam that has an improved implementation of weight decay."
- }
+ "additionalProperties": false
+ },
+ "RegenerateEndpointKeysRequest": {
+ "required": [
+ "keyType"
+ ],
+ "type": "object",
+ "properties": {
+ "keyType": {
+ "description": "[Required] Specification for which type of key to generate. Primary or Secondary.",
+ "$ref": "#/definitions/KeyType",
+ "example": "Primary"
+ },
+ "keyValue": {
+ "description": "The value the key is set to.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "Regression": {
+ "description": "Regression task in AutoML Table vertical.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TableVertical"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric for regression task.",
+ "default": "NormalizedRootMeanSquaredError",
+ "$ref": "#/definitions/RegressionPrimaryMetrics"
+ },
+ "trainingSettings": {
+ "description": "Inputs for training phase for an AutoML Job.",
+ "$ref": "#/definitions/RegressionTrainingSettings",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Regression",
+ "additionalProperties": false
+ },
+ "RegressionModelPerformanceMetric": {
+ "enum": [
+ "MeanAbsoluteError",
+ "RootMeanSquaredError",
+ "MeanSquaredError"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "RegressionModelPerformanceMetric",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "MeanAbsoluteError",
+ "description": "The Mean Absolute Error (MAE) metric."
+ },
+ {
+ "value": "RootMeanSquaredError",
+ "description": "The Root Mean Squared Error (RMSE) metric."
+ },
+ {
+ "value": "MeanSquaredError",
+ "description": "The Mean Squared Error (MSE) metric."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "RegressionModelPerformanceMetricThreshold": {
+ "required": [
+ "metric"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ModelPerformanceMetricThresholdBase"
+ }
+ ],
+ "properties": {
+ "metric": {
+ "description": "[Required] The regression model performance metric to calculate.",
+ "$ref": "#/definitions/RegressionModelPerformanceMetric",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "SweepJob": {
- "description": "Sweep job definition.",
- "required": [
- "objective",
- "samplingAlgorithm",
- "searchSpace",
- "trial"
- ],
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "Regression",
+ "additionalProperties": false
+ },
+ "RegressionModels": {
+ "description": "Enum for all Regression models supported by AutoML.",
+ "enum": [
+ "ElasticNet",
+ "GradientBoosting",
+ "DecisionTree",
+ "KNN",
+ "LassoLars",
+ "SGD",
+ "RandomForest",
+ "ExtremeRandomTrees",
+ "LightGBM",
+ "XGBoostRegressor"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "RegressionModels",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/JobBase"
- }
- ],
- "properties": {
- "earlyTermination": {
- "description": "Early termination policies enable canceling poor-performing runs before they complete",
- "$ref": "#/definitions/EarlyTerminationPolicy",
- "x-nullable": true
+ "value": "ElasticNet",
+ "description": "Elastic net is a popular type of regularized linear regression that combines two popular penalties, specifically the L1 and L2 penalty functions."
},
- "inputs": {
- "description": "Mapping of input data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Command job definition.",
- "$ref": "#/definitions/JobInput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "GradientBoosting",
+ "description": "The technique of transiting week learners into a strong learner is called Boosting. The gradient boosting algorithm process works on this theory of execution."
},
- "limits": {
- "description": "Sweep Job limit.",
- "default": "{}",
- "$ref": "#/definitions/SweepJobLimits",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "objective": {
- "description": "[Required] Optimization objective.",
- "$ref": "#/definitions/Objective"
- },
- "outputs": {
- "description": "Mapping of output data bindings used in the job.",
- "type": "object",
- "additionalProperties": {
- "description": "Job output definition container information on where to find job output/logs.",
- "$ref": "#/definitions/JobOutput",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "DecisionTree",
+ "description": "Decision Trees are a non-parametric supervised learning method used for both classification and regression tasks.\nThe goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features."
},
- "queueSettings": {
- "description": "Queue settings for the job",
- "$ref": "#/definitions/QueueSettings",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "KNN",
+ "description": "K-nearest neighbors (KNN) algorithm uses 'feature similarity' to predict the values of new datapoints\nwhich further means that the new data point will be assigned a value based on how closely it matches the points in the training set."
+ },
+ {
+ "value": "LassoLars",
+ "description": "Lasso model fit with Least Angle Regression a.k.a. Lars. It is a Linear Model trained with an L1 prior as regularizer."
+ },
+ {
+ "value": "SGD",
+ "description": "SGD: Stochastic gradient descent is an optimization algorithm often used in machine learning applications\nto find the model parameters that correspond to the best fit between predicted and actual outputs.\nIt's an inexact but powerful technique."
},
- "samplingAlgorithm": {
- "description": "[Required] The hyperparameter sampling algorithm",
- "$ref": "#/definitions/SamplingAlgorithm"
+ {
+ "value": "RandomForest",
+ "description": "Random forest is a supervised learning algorithm.\nThe \"forest\" it builds, is an ensemble of decision trees, usually trained with the “bagging†method.\nThe general idea of the bagging method is that a combination of learning models increases the overall result."
+ },
+ {
+ "value": "ExtremeRandomTrees",
+ "description": "Extreme Trees is an ensemble machine learning algorithm that combines the predictions from many decision trees. It is related to the widely used random forest algorithm."
},
- "searchSpace": {
- "description": "[Required] A dictionary containing each parameter and its distribution. The dictionary key is the name of the parameter",
- "type": "object"
+ {
+ "value": "LightGBM",
+ "description": "LightGBM is a gradient boosting framework that uses tree based learning algorithms."
},
- "trial": {
- "description": "[Required] Trial component definition.",
- "$ref": "#/definitions/TrialComponent"
+ {
+ "value": "XGBoostRegressor",
+ "description": "XGBoostRegressor: Extreme Gradient Boosting Regressor is a supervised machine learning model using ensemble of base learners."
}
- },
- "x-ms-discriminator-value": "Sweep",
- "additionalProperties": false
+ ]
},
- "SweepJobLimits": {
- "description": "Sweep Job limit class.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "RegressionPrimaryMetrics": {
+ "description": "Primary metrics for Regression task.",
+ "enum": [
+ "SpearmanCorrelation",
+ "NormalizedRootMeanSquaredError",
+ "R2Score",
+ "NormalizedMeanAbsoluteError"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "RegressionPrimaryMetrics",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/JobLimits"
- }
- ],
- "properties": {
- "maxConcurrentTrials": {
- "format": "int32",
- "description": "Sweep Job max concurrent trials.",
- "type": "integer",
- "x-nullable": true
+ "value": "SpearmanCorrelation",
+ "description": "The Spearman's rank coefficient of correlation is a nonparametric measure of rank correlation."
},
- "maxTotalTrials": {
- "format": "int32",
- "description": "Sweep Job max total trials.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "NormalizedRootMeanSquaredError",
+ "description": "The Normalized Root Mean Squared Error (NRMSE) the RMSE facilitates the comparison between models with different scales."
},
- "trialTimeout": {
- "format": "duration",
- "description": "Sweep Job Trial timeout value.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "R2Score",
+ "description": "The R2 score is one of the performance evaluation measures for forecasting-based machine learning models."
+ },
+ {
+ "value": "NormalizedMeanAbsoluteError",
+ "description": "The Normalized Mean Absolute Error (NMAE) is a validation metric to compare the Mean Absolute Error (MAE) of (time) series with different scales."
}
- },
- "x-ms-discriminator-value": "Sweep",
- "additionalProperties": false
+ ]
},
- "TableFixedParameters": {
- "description": "Fixed training parameters that won't be swept over during AutoML Table training.",
- "type": "object",
- "properties": {
- "booster": {
- "description": "Specify the boosting type, e.g gbdt for XGBoost.",
- "type": "string",
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "RegressionTrainingSettings": {
+ "description": "Regression Training related configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/TrainingSettings"
+ }
+ ],
+ "properties": {
+ "allowedTrainingAlgorithms": {
+ "description": "Allowed models for regression task.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/RegressionModels"
+ },
+ "x-nullable": true
+ },
+ "blockedTrainingAlgorithms": {
+ "description": "Blocked models for regression task.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/RegressionModels"
+ },
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "RequestLogging": {
+ "type": "object",
+ "properties": {
+ "captureHeaders": {
+ "description": "For payload logging, we only collect payload by default. If customers also want to collect the specified headers, they can set them in captureHeaders so that backend will collect those headers along with payload.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "boostingType": {
- "description": "Specify the boosting type, e.g gbdt for LightGBM.",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ResourceBase": {
+ "type": "object",
+ "properties": {
+ "description": {
+ "description": "The asset description text.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "properties": {
+ "description": "The asset property dictionary.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "growPolicy": {
- "description": "Specify the grow policy, which controls the way new nodes are added to the tree.",
+ "x-nullable": true
+ },
+ "tags": {
+ "description": "Tag dictionary. Tags can be added, removed, and updated.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "learningRate": {
- "format": "double",
- "description": "The learning rate for the training procedure.",
- "type": "number",
- "x-nullable": true
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "ResourceConfiguration": {
+ "type": "object",
+ "properties": {
+ "instanceCount": {
+ "format": "int32",
+ "description": "Optional number of instances or nodes used by the compute target.",
+ "default": 1,
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "instanceType": {
+ "description": "Optional type of VM used as supported by the compute target.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "locations": {
+ "description": "Locations where the job can run.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "maxBin": {
- "format": "int32",
- "description": "Specify the Maximum number of discrete bins to bucket continuous features .",
- "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "maxInstanceCount": {
+ "format": "int32",
+ "description": "Optional max allowed number of instances or nodes to be used by the compute target.\r\nFor use with elastic training, currently supported by PyTorch distribution type only.",
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "properties": {
+ "description": "Additional properties bag.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "object",
"x-nullable": true
},
- "maxDepth": {
- "format": "int32",
- "description": "Specify the max depth to limit the tree depth explicitly.",
- "type": "integer",
- "x-nullable": true
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "RollingRateType": {
+ "enum": [
+ "Year",
+ "Month",
+ "Day",
+ "Hour",
+ "Minute"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "RollingRateType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Year"
},
- "maxLeaves": {
- "format": "int32",
- "description": "Specify the max leaves to limit the tree leaves explicitly.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Month"
},
- "minDataInLeaf": {
- "format": "int32",
- "description": "The minimum number of data per leaf.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Day"
},
- "minSplitGain": {
- "format": "double",
- "description": "Minimum loss reduction required to make a further partition on a leaf node of the tree.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "Hour"
},
- "modelName": {
- "description": "The name of the model to train.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Minute"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "Route": {
+ "required": [
+ "path",
+ "port"
+ ],
+ "type": "object",
+ "properties": {
+ "path": {
+ "description": "[Required] The path for the route.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ },
+ "port": {
+ "format": "int32",
