class_docstr: Stanford Sentiment Treebank binary classification problems.
code: def class_labels(self, data_dir):
      del data_dir
      # Note this binary classification is different from usual MNLI.
      return ["neg", "pos"]
  
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 problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling the SentimentSSTBinary obj's underlying member method code with example usage: obj.class_labels(data_dir) and returns: list