code: def test_fixed_vocab(self, tokenized_docs, groups):
      vocabulary_terms = ["lamb", "snow", "school", "rule", "teacher"]
      vocabulary_grps = ["a", "b"]
      grp_vectorizer = representations.GroupVectorizer(
          vocabulary_terms=vocabulary_terms,
          vocabulary_grps=vocabulary_grps,
      )
      grp_term_matrix = grp_vectorizer.fit_transform(
          tokenized_docs, groups
      )
      assert len(grp_vectorizer.vocabulary_terms) == len(
          vocabulary_terms
      )
      assert grp_term_matrix.shape[1] == len(vocabulary_terms)
      assert sorted(grp_vectorizer.terms_list) == sorted(
          vocabulary_terms
      )
      assert len(grp_vectorizer.vocabulary_grps) == len(vocabulary_grps)
      assert grp_term_matrix.shape[0] == len(vocabulary_grps)
      assert sorted(grp_vectorizer.grps_list) == sorted(vocabulary_grps)
  
imports: import pytest
  import numpy
  from scipy.sparse import coo_matrix
  from textacy import extract, representations
label_desc: Use image node_id 5 for calling the TestGroupVectorizer obj's underlying member method code with example usage: obj.test_fixed_vocab(tokenized_docs, groups) without return types