Warn when loading a model with a different Python version (#192)

Author: nlathia

CHANGELOG.md

@@ -4,6 +4,8 @@
 
 **🆕  New functionality**
 
+`modelstore` will issue a warning if you `load()` a model with a different version of Python than the version that was used to train the model ([#192](https://github.com/operatorai/modelstore/pull/192)).
+
 You can now add any extra metadata to your model when uploading it, using `upload(domain, model, extra_metadata={ ... })` ([#185](https://github.com/operatorai/modelstore/pull/185)); if you want to upload extra _files_ with your model, then you should now use `extra_files=` instead of `extras=` ([#187](https://github.com/operatorai/modelstore/pull/187)).
 
 **🐛  Bug fixes & general updates**

bin/_config

@@ -1,5 +1,5 @@
-export PYTHON_VERSION=3.7.13
-#export PYTHON_VERSION=3.8.12
+#export PYTHON_VERSION=3.7.13
+export PYTHON_VERSION=3.8.12
 #export PYTHON_VERSION=3.9.9
 
 export VIRTUALENV_NAME=$(pyenv local) || ""

modelstore/metadata/code/code.py

@@ -42,7 +42,7 @@ def generate(cls, deps_list: list, created: datetime = None) -> "Code":
             # control time stamps of mock model objects
             created = datetime.now()
         return Code(
-            runtime=f"python:{runtime.get_python_version()}",
+            runtime=runtime.get_python_version(),
             user=runtime.get_user(),
             created=created.strftime("%Y/%m/%d/%H:%M:%S"),
             dependencies=remove_nones(versioned_deps),

modelstore/metadata/code/runtime.py

@@ -18,7 +18,8 @@
 def get_python_version() -> str:
     """ Returns the current python version """
     vers = sys.version_info
-    return ".".join(str(x) for x in [vers.major, vers.minor, vers.micro])
+    version = ".".join(str(x) for x in [vers.major, vers.minor, vers.micro])
+    return f"python:{version}"
 
 
 def get_user() -> str:

modelstore/models/annoy.py

@@ -66,6 +66,8 @@ def get_params(self, **kwargs) -> dict:
         }
 
     def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
+        super().load(model_path, meta_data)
+
         # pylint: disable=import-outside-toplevel
         from annoy import AnnoyIndex
 

modelstore/models/catboost.py

@@ -92,6 +92,8 @@ def get_params(self, **kwargs) -> dict:
         return kwargs["model"].get_params()
 
     def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
+        super().load(model_path, meta_data)
+
         # pylint: disable=import-outside-toplevel
         import catboost
 

modelstore/models/fastai.py

@@ -15,6 +15,7 @@
 from functools import partial
 from pathlib import Path
 from typing import Any
+import warnings
 
 from modelstore.metadata import metadata
 from modelstore.models.model_manager import ModelManager
@@ -78,6 +79,8 @@ def _get_functions(self, **kwargs) -> list:
         ]
 
     def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
+        super().load(model_path, meta_data)
+
         # pylint: disable=import-outside-toplevel
         import fastai
 
@@ -88,11 +91,8 @@ def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
 
         version = meta_data.code.dependencies.get(FastAIManager.NAME, "?")
         if version != fastai.__version__:
-            logger.warn(
-                "Model was saved with fastai==%s, trying to load it with fastai==%s",
-                version,
-                fastai.__version__,
-            )
+            msg = f"Model was saved with fastai=={version}, loading it with fastai=={fastai.__version__}"
+            warnings.warn(msg, RuntimeWarning)
 
         model_file = _model_file_path(model_path)
         return load_learner(model_file)

modelstore/models/gensim.py

@@ -68,6 +68,8 @@ def get_params(self, **kwargs) -> dict:
         return params
 
     def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
+        super().load(model_path, meta_data)
+
         # pylint: disable=import-outside-toplevel
         from gensim.models import Word2Vec
 

modelstore/models/lightgbm.py

@@ -62,6 +62,8 @@ def get_params(self, **kwargs) -> dict:
         return kwargs["model"].params
 
     def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
+        super().load(model_path, meta_data)
+
         # pylint: disable=import-outside-toplevel
         import lightgbm as lgb
 

modelstore/models/model_manager.py

@@ -21,6 +21,7 @@
 
 import numpy as np
 from modelstore.metadata import metadata
+from modelstore.metadata.code.runtime import get_python_version
 from modelstore.storage.storage import CloudStorage
 
 
@@ -88,10 +89,16 @@ def _required_kwargs(self) -> list:
 
     @abstractmethod
     def load(self, model_path: str, meta_data: metadata.Summary) -> Any:
-        """
-        Loads a model, stored in model_path, back into memory
-        """
-        raise NotImplementedError()
+        """ Loads a model, stored in model_path, back into memory """
+        version = get_python_version()
+        if meta_data is not None and meta_data.code is not None:
+            if version != meta_data.code.runtime:
+                train = f"model was trained with {meta_data.code.runtime}"
+                load = f"but is being loaded with {version}"
+                warnings.warn(
+                    f"{train}, {load}",
+                    category=RuntimeWarning,
+                )
 
     def _validate_kwargs(self, **kwargs):
         """Ensures that the required kwargs are set"""