def __init__()

in src/stepfunctions/steps/sagemaker.py [0:0]

• 18 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, state_id, endpoint_config_name, model_name, initial_instance_count, instance_type, variant_name='AllTraffic', data_capture_config=None, tags=None, **kwargs):
        """
        Args:
            state_id (str): State name whose length **must be** less than or equal to 128 unicode characters. State names **must be** unique within the scope of the whole state machine.
            endpoint_config_name (str or Placeholder): The name of the endpoint configuration to create. We recommend to use :py:class:`~stepfunctions.inputs.ExecutionInput` placeholder collection to pass the value dynamically in each execution.
            model_name (str or Placeholder): The name of the SageMaker model to attach to the endpoint configuration. We recommend to use :py:class:`~stepfunctions.inputs.ExecutionInput` placeholder collection to pass the value dynamically in each execution.
            initial_instance_count (int or Placeholder): The initial number of instances to run in the ``Endpoint`` created from this ``Model``.
            instance_type (str or Placeholder): The EC2 instance type to deploy this Model to. For example, 'ml.p2.xlarge'.
            variant_name (str, optional): The name of the production variant.
            data_capture_config (sagemaker.model_monitor.DataCaptureConfig, optional): Specifies
                configuration related to Endpoint data capture for use with
                Amazon SageMaker Model Monitoring. Default: None.
            tags (list[dict], optional): `List of tags <https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html>`_ to associate with the resource.
        """
        parameters = {
            'EndpointConfigName': endpoint_config_name,
            'ProductionVariants': [{
                'InitialInstanceCount': initial_instance_count,
                'InstanceType': instance_type,
                'ModelName': model_name,
                'VariantName': variant_name
            }]
        }

        if isinstance(data_capture_config, DataCaptureConfig):
            parameters['DataCaptureConfig'] = data_capture_config._to_request_dict()
            
        if tags:
            parameters['Tags'] = tags_dict_to_kv_list(tags)

        """
        Example resource arn: arn:aws:states:::sagemaker:createEndpointConfig
        """

        kwargs[Field.Resource.value] = get_service_integration_arn(SAGEMAKER_SERVICE_NAME,
                                                                   SageMakerApi.CreateEndpointConfig)

        kwargs[Field.Parameters.value] = parameters

        super(EndpointConfigStep, self).__init__(state_id, **kwargs)