code: def generate_input_data():
      lee_path = datapath("lee_background.cor")
      ls = gensim.models.word2vec.LineSentence(lee_path)
      ls.name = "25kB"
      yield ls
  
      text8_path = api.load("text8").fn
      labels = ("1MB", "10MB", "50MB", "100MB")
      sizes = (
          1024**2,
          10 * 1024**2,
          50 * 1024**2,
          100 * 1024**2,
      )
      for l, s in zip(labels, sizes):
          ls = gensim.models.word2vec.LineSentence(head(text8_path, s))
          ls.name = l
          yield ls
  
imports: import logging
  import gensim.downloader
  from gensim.test.utils import datapath
  from gensim import utils
  import gensim.models
  import tempfile
  import os
  import io
  import os
  import gensim.models.word2vec
  import gensim.downloader
  import smart_open
  import time
  import numpy
  import pandas
  from sklearn.decomposition import IncrementalPCA
  from sklearn.manifold import TSNE
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: generate_input_data() without return types