code: def _default_job_spec(
      region: Text,
      image_uri: Text,
      entry_point_args: Optional[Sequence[Text]] = None,
  ) -> Dict[str, Any]:
      """Creates a basic job_spec for cloud AI Training.
  
      Args:
          region: Target region for running the AI Platform Training job.
          image_uri: based image used to use for AI Platform Training
          entry_point_args: Args to pass in to the training job.
  
      Returns:
          a dictionary corresponding to AI Platform Training job spec
      """
      training_inputs = {}
  
      if entry_point_args is not None:
          training_inputs["args"] = entry_point_args
      training_inputs["region"] = region
      training_inputs["scaleTier"] = "CUSTOM"
      training_inputs["masterType"] = DEFAULT_INSTANCE_TYPE
      training_inputs["workerType"] = DEFAULT_INSTANCE_TYPE
      training_inputs["masterConfig"] = {"imageUri": image_uri}
      training_inputs["workerCount"] = DEFAULT_NUM_WORKERS
      job_spec = {"trainingInput": training_inputs}
      job_spec["job_id"] = "cloud_fit_{}".format(
          datetime.datetime.now().strftime("%Y%m%d%H%M%S")
      )
      return job_spec
  
file_path: cloud/src/python/tensorflow_cloud/tuner/cloud_fit_client.py
imports: import datetime
  import os
  import pickle
  from typing import Text, Dict, Optional, Sequence, Any, Generator
  from absl import logging
  import google.auth
  from googleapiclient import discovery
  import tensorflow
  from tensorflow_cloud.tuner import cloud_fit_utils
  from tensorflow_cloud.utils import google_api_client
label_desc: Use image node_id 3 for calling a global function with example usage: _default_job_spec(region, image_uri, entry_point_args) and returns: job_spec