Source code for airflow.providers.amazon.aws.operators.sagemaker_endpoint
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from typing import Optional
from botocore.exceptions import ClientError
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 SageMakerEndpointOperator(SageMakerBaseOperator):
    """
    Create a SageMaker endpoint.
    This operator returns The ARN of the endpoint created in Amazon SageMaker
    :param config:
        The configuration necessary to create an endpoint.
        If you need to create a SageMaker endpoint based on an existed
        SageMaker model and an existed SageMaker endpoint config::
            config = endpoint_configuration;
        If you need to create all of SageMaker model, SageMaker endpoint-config and SageMaker endpoint::
            config = {
                'Model': model_configuration,
                'EndpointConfig': endpoint_config_configuration,
                'Endpoint': endpoint_configuration
            }
        For details of the configuration parameter of model_configuration see
        :py:meth:`SageMaker.Client.create_model`
        For details of the configuration parameter of endpoint_config_configuration see
        :py:meth:`SageMaker.Client.create_endpoint_config`
        For details of the configuration parameter of endpoint_configuration see
        :py:meth:`SageMaker.Client.create_endpoint`
    :type config: dict
    :param aws_conn_id: The AWS connection ID to use.
    :type aws_conn_id: str
    :param wait_for_completion: Whether the operator should wait until the endpoint creation finishes.
    :type wait_for_completion: bool
    :param check_interval: If wait is set to True, this is the time interval, in seconds, that this operation
        waits before polling the status of the endpoint creation.
    :type check_interval: int
    :param max_ingestion_time: If wait is set to True, this operation fails if the endpoint creation doesn't
        finish within max_ingestion_time seconds. If you set this parameter to None it never times out.
    :type max_ingestion_time: int
    :param operation: Whether to create an endpoint or update an endpoint. Must be either 'create or 'update'.
    :type operation: str
    """
    @apply_defaults
    def __init__(
        self,
        *,
        config: dict,
        wait_for_completion: bool = True,
        check_interval: int = 30,
        max_ingestion_time: Optional[int] = None,
        operation: str = 'create',
        **kwargs,
    ):
        super().__init__(config=config, **kwargs)
        self.config = config
        self.wait_for_completion = wait_for_completion
        self.check_interval = check_interval
        self.max_ingestion_time = max_ingestion_time
        self.operation = operation.lower()
        if self.operation not in ['create', 'update']:
            raise ValueError('Invalid value! Argument operation has to be one of "create" and "update"')
        self.create_integer_fields()
[docs]    def create_integer_fields(self) -> None:
        """Set fields which should be casted to integers."""
        if 'EndpointConfig' in self.config:
            self.integer_fields = [['EndpointConfig', 'ProductionVariants', 'InitialInstanceCount']] 
[docs]    def expand_role(self) -> None:
        if 'Model' not in self.config:
            return
        hook = AwsBaseHook(self.aws_conn_id, client_type='iam')
        config = self.config['Model']
        if 'ExecutionRoleArn' in config:
            config['ExecutionRoleArn'] = hook.expand_role(config['ExecutionRoleArn']) 
[docs]    def execute(self, context) -> dict:
        self.preprocess_config()
        model_info = self.config.get('Model')
        endpoint_config_info = self.config.get('EndpointConfig')
        endpoint_info = self.config.get('Endpoint', self.config)
        if model_info:
            self.log.info('Creating SageMaker model %s.', model_info['ModelName'])
            self.hook.create_model(model_info)
        if endpoint_config_info:
            self.log.info('Creating endpoint config %s.', endpoint_config_info['EndpointConfigName'])
            self.hook.create_endpoint_config(endpoint_config_info)
        if self.operation == 'create':
            sagemaker_operation = self.hook.create_endpoint
            log_str = 'Creating'
        elif self.operation == 'update':
            sagemaker_operation = self.hook.update_endpoint
            log_str = 'Updating'
        else:
            raise ValueError('Invalid value! Argument operation has to be one of "create" and "update"')
        self.log.info('%s SageMaker endpoint %s.', log_str, endpoint_info['EndpointName'])
        try:
            response = sagemaker_operation(
                endpoint_info,
                wait_for_completion=self.wait_for_completion,
                check_interval=self.check_interval,
                max_ingestion_time=self.max_ingestion_time,
            )
        except ClientError:  # Botocore throws a ClientError if the endpoint is already created
            self.operation = 'update'
            sagemaker_operation = self.hook.update_endpoint
            log_str = 'Updating'
            response = sagemaker_operation(
                endpoint_info,
                wait_for_completion=self.wait_for_completion,
                check_interval=self.check_interval,
                max_ingestion_time=self.max_ingestion_time,
            )
        if response['ResponseMetadata']['HTTPStatusCode'] != 200:
            raise AirflowException(f'Sagemaker endpoint creation failed: {response}')
        else:
            return {
                'EndpointConfig': self.hook.describe_endpoint_config(endpoint_info['EndpointConfigName']),
                'Endpoint': self.hook.describe_endpoint(endpoint_info['EndpointName']),  
            }