class_docstr: A class implementing a simple chatbot problem for the DailyDialog dataset.
  
  https://arxiv.org/abs/1710.03957
  This version doesn't use any auxiliary information.
docstr: Main function where the preprocessing of the data starts.
  
  Args:
    train_mode: string, whether we are in train, dev or test mode
code: def preprocess_data(self, train_mode):
      """Main function where the preprocessing of the data starts.
  
      Args:
        train_mode: string, whether we are in train, dev or test mode
      """
  
      # Set the raw data directory and data.
      self.raw_data_dir = os.path.join(
          "/".join(self._data_dir.split("/")[:-1]), "raw_data"
      )
      self.raw_data = os.path.join(
          self._raw_data_dir, "ijcnlp_dailydialog"
      )
      self.zipped_data = os.path.join(
          self._raw_data_dir, "ijcnlp_dailydialog.zip"
      )
  
      # Create the download url.
      self.url = "http://yanran.li/files/ijcnlp_dailydialog.zip"
  
      # Check at which part of the pipeline are we at.
      self.data_pipeline_status(train_mode)
  
file_path: tensor2tensor/tensor2tensor/data_generators/dialog_dailydialog.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  from tensor2tensor.data_generators import dialog_abstract
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.utils import registry
label_desc: Use image node_id 1 for calling the DialogDailydialog16k obj's underlying member method code with example usage: obj.preprocess_data(train_mode) without return types