cb556a585da0b65d28d2fc7d52c3851ac1a7d369,open_seq2seq/utils/utils.py,,get_results_for_epoch,#Any#Any#Any#Any#Any#,202

Before Change

    if compute_loss:
      total_samples_all = MPI.COMM_WORLD.gather(total_samples)
      total_loss_all = MPI.COMM_WORLD.gather(total_loss)
    results_per_batch_all = MPI.COMM_WORLD.gather(results_per_batch)

    MPI.COMM_WORLD.Barrier()
    if MPI.COMM_WORLD.Get_rank() != 0:
      // returning dummy tuple of correct shape
      if compute_loss:
        return None, None
      else:
        return None

    if compute_loss:
      total_loss = np.sum(total_loss_all)
      total_samples = np.sum(total_samples_all)
    // moving GPU dimension into the batch dimension
    results_per_batch = [item for sl in results_per_batch_all for item in sl]

  if compute_loss:
    total_loss /= total_samples
    return results_per_batch, total_loss

  return results_per_batch

After Change

    else:
      return None

  if compute_loss:
    return results_per_batch, total_loss / total_samples
  else:
    return results_per_batch


def log_summaries_from_dict(dict_to_log, output_dir, step):
  // this returns the same writer as was created by
  // the first call to this function
  sm_writer = tf.summary.FileWriterCache.get(output_dir)

Instances