2d34259281a6251cbdc67103ce8a1310010b8ceb,orbit/controller.py,Controller,__init__,#Controller#,39

Before Change

      checkpoint_interval = self.checkpoint_manager.checkpoint_interval
      restored_path = self.restore_checkpoint()
      if restored_path:
        logging.info("Restored from checkpoint: %s", restored_path)

  def train(self, steps: int, checkpoint_at_completion: bool = True):
    Runs training.

After Change

              f"`summary interval` ({summary_interval}) must be a multiple "
              f"of `steps_per_loop` ({steps_per_loop}).")

    if global_step is None:
      raise ValueError("`global_step` is required.")
    elif not isinstance(global_step, tf.Variable):
      raise ValueError("`global_step` must be a `tf.Variable`.")

    self.trainer = trainer
    self.evaluator = evaluator

    self.strategy = strategy or tf.distribute.get_strategy()

Instances