code: def submit_batch_prediction(job_request, job_id=None):
      
  
      if job_id is None:
        job_id = 'prediction_' + datetime.datetime.now().strftime('%y%m%d_%H%M%S')
  
      job = {
          'job_id': job_id,
          'prediction_input': job_request,
      }
      context = datalab.Context.default()
      cloudml = discovery.build('ml', 'v1', credentials=context.credentials)
      request = cloudml.projects().jobs().create(body=job,
                                                 parent='projects/' + context.project_id)
      request.headers['user-agent'] = 'GoogleCloudDataLab/1.0'
      request.execute()
      return Job(job_id)
docs: Submit a batch prediction job.
  
      Args:
        job_request: the arguments of the training job in a dict. For example,
            {
              'version_name': 'projects/my-project/models/my-model/versions/my-version',
              'data_format': 'TEXT',
              'input_paths': ['gs://my_bucket/my_file.csv'],
              'output_path': 'gs://my_bucket/predict_output',
              'region': 'us-central1',
              'max_worker_count': 1,
            }
        job_id: id for the training job. If None, an id based on timestamp will be generated.
  
      Returns:
        A Job object representing the batch prediction job.