dcf116a1be143290c5c4094b2ed051d333b1e29a,opennmt/training.py,Trainer,__call__,#Trainer#Any#Any#Any#Any#Any#Any#Any#,27

Before Change

    iterator = iter(dataset)
    gradients = []
    variables = []

    @tf.function
    def _step():
      source, target = next(iterator)

After Change

      tf.get_logger().warn("Model already reached train_steps = %d. Exiting.", max_step)
      return

    with self._strategy.scope():
      self._model.create_variables(optimizer=self._optimizer)
      dataset = self._strategy.experimental_distribute_dataset(dataset)

    iterator = iter(dataset)
    variables = self._model.variables
    gradients = []
    for variable in variables:

Instances