code: def test_tfidf_vectorizer(norm, use_idf, smooth_idf, sublinear_tf):
      tfidf_mat = TfidfVectorizer(
          norm=norm,
          use_idf=use_idf,
          smooth_idf=smooth_idf,
          sublinear_tf=sublinear_tf,
      ).fit_transform(DOCS_GPU)
  
      ref = SkTfidfVect(
          norm=norm,
          use_idf=use_idf,
          smooth_idf=smooth_idf,
          sublinear_tf=sublinear_tf,
      ).fit_transform(DOCS)
  
      cp.testing.assert_array_almost_equal(
          tfidf_mat.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 23 for calling a global function with example usage: test_tfidf_vectorizer(norm, use_idf, smooth_idf, sublinear_tf) without return types