code: def test_countvectorizer_stop_words():
      ref = SkCountVect(stop_words="english").fit_transform(DOCS)
      X = CountVectorizer(stop_words="english").fit_transform(DOCS_GPU)
      cp.testing.assert_array_equal(X.todense(), 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 4 for calling a global function with example usage: test_countvectorizer_stop_words() without return types