task.py 文件源码

def _run_eval(self):
    """Run model evaluation and generate summaries."""
    coord = tf.train.Coordinator(clean_stop_exception_types=(
        tf.errors.CancelledError, tf.errors.OutOfRangeError))

    with tf.Session(graph=self._graph) as session:
      # Restores previously saved variables from latest checkpoint
      self._saver.restore(session, self._latest_checkpoint)

      session.run([
        tf.tables_initializer(),
        tf.local_variables_initializer()
      ])
      tf.train.start_queue_runners(coord=coord, sess=session)
      train_step = session.run(self._gs)

      tf.logging.info('Starting Evaluation For Step: {}'.format(train_step))
      with coord.stop_on_exception():
        eval_step = 0
        while self._eval_steps is None or eval_step < self._eval_steps:
          summaries, final_values, _ = session.run(
              [self._summary_op, self._final_ops_dict, self._eval_ops])
          if eval_step % 100 == 0:
            tf.logging.info("On Evaluation Step: {}".format(eval_step))
          eval_step += 1

      # Write the summaries
      self._file_writer.add_summary(summaries, global_step=train_step)
      self._file_writer.flush()
      tf.logging.info(final_values)