class_docstr: A language model on the untokenized wikipedia corpus, English.
class_docstr_tok: ["A","language","model","on","the","untokenized","wikipedia","corpus",",","English","."]
docstr: Generate samples.
code: def generate_samples(self, data_dir, tmp_dir, dataset_split):
      """Generate samples."""
      if dataset_split == problem.DatasetSplit.TRAIN:
          file_names_ids = self.train_names_ids
      elif dataset_split == problem.DatasetSplit.TEST:
          file_names_ids = self.test_names_ids
      else:
          file_names_ids = self.eval_names_ids
  
      wiki_generators = []
      for fname, fid in file_names_ids:
          url = "https://drive.google.com/uc?export=download&id=" + fid
          download_path = generator_utils.maybe_download_from_drive(
              tmp_dir, fname, url
          )
          wiki_file = os.path.join(tmp_dir, fname[:-3])
          if not tf.gfile.Exists(wiki_file):
              generator_utils.gunzip_file(download_path, wiki_file)
          wiki_generators.append(
              concat_generator(
                  wiki_file, self.combine_characters_threshold
              )
          )
  
      for example in mix_generators(wiki_generators):
          yield example
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import six
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the LanguagemodelEnWiki32k obj's underlying member method code with example usage: obj.generate_samples(data_dir, tmp_dir, dataset_split) without return types