class_docstr: TriviaQA is a reading comprehension dataset.
  
  It containss over 650K question-answer-evidence triples.
class_docstr_tok: ["TriviaQA","is","a","reading","comprehension","dataset",".","It","containss","over","650K","question-answer-evidence","triples","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      cfg = self.builder_config
      download_urls = dict()
      if not (cfg.unfiltered and cfg.exclude_context):
          download_urls["rc"] = _DOWNLOAD_URL_TMPL.format("rc")
      if cfg.unfiltered:
          download_urls["unfiltered"] = _DOWNLOAD_URL_TMPL.format(
              "unfiltered"
          )
      file_paths = dl_manager.download_and_extract(download_urls)
  
      qa_dir = (
          os.path.join(file_paths["unfiltered"], "triviaqa-unfiltered")
          if cfg.unfiltered
          else os.path.join(file_paths["rc"], "qa")
      )
      train_files = tf.io.gfile.glob(
          os.path.join(qa_dir, _TRAIN_FILE_FORMAT)
      )
      valid_files = tf.io.gfile.glob(
          os.path.join(qa_dir, _VALIDATION_FILE_FORMAT)
      )
      test_files = tf.io.gfile.glob(
          os.path.join(qa_dir, _TEST_FILE_FORMAT)
      )
  
      if cfg.exclude_context:
          web_evidence_dir = None
          wiki_evidence_dir = None
      else:
          web_evidence_dir = os.path.join(
              file_paths["rc"], _WEB_EVIDENCE_DIR
          )
          wiki_evidence_dir = os.path.join(
              file_paths["rc"], _WIKI_EVIDENCE_DIR
          )
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "files": train_files,
                  "web_dir": web_evidence_dir,
                  "wiki_dir": wiki_evidence_dir,
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs={
                  "files": valid_files,
                  "web_dir": web_evidence_dir,
                  "wiki_dir": wiki_evidence_dir,
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={
                  "files": test_files,
                  "web_dir": web_evidence_dir,
                  "wiki_dir": wiki_evidence_dir,
              },
          ),
      ]
  
file_path: datasets/tensorflow_datasets/datasets/trivia_qa/trivia_qa_dataset_builder.py
imports: from __future__ import annotations
  import json
  import os
  from absl import logging
  from etils import epath
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Builder obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list