class_docstr: Pet Finder.
class_docstr_tok: ["Pet","Finder","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      # petfinder: Downloads the data and defines the splits
      # dl_manager is a tfds.download.DownloadManager that can be used to
      # download and extract URLs
      # dl_paths = dl_manager.download_kaggle_data(url)
      dl_paths = dl_manager.download_and_extract(_DL_URLS)
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "csv_name": "train.csv",
                  "csv_paths": dl_paths["train"],
                  "img_paths": dl_paths["train_images"],
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={
                  "csv_name": "test.csv",
                  "csv_paths": dl_paths["test"],
                  "img_paths": dl_paths["test_images"],
              },
          ),
      ]
  
file_path: datasets/tensorflow_datasets/datasets/pet_finder/pet_finder_dataset_builder.py
imports: from __future__ import annotations
  import os
  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