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MLBlocks is a pretty heavy-weight dependency as it requires tensorflow, xgboost, etc. to be installed. To just "explore" pipelines from S3, users shoudn't need MLBlocks.
Desired functionality:
for all methods except PipelineExplorer.score_pipeline and Pipeline.score_template, MLBlocks should not need to be installed
if the user wants to score pipelines or templates using PipelineExplorer.score_pipeline and Pipeline.score_template, they can enable this by pip install piex[mlblocks] (or piex[scoring] or piex[all] or some other variant)
Note that this would require a workaround for using MLPipeline to load pipelines/templates for the express purpose of extracting metadata from them
The text was updated successfully, but these errors were encountered:
MLBlocks is a pretty heavy-weight dependency as it requires tensorflow, xgboost, etc. to be installed. To just "explore" pipelines from S3, users shoudn't need MLBlocks.
Desired functionality:
PipelineExplorer.score_pipeline
andPipeline.score_template
, MLBlocks should not need to be installedPipelineExplorer.score_pipeline
andPipeline.score_template
, they can enable this bypip install piex[mlblocks]
(orpiex[scoring]
orpiex[all]
or some other variant)Note that this would require a workaround for using MLPipeline to load pipelines/templates for the express purpose of extracting metadata from them
The text was updated successfully, but these errors were encountered: