class_docstr: Describable Textures Dataset (DTD).
code: def _split_generators(self, dl_manager):
      # Note: The file extension is .tar.gz, but it is actually a .tar file.
      data_path = dl_manager.download_and_extract(_DATA_URL)
  
      # Note: DTD defines 10-fold CV partitions. Our TRAIN/TEST/VALIDATION are
      # those of the first fold.
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs=dict(data_path=data_path, split_name="train1"),
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs=dict(data_path=data_path, split_name="test1"),
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs=dict(data_path=data_path, split_name="val1"),
          ),
      ]
  
file_path: datasets/tensorflow_datasets/image_classification/dtd.py
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 Dtd obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list