code: def run_experiment_cloud(
      run_experiment_kwargs: Dict[str, Any],
      run_kwargs: Optional[Dict[str, Any]] = None,
  ) -> Optional[Dict[str, str]]:
      """A wrapper for run API and tf-models-official run_experiment.
  
      This method takes a dictionary of the parameters for run and a dictionary
      of the parameters for run_experiment to run the experiment directly on GCP.
  
      Args:
        run_experiment_kwargs: keyword arguments for `train_lib.run_experiment`. The
          docs can be found at
        https://github.com/tensorflow/models/blob/master/official/core/train_lib.py
          The distribution_strategy param is ignored because the distribution
          strategy is selected based on run_kwargs.
        run_kwargs: keyword arguments for `tfc.run`. The docs can be found at
        https://github.com/tensorflow/cloud/blob/master/src/python/tensorflow_cloud/core/run.py
          The params entry_point and distribution_strategy are ignored.
  
      Returns:
        A dictionary with two keys.
          1. 'job_id': the training job id.
          2. 'docker_image': Docker image generated for the training job.
      """
      if run_kwargs is None:
          run_kwargs = dict()
      distribution_strategy = get_distribution_strategy_str(run_kwargs)
      run_experiment_kwargs.update(
          dict(distribution_strategy=distribution_strategy)
      )
      file_id = str(uuid.uuid4())
      params_file = save_params(run_experiment_kwargs, file_id)
      entry_point = copy_entry_point(file_id, params_file)
  
      run_kwargs.update(
          dict(entry_point=entry_point, distribution_strategy=None)
      )
      info = run.run(**run_kwargs)
      os.remove(entry_point)
      os.remove(params_file)
      return info
  
imports: import os
  import pickle
  from typing import Any, Dict, Optional
  import uuid
  from ..None import machine_config
  from ..None import run
  import tensorflow
  import tensorflow_datasets
  from official.legacy.image_classification.efficientnet import efficientnet_model
  from official.legacy.image_classification.resnet import resnet_model
label_desc: Use image node_id 11 for calling a global function with example usage: run_experiment_cloud(run_experiment_kwargs, run_kwargs) and returns: info