class_docstr: StanfordNLI classification problems.
class_docstr_tok: ["StanfordNLI","classification","problems","."]
code: def generate_samples(self, data_dir, tmp_dir, dataset_split):
      snli_dir = self._maybe_download_corpora(tmp_dir)
      if dataset_split == problem.DatasetSplit.TRAIN:
          filesplit = "snli_1.0_train.txt"
      else:
          filesplit = "snli_1.0_dev.txt"
  
      filename = os.path.join(snli_dir, filesplit)
      for example in self.example_generator(filename):
          yield example
  
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 lm1b
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.data_generators import wiki_lm
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 8 for calling the StanfordNLI obj's underlying member method code with example usage: obj.generate_samples(data_dir, tmp_dir, dataset_split) without return types