+ "description": "[Required] The port for the route.",
+ "type": "integer"
+ }
+ },
+ "additionalProperties": false
+ },
+ "SASCredentialDto": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/PendingUploadCredentialDto"
+ }
+ ],
+ "properties": {
+ "sasUri": {
+ "format": "uri",
+ "description": "Full SAS Uri, including the storage, container/blob path and SAS token",
+ "type": "string",
+ "x-nullable": true
+ },
+ "wasbsUri": {
+ "format": "uri",
+ "description": "Windows Azure Storage Blob formatted uri for mounting containers at root, a subdirectory, or a specific file\r\nexample wasbs://[container_name]@[account_name].blob.core.windows.net/[path]?sas=[sas]\r\nFor now, the URI will just be the root path ([path] will be empty).",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "SAS",
+ "additionalProperties": false
+ },
+ "SamplingAlgorithm": {
+ "description": "The Sampling Algorithm used to generate hyperparameter values, along with properties to\r\nconfigure the algorithm",
+ "required": [
+ "samplingAlgorithmType"
+ ],
+ "type": "object",
+ "properties": {
+ "samplingAlgorithmType": {
+ "description": "[Required] The algorithm used for generating hyperparameter values, along with configuration properties",
+ "$ref": "#/definitions/SamplingAlgorithmType"
+ }
+ },
+ "discriminator": "samplingAlgorithmType"
+ },
+ "SamplingAlgorithmType": {
+ "enum": [
+ "Grid",
+ "Random",
+ "Bayesian"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "SamplingAlgorithmType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Grid"
},
- "nEstimators": {
- "format": "int32",
- "description": "Specify the number of trees (or rounds) in an model.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Random"
},
- "numLeaves": {
- "format": "int32",
- "description": "Specify the number of leaves.",
- "type": "integer",
- "x-nullable": true
+ {
+ "value": "Bayesian"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "SasDatastoreCredentials": {
+ "description": "SAS datastore credentials configuration.",
+ "required": [
+ "secrets"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "properties": {
+ "secrets": {
+ "description": "[Required] Storage container secrets.",
+ "$ref": "#/definitions/SasDatastoreSecrets",
+ "x-ms-mutability": [
+ "create",
+ "update"
+ ],
+ "x-ms-secret": true
+ }
+ },
+ "x-ms-discriminator-value": "Sas",
+ "additionalProperties": false
+ },
+ "SasDatastoreSecrets": {
+ "description": "Datastore SAS secrets.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreSecrets"
+ }
+ ],
+ "properties": {
+ "sasToken": {
+ "description": "Storage container SAS token.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Sas",
+ "additionalProperties": false
+ },
+ "ScaleType": {
+ "enum": [
+ "Default",
+ "TargetUtilization"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ScaleType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Default"
},
- "preprocessorName": {
- "description": "The name of the preprocessor to use.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "TargetUtilization"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "Schedule": {
+ "description": "Base definition of a schedule",
+ "required": [
+ "action",
+ "trigger"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/ResourceBase"
+ }
+ ],
+ "properties": {
+ "action": {
+ "description": "[Required] Specifies the action of the schedule",
+ "$ref": "#/definitions/ScheduleActionBase",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ },
+ "displayName": {
+ "description": "Display name of schedule.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "isEnabled": {
+ "description": "Is the schedule enabled?",
+ "default": true,
+ "type": "boolean",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ },
+ "provisioningState": {
+ "description": "Provisioning state for the schedule.",
+ "$ref": "#/definitions/ScheduleProvisioningStatus",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
+ },
+ "trigger": {
+ "description": "[Required] Specifies the trigger details",
+ "$ref": "#/definitions/TriggerBase",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "x-ms-client-name": "ScheduleProperties",
+ "additionalProperties": false
+ },
+ "ScheduleActionBase": {
+ "required": [
+ "actionType"
+ ],
+ "type": "object",
+ "properties": {
+ "actionType": {
+ "description": "[Required] Specifies the action type of the schedule",
+ "$ref": "#/definitions/ScheduleActionType",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
+ },
+ "discriminator": "actionType"
+ },
+ "ScheduleActionType": {
+ "enum": [
+ "CreateJob",
+ "InvokeBatchEndpoint",
+ "ImportData",
+ "CreateMonitor"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ScheduleActionType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "CreateJob"
},
- "regAlpha": {
- "format": "double",
- "description": "L1 regularization term on weights.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "InvokeBatchEndpoint"
},
- "regLambda": {
- "format": "double",
- "description": "L2 regularization term on weights.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "ImportData"
},
- "subsample": {
- "format": "double",
- "description": "Subsample ratio of the training instance.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "CreateMonitor"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ScheduleListViewType": {
+ "enum": [
+ "EnabledOnly",
+ "DisabledOnly",
+ "All"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ScheduleListViewType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "EnabledOnly"
},
- "subsampleFreq": {
- "format": "double",
- "description": "Frequency of subsample.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "DisabledOnly"
},
- "treeMethod": {
- "description": "Specify the tree method.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "All"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ScheduleProvisioningStatus": {
+ "enum": [
+ "Creating",
+ "Updating",
+ "Deleting",
+ "Succeeded",
+ "Failed",
+ "Canceled"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ScheduleProvisioningStatus",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Creating"
},
- "withMean": {
- "description": "If true, center before scaling the data with StandardScalar.",
- "default": false,
- "type": "boolean"
+ {
+ "value": "Updating"
},
- "withStd": {
- "description": "If true, scaling the data with Unit Variance with StandardScalar.",
- "default": false,
- "type": "boolean"
+ {
+ "value": "Deleting"
+ },
+ {
+ "value": "Succeeded"
+ },
+ {
+ "value": "Failed"
+ },
+ {
+ "value": "Canceled"
}
- },
- "additionalProperties": false
+ ]
},
- "TableParameterSubspace": {
- "type": "object",
+ "additionalProperties": false
+ },
+ "ScheduleResource": {
+ "description": "Azure Resource Manager resource envelope.",
+ "required": [
+ "properties"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/Resource"
+ }
+ ],
+ "properties": {
"properties": {
- "booster": {
- "description": "Specify the boosting type, e.g gbdt for XGBoost.",
- "type": "string",
- "x-nullable": true
+ "description": "[Required] Additional attributes of the entity.",
+ "$ref": "#/definitions/Schedule"
+ }
+ },
+ "x-ms-client-name": "Schedule",
+ "additionalProperties": false
+ },
+ "ScheduleResourceArmPaginatedResult": {
+ "description": "A paginated list of Schedule entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of Schedule objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type Schedule.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ScheduleResource"
+ }
+ }
+ },
+ "additionalProperties": false
+ },
+ "Seasonality": {
+ "description": "Forecasting seasonality.",
+ "required": [
+ "mode"
+ ],
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "[Required] Seasonality mode.",
+ "$ref": "#/definitions/SeasonalityMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "mode"
+ },
+ "SeasonalityMode": {
+ "description": "Forecasting seasonality mode.",
+ "enum": [
+ "Auto",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "SeasonalityMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Auto",
+ "description": "Seasonality to be determined automatically."
},
- "boostingType": {
- "description": "Specify the boosting type, e.g gbdt for LightGBM.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Custom",
+ "description": "Use the custom seasonality value."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "SecretConfiguration": {
+ "description": "Secret Configuration definition.",
+ "type": "object",
+ "properties": {
+ "uri": {
+ "description": "Secret Uri.\r\nSample Uri : https://myvault.vault.azure.net/secrets/mysecretname/secretversion",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "workspaceSecretName": {
+ "description": "Name of secret in workspace key vault.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "SecretsType": {
+ "description": "Enum to determine the datastore secrets type.",
+ "enum": [
+ "AccountKey",
+ "Certificate",
+ "Sas",
+ "ServicePrincipal",
+ "KerberosPassword",
+ "KerberosKeytab"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "SecretsType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "AccountKey"
},
- "growPolicy": {
- "description": "Specify the grow policy, which controls the way new nodes are added to the tree.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Certificate"
},
- "learningRate": {
- "description": "The learning rate for the training procedure.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Sas"
},
- "maxBin": {
- "description": "Specify the Maximum number of discrete bins to bucket continuous features .",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "ServicePrincipal"
},
- "maxDepth": {
- "description": "Specify the max depth to limit the tree depth explicitly.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "KerberosPassword"
},
- "maxLeaves": {
- "description": "Specify the max leaves to limit the tree leaves explicitly.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "KerberosKeytab"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ServiceDataAccessAuthIdentity": {
+ "enum": [
+ "None",
+ "WorkspaceSystemAssignedIdentity",
+ "WorkspaceUserAssignedIdentity"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ServiceDataAccessAuthIdentity",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None",
+ "description": "Do not use any identity for service data access."
},
- "minDataInLeaf": {
- "description": "The minimum number of data per leaf.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "WorkspaceSystemAssignedIdentity",
+ "description": "Use the system assigned managed identity of the Workspace to authenticate service data access."
},
- "minSplitGain": {
- "description": "Minimum loss reduction required to make a further partition on a leaf node of the tree.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "WorkspaceUserAssignedIdentity",
+ "description": "Use the user assigned managed identity of the Workspace to authenticate service data access."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "ServicePrincipalDatastoreCredentials": {
+ "description": "Service Principal datastore credentials configuration.",
+ "required": [
+ "clientId",
+ "secrets",
+ "tenantId"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreCredentials"
+ }
+ ],
+ "properties": {
+ "authorityUrl": {
+ "description": "Authority URL used for authentication.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "clientId": {
+ "format": "uuid",
+ "description": "[Required] Service principal client ID.",
+ "type": "string"
+ },
+ "resourceUrl": {
+ "description": "Resource the service principal has access to.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "secrets": {
+ "description": "[Required] Service principal secrets.",
+ "$ref": "#/definitions/ServicePrincipalDatastoreSecrets",
+ "x-ms-mutability": [
+ "create",
+ "update"
+ ],
+ "x-ms-secret": true
+ },
+ "tenantId": {
+ "format": "uuid",
+ "description": "[Required] ID of the tenant to which the service principal belongs.",
+ "type": "string"
+ }
+ },
+ "x-ms-discriminator-value": "ServicePrincipal",
+ "additionalProperties": false
+ },
+ "ServicePrincipalDatastoreSecrets": {
+ "description": "Datastore Service Principal secrets.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DatastoreSecrets"
+ }
+ ],
+ "properties": {
+ "clientSecret": {
+ "description": "Service principal secret.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "ServicePrincipal",
+ "additionalProperties": false
+ },
+ "ShortSeriesHandlingConfiguration": {
+ "description": "The parameter defining how if AutoML should handle short time series.",
+ "enum": [
+ "None",
+ "Auto",
+ "Pad",
+ "Drop"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ShortSeriesHandlingConfiguration",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None",
+ "description": "Represents no/null value."
+ },
+ {
+ "value": "Auto",
+ "description": "Short series will be padded if there are no long series, otherwise short series will be dropped."
