code: def test_vectorizer_inverse_transform():
      vectorizer = CountVectorizer()
      transformed_data = vectorizer.fit_transform(DOCS_GPU)
      inversed_data = vectorizer.inverse_transform(transformed_data)
  
      sk_vectorizer = SkCountVect()
      sk_transformed_data = sk_vectorizer.fit_transform(DOCS)
      sk_inversed_data = sk_vectorizer.inverse_transform(
          sk_transformed_data
      )
  
      for doc, sk_doc in zip(inversed_data, sk_inversed_data):
          doc = np.sort(doc.to_arrow().to_pylist())
          sk_doc = np.sort(sk_doc)
          if len(doc) + len(sk_doc) == 0:
              continue
          assert_array_equal(doc, sk_doc)
  
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 12 for calling a global function with example usage: test_vectorizer_inverse_transform() without return types