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Hi there,
Thanks for reaching out and for the question.
Unlike the Estimator subclass which takes 'metric_definitions ' as a parameter, the ProcessingStep does not take on this parameter. An alternative is to make use of the the property_files parameter within the ProcessongStep (see link [1.]) to store information from the output of a processing step which can later be processed using the 'JsonGet' (see link [2.]). At best this will allow you to persist the metrics you'd like to capture and you can fetch the json file from the s3 output location, however this will not be published to the UI like your training jobs. Link [3.] provides an example of how this propertyfile can be defined and passed in the ProcessingStep.
[1.] https://sagemaker.readthedocs.io/en/stable/workflows/pipelines/sagemaker.workflow.pipelines.html#sagemaker.workflow.steps.ProcessingStep [2.] https://docs.aws.amazon.com/sagemaker/latest/dg/build-and-manage-propertyfile.html [3.] https://github.com/aws/amazon-sagemaker-examples/blob/main/sagemaker-pipelines/tabular/customizing_build_train_deploy_project/modelbuild/pipelines/customer_churn/pipeline.py#L183
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