code: def test_process_from_file_proc(self):
      data_set_dict = {
          "yelp.p": (
              "data_for_tests/io/yelp_review_polarity",
              YelpPolarityPipe,
              {"train": 6, "dev": 6, "test": 6},
              {"words": 1176, "target": 2},
              False,
          ),
          "yelp.f": (
              "data_for_tests/io/yelp_review_full",
              YelpFullPipe,
              {"train": 6, "dev": 6, "test": 6},
              {"words": 1166, "target": 5},
              False,
          ),
          "sst-2": (
              "data_for_tests/io/SST-2",
              SST2Pipe,
              {"train": 5, "dev": 5, "test": 5},
              {"words": 139, "target": 2},
              True,
          ),
          "sst": (
              "data_for_tests/io/SST",
              SSTPipe,
              {"train": 354, "dev": 6, "test": 6},
              {"words": 232, "target": 5},
              False,
          ),
          "imdb": (
              "data_for_tests/io/imdb",
              IMDBPipe,
              {"train": 6, "dev": 6, "test": 6},
              {"words": 1670, "target": 2},
              False,
          ),
          "ag": (
              "data_for_tests/io/ag",
              AGsNewsPipe,
              {"train": 4, "test": 5},
              {"words": 257, "target": 4},
              False,
          ),
          "dbpedia": (
              "data_for_tests/io/dbpedia",
              DBPediaPipe,
              {"train": 14, "test": 5},
              {"words": 496, "target": 14},
              False,
          ),
          "ChnSentiCorp": (
              "data_for_tests/io/ChnSentiCorp",
              ChnSentiCorpPipe,
              {"train": 6, "dev": 6, "test": 6},
              {
                  "chars": 529,
                  "bigrams": 1296,
                  "trigrams": 1483,
                  "target": 2,
              },
              False,
          ),
          "Chn-THUCNews": (
              "data_for_tests/io/THUCNews",
              THUCNewsPipe,
              {"train": 9, "dev": 9, "test": 9},
              {"chars": 1864, "target": 9},
              False,
          ),
          "Chn-WeiboSenti100k": (
              "data_for_tests/io/WeiboSenti100k",
              WeiboSenti100kPipe,
              {"train": 6, "dev": 6, "test": 7},
              {"chars": 452, "target": 2},
              False,
          ),
      }
      for k, v in data_set_dict.items():
          path, pipe, data_set, vocab, warns = v
          if "Chn" not in k:
              if warns:
                  data_bundle = pipe(
                      tokenizer="raw", num_proc=2
                  ).process_from_file(path)
              else:
                  data_bundle = pipe(
                      tokenizer="raw", num_proc=2
                  ).process_from_file(path)
          else:
              # if k == 'ChnSentiCorp':
              #     data_bundle = pipe(bigrams=True, trigrams=True).process_from_file(path)
              # else:
              data_bundle = pipe(
                  bigrams=True, trigrams=True, num_proc=2
              ).process_from_file(path)
  
          assert isinstance(data_bundle, DataBundle)
          assert len(data_set) == data_bundle.num_dataset
          for name, dataset in data_bundle.iter_datasets():
              assert name in data_set.keys()
              assert data_set[name] == len(dataset)
  
          assert len(vocab) == data_bundle.num_vocab
          for name, vocabs in data_bundle.iter_vocabs():
              assert name in vocab.keys()
              assert vocab[name] == len(vocabs)
  
file_path: fastNLP/tests/io/pipe/test_classification.py
imports: import pytest
  import os
  from fastNLP.io import DataBundle
  from fastNLP.io.pipe.classification import SSTPipe, SST2Pipe, IMDBPipe, YelpFullPipe, YelpPolarityPipe, AGsNewsPipe, DBPediaPipe
  from fastNLP.io.pipe.classification import ChnSentiCorpPipe, THUCNewsPipe, WeiboSenti100kPipe
label_desc: Use image node_id 2 for calling the TestRunClassificationPipe obj's underlying member method code with example usage: obj.test_process_from_file_proc() without return types