class_docstr: 测试多卡情况下 save 和 load 相关函数的表现
class_docstr_tok: ["\u6d4b\u8bd5\u591a\u5361\u60c5\u51b5\u4e0b","save","\u548c","load","\u76f8\u5173\u51fd\u6570\u7684\u8868\u73b0"]
code: def setup_method(self):
      self.dataset = TorchNormalXYDataset(100)
  
imports: import os
  import pytest
  from pathlib import Path
  from fastNLP.core.drivers.torch_driver.ddp import TorchDDPDriver
  from fastNLP import prepare_torch_dataloader
  from fastNLP.core.samplers import RandomSampler, UnrepeatedSampler, BucketedBatchSampler, UnrepeatedRandomSampler, UnrepeatedSequentialSampler
  from tests.helpers.models.torch_model import TorchNormalModel_Classification_1
  from tests.helpers.datasets.torch_data import TorchNormalDataset, TorchNormalXYDataset
  from tests.helpers.utils import magic_argv_env_context, recover_logger, Capturing
  from fastNLP.envs.distributed import rank_zero_rm
  from fastNLP import logger
  from fastNLP.core.drivers.torch_driver.dist_utils import fastnlp_torch_all_gather
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
label_desc: Use image node_id 1 for calling the TestSaveLoad obj's underlying member method code with example usage: obj.setup_method() without return types