d7db4b1b9a6c9577ca3a09c4241cdd9db58b31bc,opennmt/training.py,Trainer,__call__,#Trainer#Any#Any#Any#Any#Any#Any#Any#Any#,45

Before Change

    last_step = 0

    with self._summary_writer.as_default():
      if self._optimizer.iterations.numpy() == 0:
        self._checkpoint.save(0)
      self._model.visualize(self._checkpoint.model_dir)

After Change

      last_report_time = time.time()
      for loss in self._steps(dataset, accum_steps=accum_steps, report_steps=report_steps):
        if tf.math.is_nan(loss):
          raise RuntimeError("Model diverged with loss = NaN.")
        step = iterations.numpy()
        if step % report_steps == 0:
          _report_training_status(
              step,

Instances