| :mod:`airflow.providers.amazon.aws.operators.sagemaker_training` |
| ================================================================ |
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| .. py:module:: airflow.providers.amazon.aws.operators.sagemaker_training |
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| Module Contents |
| --------------- |
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| .. py:class:: SageMakerTrainingOperator(*, config: dict, wait_for_completion: bool = True, print_log: bool = True, check_interval: int = 30, max_ingestion_time: Optional[int] = None, action_if_job_exists: str = 'increment', **kwargs) |
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| Bases: :class:`airflow.providers.amazon.aws.operators.sagemaker_base.SageMakerBaseOperator` |
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| Initiate a SageMaker training job. |
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| This operator returns The ARN of the training job created in Amazon SageMaker. |
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| :param config: The configuration necessary to start a training job (templated). |
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| For details of the configuration parameter see :py:meth:`SageMaker.Client.create_training_job` |
| :type config: dict |
| :param aws_conn_id: The AWS connection ID to use. |
| :type aws_conn_id: str |
| :param wait_for_completion: If wait is set to True, the time interval, in seconds, |
| that the operation waits to check the status of the training job. |
| :type wait_for_completion: bool |
| :param print_log: if the operator should print the cloudwatch log during training |
| :type print_log: 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 training job |
| :type check_interval: int |
| :param max_ingestion_time: If wait is set to True, the operation fails if the training job |
| doesn't finish within max_ingestion_time seconds. If you set this parameter to None, |
| the operation does not timeout. |
| :type max_ingestion_time: int |
| :param action_if_job_exists: Behaviour if the job name already exists. Possible options are "increment" |
| (default) and "fail". |
| :type action_if_job_exists: str |
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| .. attribute:: integer_fields |
| :annotation: = [['ResourceConfig', 'InstanceCount'], ['ResourceConfig', 'VolumeSizeInGB'], ['StoppingCondition', 'MaxRuntimeInSeconds']] |
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| .. method:: expand_role(self) |
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| .. method:: execute(self, context) |
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