Source code for airflow.contrib.sensors.sagemaker_tuning_sensor
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from airflow.contrib.hooks.sagemaker_hook import SageMakerHook
from airflow.contrib.sensors.sagemaker_base_sensor import SageMakerBaseSensor
from airflow.utils.decorators import apply_defaults
[docs]class SageMakerTuningSensor(SageMakerBaseSensor):
    """
    Asks for the state of the tuning state until it reaches a terminal state.
    The sensor will error if the job errors, throwing a AirflowException
    containing the failure reason.
    :param job_name: job_name of the tuning instance to check the state of
    :type job_name: str
    """
[docs]    template_fields = ['job_name'] 
    @apply_defaults
    def __init__(self,
                 job_name,
                 *args,
                 **kwargs):
        super(SageMakerTuningSensor, self).__init__(*args, **kwargs)
        self.job_name = job_name
[docs]    def non_terminal_states(self):
        return SageMakerHook.non_terminal_states 
[docs]    def failed_states(self):
        return SageMakerHook.failed_states 
[docs]    def get_sagemaker_response(self):
        sagemaker = SageMakerHook(aws_conn_id=self.aws_conn_id)
        self.log.info('Poking Sagemaker Tuning Job %s', self.job_name)
        return sagemaker.describe_tuning_job(self.job_name) 
[docs]    def get_failed_reason_from_response(self, response):
        return response['FailureReason'] 
[docs]    def state_from_response(self, response):
        return response['HyperParameterTuningJobStatus']