yangaws commented on a change in pull request #4091: [AIRFLOW-2524] Update SageMaker hook, operator and sensor for training, tuning and transform URL: https://github.com/apache/incubator-airflow/pull/4091#discussion_r228373427
########## File path: airflow/contrib/operators/sagemaker_transform_operator.py ########## @@ -0,0 +1,123 @@ +# -*- coding: utf-8 -*- +# +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# 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.contrib.operators.sagemaker_base_operator import SageMakerBaseOperator +from airflow.utils.decorators import apply_defaults +from airflow.exceptions import AirflowException + + +class SageMakerTransformOperator(SageMakerBaseOperator): + """ + Initiate a SageMaker transform + This operator returns The ARN of the model created in Amazon SageMaker + + :param config: The configuration necessary to start a transform job (templated) + :type config: dict + :param model_config: + The configuration necessary to create a SageMaker model, the default is none + which means the SageMaker model used for the SageMaker transform job already exists. + If given, it will be used to create a SageMaker model before creating + the SageMaker transform job + :type model_config: dict + :param aws_conn_id: The AWS connection ID to use. + :type aws_conn_id: string + :param wait_for_completion: if the program should keep running until job finishes + :type wait_for_completion: bool + :param check_interval: if wait is set to be true, this is the time interval + in seconds which the operator will check the status of the transform job + :type check_interval: int + :param max_ingestion_time: if wait is set to be true, the operator will fail + if the transform job hasn't finish within the max_ingestion_time in seconds + (Caution: be careful to set this parameters because transform can take very long) + :type max_ingestion_time: int + """ + + @apply_defaults + def __init__(self, + config, + aws_conn_id='aws_default', + wait_for_completion=True, + check_interval=30, + max_ingestion_time=None, + *args, **kwargs): + super(SageMakerTransformOperator, self).__init__(config=config, + aws_conn_id=aws_conn_id, + *args, **kwargs) + + self.aws_conn_id = aws_conn_id + self.config = config + self.wait_for_completion = wait_for_completion + self.check_interval = check_interval + self.max_ingestion_time = max_ingestion_time + self.create_integer_fields() + + def create_integer_fields(self): + self.integer_fields = [ + ['Transform', 'TransformResources', 'InstanceCount'], + ['Transform', 'MaxConcurrentTransforms'], + ['Transform', 'MaxPayloadInMB'] + ] + if 'Transform' not in self.config: + for field in self.integer_fields: + field.pop(0) + + def expand_role(self): + if 'Model' not in self.config: + return + config = self.config['Model'] + if 'ExecutionRoleArn' in config: + config['ExecutionRoleArn'] = \ + self.hook.expand_role(config['ExecutionRoleArn']) + + def execute(self, context): + self.preprocess_config() + + model_config = self.config['Model']\ + if 'Model' in self.config else None + transform_config = self.config['Transform']\ + if 'Transform' in self.config else self.config + + if model_config: + self.log.info( + 'Creating SageMaker Model %s for transform job' + % model_config['ModelName'] + ) + self.hook.create_model(model_config) + + self.log.info( + 'Creating SageMaker transform Job %s.' + % transform_config['TransformJobName'] + ) Review comment: self.config can be in two format Either a combination of both model and transform config { 'Model': { ModelConfig } 'Transform': { TransformConfig } } Or just transform config(same as the one in above after 'Transform') { TransformConfig } So we will evaluate transform_config. It's either self.config or self.config['Transform']. Hence when we reach this line, transform_config will never have a key 'Transform' here. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
