class_docstr: MIT Scene Parsing Benchmark dataset.
code: def _split_generators(self, dl_manager):
      dl_paths = dl_manager.download_and_extract(
          {
              "images": _TRAIN_URL["images"],
              "annotations": _TRAIN_URL["annotations"],
          }
      )
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "images_dir_path": os.path.join(
                      dl_paths["images"], "images/training"
                  ),
                  "annotations_dir_path": os.path.join(
                      dl_paths["annotations"],
                      "annotations_instance/training",
                  ),
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={
                  "images_dir_path": os.path.join(
                      dl_paths["images"], "images/validation"
                  ),
                  "annotations_dir_path": os.path.join(
                      dl_paths["annotations"],
                      "annotations_instance/validation",
                  ),
              },
          ),
      ]
  
imports: import os
  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