airflow.providers.amazon.aws.operators.sagemaker_tuning
¶
Module Contents¶
-
class
airflow.providers.amazon.aws.operators.sagemaker_tuning.
SageMakerTuningOperator
(*, config: dict, wait_for_completion: bool = True, check_interval: int = 30, max_ingestion_time: Optional[int] = None, **kwargs)[source]¶ Bases:
airflow.providers.amazon.aws.operators.sagemaker_base.SageMakerBaseOperator
Initiate a SageMaker hyperparameter tuning job.
This operator returns The ARN of the tuning job created in Amazon SageMaker.
- Parameters
config (dict) --
The configuration necessary to start a tuning job (templated).
For details of the configuration parameter see
SageMaker.Client.create_hyper_parameter_tuning_job()
aws_conn_id (str) -- The AWS connection ID to use.
wait_for_completion (bool) -- Set to True to wait until the tuning job finishes.
check_interval (int) -- If wait is set to True, the time interval, in seconds, that this operation waits to check the status of the tuning job.
max_ingestion_time (int) -- If wait is set to True, the operation fails if the tuning job doesn't finish within max_ingestion_time seconds. If you set this parameter to None, the operation does not timeout.
-
integer_fields
= [['HyperParameterTuningJobConfig', 'ResourceLimits', 'MaxNumberOfTrainingJobs'], ['HyperParameterTuningJobConfig', 'ResourceLimits', 'MaxParallelTrainingJobs'], ['TrainingJobDefinition', 'ResourceConfig', 'InstanceCount'], ['TrainingJobDefinition', 'ResourceConfig', 'VolumeSizeInGB'], ['TrainingJobDefinition', 'StoppingCondition', 'MaxRuntimeInSeconds']][source]¶