class_docstr: Poll the auto ML job until it reaches a terminal state; raise AirflowException with the failure reason.
  
  .. seealso::
      For more information on how to use this sensor, take a look at the guide:
      :ref:`howto/sensor:SageMakerAutoMLSensor`
  
  :param job_name: unique name of the AutoML job to watch.
class_docstr_tok: ["Poll","the","auto","ML","job","until","it","reaches","a","terminal","state",";","raise","AirflowException","with","the","failure","reason",".","..","seealso",":",":","For","more","information","on","how","to","use","this","sensor",",","take","a","look","at","the","guide",":",":","ref",":","`","howto\/sensor",":","SageMakerAutoMLSensor","`",":","param","job_name",":","unique","name","of","the","AutoML","job","to","watch","."]
code: def __init__(self, *, job_name: str, **kwargs):
      super().__init__(resource_type="autoML job", **kwargs)
      self.job_name = job_name
  
imports: from __future__ import annotations
  import time
  from functools import cached_property
  from typing import TYPE_CHECKING, Sequence
  from deprecated import deprecated
  from airflow.exceptions import AirflowException, AirflowProviderDeprecationWarning, AirflowSkipException
  from airflow.providers.amazon.aws.hooks.sagemaker import LogState, SageMakerHook
  from airflow.sensors.base import BaseSensorOperator
label_desc: Use image node_id 1 to create a new SageMakerAutoMLSensor object from inherited base classes: SageMakerBaseSensor with example: obj = SageMakerAutoMLSensor()