airflow.providers.amazon.aws.sensors.sagemaker

Module Contents

Classes

SageMakerBaseSensor

Contains general sensor behavior for SageMaker.

SageMakerEndpointSensor

Polls the endpoint state until it reaches a terminal state. Raises an

SageMakerTransformSensor

Polls the transform job until it reaches a terminal state. Raises an

SageMakerTuningSensor

Asks for the state of the tuning state until it reaches a terminal state.

SageMakerTrainingSensor

Polls the training job until it reaches a terminal state. Raises an

class airflow.providers.amazon.aws.sensors.sagemaker.SageMakerBaseSensor(*, aws_conn_id='aws_default', **kwargs)[source]

Bases: airflow.sensors.base.BaseSensorOperator

Contains general sensor behavior for SageMaker.

Subclasses should implement get_sagemaker_response() and state_from_response() methods. Subclasses should also implement NON_TERMINAL_STATES and FAILED_STATE methods.

ui_color = #ededed[source]
get_hook()[source]

Get SageMakerHook.

poke(context)[source]

Function that the sensors defined while deriving this class should override.

abstract non_terminal_states()[source]

Placeholder for returning states with should not terminate.

abstract failed_states()[source]

Placeholder for returning states with are considered failed.

abstract get_sagemaker_response()[source]

Placeholder for checking status of a SageMaker task.

get_failed_reason_from_response(response)[source]

Placeholder for extracting the reason for failure from an AWS response.

abstract state_from_response(response)[source]

Placeholder for extracting the state from an AWS response.

class airflow.providers.amazon.aws.sensors.sagemaker.SageMakerEndpointSensor(*, endpoint_name, **kwargs)[source]

Bases: SageMakerBaseSensor

Polls the endpoint state until it reaches a terminal state. Raises an AirflowException with the failure reason if a failed state is reached.

See also

For more information on how to use this sensor, take a look at the guide: Wait on an Amazon SageMaker endpoint state

Parameters

endpoint_name -- Name of the endpoint instance to watch.

template_fields :Sequence[str] = ['endpoint_name'][source]
template_ext :Sequence[str] = [][source]
non_terminal_states()[source]

Placeholder for returning states with should not terminate.

failed_states()[source]

Placeholder for returning states with are considered failed.

get_sagemaker_response()[source]

Placeholder for checking status of a SageMaker task.

get_failed_reason_from_response(response)[source]

Placeholder for extracting the reason for failure from an AWS response.

state_from_response(response)[source]

Placeholder for extracting the state from an AWS response.

class airflow.providers.amazon.aws.sensors.sagemaker.SageMakerTransformSensor(*, job_name, **kwargs)[source]

Bases: SageMakerBaseSensor

Polls the transform job until it reaches a terminal state. Raises an AirflowException with the failure reason if a failed state is reached.

See also

For more information on how to use this sensor, take a look at the guide: Wait on an Amazon SageMaker transform job state

Parameters

job_name (str) -- Name of the transform job to watch.

template_fields :Sequence[str] = ['job_name'][source]
template_ext :Sequence[str] = [][source]
non_terminal_states()[source]

Placeholder for returning states with should not terminate.

failed_states()[source]

Placeholder for returning states with are considered failed.

get_sagemaker_response()[source]

Placeholder for checking status of a SageMaker task.

get_failed_reason_from_response(response)[source]

Placeholder for extracting the reason for failure from an AWS response.

state_from_response(response)[source]

Placeholder for extracting the state from an AWS response.

class airflow.providers.amazon.aws.sensors.sagemaker.SageMakerTuningSensor(*, job_name, **kwargs)[source]

Bases: SageMakerBaseSensor

Asks for the state of the tuning state until it reaches a terminal state. Raises an AirflowException with the failure reason if a failed state is reached.

See also

For more information on how to use this sensor, take a look at the guide: Wait on an Amazon SageMaker tuning job state

Parameters

job_name (str) -- Name of the tuning instance to watch.

template_fields :Sequence[str] = ['job_name'][source]
template_ext :Sequence[str] = [][source]
non_terminal_states()[source]

Placeholder for returning states with should not terminate.

failed_states()[source]

Placeholder for returning states with are considered failed.

get_sagemaker_response()[source]

Placeholder for checking status of a SageMaker task.

get_failed_reason_from_response(response)[source]

Placeholder for extracting the reason for failure from an AWS response.

state_from_response(response)[source]

Placeholder for extracting the state from an AWS response.

class airflow.providers.amazon.aws.sensors.sagemaker.SageMakerTrainingSensor(*, job_name, print_log=True, **kwargs)[source]

Bases: SageMakerBaseSensor

Polls the training job until it reaches a terminal state. Raises an AirflowException with the failure reason if a failed state is reached.

See also

For more information on how to use this sensor, take a look at the guide: Wait on an Amazon SageMaker training job state

Parameters
  • job_name -- Name of the training job to watch.

  • print_log -- Prints the cloudwatch log if True; Defaults to True.

template_fields :Sequence[str] = ['job_name'][source]
template_ext :Sequence[str] = [][source]
init_log_resource(hook)[source]

Set tailing LogState for associated training job.

non_terminal_states()[source]

Placeholder for returning states with should not terminate.

failed_states()[source]

Placeholder for returning states with are considered failed.

get_sagemaker_response()[source]

Placeholder for checking status of a SageMaker task.

get_failed_reason_from_response(response)[source]

Placeholder for extracting the reason for failure from an AWS response.

state_from_response(response)[source]

Placeholder for extracting the state from an AWS response.

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