},
- "modelName": {
- "description": "The name of the model to train.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Pad",
+ "description": "All the short series will be padded."
},
- "nEstimators": {
- "description": "Specify the number of trees (or rounds) in an model.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Drop",
+ "description": "All the short series will be dropped."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "SkuCapacity": {
+ "description": "SKU capacity information",
+ "type": "object",
+ "properties": {
+ "default": {
+ "format": "int32",
+ "description": "Gets or sets the default capacity.",
+ "default": 0,
+ "type": "integer"
+ },
+ "maximum": {
+ "format": "int32",
+ "description": "Gets or sets the maximum.",
+ "default": 0,
+ "type": "integer"
+ },
+ "minimum": {
+ "format": "int32",
+ "description": "Gets or sets the minimum.",
+ "default": 0,
+ "type": "integer"
+ },
+ "scaleType": {
+ "description": "Gets or sets the type of the scale.",
+ "default": "Automatic",
+ "$ref": "#/definitions/SkuScaleType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "SkuResource": {
+ "description": "Fulfills ARM Contract requirement to list all available SKUS for a resource.",
+ "type": "object",
+ "properties": {
+ "capacity": {
+ "description": "Gets or sets the Sku Capacity.",
+ "$ref": "#/definitions/SkuCapacity",
+ "x-nullable": true
+ },
+ "resourceType": {
+ "description": "The resource type name.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "sku": {
+ "description": "Gets or sets the Sku.",
+ "$ref": "#/definitions/SkuSetting",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "SkuResourceArmPaginatedResult": {
+ "description": "A paginated list of SkuResource entities.",
+ "type": "object",
+ "properties": {
+ "nextLink": {
+ "description": "The link to the next page of SkuResource objects. If null, there are no additional pages.",
+ "type": "string"
+ },
+ "value": {
+ "description": "An array of objects of type SkuResource.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/SkuResource"
+ },
+ "x-ms-identifiers": []
+ }
+ },
+ "additionalProperties": false
+ },
+ "SkuScaleType": {
+ "description": "Node scaling setting for the compute sku.",
+ "enum": [
+ "Automatic",
+ "Manual",
+ "None"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "SkuScaleType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Automatic",
+ "description": "Automatically scales node count."
},
- "numLeaves": {
- "description": "Specify the number of leaves.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "Manual",
+ "description": "Node count scaled upon user request."
},
- "preprocessorName": {
- "description": "The name of the preprocessor to use.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "None",
+ "description": "Fixed set of nodes."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "SkuSetting": {
+ "description": "SkuSetting fulfills the need for stripped down SKU info in ARM contract.",
+ "required": [
+ "name"
+ ],
+ "type": "object",
+ "properties": {
+ "name": {
+ "description": "[Required] The name of the SKU. Ex - P3. It is typically a letter+number code.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ },
+ "tier": {
+ "description": "This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.",
+ "default": "Basic",
+ "$ref": "../../../../../common-types/resource-management/v3/types.json#/definitions/SkuTier"
+ }
+ },
+ "additionalProperties": false
+ },
+ "SparkJob": {
+ "description": "Spark job definition.",
+ "required": [
+ "codeId",
+ "entry"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobBase"
+ }
+ ],
+ "properties": {
+ "archives": {
+ "description": "Archive files used in the job.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "regAlpha": {
- "description": "L1 regularization term on weights.",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "args": {
+ "description": "Arguments for the job.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "codeId": {
+ "description": "[Required] ARM resource ID of the code asset.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "conf": {
+ "description": "Spark configured properties.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "regLambda": {
- "description": "L2 regularization term on weights.",
- "type": "string",
- "x-nullable": true
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "entry": {
+ "description": "[Required] The entry to execute on startup of the job.",
+ "$ref": "#/definitions/SparkJobEntry",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "environmentId": {
+ "description": "The ARM resource ID of the Environment specification for the job.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "files": {
+ "description": "Files used in the job.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "subsample": {
- "description": "Subsample ratio of the training instance.",
- "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "inputs": {
+ "description": "Mapping of input data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Command job definition.",
+ "$ref": "#/definitions/JobInput",
"x-nullable": true
},
- "subsampleFreq": {
- "description": "Frequency of subsample",
- "type": "string",
- "x-nullable": true
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "jars": {
+ "description": "Jar files used in the job.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "treeMethod": {
- "description": "Specify the tree method.",
- "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "outputs": {
+ "description": "Mapping of output data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Job output definition container information on where to find job output/logs.",
+ "$ref": "#/definitions/JobOutput",
"x-nullable": true
},
- "withMean": {
- "description": "If true, center before scaling the data with StandardScalar.",
- "type": "string",
- "x-nullable": true
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "pyFiles": {
+ "description": "Python files used in the job.",
+ "type": "array",
+ "items": {
+ "type": "string"
},
- "withStd": {
- "description": "If true, scaling the data with Unit Variance with StandardScalar.",
- "type": "string",
- "x-nullable": true
- }
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "queueSettings": {
+ "description": "Queue settings for the job",
+ "$ref": "#/definitions/QueueSettings",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
+ "resources": {
+ "description": "Compute Resource configuration for the job.",
+ "$ref": "#/definitions/SparkResourceConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "TableSweepSettings": {
- "required": [
- "samplingAlgorithm"
- ],
- "type": "object",
- "properties": {
- "earlyTermination": {
- "description": "Type of early termination policy for the sweeping job.",
- "$ref": "#/definitions/EarlyTerminationPolicy",
- "x-nullable": true
+ "x-ms-discriminator-value": "Spark",
+ "additionalProperties": false
+ },
+ "SparkJobEntry": {
+ "description": "Spark job entry point definition.",
+ "required": [
+ "sparkJobEntryType"
+ ],
+ "type": "object",
+ "properties": {
+ "sparkJobEntryType": {
+ "description": "[Required] Type of the job's entry point.",
+ "$ref": "#/definitions/SparkJobEntryType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "discriminator": "sparkJobEntryType"
+ },
+ "SparkJobEntryType": {
+ "enum": [
+ "SparkJobPythonEntry",
+ "SparkJobScalaEntry"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "SparkJobEntryType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "SparkJobPythonEntry"
},
- "samplingAlgorithm": {
- "description": "[Required] Type of sampling algorithm.",
- "$ref": "#/definitions/SamplingAlgorithmType"
+ {
+ "value": "SparkJobScalaEntry"
}
- },
- "additionalProperties": false
+ ]
},
- "TableVertical": {
- "description": "Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.",
- "type": "object",
- "properties": {
- "cvSplitColumnNames": {
- "description": "Columns to use for CVSplit data.",
- "type": "array",
- "items": {
- "type": "string"
- },
- "x-nullable": true
- },
- "featurizationSettings": {
- "description": "Featurization inputs needed for AutoML job.",
- "$ref": "#/definitions/TableVerticalFeaturizationSettings",
- "x-nullable": true
- },
- "fixedParameters": {
- "description": "Model/training parameters that will remain constant throughout training.",
- "$ref": "#/definitions/TableFixedParameters",
- "x-nullable": true
- },
- "limitSettings": {
- "description": "Execution constraints for AutoMLJob.",
- "$ref": "#/definitions/TableVerticalLimitSettings",
- "x-nullable": true
- },
- "nCrossValidations": {
- "description": "Number of cross validation folds to be applied on training dataset\r\nwhen validation dataset is not provided.",
- "$ref": "#/definitions/NCrossValidations",
- "x-nullable": true
+ "additionalProperties": false
+ },
+ "SparkJobPythonEntry": {
+ "required": [
+ "file"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/SparkJobEntry"
+ }
+ ],
+ "properties": {
+ "file": {
+ "description": "[Required] Relative python file path for job entry point.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "example": "train.py",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "SparkJobPythonEntry",
+ "additionalProperties": false
+ },
+ "SparkJobScalaEntry": {
+ "required": [
+ "className"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/SparkJobEntry"
+ }
+ ],
+ "properties": {
+ "className": {
+ "description": "[Required] Scala class name used as entry point.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "example": "microsoft.aml.sample.myapp",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "SparkJobScalaEntry",
+ "additionalProperties": false
+ },
+ "SparkResourceConfiguration": {
+ "type": "object",
+ "properties": {
+ "instanceType": {
+ "description": "Optional type of VM used as supported by the compute target.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "runtimeVersion": {
+ "description": "Version of spark runtime used for the job.",
+ "default": "3.1",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "additionalProperties": false
+ },
+ "StackEnsembleSettings": {
+ "description": "Advances setting to customize StackEnsemble run.",
+ "type": "object",
+ "properties": {
+ "stackMetaLearnerKWargs": {
+ "description": "Optional parameters to pass to the initializer of the meta-learner.",
+ "type": "object",
+ "x-nullable": true
+ },
+ "stackMetaLearnerTrainPercentage": {
+ "format": "double",
+ "description": "Specifies the proportion of the training set (when choosing train and validation type of training) to be reserved for training the meta-learner. Default value is 0.2.",
+ "default": 0.2,
+ "type": "number"
+ },
+ "stackMetaLearnerType": {
+ "description": "The meta-learner is a model trained on the output of the individual heterogeneous models.",
+ "default": "None",
+ "$ref": "#/definitions/StackMetaLearnerType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "StackMetaLearnerType": {
+ "description": "The meta-learner is a model trained on the output of the individual heterogeneous models.\r\nDefault meta-learners are LogisticRegression for classification tasks (or LogisticRegressionCV if cross-validation is enabled) and ElasticNet for regression/forecasting tasks (or ElasticNetCV if cross-validation is enabled).\r\nThis parameter can be one of the following strings: LogisticRegression, LogisticRegressionCV, LightGBMClassifier, ElasticNet, ElasticNetCV, LightGBMRegressor, or LinearRegression",
+ "enum": [
+ "None",
+ "LogisticRegression",
+ "LogisticRegressionCV",
+ "LightGBMClassifier",
+ "ElasticNet",
+ "ElasticNetCV",
+ "LightGBMRegressor",
+ "LinearRegression"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "StackMetaLearnerType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None"
},
- "searchSpace": {
- "description": "Search space for sampling different combinations of models and their hyperparameters.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/TableParameterSubspace"
- },
- "x-nullable": true,
- "x-ms-identifiers": []
+ {
+ "value": "LogisticRegression",
+ "description": "Default meta-learners are LogisticRegression for classification tasks."
},
- "sweepSettings": {
- "description": "Settings for model sweeping and hyperparameter tuning.",
- "$ref": "#/definitions/TableSweepSettings",
- "x-nullable": true
+ {
+ "value": "LogisticRegressionCV",
+ "description": "Default meta-learners are LogisticRegression for classification task when CV is on."
