code: def test_load_proc(self):
      data_set_dict = {
          "RTE": (
              "data_for_tests/io/RTE",
              RTEPipe,
              RTEBertPipe,
              (5, 5, 5),
              (449, 2),
              True,
          ),
          "SNLI": (
              "data_for_tests/io/SNLI",
              SNLIPipe,
              SNLIBertPipe,
              (5, 5, 5),
              (110, 3),
              False,
          ),
          "QNLI": (
              "data_for_tests/io/QNLI",
              QNLIPipe,
              QNLIBertPipe,
              (5, 5, 5),
              (372, 2),
              True,
          ),
          "MNLI": (
              "data_for_tests/io/MNLI",
              MNLIPipe,
              MNLIBertPipe,
              (5, 5, 5, 5, 6),
              (459, 3),
              True,
          ),
          "BQCorpus": (
              "data_for_tests/io/BQCorpus",
              BQCorpusPipe,
              BQCorpusBertPipe,
              (5, 5, 5),
              (32, 2),
              False,
          ),
          "XNLI": (
              "data_for_tests/io/XNLI",
              CNXNLIPipe,
              CNXNLIBertPipe,
              (6, 6, 8),
              (39, 3),
              False,
          ),
          "LCQMC": (
              "data_for_tests/io/LCQMC",
              LCQMCPipe,
              LCQMCBertPipe,
              (6, 5, 6),
              (36, 2),
              False,
          ),
      }
      for k, v in data_set_dict.items():
          path, pipe1, pipe2, data_set, vocab, warns = v
          if warns:
              data_bundle1 = pipe1(
                  tokenizer="raw", num_proc=2
              ).process_from_file(path)
              data_bundle2 = pipe2(
                  tokenizer="raw", num_proc=2
              ).process_from_file(path)
          else:
              data_bundle1 = pipe1(
                  tokenizer="raw", num_proc=2
              ).process_from_file(path)
              data_bundle2 = pipe2(
                  tokenizer="raw", num_proc=2
              ).process_from_file(path)
  
          assert isinstance(data_bundle1, DataBundle)
          assert len(data_set) == data_bundle1.num_dataset
          print(k)
          print(data_bundle1)
          print(data_bundle2)
          for x, y in zip(data_set, data_bundle1.iter_datasets()):
              name, dataset = y
              assert x == len(dataset)
          assert len(data_set) == data_bundle2.num_dataset
          for x, y in zip(data_set, data_bundle2.iter_datasets()):
              name, dataset = y
              assert x == len(dataset)
  
          assert len(vocab) == data_bundle1.num_vocab
          for x, y in zip(vocab, data_bundle1.iter_vocabs()):
              name, vocabs = y
              assert x == len(vocabs)
          assert len(vocab) == data_bundle2.num_vocab
          for x, y in zip(vocab, data_bundle1.iter_vocabs()):
              name, vocabs = y
              assert x + 1 if name == "words" else x == len(vocabs)
  
file_path: fastNLP/tests/io/pipe/test_matching.py
imports: import pytest
  import os
  from fastNLP.io import DataBundle
  from fastNLP.io.pipe.matching import SNLIPipe, RTEPipe, QNLIPipe, QuoraPipe, MNLIPipe, CNXNLIPipe, BQCorpusPipe, LCQMCPipe
  from fastNLP.io.pipe.matching import SNLIBertPipe, RTEBertPipe, QNLIBertPipe, QuoraBertPipe, MNLIBertPipe, CNXNLIBertPipe, BQCorpusBertPipe, LCQMCBertPipe
label_desc: Use image node_id 2 for calling the TestRunMatchingPipe obj's underlying member method code with example usage: obj.test_load_proc() without return types