benchmark_cnn.py 文件源码

def _eval_cnn(self):
    """Evaluate a model every self.params.eval_interval_secs.

    Returns:
      Dictionary containing eval statistics. Currently returns an empty
      dictionary.
    """
    (image_producer_ops, enqueue_ops, fetches) = self._build_model()
    saver = tf.train.Saver(self.variable_mgr.savable_variables())
    summary_writer = tf.summary.FileWriter(self.params.eval_dir,
                                           tf.get_default_graph())
    target = ''
    local_var_init_op = tf.local_variables_initializer()
    variable_mgr_init_ops = [local_var_init_op]
    with tf.control_dependencies([local_var_init_op]):
      variable_mgr_init_ops.extend(self.variable_mgr.get_post_init_ops())
    local_var_init_op_group = tf.group(*variable_mgr_init_ops)
    summary_op = tf.summary.merge_all()
    # TODO(huangyp): Check if checkpoints haven't updated for hours and abort.
    while True:
      self._eval_once(saver, summary_writer, target, local_var_init_op_group,
                      image_producer_ops, enqueue_ops, fetches, summary_op)
      if self.params.eval_interval_secs <= 0:
        break
      time.sleep(self.params.eval_interval_secs)
    return {}