class_docstr: DatasetBuilder for tao dataset.
class_docstr_tok: ["DatasetBuilder","for","tao","dataset","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(
      self, dl_manager: tfds.download.DownloadManager
  ):
      """Returns SplitGenerators."""
  
      data = dl_manager.download_and_extract(
          {
              "train": _VIDEO_URL + "1-TAO_TRAIN.zip",
              "val": _VIDEO_URL + "2-TAO_VAL.zip",
              "annotations": _ANNOTATIONS_URL,
          }
      )
  
      manual_train, manual_val = _maybe_prepare_manual_data(dl_manager)
      id_map = _get_category_id_map(
          data["annotations"] / "annotations-1.2"
      )
  
      return {
          tfds.Split.TRAIN: self._generate_examples(
              data_path=data["train"],
              manual_path=manual_train,
              annotations_path=data["annotations"]
              / "annotations-1.2"
              / "train.json",
              id_map=id_map,
          ),
          tfds.Split.VALIDATION: self._generate_examples(
              data_path=data["val"],
              manual_path=manual_val,
              annotations_path=data["annotations"]
              / "annotations-1.2"
              / "validation.json",
              id_map=id_map,
          ),
      }
  
imports: from __future__ import annotations
  import collections
  import json
  import os
  from typing import Any, Dict, Optional, Tuple
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Tao obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: dict