Method restore

tensorflow/python/training/saver.py:1518–1588

Restores previously saved variables. This method runs the ops added by the constructor for restoring variables. It requires a session in which the graph was launched. The variables to restore do not have to have been initialized, as restoring is itself a way to initialize variables

(self, sess, save_path)

        save_debug_info=save_debug_info)

  def restore(self, sess, save_path):
    """Restores previously saved variables.

    This method runs the ops added by the constructor for restoring variables.
    It requires a session in which the graph was launched.  The variables to
    restore do not have to have been initialized, as restoring is itself a way
    to initialize variables.

    The `save_path` argument is typically a value previously returned from a
    `save()` call, or a call to `latest_checkpoint()`.

    Args:
      sess: A `Session` to use to restore the parameters. None in eager mode.
      save_path: Path where parameters were previously saved.

    Raises:
      ValueError: If save_path is None or not a valid checkpoint.
    """
    if self._is_empty:
      return
    if save_path is None:
      raise ValueError("Can't load save_path when it is None.")

    checkpoint_prefix = compat.as_text(save_path)
    if not checkpoint_management.checkpoint_exists_internal(checkpoint_prefix):
      raise ValueError("The passed save_path is not a valid checkpoint: " +
                       checkpoint_prefix)

    logging.info("Restoring parameters from %s", checkpoint_prefix)
    try:
      if context.executing_eagerly():
        self._build_eager(save_path, build_save=False, build_restore=True)
      else:
        sess.run(self.saver_def.restore_op_name,
                 {self.saver_def.filename_tensor_name: save_path})
    except errors.NotFoundError as err:
      # There are three common conditions that might cause this error:
      # 0. The file is missing. We ignore here, as this is checked above.
      # 1. This is an object-based checkpoint trying name-based loading.
      # 2. The graph has been altered and a variable or other name is missing.

      # 1. The checkpoint would not be loaded successfully as is. Try to parse
      # it as an object-based checkpoint.
      try:
        names_to_keys = object_graph_key_mapping(save_path)
      except errors.NotFoundError:
        # 2. This is not an object-based checkpoint, which likely means there
        # is a graph mismatch. Re-raise the original error with
        # a helpful message (b/110263146)
        raise _wrap_restore_error_with_msg(
            err, "a Variable name or other graph key that is missing")

      # This is an object-based checkpoint. We'll print a warning and then do
      # the restore.
      logging.warning(
          "Restoring an object-based checkpoint using a name-based saver. This "
          "may be somewhat fragile, and will re-build the Saver. Instead, "
          "consider loading object-based checkpoints using "