def METHOD_NAME(sagemaker_session, coach_tensorflow_latest_version, cpu_instance_type):
    estimator = _test_coach(
        sagemaker_session,
        RLFramework.TENSORFLOW,
        coach_tensorflow_latest_version,
        cpu_instance_type,
    )
    job_name = unique_name_from_base("test-coach-tf")
    with timeout(minutes=15):
        estimator.fit(job_name=job_name)
    endpoint_name = "test-tf-coach-deploy-{}".format(sagemaker_timestamp())
    with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
        predictor = estimator.deploy(1, cpu_instance_type)
        observation = numpy.asarray([0, 0, 0, 0])
        action = predictor.predict(observation)
    assert action == {"predictions": [[0.5, 0.5]]}