},
- "testData": {
- "description": "Test data input.",
- "$ref": "#/definitions/MLTableJobInput",
- "x-nullable": true
+ {
+ "value": "LightGBMClassifier"
},
- "testDataSize": {
- "format": "double",
- "description": "The fraction of test dataset that needs to be set aside for validation purpose.\r\nValues between (0.0 , 1.0)\r\nApplied when validation dataset is not provided.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "ElasticNet",
+ "description": "Default meta-learners are LogisticRegression for regression task."
},
- "validationData": {
- "description": "Validation data inputs.",
- "$ref": "#/definitions/MLTableJobInput",
- "x-nullable": true
+ {
+ "value": "ElasticNetCV",
+ "description": "Default meta-learners are LogisticRegression for regression task when CV is on."
},
- "validationDataSize": {
- "format": "double",
- "description": "The fraction of training dataset that needs to be set aside for validation purpose.\r\nValues between (0.0 , 1.0)\r\nApplied when validation dataset is not provided.",
- "type": "number",
- "x-nullable": true
+ {
+ "value": "LightGBMRegressor"
},
- "weightColumnName": {
- "description": "The name of the sample weight column. Automated ML supports a weighted column as an input, causing rows in the data to be weighted up or down.",
- "type": "string",
- "x-nullable": true
+ {
+ "value": "LinearRegression"
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "StatusMessage": {
+ "description": "Active message associated with project",
+ "type": "object",
+ "properties": {
+ "code": {
+ "description": "Service-defined message code.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "createdDateTime": {
+ "format": "date-time",
+ "description": "Time in UTC at which the message was created.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "level": {
+ "description": "Severity level of message.",
+ "$ref": "#/definitions/StatusMessageLevel",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ]
},
- "additionalProperties": false
+ "message": {
+ "description": "A human-readable representation of the message code.",
+ "type": "string",
+ "readOnly": true,
+ "x-ms-mutability": [
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "TableVerticalFeaturizationSettings": {
- "description": "Featurization Configuration.",
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "StatusMessageLevel": {
+ "enum": [
+ "Error",
+ "Information",
+ "Warning"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "StatusMessageLevel",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/FeaturizationSettings"
- }
- ],
- "properties": {
- "blockedTransformers": {
- "description": "These transformers shall not be used in featurization.",
- "type": "array",
- "items": {
- "$ref": "#/definitions/BlockedTransformers"
- },
- "x-nullable": true
- },
- "columnNameAndTypes": {
- "description": "Dictionary of column name and its type (int, float, string, datetime etc).",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-nullable": true
- },
- "enableDnnFeaturization": {
- "description": "Determines whether to use Dnn based featurizers for data featurization.",
- "default": false,
- "type": "boolean"
+ "value": "Error"
},
- "mode": {
- "description": "Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase.\r\nIf 'Off' is selected then no featurization is done.\r\nIf 'Custom' is selected then user can specify additional inputs to customize how featurization is done.",
- "default": "Auto",
- "$ref": "#/definitions/FeaturizationMode"
+ {
+ "value": "Information"
},
- "transformerParams": {
- "description": "User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor.",
- "type": "object",
- "additionalProperties": {
- "type": "array",
- "items": {
- "$ref": "#/definitions/ColumnTransformer"
- },
- "x-nullable": true,
- "x-ms-identifiers": []
- },
- "x-nullable": true
+ {
+ "value": "Warning"
}
- },
- "additionalProperties": false
+ ]
},
- "TableVerticalLimitSettings": {
- "description": "Job execution constraints.",
- "type": "object",
- "properties": {
- "enableEarlyTermination": {
- "description": "Enable early termination, determines whether or not if AutoMLJob will terminate early if there is no score improvement in last 20 iterations.",
- "default": true,
- "type": "boolean"
- },
- "exitScore": {
- "format": "double",
- "description": "Exit score for the AutoML job.",
- "type": "number",
- "x-nullable": true
- },
- "maxConcurrentTrials": {
- "format": "int32",
- "description": "Maximum Concurrent iterations.",
- "default": 1,
- "type": "integer"
- },
- "maxCoresPerTrial": {
- "format": "int32",
- "description": "Max cores per iteration.",
- "default": -1,
- "type": "integer"
- },
- "maxNodes": {
- "format": "int32",
- "description": "Maximum nodes to use for the experiment.",
- "default": 1,
- "type": "integer"
+ "additionalProperties": false
+ },
+ "StochasticOptimizer": {
+ "description": "Stochastic optimizer for image models.",
+ "enum": [
+ "None",
+ "Sgd",
+ "Adam",
+ "Adamw"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "StochasticOptimizer",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "None",
+ "description": "No optimizer selected."
},
- "maxTrials": {
- "format": "int32",
- "description": "Number of iterations.",
- "default": 1000,
- "type": "integer"
+ {
+ "value": "Sgd",
+ "description": "Stochastic Gradient Descent optimizer."
},
- "sweepConcurrentTrials": {
- "format": "int32",
- "description": "Number of concurrent sweeping runs that user wants to trigger.",
- "default": 0,
- "type": "integer"
+ {
+ "value": "Adam",
+ "description": "Adam is algorithm the optimizes stochastic objective functions based on adaptive estimates of moments"
},
- "sweepTrials": {
- "format": "int32",
- "description": "Number of sweeping runs that user wants to trigger.",
- "default": 0,
- "type": "integer"
+ {
+ "value": "Adamw",
+ "description": "AdamW is a variant of the optimizer Adam that has an improved implementation of weight decay."
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "SweepJob": {
+ "description": "Sweep job definition.",
+ "required": [
+ "objective",
+ "samplingAlgorithm",
+ "searchSpace",
+ "trial"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobBase"
+ }
+ ],
+ "properties": {
+ "earlyTermination": {
+ "description": "Early termination policies enable canceling poor-performing runs before they complete",
+ "$ref": "#/definitions/EarlyTerminationPolicy",
+ "x-nullable": true
+ },
+ "inputs": {
+ "description": "Mapping of input data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Command job definition.",
+ "$ref": "#/definitions/JobInput",
+ "x-nullable": true
+ },
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "limits": {
+ "description": "Sweep Job limit.",
+ "default": "{}",
+ "$ref": "#/definitions/SweepJobLimits",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "objective": {
+ "description": "[Required] Optimization objective.",
+ "$ref": "#/definitions/Objective"
+ },
+ "outputs": {
+ "description": "Mapping of output data bindings used in the job.",
+ "type": "object",
+ "additionalProperties": {
+ "description": "Job output definition container information on where to find job output/logs.",
+ "$ref": "#/definitions/JobOutput",
+ "x-nullable": true
},
- "timeout": {
- "format": "duration",
- "description": "AutoML job timeout.",
- "default": "PT6H",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "queueSettings": {
+ "description": "Queue settings for the job",
+ "$ref": "#/definitions/QueueSettings",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "samplingAlgorithm": {
+ "description": "[Required] The hyperparameter sampling algorithm",
+ "$ref": "#/definitions/SamplingAlgorithm"
+ },
+ "searchSpace": {
+ "description": "[Required] A dictionary containing each parameter and its distribution. The dictionary key is the name of the parameter",
+ "type": "object"
+ },
+ "trial": {
+ "description": "[Required] Trial component definition.",
+ "$ref": "#/definitions/TrialComponent"
+ }
+ },
+ "x-ms-discriminator-value": "Sweep",
+ "additionalProperties": false
+ },
+ "SweepJobLimits": {
+ "description": "Sweep Job limit class.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/JobLimits"
+ }
+ ],
+ "properties": {
+ "maxConcurrentTrials": {
+ "format": "int32",
+ "description": "Sweep Job max concurrent trials.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "maxTotalTrials": {
+ "format": "int32",
+ "description": "Sweep Job max total trials.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "trialTimeout": {
+ "format": "duration",
+ "description": "Sweep Job Trial timeout value.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Sweep",
+ "additionalProperties": false
+ },
+ "TableFixedParameters": {
+ "description": "Fixed training parameters that won't be swept over during AutoML Table training.",
+ "type": "object",
+ "properties": {
+ "booster": {
+ "description": "Specify the boosting type, e.g gbdt for XGBoost.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "boostingType": {
+ "description": "Specify the boosting type, e.g gbdt for LightGBM.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "growPolicy": {
+ "description": "Specify the grow policy, which controls the way new nodes are added to the tree.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "learningRate": {
+ "format": "double",
+ "description": "The learning rate for the training procedure.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "maxBin": {
+ "format": "int32",
+ "description": "Specify the Maximum number of discrete bins to bucket continuous features .",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "maxDepth": {
+ "format": "int32",
+ "description": "Specify the max depth to limit the tree depth explicitly.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "maxLeaves": {
+ "format": "int32",
+ "description": "Specify the max leaves to limit the tree leaves explicitly.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "minDataInLeaf": {
+ "format": "int32",
+ "description": "The minimum number of data per leaf.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "minSplitGain": {
+ "format": "double",
+ "description": "Minimum loss reduction required to make a further partition on a leaf node of the tree.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "modelName": {
+ "description": "The name of the model to train.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "nEstimators": {
+ "format": "int32",
+ "description": "Specify the number of trees (or rounds) in an model.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "numLeaves": {
+ "format": "int32",
+ "description": "Specify the number of leaves.",
+ "type": "integer",
+ "x-nullable": true
+ },
+ "preprocessorName": {
+ "description": "The name of the preprocessor to use.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "regAlpha": {
+ "format": "double",
+ "description": "L1 regularization term on weights.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "regLambda": {
+ "format": "double",
+ "description": "L2 regularization term on weights.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "subsample": {
+ "format": "double",
+ "description": "Subsample ratio of the training instance.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "subsampleFreq": {
+ "format": "double",
+ "description": "Frequency of subsample.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "treeMethod": {
+ "description": "Specify the tree method.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "withMean": {
+ "description": "If true, center before scaling the data with StandardScalar.",
+ "default": false,
+ "type": "boolean"
+ },
+ "withStd": {
+ "description": "If true, scaling the data with Unit Variance with StandardScalar.",
+ "default": false,
+ "type": "boolean"
+ }
+ },
+ "additionalProperties": false
+ },
+ "TableParameterSubspace": {
+ "type": "object",
+ "properties": {
+ "booster": {
+ "description": "Specify the boosting type, e.g gbdt for XGBoost.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "boostingType": {
+ "description": "Specify the boosting type, e.g gbdt for LightGBM.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "growPolicy": {
+ "description": "Specify the grow policy, which controls the way new nodes are added to the tree.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "learningRate": {
+ "description": "The learning rate for the training procedure.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "maxBin": {
