fix: environment variables specified in Model or Estimator are not passed through to SageMaker ModelStep - Githubissues

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

Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS

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fix: environment variables specified in Model or Estimator are not passed through to SageMaker ModelStep #160

Closed ca-nguyen closed 3 years ago

ca-nguyen commented 3 years ago

Issue #, if available: #82

Description of changes: 1. fix: environment variables are overwritten and not passed through to SageMaker ModelStep

The environment variables are not passed from the model to ModelStep parameters (they are overwritten here) for models without instance type (models other than sagemake.model.FrameworkModel)
With this change, the Model env parameters are passed to the ModelStep.

New bug uncovered: 2. fix: env variables defined in the Estimator are not translated to Model when calling TrainingStep.get_expected_model()

Fixed by passing the env from the estimator to the expected Model
Added a new estimator (pca_estimator_with_env) with defined env parameters to use in test and confirm that the env variables are passed through to the Model
With this change, the env variables defined in the estimator are passed to the expected Model when calling TrainingStep.get_expected_model()

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StepFunctions-Bot commented 3 years ago

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CodeBuild project: AutoBuildProject6AEA49D1-sEHrOdk7acJc
Commit ID: dda1dfbe2b3b4a4651e2c35148e156570aaded9f
Result: SUCCEEDED
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