aws / aws/aws-step-functions-data-science-sdk-python

Feature Request: Improved Support/Documentation for PipelineModel

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Description

While an example includes use of PipelineModel: https://github.com/aws/aws-step-functions-data-science-sdk-python/blob/main/src/stepfunctions/template/pipeline/inference.py#L128

This is a no-op: https://github.com/aws/aws-step-functions-data-science-sdk-python/blob/main/src/stepfunctions/template/pipeline/inference.py#L142

Setting the parameters property results in no changes to the CreateModel API call.
Instead, this method should be called: https://github.com/aws/aws-step-functions-data-science-sdk-python/blob/master/src/stepfunctions/steps/states.py#L201

which performs the desired update: self.fields[Field.Parameters.value] = params

Overall, while the example should likely be updated and documentation provided on use of PipelineModel, this method of parameter updating feels like a workaround. Ideally, ModelStep could take PipelineModel as input.

Contributor guide

Open the contributing guide

Research direction

Start with the PipelineModel example and no-op parameters property in src/stepfunctions/template/pipeline/inference.py, then compare it with the parameter update in src/stepfunctions/steps/states.py. Determine the intended relationship between PipelineModel and ModelStep, update the example and documentation, and ensure parameter changes affect the CreateModel API call.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, python
Domain
backend-api-design, machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
30/100

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