code: def write_to_files_np(features, tokenizer, max_seq_length,
                        max_predictions_per_seq, output_files):
      # pylint: disable=unused-argument
      
      next_sentence_labels = []
      valid_lengths = []
  
      assert len(output_files) == 1, 'numpy format only support single output file'
      output_file = output_files[0]
      (input_ids, segment_ids, masked_lm_positions, masked_lm_ids,
       masked_lm_weights, next_sentence_labels, valid_lengths) = features
      total_written = len(next_sentence_labels)
  
      # store variable length numpy array object directly.
      outputs = collections.OrderedDict()
      outputs['input_ids'] = np.array(input_ids, dtype=object)
      outputs['segment_ids'] = np.array(segment_ids, dtype=object)
      outputs['masked_lm_positions'] = np.array(masked_lm_positions, dtype=object)
      outputs['masked_lm_ids'] = np.array(masked_lm_ids, dtype=object)
      outputs['masked_lm_weights'] = np.array(masked_lm_weights, dtype=object)
      outputs['next_sentence_labels'] = np.array(next_sentence_labels, dtype='int32')
      outputs['valid_lengths'] = np.array(valid_lengths, dtype='int32')
  
      np.savez_compressed(output_file, **outputs)
      logging.info('Wrote %d total instances', total_written)
docs: Write to numpy files from `TrainingInstance`s.