class_docstr: `The Stanford Natural Language Inference (SNLI) corpus <https://nlp.stanford.edu/projects/snli/>`_ is a dataset for natural language inference. It is first released in `A large annotated corpus for learning natural language inference (Bowman et al. 2015) <https://nlp.stanford.edu/pubs/snli_paper.pdf>`_
  
  We use the data released in `Making Pre-trained Language Models Better Few-shot Learners (Gao et al. 2020) <https://arxiv.org/pdf/2012.15723.pdf>`_
  
  Examples:
  
  ..  code-block:: python
  
      from openprompt.data_utils.lmbff_dataset import PROCESSORS
  
      base_path = "datasets"
  
      dataset_name = "SNLI"
      dataset_path = os.path.join(base_path, dataset_name, '16-13')
      processor = PROCESSORS[dataset_name.lower()]()
      train_dataset = processor.get_train_examples(dataset_path)
      dev_dataset = processor.get_dev_examples(dataset_path)
      test_dataset = processor.get_test_examples(dataset_path)
  
      assert processor.get_num_labels() == 3
      assert processor.get_labels() == ['entailment', 'neutral', 'contradiction']
      assert len(train_dataset) == 549367
      assert len(dev_dataset) == 9842
      assert len(test_dataset) == 9824
      assert train_dataset[0].text_a == 'A person on a horse jumps over a broken down airplane.'
      assert train_dataset[0].text_b == 'A person is training his horse for a competition.'
      assert train_dataset[0].label == 1
code: def get_examples(self, data_dir, split):
      path = os.path.join(data_dir, f"{split}.tsv")
      examples = []
      with open(path, encoding="utf-8") as f:
          lines = f.readlines()
          for idx, line in enumerate(lines[1:]):
              linelist = line.strip().split("\t")
              guid = "%s-%s" % (split, idx)
              label = linelist[-1]
              text_a = linelist[7]
              text_b = linelist[8]
              example = InputExample(
                  guid=guid,
                  text_a=text_a,
                  text_b=text_b,
                  label=self.get_label_id(label),
              )
              examples.append(example)
      return examples
  
file_path: OpenPrompt/openprompt/data_utils/nli_dataset.py
imports: import os
  from typing import List
  from openprompt.data_utils import InputExample
  from openprompt.data_utils.data_processor import DataProcessor
label_desc: Use image node_id 2 for calling the SNLIProcessor obj's underlying member method code with example usage: obj.get_examples(data_dir, split) and returns: examples