code: def test_transform(self):
      vectorizer = CountVectorizer(
          max_doc_freq=2, min_doc_freq=1, max_features=1
      )
      vectorizer.fit(self.docs)
      sequences, X = vectorizer.transform(self.docs)
      npt.assert_array_equal(X.A, np.asarray([[0], [2], [0]]))
  
      vectorizer.binary = True
      _, X1 = vectorizer.fit_transform(self.docs)
      _, X2 = vectorizer.transform(self.docs)
      npt.assert_array_equal(X1.A, X2.A)
  
imports: import unittest
  from collections import defaultdict
  import numpy
  import numpy.testing
  from cornac.data import TextModality, ReviewModality
  from cornac.data.text import SPECIAL_TOKENS, DEFAULT_PRE_RULES, BaseTokenizer, Vocabulary, CountVectorizer, TfidfVectorizer
label_desc: Use image node_id 4 for calling the TestCountVectorizer obj's underlying member method code with example usage: obj.test_transform() without return types