+ "description": "Specify the Maximum number of discrete bins to bucket continuous features .",
+ "type": "string",
+ "x-nullable": true
+ },
+ "maxDepth": {
+ "description": "Specify the max depth to limit the tree depth explicitly.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "maxLeaves": {
+ "description": "Specify the max leaves to limit the tree leaves explicitly.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "minDataInLeaf": {
+ "description": "The minimum number of data per leaf.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "minSplitGain": {
+ "description": "Minimum loss reduction required to make a further partition on a leaf node of the tree.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "modelName": {
+ "description": "The name of the model to train.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "nEstimators": {
+ "description": "Specify the number of trees (or rounds) in an model.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "numLeaves": {
+ "description": "Specify the number of leaves.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "preprocessorName": {
+ "description": "The name of the preprocessor to use.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "regAlpha": {
+ "description": "L1 regularization term on weights.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "regLambda": {
+ "description": "L2 regularization term on weights.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "subsample": {
+ "description": "Subsample ratio of the training instance.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "subsampleFreq": {
+ "description": "Frequency of subsample",
+ "type": "string",
+ "x-nullable": true
+ },
+ "treeMethod": {
+ "description": "Specify the tree method.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "withMean": {
+ "description": "If true, center before scaling the data with StandardScalar.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "withStd": {
+ "description": "If true, scaling the data with Unit Variance with StandardScalar.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "TableSweepSettings": {
+ "required": [
+ "samplingAlgorithm"
+ ],
+ "type": "object",
+ "properties": {
+ "earlyTermination": {
+ "description": "Type of early termination policy for the sweeping job.",
+ "$ref": "#/definitions/EarlyTerminationPolicy",
+ "x-nullable": true
+ },
+ "samplingAlgorithm": {
+ "description": "[Required] Type of sampling algorithm.",
+ "$ref": "#/definitions/SamplingAlgorithmType"
+ }
+ },
+ "additionalProperties": false
+ },
+ "TableVertical": {
+ "description": "Abstract class for AutoML tasks that use table dataset as input - such as Classification/Regression/Forecasting.",
+ "type": "object",
+ "properties": {
+ "cvSplitColumnNames": {
+ "description": "Columns to use for CVSplit data.",
+ "type": "array",
+ "items": {
"type": "string"
},
- "trialTimeout": {
- "format": "duration",
- "description": "Iteration timeout.",
- "default": "PT30M",
- "type": "string"
- }
+ "x-nullable": true
+ },
+ "featurizationSettings": {
+ "description": "Featurization inputs needed for AutoML job.",
+ "$ref": "#/definitions/TableVerticalFeaturizationSettings",
+ "x-nullable": true
+ },
+ "fixedParameters": {
+ "description": "Model/training parameters that will remain constant throughout training.",
+ "$ref": "#/definitions/TableFixedParameters",
+ "x-nullable": true
+ },
+ "limitSettings": {
+ "description": "Execution constraints for AutoMLJob.",
+ "$ref": "#/definitions/TableVerticalLimitSettings",
+ "x-nullable": true
+ },
+ "nCrossValidations": {
+ "description": "Number of cross validation folds to be applied on training dataset\r\nwhen validation dataset is not provided.",
+ "$ref": "#/definitions/NCrossValidations",
+ "x-nullable": true
+ },
+ "searchSpace": {
+ "description": "Search space for sampling different combinations of models and their hyperparameters.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/TableParameterSubspace"
+ },
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ },
+ "sweepSettings": {
+ "description": "Settings for model sweeping and hyperparameter tuning.",
+ "$ref": "#/definitions/TableSweepSettings",
+ "x-nullable": true
+ },
+ "testData": {
+ "description": "Test data input.",
+ "$ref": "#/definitions/MLTableJobInput",
+ "x-nullable": true
+ },
+ "testDataSize": {
+ "format": "double",
+ "description": "The fraction of test dataset that needs to be set aside for validation purpose.\r\nValues between (0.0 , 1.0)\r\nApplied when validation dataset is not provided.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "validationData": {
+ "description": "Validation data inputs.",
+ "$ref": "#/definitions/MLTableJobInput",
+ "x-nullable": true
+ },
+ "validationDataSize": {
+ "format": "double",
+ "description": "The fraction of training dataset that needs to be set aside for validation purpose.\r\nValues between (0.0 , 1.0)\r\nApplied when validation dataset is not provided.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "weightColumnName": {
+ "description": "The name of the sample weight column. Automated ML supports a weighted column as an input, causing rows in the data to be weighted up or down.",
+ "type": "string",
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "TableVerticalFeaturizationSettings": {
+ "description": "Featurization Configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/FeaturizationSettings"
+ }
+ ],
+ "properties": {
+ "blockedTransformers": {
+ "description": "These transformers shall not be used in featurization.",
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/BlockedTransformers"
+ },
+ "x-nullable": true
+ },
+ "columnNameAndTypes": {
+ "description": "Dictionary of column name and its type (int, float, string, datetime etc).",
+ "type": "object",
+ "additionalProperties": {
+ "type": "string",
+ "x-nullable": true
+ },
+ "x-nullable": true
},
- "additionalProperties": false
- },
- "TargetAggregationFunction": {
- "description": "Target aggregate function.",
- "enum": [
- "None",
- "Sum",
- "Max",
- "Min",
- "Mean"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TargetAggregationFunction",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "Represent no value set."
- },
- {
- "value": "Sum"
- },
- {
- "value": "Max"
- },
- {
- "value": "Min"
- },
- {
- "value": "Mean"
- }
- ]
+ "enableDnnFeaturization": {
+ "description": "Determines whether to use Dnn based featurizers for data featurization.",
+ "default": false,
+ "type": "boolean"
},
- "additionalProperties": false
- },
- "TargetLags": {
- "description": "The number of past periods to lag from the target column.",
- "required": [
- "mode"
- ],
- "type": "object",
- "properties": {
- "mode": {
- "description": "[Required] Set target lags mode - Auto/Custom",
- "$ref": "#/definitions/TargetLagsMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "mode"
- },
- "TargetLagsMode": {
- "description": "Target lags selection modes.",
- "enum": [
- "Auto",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TargetLagsMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Target lags to be determined automatically."
- },
- {
- "value": "Custom",
- "description": "Use the custom target lags."
- }
- ]
+ "mode": {
+ "description": "Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase.\r\nIf 'Off' is selected then no featurization is done.\r\nIf 'Custom' is selected then user can specify additional inputs to customize how featurization is done.",
+ "default": "Auto",
+ "$ref": "#/definitions/FeaturizationMode"
},
- "additionalProperties": false
- },
- "TargetRollingWindowSize": {
- "description": "Forecasting target rolling window size.",
- "required": [
- "mode"
- ],
- "type": "object",
- "properties": {
- "mode": {
- "description": "[Required] TargetRollingWindowSiz detection mode.",
- "$ref": "#/definitions/TargetRollingWindowSizeMode",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- }
- },
- "discriminator": "mode"
- },
- "TargetRollingWindowSizeMode": {
- "description": "Target rolling windows size mode.",
- "enum": [
- "Auto",
- "Custom"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TargetRollingWindowSizeMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Determine rolling windows size automatically."
+ "transformerParams": {
+ "description": "User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor.",
+ "type": "object",
+ "additionalProperties": {
+ "type": "array",
+ "items": {
+ "$ref": "#/definitions/ColumnTransformer"
},
- {
- "value": "Custom",
- "description": "Use the specified rolling window size."
- }
- ]
- },
- "additionalProperties": false
+ "x-nullable": true,
+ "x-ms-identifiers": []
+ },
+ "x-nullable": true
+ }
+ },
+ "additionalProperties": false
+ },
+ "TableVerticalLimitSettings": {
+ "description": "Job execution constraints.",
+ "type": "object",
+ "properties": {
+ "enableEarlyTermination": {
+ "description": "Enable early termination, determines whether or not if AutoMLJob will terminate early if there is no score improvement in last 20 iterations.",
+ "default": true,
+ "type": "boolean"
+ },
+ "exitScore": {
+ "format": "double",
+ "description": "Exit score for the AutoML job.",
+ "type": "number",
+ "x-nullable": true
+ },
+ "maxConcurrentTrials": {
+ "format": "int32",
+ "description": "Maximum Concurrent iterations.",
+ "default": 1,
+ "type": "integer"
+ },
+ "maxCoresPerTrial": {
+ "format": "int32",
+ "description": "Max cores per iteration.",
+ "default": -1,
+ "type": "integer"
+ },
+ "maxNodes": {
+ "format": "int32",
+ "description": "Maximum nodes to use for the experiment.",
+ "default": 1,
+ "type": "integer"
+ },
+ "maxTrials": {
+ "format": "int32",
+ "description": "Number of iterations.",
+ "default": 1000,
+ "type": "integer"
+ },
+ "sweepConcurrentTrials": {
+ "format": "int32",
+ "description": "Number of concurrent sweeping runs that user wants to trigger.",
+ "default": 0,
+ "type": "integer"
+ },
+ "sweepTrials": {
+ "format": "int32",
+ "description": "Number of sweeping runs that user wants to trigger.",
+ "default": 0,
+ "type": "integer"
+ },
+ "timeout": {
+ "format": "duration",
+ "description": "AutoML job timeout.",
+ "default": "PT6H",
+ "type": "string"
+ },
+ "trialTimeout": {
+ "format": "duration",
+ "description": "Iteration timeout.",
+ "default": "PT30M",
+ "type": "string"
+ }
},
- "TargetUtilizationScaleSettings": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "TargetAggregationFunction": {
+ "description": "Target aggregate function.",
+ "enum": [
+ "None",
+ "Sum",
+ "Max",
+ "Min",
+ "Mean"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TargetAggregationFunction",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/OnlineScaleSettings"
- }
- ],
- "properties": {
- "maxInstances": {
- "format": "int32",
- "description": "The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.",
- "default": 1,
- "type": "integer"
+ "value": "None",
+ "description": "Represent no value set."
},
- "minInstances": {
- "format": "int32",
- "description": "The minimum number of instances to always be present.",
- "default": 1,
- "type": "integer"
+ {
+ "value": "Sum"
},
- "pollingInterval": {
- "format": "duration",
- "description": "The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.",
- "default": "PT1S",
- "type": "string"
+ {
+ "value": "Max"
},
- "targetUtilizationPercentage": {
- "format": "int32",
- "description": "Target CPU usage for the autoscaler.",
- "default": 70,
- "type": "integer"
- }
- },
- "x-ms-discriminator-value": "TargetUtilization",
- "additionalProperties": false
- },
- "TaskType": {
- "description": "AutoMLJob Task type.",
- "enum": [
- "Classification",
- "Regression",
- "Forecasting",
- "ImageClassification",
- "ImageClassificationMultilabel",
- "ImageObjectDetection",
- "ImageInstanceSegmentation",
- "TextClassification",
- "TextClassificationMultilabel",
- "TextNER"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TaskType",
- "modelAsString": true,
- "values": [
- {
- "value": "Classification",
- "description": "Classification in machine learning and statistics is a supervised learning approach in which\nthe computer program learns from the data given to it and make new observations or classifications."
- },
- {
- "value": "Regression",
- "description": "Regression means to predict the value using the input data. Regression models are used to predict a continuous value."
