ab6f9e4c489beea3bec518d60629c0f8af0b6123,opennmt/runner.py,Runner,train,#Runner#Any#,263

Before Change

        _apply_gradients()

      for key, value in six.iteritems(num_words):
        value = value.numpy()
        if key not in accum_num_words:
          accum_num_words[key] = value
        else:
          accum_num_words[key] += value

      step = optimizer.iterations.numpy()
      if step % report_every == 0:
        last_report_time = _report_training_status(
            step,

After Change

      if step == train_steps:
        break

    _save_checkpoint(step)
    return self._maybe_average_checkpoints()

  def evaluate(self, checkpoint_path=None):
    Runs evaluation.

Instances