def METHOD_NAME(name, image, command,
                      chief_cpu_limit, chief_memory_limit, chief_port,
                      workers, worker_image, worker_cpu_limit, worker_memory_limit,
                      parameter_servers, ps_image, ps_cpu_limit, ps_memory_limit, ps_port,
                      gpus, rdma,
                      tensorboard,
                      worker_port, annotations=[],
                      evaluator=False, evaluator_cpu_limit='0', evaluator_memory_limit='0',
                      env=[], data=[], sync_source=None,
                      metrics=['Train-accuracy:PERCENTAGE'],
                      arena_image='cheyang/arena_launcher:v0.7',
                      timeout_hours=240):
    """This function submits Distributed TFJob in Estimator mode.
          Args:
            name: the name of parameter_servers_op
            image: the docker image name of training job
            data: specify the datasource to mount to the job, like <name_of_datasource>:<mount_point_on_job>
            command: the command to run
          """
    return distributed_tf_op(name=name, image=image, command=command, envs=envs, data=data, sync_source=sync_source,
                      workers=workers, worker_image=worker_image, worker_cpu_limit=worker_cpu_limit, worker_memory_limit=worker_memory,
                      parameter_servers=parameter_servers, ps_image=ps_image, ps_cpu_limit=ps_cpu_limit, ps_memory_limit=ps_memory_limit,
                      gpus=gpus, rdma=rdma,
                      chief=True,
                      chief_cpu_limit=chief_cpu_limit,
                      worker_port=worker_port,
                      ps_port=ps_port,
                      tensorboard=tensorboard,
                      metrics=metrics,
                      arena_image=arena_image,
                      timeout_hours=timeout_hours)