- },
- {
- "value": "Forecasting",
- "description": "Forecasting is a special kind of regression task that deals with time-series data and creates forecasting model\nthat can be used to predict the near future values based on the inputs."
- },
- {
- "value": "ImageClassification",
- "description": "Image Classification. Multi-class image classification is used when an image is classified with only a single label\nfrom a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog' or a 'duck'."
- },
- {
- "value": "ImageClassificationMultilabel",
- "description": "Image Classification Multilabel. Multi-label image classification is used when an image could have one or more labels\nfrom a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'."
- },
- {
- "value": "ImageObjectDetection",
- "description": "Image Object Detection. Object detection is used to identify objects in an image and locate each object with a\nbounding box e.g. locate all dogs and cats in an image and draw a bounding box around each."
- },
- {
- "value": "ImageInstanceSegmentation",
- "description": "Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level,\ndrawing a polygon around each object in the image."
- },
- {
- "value": "TextClassification",
- "description": "Text classification (also known as text tagging or text categorization) is the process of sorting texts into categories.\nCategories are mutually exclusive."
- },
- {
- "value": "TextClassificationMultilabel",
- "description": "Multilabel classification task assigns each sample to a group (zero or more) of target labels."
- },
- {
- "value": "TextNER",
- "description": "Text Named Entity Recognition a.k.a. TextNER.\nNamed Entity Recognition (NER) is the ability to take free-form text and identify the occurrences of entities such as people, locations, organizations, and more."
- }
- ]
- },
- "additionalProperties": false
- },
- "TensorFlow": {
- "description": "TensorFlow distribution configuration.",
- "type": "object",
- "allOf": [
{
- "$ref": "#/definitions/DistributionConfiguration"
- }
- ],
- "properties": {
- "parameterServerCount": {
- "format": "int32",
- "description": "Number of parameter server tasks.",
- "default": 0,
- "type": "integer",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ "value": "Min"
},
- "workerCount": {
- "format": "int32",
- "description": "Number of workers. If not specified, will default to the instance count.",
- "type": "integer",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Mean"
}
- },
- "x-ms-discriminator-value": "TensorFlow",
- "additionalProperties": false
+ ]
},
- "TextAnnotationType": {
- "description": "Annotation type of text data.",
- "enum": [
- "Classification",
- "NamedEntityRecognition"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TextAnnotationType",
- "modelAsString": true,
- "values": [
- {
- "value": "Classification"
- },
- {
- "value": "NamedEntityRecognition"
- }
+ "additionalProperties": false
+ },
+ "TargetLags": {
+ "description": "The number of past periods to lag from the target column.",
+ "required": [
+ "mode"
+ ],
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "[Required] Set target lags mode - Auto/Custom",
+ "$ref": "#/definitions/TargetLagsMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
]
- },
- "additionalProperties": false
+ }
},
- "TextClassification": {
- "description": "Text Classification task in AutoML NLP vertical.\r\nNLP - Natural Language Processing.",
- "type": "object",
- "allOf": [
+ "discriminator": "mode"
+ },
+ "TargetLagsMode": {
+ "description": "Target lags selection modes.",
+ "enum": [
+ "Auto",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TargetLagsMode",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/NlpVertical"
+ "value": "Auto",
+ "description": "Target lags to be determined automatically."
},
{
- "$ref": "#/definitions/AutoMLVertical"
+ "value": "Custom",
+ "description": "Use the custom target lags."
}
- ],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric for Text-Classification task.",
- "default": "Accuracy",
- "$ref": "#/definitions/ClassificationPrimaryMetrics"
- }
- },
- "x-ms-discriminator-value": "TextClassification",
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "TargetRollingWindowSize": {
+ "description": "Forecasting target rolling window size.",
+ "required": [
+ "mode"
+ ],
+ "type": "object",
+ "properties": {
+ "mode": {
+ "description": "[Required] TargetRollingWindowSiz detection mode.",
+ "$ref": "#/definitions/TargetRollingWindowSizeMode",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "TextClassificationMultilabel": {
- "description": "Text Classification Multilabel task in AutoML NLP vertical.\r\nNLP - Natural Language Processing.",
- "type": "object",
- "allOf": [
+ "discriminator": "mode"
+ },
+ "TargetRollingWindowSizeMode": {
+ "description": "Target rolling windows size mode.",
+ "enum": [
+ "Auto",
+ "Custom"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TargetRollingWindowSizeMode",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/NlpVertical"
+ "value": "Auto",
+ "description": "Determine rolling windows size automatically."
},
{
- "$ref": "#/definitions/AutoMLVertical"
- }
- ],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric for Text-Classification-Multilabel task.\r\nCurrently only Accuracy is supported as primary metric, hence user need not set it explicitly.",
- "$ref": "#/definitions/ClassificationMultilabelPrimaryMetrics",
- "readOnly": true
+ "value": "Custom",
+ "description": "Use the specified rolling window size."
}
- },
- "x-ms-discriminator-value": "TextClassificationMultilabel",
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "TargetUtilizationScaleSettings": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/OnlineScaleSettings"
+ }
+ ],
+ "properties": {
+ "maxInstances": {
+ "format": "int32",
+ "description": "The maximum number of instances that the deployment can scale to. The quota will be reserved for max_instances.",
+ "default": 1,
+ "type": "integer"
+ },
+ "minInstances": {
+ "format": "int32",
+ "description": "The minimum number of instances to always be present.",
+ "default": 1,
+ "type": "integer"
+ },
+ "pollingInterval": {
+ "format": "duration",
+ "description": "The polling interval in ISO 8691 format. Only supports duration with precision as low as Seconds.",
+ "default": "PT1S",
+ "type": "string"
+ },
+ "targetUtilizationPercentage": {
+ "format": "int32",
+ "description": "Target CPU usage for the autoscaler.",
+ "default": 70,
+ "type": "integer"
+ }
},
- "TextNer": {
- "description": "Text-NER task in AutoML NLP vertical.\r\nNER - Named Entity Recognition.\r\nNLP - Natural Language Processing.",
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "TargetUtilization",
+ "additionalProperties": false
+ },
+ "TaskType": {
+ "description": "AutoMLJob Task type.",
+ "enum": [
+ "Classification",
+ "Regression",
+ "Forecasting",
+ "ImageClassification",
+ "ImageClassificationMultilabel",
+ "ImageObjectDetection",
+ "ImageInstanceSegmentation",
+ "TextClassification",
+ "TextClassificationMultilabel",
+ "TextNER"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TaskType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/NlpVertical"
+ "value": "Classification",
+ "description": "Classification in machine learning and statistics is a supervised learning approach in which\nthe computer program learns from the data given to it and make new observations or classifications."
},
{
- "$ref": "#/definitions/AutoMLVertical"
- }
- ],
- "properties": {
- "primaryMetric": {
- "description": "Primary metric for Text-NER task.\r\nOnly 'Accuracy' is supported for Text-NER, so user need not set this explicitly.",
- "$ref": "#/definitions/ClassificationPrimaryMetrics",
- "readOnly": true
- }
- },
- "x-ms-discriminator-value": "TextNER",
- "additionalProperties": false
- },
- "TrainingMode": {
- "description": "Training mode dictates whether to use distributed training or not",
- "enum": [
- "Auto",
- "Distributed",
- "NonDistributed"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TrainingMode",
- "modelAsString": true,
- "values": [
- {
- "value": "Auto",
- "description": "Auto mode"
- },
- {
- "value": "Distributed",
- "description": "Distributed training mode"
- },
- {
- "value": "NonDistributed",
- "description": "Non distributed training mode"
- }
- ]
- },
- "additionalProperties": false
- },
- "TrainingSettings": {
- "description": "Training related configuration.",
- "type": "object",
- "properties": {
- "enableDnnTraining": {
- "description": "Enable recommendation of DNN models.",
- "default": false,
- "type": "boolean"
+ "value": "Regression",
+ "description": "Regression means to predict the value using the input data. Regression models are used to predict a continuous value."
},
- "enableModelExplainability": {
- "description": "Flag to turn on explainability on best model.",
- "default": true,
- "type": "boolean"
+ {
+ "value": "Forecasting",
+ "description": "Forecasting is a special kind of regression task that deals with time-series data and creates forecasting model\nthat can be used to predict the near future values based on the inputs."
},
- "enableOnnxCompatibleModels": {
- "description": "Flag for enabling onnx compatible models.",
- "default": false,
- "type": "boolean"
+ {
+ "value": "ImageClassification",
+ "description": "Image Classification. Multi-class image classification is used when an image is classified with only a single label\nfrom a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog' or a 'duck'."
},
- "enableStackEnsemble": {
- "description": "Enable stack ensemble run.",
- "default": true,
- "type": "boolean"
+ {
+ "value": "ImageClassificationMultilabel",
+ "description": "Image Classification Multilabel. Multi-label image classification is used when an image could have one or more labels\nfrom a set of labels - e.g. an image could be labeled with both 'cat' and 'dog'."
},
- "enableVoteEnsemble": {
- "description": "Enable voting ensemble run.",
- "default": true,
- "type": "boolean"
+ {
+ "value": "ImageObjectDetection",
+ "description": "Image Object Detection. Object detection is used to identify objects in an image and locate each object with a\nbounding box e.g. locate all dogs and cats in an image and draw a bounding box around each."
},
- "ensembleModelDownloadTimeout": {
- "format": "duration",
- "description": "During VotingEnsemble and StackEnsemble model generation, multiple fitted models from the previous child runs are downloaded.\r\nConfigure this parameter with a higher value than 300 secs, if more time is needed.",
- "default": "PT5M",
- "type": "string"
+ {
+ "value": "ImageInstanceSegmentation",
+ "description": "Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level,\ndrawing a polygon around each object in the image."
},
- "stackEnsembleSettings": {
- "description": "Stack ensemble settings for stack ensemble run.",
- "$ref": "#/definitions/StackEnsembleSettings",
- "x-nullable": true
+ {
+ "value": "TextClassification",
+ "description": "Text classification (also known as text tagging or text categorization) is the process of sorting texts into categories.\nCategories are mutually exclusive."
+ },
+ {
+ "value": "TextClassificationMultilabel",
+ "description": "Multilabel classification task assigns each sample to a group (zero or more) of target labels."
},
- "trainingMode": {
- "description": "TrainingMode mode - Setting to 'auto' is same as setting it to 'non-distributed' for now, however in the future may result in mixed mode or heuristics based mode selection. Default is 'auto'.\r\nIf 'Distributed' then only distributed featurization is used and distributed algorithms are chosen.\r\nIf 'NonDistributed' then only non distributed algorithms are chosen.",
- "default": "Auto",
- "$ref": "#/definitions/TrainingMode"
+ {
+ "value": "TextNER",
+ "description": "Text Named Entity Recognition a.k.a. TextNER.\nNamed Entity Recognition (NER) is the ability to take free-form text and identify the occurrences of entities such as people, locations, organizations, and more."
