class_docstr: The Winogrande challenge.
code: def _split_generators(self, dl_manager):
      dl_dir = dl_manager.download_and_extract(_DATA_URL)
      data_dir = os.path.join(dl_dir, "winogrande_1.1")
  
      # Winogrande has different standardized training data sizes and reports
      # numbers for each of these data sizes, so make those available.
      data_sizes = ["xs", "s", "m", "l", "xl"]
      train_splits = []
      for size in data_sizes:
          train_splits.append(
              tfds.core.SplitGenerator(
                  name=tfds.Split("train_{}".format(size)),
                  gen_kwargs={
                      "filepath": os.path.join(
                          data_dir, "train_{}.jsonl".format(size)
                      )
                  },
              )
          )
      return train_splits + [
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={
                  "filepath": os.path.join(data_dir, "test.jsonl")
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs={
                  "filepath": os.path.join(data_dir, "dev.jsonl")
              },
          ),
      ]
  
file_path: datasets/tensorflow_datasets/text/winogrande.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import os
  from etils import epath
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Winogrande obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: unknown