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doc: automlstep doc update (aws#732)
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doc/amazon_sagemaker_model_building_pipeline.rst

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@@ -362,6 +362,52 @@ Example:
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prefix=model_prefix
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)
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AutoMLStep
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`````````````
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Referable Property List:
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- `DescribeAutoMLJob`_
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- `BestCandidateProperties.ModelInsightsJsonReportPath`_
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- `BestCandidateProperties.ExplainabilityJsonReportPath`_
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.. _DescribeAutoMLJob: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJob
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.. _BestCandidateProperties.ModelInsightsJsonReportPath: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CandidateArtifactLocations.html#sagemaker-Type-CandidateArtifactLocations-ModelInsights
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.. _BestCandidateProperties.ExplainabilityJsonReportPath: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CandidateArtifactLocations.html#sagemaker-Type-CandidateArtifactLocations-Explainability
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Example:
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.. code-block:: python
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step_automl = AutoMLStep(...)
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auto_ml_model = step_automl.get_best_model(<role>)
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model_metrics = ModelMetrics(
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model_statistics=MetricsSource(
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s3_uri=auto_ml_step.properties.BestCandidateProperties.ModelInsightsJsonReportPath,
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content_type="application/json",
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),
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explainability=MetricsSource(
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s3_uri=auto_ml_step.properties.BestCandidateProperties.ExplainabilityJsonReportPath,
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content_type="application/json",
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)
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)
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step_args_register_model = auto_ml_model.register(
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content_types=["text/csv"],
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response_types=["text/csv"],
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inference_instances=["ml.t2.medium", "ml.m5.large"],
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transform_instances=["ml.m5.large"],
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model_package_group_name="My model package group name",
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approval_status="PendingManualApproval",
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model_metrics=model_metrics,
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)
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step_register_model = ModelStep(
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name="auto-ml-model-register",
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step_args=step_args_register_model,
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)
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CreateModelStep
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````````````````
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Referable Property List:

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