code: def test_tfidf_transformer_copy(
      norm, use_idf, smooth_idf, sublinear_tf
  ):
      if use_idf:
          pytest.xfail(
              "cupyx.scipy.sparse.csr does not support inplace multiply."
          )
  
      data_gpu = cupyx.scipy.sparse.csr_matrix(
          cp.array(
              [[0, 1, 1, 1], [0, 2, 0, 1]], dtype=cp.float64, order="F"
          )
      )
  
      tfidf = TfidfTransformer(
          norm=norm,
          use_idf=use_idf,
          smooth_idf=smooth_idf,
          sublinear_tf=sublinear_tf,
      )
  
      res = tfidf.fit_transform(data_gpu, copy=False)
  
      cp.testing.assert_array_almost_equal(
          data_gpu.todense(), res.todense()
      )
  
imports: from sklearn.feature_extraction.text import TfidfTransformer
  from cuml.feature_extraction.text import TfidfTransformer
  from cuml.internals.safe_imports import gpu_only_import
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 2 for calling a global function with example usage: test_tfidf_transformer_copy(norm, use_idf, smooth_idf, sublinear_tf) without return types