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Merge branch 'aws:master' into fix/make-instance-type-optional
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‎doc/amazon_sagemaker_model_building_pipeline.rst

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‎doc/index.rst

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@@ -102,3 +102,14 @@ You can use Amazon SageMaker Processing to perform data processing tasks such as
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:maxdepth: 2
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amazon_sagemaker_processing
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*****************************************
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Amazon SageMaker Model Building Pipeline
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*****************************************
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You can use Amazon SageMaker Model Building Pipelines to orchestrate your machine learning workflow.
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.. toctree::
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:maxdepth: 2
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amazon_sagemaker_model_building_pipeline

‎doc/overview.rst

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@@ -1727,6 +1727,16 @@ For more information, see `SageMaker Workflow in Apache Airflow`_.
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.. _SageMaker Workflow in Apache Airflow: https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/workflow/README.rst
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************************************
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SageMaker Model Building Pipeline
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************************************
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You can use Amazon SageMaker Model Building Pipelines to orchestrate your machine learning workflow.
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For more information, see `SageMaker Model Building Pipeline`_.
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.. _SageMaker Model Building Pipeline: https://github.com/aws/sagemaker-python-sdk/blob/master/doc/amazon_sagemaker_model_building_pipeline.rst
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**************************
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SageMaker Model Monitoring
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**************************

‎doc/requirements.txt

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sphinx==3.1.1
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sphinx==3.1.2
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sphinx-rtd-theme==0.5.0
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docutils==0.15.2
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packaging==20.9

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

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@@ -52,6 +52,7 @@ Execution Variables
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.. autoclass:: sagemaker.workflow.execution_variables.ExecutionVariable
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.. autoclass:: sagemaker.workflow.execution_variables.ExecutionVariables
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:members: START_DATETIME, CURRENT_DATETIME, PIPELINE_EXECUTION_ID, PIPELINE_EXECUTION_ARN, PIPELINE_NAME, PIPELINE_ARN
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Functions
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---------
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.. autoclass:: sagemaker.workflow.parameters.ParameterFloat
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.. autoclass:: sagemaker.workflow.parameters.ParameterBoolean
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Pipeline
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--------
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.. autoclass:: sagemaker.workflow.pipeline._PipelineExecution
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:members:
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Pipeline Context
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------------------
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.. autoclass:: sagemaker.workflow.pipeline_context.PipelineSession
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:members:
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Parallelism Configuration
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-------------------------
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.. autoclass:: sagemaker.workflow.step_collections.EstimatorTransformer
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.. autoclass:: sagemaker.workflow.model_step.ModelStep
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Steps
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-----
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‎src/sagemaker/estimator.py

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@@ -1280,6 +1280,7 @@ def register(
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model_name=None,
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drift_check_baselines=None,
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customer_metadata_properties=None,
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domain=None,
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**kwargs,
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):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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**kwargs: Passed to invocation of ``create_model()``. Implementations may customize
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``create_model()`` to accept ``**kwargs`` to customize model creation during
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deploy. For more, see the implementation docs.
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description,
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drift_check_baselines=drift_check_baselines,
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customer_metadata_properties=customer_metadata_properties,
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domain=domain,
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)
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@property

‎src/sagemaker/huggingface/model.py

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approval_status=None,
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description=None,
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drift_check_baselines=None,
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customer_metadata_properties=None,
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domain=None,
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):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
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@@ -331,6 +333,10 @@ def register(
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or "PendingManualApproval". Defaults to ``PendingManualApproval``.
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description (str): Model Package description. Defaults to ``None``.
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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Returns:
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A `sagemaker.model.ModelPackage` instance.
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approval_status,
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description,
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drift_check_baselines=drift_check_baselines,
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customer_metadata_properties=customer_metadata_properties,
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domain=domain,
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)
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def prepare_container_def(

‎src/sagemaker/image_uri_config/sklearn.json

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"us-west-2": "246618743249"
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},
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"repository": "sagemaker-scikit-learn"
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},
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"1.0-1": {
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"py_versions": ["py3"],
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"registries": {
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"af-south-1": "510948584623",
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"ap-east-1": "651117190479",
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"ap-northeast-1": "354813040037",
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"ap-northeast-2": "366743142698",
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"ap-northeast-3": "867004704886",
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"ap-south-1": "720646828776",
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"ap-southeast-1": "121021644041",
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"ap-southeast-2": "783357654285",
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"ca-central-1": "341280168497",
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"cn-north-1": "450853457545",
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"cn-northwest-1": "451049120500",
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"eu-central-1": "492215442770",
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"eu-north-1": "662702820516",
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"eu-west-1": "141502667606",
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"eu-west-2": "764974769150",
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"eu-west-3": "659782779980",
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"eu-south-1": "978288397137",
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"me-south-1": "801668240914",
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"sa-east-1": "737474898029",
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"us-east-1": "683313688378",
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"us-east-2": "257758044811",
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"us-gov-west-1": "414596584902",
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"us-iso-east-1": "833128469047",
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"us-west-1": "746614075791",
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"us-west-2": "246618743249"
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},
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"repository": "sagemaker-scikit-learn"
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}
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}
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}