}
+ ]
+ },
+ "additionalProperties": false
+ },
+ "TensorFlow": {
+ "description": "TensorFlow distribution configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DistributionConfiguration"
+ }
+ ],
+ "properties": {
+ "parameterServerCount": {
+ "format": "int32",
+ "description": "Number of parameter server tasks.",
+ "default": 0,
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
},
- "additionalProperties": false
+ "workerCount": {
+ "format": "int32",
+ "description": "Number of workers. If not specified, will default to the instance count.",
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ }
},
- "TrialComponent": {
- "description": "Trial component definition.",
- "required": [
- "command",
- "environmentId"
- ],
- "type": "object",
- "properties": {
- "codeId": {
- "description": "ARM resource ID of the code asset.",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
- },
- "command": {
- "description": "[Required] The command to execute on startup of the job. eg. \"python train.py\"",
- "minLength": 1,
- "pattern": "[a-zA-Z0-9_]",
- "type": "string",
- "x-ms-mutability": [
- "create",
- "read"
- ]
- },
- "distribution": {
- "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.",
- "$ref": "#/definitions/DistributionConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ "x-ms-discriminator-value": "TensorFlow",
+ "additionalProperties": false
+ },
+ "TextAnnotationType": {
+ "description": "Annotation type of text data.",
+ "enum": [
+ "Classification",
+ "NamedEntityRecognition"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TextAnnotationType",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Classification"
},
- "environmentId": {
- "description": "[Required] The ARM resource ID of the Environment specification for the job.",
- "pattern": "[a-zA-Z0-9_]",
- "type": "string"
+ {
+ "value": "NamedEntityRecognition"
+ }
+ ]
+ },
+ "additionalProperties": false
+ },
+ "TextClassification": {
+ "description": "Text Classification task in AutoML NLP vertical.\r\nNLP - Natural Language Processing.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/NlpVertical"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric for Text-Classification task.",
+ "default": "Accuracy",
+ "$ref": "#/definitions/ClassificationPrimaryMetrics"
+ }
+ },
+ "x-ms-discriminator-value": "TextClassification",
+ "additionalProperties": false
+ },
+ "TextClassificationMultilabel": {
+ "description": "Text Classification Multilabel task in AutoML NLP vertical.\r\nNLP - Natural Language Processing.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/NlpVertical"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric for Text-Classification-Multilabel task.\r\nCurrently only Accuracy is supported as primary metric, hence user need not set it explicitly.",
+ "$ref": "#/definitions/ClassificationMultilabelPrimaryMetrics",
+ "readOnly": true
+ }
+ },
+ "x-ms-discriminator-value": "TextClassificationMultilabel",
+ "additionalProperties": false
+ },
+ "TextNer": {
+ "description": "Text-NER task in AutoML NLP vertical.\r\nNER - Named Entity Recognition.\r\nNLP - Natural Language Processing.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/NlpVertical"
+ },
+ {
+ "$ref": "#/definitions/AutoMLVertical"
+ }
+ ],
+ "properties": {
+ "primaryMetric": {
+ "description": "Primary metric for Text-NER task.\r\nOnly 'Accuracy' is supported for Text-NER, so user need not set this explicitly.",
+ "$ref": "#/definitions/ClassificationPrimaryMetrics",
+ "readOnly": true
+ }
+ },
+ "x-ms-discriminator-value": "TextNER",
+ "additionalProperties": false
+ },
+ "TopNFeaturesByAttribution": {
+ "required": [
+ "filterType"
+ ],
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/MonitoringFeatureFilterBase"
+ }
+ ],
+ "properties": {
+ "top": {
+ "format": "int32",
+ "description": "The number of top features to include.",
+ "default": 10,
+ "type": "integer",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
+ },
+ "x-ms-discriminator-value": "TopNByAttribution",
+ "additionalProperties": false
+ },
+ "TrainingMode": {
+ "description": "Training mode dictates whether to use distributed training or not",
+ "enum": [
+ "Auto",
+ "Distributed",
+ "NonDistributed"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TrainingMode",
+ "modelAsString": true,
+ "values": [
+ {
+ "value": "Auto",
+ "description": "Auto mode"
},
- "environmentVariables": {
- "description": "Environment variables included in the job.",
- "type": "object",
- "additionalProperties": {
- "type": "string",
- "x-nullable": true
- },
- "x-ms-mutability": [
- "create",
- "read"
- ],
- "x-nullable": true
+ {
+ "value": "Distributed",
+ "description": "Distributed training mode"
},
- "resources": {
- "description": "Compute Resource configuration for the job.",
- "default": "{}",
- "$ref": "#/definitions/JobResourceConfiguration",
- "x-ms-mutability": [
- "create",
- "read"
- ]
+ {
+ "value": "NonDistributed",
+ "description": "Non distributed training mode"
}
- },
- "additionalProperties": false
+ ]
},
- "TriggerBase": {
- "required": [
- "triggerType"
- ],
- "type": "object",
- "properties": {
- "endTime": {
- "description": "Specifies end time of schedule in ISO 8601, but without a UTC offset. Refer https://en.wikipedia.org/wiki/ISO_8601.\r\nRecommented format would be \"2022-06-01T00:00:01\"\r\nIf not present, the schedule will run indefinitely",
- "type": "string",
- "x-nullable": true
- },
- "startTime": {
- "description": "Specifies start time of schedule in ISO 8601 format, but without a UTC offset.",
+ "additionalProperties": false
+ },
+ "TrainingSettings": {
+ "description": "Training related configuration.",
+ "type": "object",
+ "properties": {
+ "enableDnnTraining": {
+ "description": "Enable recommendation of DNN models.",
+ "default": false,
+ "type": "boolean"
+ },
+ "enableModelExplainability": {
+ "description": "Flag to turn on explainability on best model.",
+ "default": true,
+ "type": "boolean"
+ },
+ "enableOnnxCompatibleModels": {
+ "description": "Flag for enabling onnx compatible models.",
+ "default": false,
+ "type": "boolean"
+ },
+ "enableStackEnsemble": {
+ "description": "Enable stack ensemble run.",
+ "default": true,
+ "type": "boolean"
+ },
+ "enableVoteEnsemble": {
+ "description": "Enable voting ensemble run.",
+ "default": true,
+ "type": "boolean"
+ },
+ "ensembleModelDownloadTimeout": {
+ "format": "duration",
+ "description": "During VotingEnsemble and StackEnsemble model generation, multiple fitted models from the previous child runs are downloaded.\r\nConfigure this parameter with a higher value than 300 secs, if more time is needed.",
+ "default": "PT5M",
+ "type": "string"
+ },
+ "stackEnsembleSettings": {
+ "description": "Stack ensemble settings for stack ensemble run.",
+ "$ref": "#/definitions/StackEnsembleSettings",
+ "x-nullable": true
+ },
+ "trainingMode": {
+ "description": "TrainingMode mode - Setting to 'auto' is same as setting it to 'non-distributed' for now, however in the future may result in mixed mode or heuristics based mode selection. Default is 'auto'.\r\nIf 'Distributed' then only distributed featurization is used and distributed algorithms are chosen.\r\nIf 'NonDistributed' then only non distributed algorithms are chosen.",
+ "default": "Auto",
+ "$ref": "#/definitions/TrainingMode"
+ }
+ },
+ "additionalProperties": false
+ },
+ "TrialComponent": {
+ "description": "Trial component definition.",
+ "required": [
+ "command",
+ "environmentId"
+ ],
+ "type": "object",
+ "properties": {
+ "codeId": {
+ "description": "ARM resource ID of the code asset.",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "command": {
+ "description": "[Required] The command to execute on startup of the job. eg. \"python train.py\"",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ },
+ "distribution": {
+ "description": "Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.",
+ "$ref": "#/definitions/DistributionConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "environmentId": {
+ "description": "[Required] The ARM resource ID of the Environment specification for the job.",
+ "minLength": 1,
+ "pattern": "[a-zA-Z0-9_]",
+ "type": "string"
+ },
+ "environmentVariables": {
+ "description": "Environment variables included in the job.",
+ "type": "object",
+ "additionalProperties": {
"type": "string",
"x-nullable": true
},
- "timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
- "default": "UTC",
- "type": "string"
- },
- "triggerType": {
- "description": "[Required] ",
- "$ref": "#/definitions/TriggerType",
- "x-ms-mutability": [
- "create",
- "read",
- "update"
- ]
- }
- },
- "discriminator": "triggerType"
- },
- "TriggerType": {
- "enum": [
- "Recurrence",
- "Cron"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "TriggerType",
- "modelAsString": true,
- "values": [
- {
- "value": "Recurrence"
- },
- {
- "value": "Cron"
- }
- ]
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
},
- "additionalProperties": false
+ "resources": {
+ "description": "Compute Resource configuration for the job.",
+ "default": "{}",
+ "$ref": "#/definitions/JobResourceConfiguration",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "TritonInferencingServer": {
- "description": "Triton inferencing server configurations.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/InferencingServer"
- }
- ],
- "properties": {
- "inferenceConfiguration": {
- "description": "Inference configuration for Triton.",
- "$ref": "#/definitions/OnlineInferenceConfiguration",
- "x-nullable": true
- }
- },
- "x-ms-discriminator-value": "Triton",
- "additionalProperties": false
+ "additionalProperties": false
+ },
+ "TriggerBase": {
+ "required": [
+ "triggerType"
+ ],
+ "type": "object",
+ "properties": {
+ "endTime": {
+ "description": "Specifies end time of schedule in ISO 8601, but without a UTC offset. Refer https://en.wikipedia.org/wiki/ISO_8601.\r\nRecommented format would be \"2022-06-01T00:00:01\"\r\nIf not present, the schedule will run indefinitely",
+ "type": "string",
+ "x-nullable": true
+ },
+ "startTime": {
+ "description": "Specifies start time of schedule in ISO 8601 format, but without a UTC offset.",
+ "type": "string",
+ "x-nullable": true
+ },
+ "timeZone": {
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "default": "UTC",
+ "type": "string"
+ },
+ "triggerType": {
+ "description": "[Required] ",
+ "$ref": "#/definitions/TriggerType",
+ "x-ms-mutability": [
+ "create",
+ "read",
+ "update"
+ ]
+ }
},
- "TritonModelJobInput": {
- "type": "object",
- "allOf": [
+ "discriminator": "triggerType"
+ },
+ "TriggerType": {
+ "enum": [
+ "Recurrence",
+ "Cron"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "TriggerType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobInput"
+ "value": "Recurrence"
},
{
- "$ref": "#/definitions/JobInput"
+ "value": "Cron"
}
- ],
- "x-ms-discriminator-value": "triton_model",
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "TritonInferencingServer": {
+ "description": "Triton inferencing server configurations.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/InferencingServer"
+ }
+ ],
+ "properties": {
+ "inferenceConfiguration": {
+ "description": "Inference configuration for Triton.",
+ "$ref": "#/definitions/OnlineInferenceConfiguration",
+ "x-nullable": true
+ }
+ },
+ "x-ms-discriminator-value": "Triton",
+ "additionalProperties": false
+ },
+ "TritonModelJobInput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobInput"
+ },
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "x-ms-discriminator-value": "triton_model",
+ "additionalProperties": false
+ },
+ "TritonModelJobOutput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobOutput"
+ },
+ {
+ "$ref": "#/definitions/JobOutput"
+ }
+ ],
+ "x-ms-discriminator-value": "triton_model",
+ "additionalProperties": false
+ },
+ "TruncationSelectionPolicy": {
+ "description": "Defines an early termination policy that cancels a given percentage of runs at each evaluation interval.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/EarlyTerminationPolicy"
+ }
+ ],
+ "properties": {
+ "truncationPercentage": {
+ "format": "int32",
+ "description": "The percentage of runs to cancel at each evaluation interval.",
+ "default": 0,
+ "type": "integer"
+ }
},
- "TritonModelJobOutput": {
- "type": "object",
- "allOf": [
+ "x-ms-discriminator-value": "TruncationSelection",
+ "additionalProperties": false
+ },
+ "UriFileDataVersion": {
+ "description": "uri-file data version entity",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataVersionBase"
+ }
+ ],
+ "x-ms-discriminator-value": "uri_file",
+ "additionalProperties": false
+ },
+ "UriFileJobInput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobInput"
+ },
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "x-ms-discriminator-value": "uri_file",
+ "additionalProperties": false
+ },
+ "UriFileJobOutput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobOutput"
+ },
+ {
+ "$ref": "#/definitions/JobOutput"
+ }
+ ],
+ "x-ms-discriminator-value": "uri_file",
+ "additionalProperties": false
+ },
+ "UriFolderDataVersion": {
+ "description": "uri-folder data version entity",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/DataVersionBase"
+ }
+ ],
+ "x-ms-discriminator-value": "uri_folder",
+ "additionalProperties": false
+ },
+ "UriFolderJobInput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobInput"
+ },
+ {
+ "$ref": "#/definitions/JobInput"
+ }
+ ],
+ "x-ms-discriminator-value": "uri_folder",
+ "additionalProperties": false
+ },
+ "UriFolderJobOutput": {
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/AssetJobOutput"
+ },
+ {
+ "$ref": "#/definitions/JobOutput"
+ }
+ ],
+ "x-ms-discriminator-value": "uri_folder",
+ "additionalProperties": false
+ },
+ "UseStl": {
+ "description": "Configure STL Decomposition of the time-series target column.",
+ "enum": [
+ "None",
+ "Season",
+ "SeasonTrend"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "UseStl",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobOutput"
+ "value": "None",
+ "description": "No stl decomposition."
