class_docstr: A corpus of a large number of docs & large vocab
code: def __iter__(self):
      for _ in range(self.num_docs):
          doc_len = np.random.poisson(self.doc_len)
          ids = np.random.randint(0, len(self.dictionary), doc_len)
          if self.words_only:
              yield [str(idx) for idx in ids]
          else:
              weights = np.random.poisson(3, doc_len)
              yield sorted(zip(ids, weights))
  
file_path: gensim/gensim/test/test_big.py
imports: import logging
  import unittest
  import os
  import numpy
  import gensim
  from gensim.test.utils import get_tmpfile
label_desc: Use image node_id 2 for calling the BigCorpus obj's underlying member method code with example usage: obj.__iter__() without return types