Source code for airflow.providers.amazon.aws.operators.sagemaker_model

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from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
from airflow.providers.amazon.aws.operators.sagemaker_base import SageMakerBaseOperator
from airflow.utils.decorators import apply_defaults


[docs]class SageMakerModelOperator(SageMakerBaseOperator):
    """
    Create a SageMaker model.

    This operator returns The ARN of the model created in Amazon SageMaker

    :param config: The configuration necessary to create a model.

        For details of the configuration parameter see :py:meth:`SageMaker.Client.create_model`
    :type config: dict
    :param aws_conn_id: The AWS connection ID to use.
    :type aws_conn_id: str
    """

    @apply_defaults
    def __init__(self, *, config, **kwargs):
        super().__init__(config=config, **kwargs)

        self.config = config

[docs]    def expand_role(self) -> None:
        if 'ExecutionRoleArn' in self.config:
            hook = AwsBaseHook(self.aws_conn_id, client_type='iam')
            self.config['ExecutionRoleArn'] = hook.expand_role(self.config['ExecutionRoleArn'])

[docs]    def execute(self, context) -> dict:
        self.preprocess_config()

        self.log.info('Creating SageMaker Model %s.', self.config['ModelName'])
        response = self.hook.create_model(self.config)
        if response['ResponseMetadata']['HTTPStatusCode'] != 200:
            raise AirflowException('Sagemaker model creation failed: %s' % response)
        else:
            return {'Model': self.hook.describe_model(self.config['ModelName'])}