evaluator.py 文件源码

def run(self):
    """Run evaluation."""
    # Create logging directory if not exists.
    if not os.path.isdir(self._eval_log_dir):
      os.makedirs(self._eval_log_dir)

    # Compute loss function and other evaluating metrics.
    self._initialize()

    # Visualize input images in Tensorboard.
    self._summary_ops.append(tf.image_summary("Eval_Image", self._observations, max_images=5))

    # Use `slim.evaluation.evaluation_loop` to evaluate the model periodically.
    slim.evaluation.evaluation_loop(
        master='',
        checkpoint_dir=self._train_log_dir,
        logdir=self._eval_log_dir,
        num_evals=self._config.num_batches,
        eval_op=self._metrics_to_updates.values(),
        summary_op=tf.merge_summary(self._summary_ops),
        eval_interval_secs=self._config.eval_interval_secs)