Dynamic customer_metadata_properties

[alex-vinnik-sp]

Hi there,

I see that there is new parameter in class RegisterModel(...) in version 2.77.1 to attach customer metadata to a model. However, I am trying to figure if there is a way to pass this metadata dynamically from an estimator/training step during pipeline execution. Any ideas?

   customer_metadata_properties = {"key1": "value1"}
    estimator = XGBoost(
        entry_point="training.py",
        source_dir=os.path.join(DATA_DIR, "sip"),
        instance_type=instance_type,
        instance_count=instance_count,
        framework_version="0.90-2",
        sagemaker_session=sagemaker_session,
        py_version="py3",
        role=role,
    )
    step_register = RegisterModel(
        name="MyRegisterModelStep",
        estimator=estimator,
        model_data=model_uri_param,
        content_types=["application/json"],
        response_types=["application/json"],
        inference_instances=["ml.t2.medium", "ml.m5.xlarge"],
        transform_instances=["ml.m5.xlarge"],
        model_package_group_name="testModelPackageGroup",
        model_metrics=model_metrics,
        drift_check_baselines=drift_check_baselines,
        customer_metadata_properties=customer_metadata_properties,
    )