Method _call_batch_hook

tensorflow/python/keras/callbacks.py:221–245

Helper function for all batch_{begin | end} methods.

(self, mode, hook, batch, logs=None)

      callback.set_model(model)

  def _call_batch_hook(self, mode, hook, batch, logs=None):
    """Helper function for all batch_{begin | end} methods."""
    if not self.callbacks:
      return
    hook_name = 'on_{mode}_batch_{hook}'.format(mode=mode, hook=hook)
    if hook == 'begin':
      self._t_enter_batch = time.time()
    if hook == 'end':
      # Batch is ending, calculate batch time.
      self._delta_t_batch = time.time() - self._t_enter_batch

    logs = logs or {}
    t_before_callbacks = time.time()
    for callback in self.callbacks:
      batch_hook = getattr(callback, hook_name)
      batch_hook(batch, logs)
    self._delta_ts[hook_name].append(time.time() - t_before_callbacks)

    delta_t_median = np.median(self._delta_ts[hook_name])
    if (self._delta_t_batch > 0. and
        delta_t_median > 0.95 * self._delta_t_batch and delta_t_median > 0.1):
      logging.warning(
          'Method (%s) is slow compared '
          'to the batch update (%f). Check your callbacks.', hook_name,
          delta_t_median)

  def _call_begin_hook(self, mode):
    """Helper function for on_{train|test|predict}_begin methods."""