class_docstr: Lost and Found Road Hazard Dataset.
class_docstr_tok: ["Lost","and","Found","Road","Hazard","Dataset","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      base_url = "http://www.dhbw-stuttgart.de/~sgehrig/lostAndFoundDataset/{}.zip"
  
      # For each feature, this is the name of the zipfile and
      # root-directory in the archive
      zip_file_names = {
          "image_left": self.builder_config.left_image_string,
          "image_right": self.builder_config.right_image_string,
          "segmentation_label": "gtCoarse",
          "instance_id": "gtCoarse",
          "disparity_map": "disparity",
      }
  
      download_urls = {
          feat: base_url.format(zip_file_names[feat])
          for feat in self.builder_config.features
      }
      # Split download and extract in two functions such that mock-data can
      # replace the result of the download function and is still used as input to
      # extract. Therefore, fake_data can be compressed zip archives.
      dl_paths = dl_manager.extract(dl_manager.download(download_urls))
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              # These kwargs will be passed to _generate_examples
              gen_kwargs={
                  feat: path.join(
                      dl_paths[feat], zip_file_names[feat], "train"
                  )
                  for feat in self.builder_config.features
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              # These kwargs will be passed to _generate_examples
              gen_kwargs={
                  feat: path.join(
                      dl_paths[feat], zip_file_names[feat], "test"
                  )
                  for feat in self.builder_config.features
              },
          ),
      ]
  
file_path: datasets/tensorflow_datasets/datasets/lost_and_found/lost_and_found_dataset_builder.py
imports: from os import path
  import re
  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