code: def tokenized_docs(lang_en, texts_short_en):
      docs = list(lang_en.pipe(texts_short_en))
      tokenized_docs = [
          [term.text.lower() for term in extract.terms(doc, ngs=1)]
          for doc in docs
      ]
      return tokenized_docs
  
imports: import pytest
  import numpy
  from scipy.sparse import coo_matrix
  from textacy import extract, representations
label_desc: Use image node_id 1 for calling a global function with example usage: tokenized_docs(lang_en, texts_short_en) and returns: tokenized_docs