class_docstr: CelebA dataset, aligned and cropped images.
class_docstr_tok: ["CelebA","dataset",",","aligned","and","cropped","images","."]
code: def generate_data(self, data_dir, tmp_dir, task_id=-1):
      train_gen = self.generator(tmp_dir, 162770)
      train_paths = self.training_filepaths(
          data_dir, self.train_shards, shuffled=False
      )
      generator_utils.generate_files(train_gen, train_paths)
  
      dev_gen = self.generator(tmp_dir, 19867, 162770)
      dev_paths = self.dev_filepaths(
          data_dir, self.dev_shards, shuffled=False
      )
      generator_utils.generate_files(dev_gen, dev_paths)
  
      test_gen = self.generator(tmp_dir, 19962, 162770 + 19867)
      test_paths = self.test_filepaths(
          data_dir, self.test_shards, shuffled=False
      )
      generator_utils.generate_files(test_gen, test_paths)
  
      generator_utils.shuffle_dataset(
          train_paths + dev_paths + test_paths
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import zipfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import image_utils
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the ImageCeleba obj's underlying member method code with example usage: obj.generate_data(data_dir, tmp_dir, task_id) without return types