Method write

tensorflow/python/training/tracking/util.py:1800–1828

Writes a training checkpoint. The checkpoint includes variables created by this object and any trackable objects it depends on at the time `Checkpoint.write()` is called. `write` does not number checkpoints, increment `save_counter`, or update the metadata used by `tf.train.lat

(self, file_prefix)

                trainable=False))

  def write(self, file_prefix):
    """Writes a training checkpoint.

    The checkpoint includes variables created by this object and any
    trackable objects it depends on at the time `Checkpoint.write()` is
    called.

    `write` does not number checkpoints, increment `save_counter`, or update the
    metadata used by `tf.train.latest_checkpoint`. It is primarily intended for
    use by higher level checkpoint management utilities. `save` provides a very
    basic implementation of these features.

    Args:
      file_prefix: A prefix to use for the checkpoint filenames
        (/path/to/directory/and_a_prefix).

    Returns:
      The full path to the checkpoint (i.e. `file_prefix`).
    """
    output = self._saver.save(file_prefix=file_prefix)
    if tensor_util.is_tensor(output):
      if context.executing_eagerly():
        return compat.as_str(output.numpy())
      else:
        # Function building
        return output
    else:
      # Graph + Session, so we already session.ran it.
      return compat.as_str(output)

  @property
  def save_counter(self):