code: def grp_vectorizer_and_gtm(tokenized_docs, groups):
      grp_vectorizer = representations.GroupVectorizer(
          tf_type="linear",
          norm=None,
          min_df=1,
          max_df=1.0,
          max_n_terms=None,
      )
      grp_term_matrix = grp_vectorizer.fit_transform(
          tokenized_docs, groups
      )
      return grp_vectorizer, grp_term_matrix
  
imports: import pytest
  import numpy
  from scipy.sparse import coo_matrix
  from textacy import extract, representations
label_desc: Use image node_id 4 for calling a global function with example usage: grp_vectorizer_and_gtm(tokenized_docs, groups) and returns: grp_vectorizer,  grp_term_matrix