Enable OnnxTransformer to accept KeyDataViewTypes as if they were UInt32 - #4824
Merged
Conversation
harishsk
reviewed
Feb 11, 2020
harishsk
left a comment
harishsk
left a comment
Contributor
There was a problem hiding this comment.
Can you please add a test and also a comment in the code describing the scenario this is necessary for?
Contributor
Author
|
/azp run |
|
Azure Pipelines successfully started running 1 pipeline(s). |
harishsk
reviewed
Feb 11, 2020
ghost
locked as resolved and limited conversation to collaborators
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
3 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Addresses microsoft/NimbusML#426
As discussed offline with @harishsk , @ganik and @pieths , the update in here is the best temporary solution to the problem.
Simply enables OnnxTransformer to accept a
KeyDataViewTypecolumn as input of a model that actually expects anUInt32input column. This, because of the way that NimbusML works with Category columns in Pandas' DataFrames, by converting them intoKeyDataViewTypecolumns in ML.NET, without actually adding KeyToValueTransformers into the pipeline.