text: #
  # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
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  # regarding copyright ownership.  The ASF licenses this file
  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License.  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  # KIND, either express or implied.  See the License for the
  # specific language governing permissions and limitations
  # under the License.
  
  from airflow.exceptions import AirflowException
  from airflow.providers.amazon.aws.hooks.aws_hook import AwsHook
  from airflow.providers.amazon.aws.operators.sagemaker_base import SageMakerBaseOperator
  from airflow.utils.decorators import apply_defaults
  
  
  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,
                   *args, **kwargs):
          super().__init__(config=config,
                           *args, **kwargs)
  
          self.config = config
  
      def expand_role(self):
          if 'ExecutionRoleArn' in self.config:
              hook = AwsHook(self.aws_conn_id)
              self.config['ExecutionRoleArn'] = hook.expand_role(self.config['ExecutionRoleArn'])
  
      def execute(self, context):
          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']
                  )
              }
  