‎src/sagemaker/model.py

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drift_check_baselines=None,
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customer_metadata_properties=None,
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validation_specification=None,
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domain=None,
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):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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A `sagemaker.model.ModelPackage` instance.
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drift_check_baselines=drift_check_baselines,
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customer_metadata_properties=customer_metadata_properties,
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validation_specification=validation_specification,
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domain=domain,
367371
)
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model_package = self.sagemaker_session.create_model_package_from_containers(
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**model_pkg_args

‎src/sagemaker/mxnet/model.py

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description=None,
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drift_check_baselines=None,
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customer_metadata_properties=None,
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domain=None,
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):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
189+
domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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Returns:
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description,
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drift_check_baselines=drift_check_baselines,
216219
customer_metadata_properties=customer_metadata_properties,
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domain=domain,
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)
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def prepare_container_def(

‎src/sagemaker/pytorch/model.py

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description=None,
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drift_check_baselines=None,
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customer_metadata_properties=None,
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domain=None,
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):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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description,
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drift_check_baselines=drift_check_baselines,
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customer_metadata_properties=customer_metadata_properties,
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domain=domain,
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)
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def prepare_container_def(

‎src/sagemaker/session.py

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validation_specification=None,
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domain=None,
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):
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"""Get request dictionary for CreateModelPackage API.
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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"""
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28352838
model_pkg_request = get_create_model_package_request(
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customer_metadata_properties=customer_metadata_properties,
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validation_specification=validation_specification,
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domain=domain,
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)
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def submit(request):
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drift_check_baselines=None,
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customer_metadata_properties=None,
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validation_specification=None,
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):
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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dict: A dictionary of method argument names and values.
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"""
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model_package_args["customer_metadata_properties"] = customer_metadata_properties
42904297
if validation_specification is not None:
42914298
model_package_args["validation_specification"] = validation_specification
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if domain is not None:
4300+
model_package_args["domain"] = domain
42924301
return model_package_args
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42944303

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customer_metadata_properties=None,
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validation_specification=None,
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domain=None,
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):
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"""Get request dictionary for CreateModelPackage API.
43144324
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drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
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customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
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metadata properties (default: None).
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domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
43404352
"""
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43424354
if all([model_package_name, model_package_group_name]):
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request_dict["CustomerMetadataProperties"] = customer_metadata_properties
43634375
if validation_specification:
43644376
request_dict["ValidationSpecification"] = validation_specification
4377+
if domain is not None:
4378+
request_dict["Domain"] = domain
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if containers is not None:
43664380
if not all([content_types, response_types]):
43674381
raise ValueError(

‎src/sagemaker/sklearn/model.py

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marketplace_cert=False,
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approval_status=None,
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description=None,
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drift_check_baselines=None,
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customer_metadata_properties=None,
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domain=None,
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):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
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175178
approval_status (str): Model Approval Status, values can be "Approved", "Rejected",
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or "PendingManualApproval" (default: "PendingManualApproval").
177180
description (str): Model Package description (default: None).
181+
drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
182+
customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
183+
metadata properties (default: None).
184+
domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
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"MACHINE_LEARNING" (default: None).
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202210
marketplace_cert,
203211
approval_status,
204212
description,
213+
drift_check_baselines=drift_check_baselines,
214+
customer_metadata_properties=customer_metadata_properties,
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domain=domain,
205216
)
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207218
def prepare_container_def(

‎src/sagemaker/tensorflow/model.py

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description=None,
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drift_check_baselines=None,
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customer_metadata_properties=None,
208+
domain=None,
208209
):
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"""Creates a model package for creating SageMaker models or listing on Marketplace.
210211
@@ -232,7 +233,8 @@ def register(
232233
drift_check_baselines (DriftCheckBaselines): DriftCheckBaselines object (default: None).
233234
customer_metadata_properties (dict[str, str]): A dictionary of key-value paired
234235
metadata properties (default: None).
235-
236+
domain (str): Domain values can be "COMPUTER_VISION", "NATURAL_LANGUAGE_PROCESSING",
237+
"MACHINE_LEARNING" (default: None).
236238
237239
Returns:
238240
A `sagemaker.model.ModelPackage` instance.
@@ -262,6 +264,7 @@ def register(
262264
description,
263265
drift_check_baselines=drift_check_baselines,
264266
customer_metadata_properties=customer_metadata_properties,
267+
domain=domain,
265268
)
266269

267270
def deploy(

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