write_train_files

write_train_files.py

 if not is_tuning_job:
      # this is a training job, just upload
      write_experiment_results(files_to_be_uploaded, s3_run_dir)
  else:
      # this is a tuning job, the run dir should only have the best result
      if folder_exists(bucket, s3_run_dir):
          temp_file = os.path.join(os.getcwd(), 'remote_best_model_stats.json')
          s3_path = os.path.join(s3_run_dir, 'best_model_stats.json')
          bucket.download_file(s3_path, temp_file)
          with open(temp_file) as f:
              remote_model_stats = json.load(f)
          with open(local_best_model_stats) as f:
              local_model_stats = json.load(f)
          remote_f1 = remote_model_stats["best_valid_f1"]
          local_f1 = local_model_stats["best_valid_f1"]
          if local_f1 > remote_f1:
              write_experiment_results(files_to_be_uploaded, s3_run_dir)

      else:
          # no tuning job has written yet
          write_experiment_results(files_to_be_uploaded, s3_run_dir)