class_docstr: 注意 metrics 的输入只支持：Dict[str, Metric]；
  并且通过对 update() , reset() , get_metric() 函数的封装，实现支持 fastNLP 的 metric 以及 torchmetrics 或者更多。
docstr: 将 Metric 中的状态重新设置。
  
  :return:
code: def reset(self):
      """
      将 Metric 中的状态重新设置。
  
      :return:
      """
      for metric in self._metrics:
          if _is_allennlp_metric(metric):
              metric.get_metric(reset=True)
          elif (
              _is_torchmetrics_metric(metric)
              or _is_paddle_metric(metric)
              or isinstance(metric, Metric)
          ):
              metric.reset()
  
imports: from typing import Union, List, Optional, Dict, Callable, BinaryIO
  import os
  from pathlib import Path
  import io
  from dataclasses import is_dataclass
  from fastNLP.core.drivers import Driver, TorchDriver
  from ..drivers.choose_driver import choose_driver
  from .loops import Loop, EvaluateBatchLoop
  from fastNLP.core.utils import auto_param_call, dataclass_to_dict, match_and_substitute_params, f_rich_progress, flat_nest_dict, f_tqdm_progress
  from fastNLP.core.metrics import Metric
  from fastNLP.core.metrics.utils import _is_torchmetrics_metric, _is_paddle_metric, _is_allennlp_metric
  from fastNLP.core.controllers.utils.utils import _TruncatedDataLoader
  from fastNLP.core.utils.utils import _check_valid_parameters_number
  from fastNLP.core.log import logger
  from fastNLP.envs import FASTNLP_MODEL_FILENAME
label_desc: Use image node_id 3 for calling the _MetricsWrapper obj's underlying member method code with example usage: obj.reset() without return types