Merge branch 'master' into lzao/debugger-rule-removal

Author: mufaddal-rohawala

doc/amazon_sagemaker_model_building_pipeline.rst

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

doc/api/governance/index.rst

@@ -0,0 +1,9 @@
+###############
+Governance APIs
+###############
+
+.. toctree::
+   :maxdepth: 1
+   :glob:
+
+   *

doc/api/governance/model_card.rst

@@ -0,0 +1,43 @@
+Amazon SageMaker Model Cards
+----------------------------
+
+For more information about using model cards with the SageMaker Python SDK,
+see `Amazon SageMaker Model Cards <https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards.html>`__ in the *Amazon SageMaker Developer Guide*.
+
+.. currentmodule:: sagemaker.model_card
+
+.. autoclass:: AdditionalInformation
+    :show-inheritance:
+
+.. autoclass:: Environment
+    :show-inheritance:
+
+.. autoclass:: EvaluationJob
+    :show-inheritance:
+
+.. autoclass:: Function
+    :show-inheritance:
+
+.. autoclass:: IntendedUses
+    :show-inheritance:
+
+.. autoclass:: Metric
+    :show-inheritance:
+
+.. autoclass:: MetricGroup
+    :show-inheritance:
+
+.. autoclass:: ModelCard
+    :show-inheritance:
+
+.. autoclass:: ModelOverview
+    :show-inheritance:
+
+.. autoclass:: ObjectiveFunction
+    :show-inheritance:
+
+.. autoclass:: TrainingDetails
+    :show-inheritance:
+
+.. autoclass:: TrainingJobDetails
+    :show-inheritance:

doc/api/index.rst

@@ -11,4 +11,5 @@ The SageMaker Python SDK consists of a variety classes for preparing data, train
     training/index
     training/distributed
     inference/index
+    governance/index
     utility/index

doc/workflows/pipelines/sagemaker.workflow.pipelines.rst

@@ -168,3 +168,5 @@ Steps
 .. autoclass:: sagemaker.workflow.clarify_check_step.ClarifyCheckStep
 
 .. autoclass:: sagemaker.workflow.fail_step.FailStep
+
+.. autoclass:: sagemaker.workflow.automl_step.AutoMLStep

setup.py

@@ -48,7 +48,7 @@ def read_requirements(filename):
 # Declare minimal set for installation
 required_packages = [
     "attrs>=20.3.0,<23",
-    "boto3>=1.20.21,<2.0",
+    "boto3>=1.26.20,<2.0",
     "google-pasta",
     "numpy>=1.9.0,<2.0",
     "protobuf>=3.1,<4.0",