code: def test_subword_custom_token(model):
      parser = learn_subword.get_parser()
      corpus_path = os.path.join(
          _CURR_DIR, "data", "wmt19-test-zh-en.zh.jieba"
      )
      with tempfile.TemporaryDirectory() as tempdir:
          dir_path = tempdir
          arguments = (
              ["--corpus"]
              + [corpus_path]
              + [
                  "--model",
                  model,
                  "--vocab-size",
                  "5000",
                  "--save-dir",
                  dir_path,
                  "--disable-bos",
                  "--disable-eos",
                  "--custom-special-tokens",
                  "cls_token=<cls>",
                  "sep_token=<sep>",
              ]
          )
          args = parser.parse_args(arguments)
          # Train the tokenizer
          learn_subword.main(args)
          if model in ["yttm", "spm", "subword_nmt"]:
              model_key = model
          else:
              model_key = "hf_tokenizer"
          tokenizer = tokenizers.create(
              model_key,
              model_path=os.path.join(
                  dir_path, "{}.model".format(model)
              ),
              vocab=os.path.join(dir_path, "{}.vocab".format(model)),
          )
          assert tokenizer.vocab.sep_token == "<sep>"
          assert tokenizer.vocab.cls_token == "<cls>"
  
file_path: gluon-nlp/tests/process_cli/test_learn_apply_subword.py
imports: import os
  import pytest
  import tempfile
  from gluonnlp.cli.process import learn_subword, apply_subword
  from gluonnlp.data import tokenizers
label_desc: Use image node_id 4 for calling a global function with example usage: test_subword_custom_token(model) without return types