code: def test_transform_unsigned_categories(query):
      token = "a"
      thousand_tokens = list()
      for i in range(1000):
          thousand_tokens.append(token)
          token += "a"
      thousand_tokens[128] = "science"
  
      vec = CountVectorizer().fit(Series(thousand_tokens))
      res = vec.transform(query)
  
      assert res.shape[0] == len(query)
  
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 20 for calling a global function with example usage: test_transform_unsigned_categories(query) without return types