class_docstr: HANS NLI challenge set (https://arxiv.org/abs/1902.01007); 30k examples.
class_docstr_tok: ["HANS","NLI","challenge","set","(","https",":","\/\/arxiv.org\/abs\/1902.01007",")",";","30k","examples","."]
code: def __init__(self, path: str):
      with open(path) as fd:
          df = pd.read_csv(fd, sep="\t", header=0)
      # pylint: disable=g-complex-comprehension
      self._examples = [
          {
              "premise": row["sentence1"],
              "hypothesis": row["sentence2"],
              "label2": row["gold_label"],
              "heuristic": row["heuristic"],
              "template": row["template"],
          }
          for _, row in df.iterrows()
      ]
  
imports: from typing import Optional
  from absl import logging
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  import pandas
  import tensorflow_datasets
label_desc: Use image node_id 1 to create a new HansNLIData object from inherited base classes: lit_dataset with example: obj = HansNLIData(path)