code: def test_hashingvectorizer_delimiter():
      corpus = ["a0b0c", "a 0 b0e", "c0d0f"]
      res = HashingVectorizer(
          delimiter="0", norm=None, preprocessor=lambda s: s
      ).fit_transform(Series(corpus))
      # equivalent logic for sklearn
      ref = SkHashVect(
          tokenizer=lambda s: s.split("0"),
          norm=None,
          token_pattern=None,
          preprocessor=lambda s: s,
      ).fit_transform(corpus)
      assert_almost_equal_hash_matrices(
          res.todense().get(), ref.toarray()
      )
  
imports: from cuml.internals.safe_imports import cpu_only_import
  from cuml.internals.safe_imports import cpu_only_import_from
  from cuml.internals.safe_imports import gpu_only_import_from
  from sklearn.feature_extraction.text import TfidfVectorizer
  from sklearn.feature_extraction.text import HashingVectorizer
  from sklearn.feature_extraction.text import CountVectorizer
  import pytest
  from cuml.feature_extraction.text import CountVectorizer
  from cuml.feature_extraction.text import TfidfVectorizer
  from cuml.feature_extraction.text import HashingVectorizer
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 34 for calling a global function with example usage: test_hashingvectorizer_delimiter() without return types