class_docstr: CIFAR-10.
class_docstr_tok: ["CIFAR-10","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      cifar_path = dl_manager.download_and_extract(self._cifar_info.url)
      cifar_info = self._cifar_info
  
      cifar_path = os.path.join(cifar_path, cifar_info.prefix)
  
      # Load the label names
      for label_key, label_file in zip(
          cifar_info.label_keys, cifar_info.label_files
      ):
          labels_path = os.path.join(cifar_path, label_file)
          with epath.Path(labels_path).open() as label_f:
              label_names = [
                  name for name in label_f.read().split("\n") if name
              ]
          self.info.features[label_key].names = label_names
  
      # Define the splits
      def gen_filenames(filenames):
          for f in filenames:
              yield os.path.join(cifar_path, f)
  
      return {
          tfds.Split.TRAIN: self._generate_examples(
              "train_", gen_filenames(cifar_info.train_files)
          ),
          tfds.Split.TEST: self._generate_examples(
              "test_", gen_filenames(cifar_info.test_files)
          ),
      }
  
file_path: datasets/tensorflow_datasets/image_classification/cifar.py
imports: import collections
  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 3 for calling the Cifar10 obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: dict