class_docstr: STL-10 dataset.
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      train_files = ["train_X.bin", "train_y.bin"]
      test_files = ["test_X.bin", "test_y.bin"]
      unlabeled_files = ["unlabeled_X.bin"]
  
      stl10_path = dl_manager.download_and_extract(URL)
      stl10_path = os.path.join(stl10_path, "stl10_binary/")
  
      def gen_filenames(filenames):
          for f in filenames:
              yield os.path.join(stl10_path, f)
  
      # Adds the class names to the feature description.
      with tf.io.gfile.GFile(
          next(gen_filenames(["class_names.txt"])), "r"
      ) as f:
          class_names = [l.strip("\n") for l in f]
      self.info.features["label"].names = class_names
  
      # Define the splits
      splits = [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={"filepaths": gen_filenames(train_files)},
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={"filepaths": gen_filenames(test_files)},
          ),
          tfds.core.SplitGenerator(
              name=UNLABELLED,
              gen_kwargs={"filepaths": gen_filenames(unlabeled_files)},
          ),
      ]
  
      return splits
  
file_path: datasets/tensorflow_datasets/datasets/stl10/stl10_dataset_builder.py
imports: import os
  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: splits