code: def test_hashingvectorizer_lowercase(lowercase):
      corpus = [
          "This Is DoC",
          "this DoC is the second DoC.",
          "And this document is the third one.",
          "and Is this the first document?",
      ]
      res = HashingVectorizer(lowercase=lowercase).fit_transform(
          Series(corpus)
      )
      ref = SkHashVect(lowercase=lowercase).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 28 for calling a global function with example usage: test_hashingvectorizer_lowercase(lowercase) without return types