code: def get_config():
      """Get the hyperparameter configuration to train on TPUs."""
      config = default_lib.get_config()
  
      # Consider setting the batch size to max(tpu_chips * 256, 8 * 1024) if you
      # train on a larger pod slice.
      config.batch_size = 1024
      config.shuffle_buffer_size = 16 * 1024
      config.cache = True
      config.half_precision = True
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config() and returns: config