},
{
- "$ref": "#/definitions/JobOutput"
- }
- ],
- "x-ms-discriminator-value": "triton_model",
- "additionalProperties": false
- },
- "TruncationSelectionPolicy": {
- "description": "Defines an early termination policy that cancels a given percentage of runs at each evaluation interval.",
- "type": "object",
- "allOf": [
- {
- "$ref": "#/definitions/EarlyTerminationPolicy"
- }
- ],
- "properties": {
- "truncationPercentage": {
- "format": "int32",
- "description": "The percentage of runs to cancel at each evaluation interval.",
- "default": 0,
- "type": "integer"
- }
- },
- "x-ms-discriminator-value": "TruncationSelection",
- "additionalProperties": false
- },
- "UriFileDataVersion": {
- "description": "uri-file data version entity",
- "type": "object",
- "allOf": [
+ "value": "Season"
+ },
{
- "$ref": "#/definitions/DataVersionBase"
+ "value": "SeasonTrend"
}
- ],
- "x-ms-discriminator-value": "uri_file",
- "additionalProperties": false
+ ]
},
- "UriFileJobInput": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "UserIdentity": {
+ "description": "User identity configuration.",
+ "type": "object",
+ "allOf": [
+ {
+ "$ref": "#/definitions/IdentityConfiguration"
+ }
+ ],
+ "x-ms-discriminator-value": "UserIdentity",
+ "additionalProperties": false
+ },
+ "ValidationMetricType": {
+ "description": "Metric computation method to use for validation metrics in image tasks.",
+ "enum": [
+ "None",
+ "Coco",
+ "Voc",
+ "CocoVoc"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "ValidationMetricType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobInput"
+ "value": "None",
+ "description": "No metric."
},
{
- "$ref": "#/definitions/JobInput"
- }
- ],
- "x-ms-discriminator-value": "uri_file",
- "additionalProperties": false
- },
- "UriFileJobOutput": {
- "type": "object",
- "allOf": [
+ "value": "Coco",
+ "description": "Coco metric."
+ },
{
- "$ref": "#/definitions/AssetJobOutput"
+ "value": "Voc",
+ "description": "Voc metric."
},
{
- "$ref": "#/definitions/JobOutput"
+ "value": "CocoVoc",
+ "description": "CocoVoc metric."
}
- ],
- "x-ms-discriminator-value": "uri_file",
- "additionalProperties": false
+ ]
+ },
+ "additionalProperties": false
+ },
+ "Webhook": {
+ "description": "Webhook base",
+ "required": [
+ "webhookType"
+ ],
+ "type": "object",
+ "properties": {
+ "eventType": {
+ "description": "Send callback on a specified notification event",
+ "type": "string",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ],
+ "x-nullable": true
+ },
+ "webhookType": {
+ "description": "[Required] Specifies the type of service to send a callback",
+ "$ref": "#/definitions/WebhookType",
+ "x-ms-mutability": [
+ "create",
+ "read"
+ ]
+ }
},
- "UriFolderDataVersion": {
- "description": "uri-folder data version entity",
- "type": "object",
- "allOf": [
+ "discriminator": "webhookType"
+ },
+ "WebhookType": {
+ "description": "Enum to determine the webhook callback service type.",
+ "enum": [
+ "AzureDevOps"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "WebhookType",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/DataVersionBase"
+ "value": "AzureDevOps"
}
- ],
- "x-ms-discriminator-value": "uri_folder",
- "additionalProperties": false
+ ]
},
- "UriFolderJobInput": {
- "type": "object",
- "allOf": [
+ "additionalProperties": false
+ },
+ "WeekDay": {
+ "description": "Enum of weekday",
+ "enum": [
+ "Monday",
+ "Tuesday",
+ "Wednesday",
+ "Thursday",
+ "Friday",
+ "Saturday",
+ "Sunday"
+ ],
+ "type": "string",
+ "x-ms-enum": {
+ "name": "WeekDay",
+ "modelAsString": true,
+ "values": [
{
- "$ref": "#/definitions/AssetJobInput"
+ "value": "Monday",
+ "description": "Monday weekday"
},
{
- "$ref": "#/definitions/JobInput"
- }
- ],
- "x-ms-discriminator-value": "uri_folder",
- "additionalProperties": false
- },
- "UriFolderJobOutput": {
- "type": "object",
- "allOf": [
+ "value": "Tuesday",
+ "description": "Tuesday weekday"
+ },
{
- "$ref": "#/definitions/AssetJobOutput"
+ "value": "Wednesday",
+ "description": "Wednesday weekday"
},
{
- "$ref": "#/definitions/JobOutput"
- }
- ],
- "x-ms-discriminator-value": "uri_folder",
- "additionalProperties": false
- },
- "UserIdentity": {
- "description": "User identity configuration.",
- "type": "object",
- "allOf": [
+ "value": "Thursday",
+ "description": "Thursday weekday"
+ },
+ {
+ "value": "Friday",
+ "description": "Friday weekday"
+ },
+ {
+ "value": "Saturday",
+ "description": "Saturday weekday"
+ },
{
- "$ref": "#/definitions/IdentityConfiguration"
+ "value": "Sunday",
+ "description": "Sunday weekday"
}
- ],
- "x-ms-discriminator-value": "UserIdentity",
- "additionalProperties": false
+ ]
},
- "UseStl": {
- "description": "Configure STL Decomposition of the time-series target column.",
- "enum": [
- "None",
- "Season",
- "SeasonTrend"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "UseStl",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No stl decomposition."
- },
- {
- "value": "Season"
- },
- {
- "value": "SeasonTrend"
- }
- ]
- },
- "additionalProperties": false
- },
- "ValidationMetricType": {
- "description": "Metric computation method to use for validation metrics in image tasks.",
- "enum": [
- "None",
- "Coco",
- "Voc",
- "CocoVoc"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "ValidationMetricType",
- "modelAsString": true,
- "values": [
- {
- "value": "None",
- "description": "No metric."
- },
- {
- "value": "Coco",
- "description": "Coco metric."
- },
- {
- "value": "Voc",
- "description": "Voc metric."
- },
- {
- "value": "CocoVoc",
- "description": "CocoVoc metric."
- }
- ]
- },
- "additionalProperties": false
- },
- "WeekDay": {
- "description": "Enum of weekday",
- "enum": [
- "Monday",
- "Tuesday",
- "Wednesday",
- "Thursday",
- "Friday",
- "Saturday",
- "Sunday"
- ],
- "type": "string",
- "x-ms-enum": {
- "name": "WeekDay",
- "modelAsString": true,
- "values": [
- {
- "value": "Monday",
- "description": "Monday weekday"
- },
- {
- "value": "Tuesday",
- "description": "Tuesday weekday"
- },
- {
- "value": "Wednesday",
- "description": "Wednesday weekday"
- },
- {
- "value": "Thursday",
- "description": "Thursday weekday"
- },
- {
- "value": "Friday",
- "description": "Friday weekday"
- },
- {
- "value": "Saturday",
- "description": "Saturday weekday"
- },
- {
- "value": "Sunday",
- "description": "Sunday weekday"
- }
- ]
- },
- "additionalProperties": false
- }
- },
- "securityDefinitions": {
- "azure_auth": {
- "type": "oauth2",
- "flow": "implicit",
- "authorizationUrl": "https://login.microsoftonline.com/common/oauth2/authorize",
- "scopes": {
- "user_impersonation": "impersonate your user account"
- },
- "description": "Azure Active Directory OAuth2 Flow."
- }
+ "additionalProperties": false
+ }
+ },
+ "securityDefinitions": {
+ "azure_auth": {
+ "type": "oauth2",
+ "flow": "implicit",
+ "authorizationUrl": "https://login.microsoftonline.com/common/oauth2/authorize",
+ "scopes": {
+ "user_impersonation": "impersonate your user account"
+ },
+ "description": "Azure Active Directory OAuth2 Flow."
}
- }
\ No newline at end of file
+ }
+}
\ No newline at end of file