class_docstr: DAta Record to Text Generation.
class_docstr_tok: ["DAta","Record","to","Text","Generation","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      extracted_path = os.path.join(
          dl_manager.download_and_extract(_URL),
          "dart-master",
          "data",
          "v1.1.1",
      )
      return {
          tfds.Split.TRAIN: self._generate_examples(
              json_file=os.path.join(
                  extracted_path, "dart-v1.1.1-full-train.json"
              )
          ),
          tfds.Split.VALIDATION: self._generate_examples(
              json_file=os.path.join(
                  extracted_path, "dart-v1.1.1-full-dev.json"
              )
          ),
          tfds.Split.TEST: self._generate_examples(
              json_file=os.path.join(
                  extracted_path, "dart-v1.1.1-full-test.json"
              )
          ),
      }
  
file_path: datasets/tensorflow_datasets/structured/dart/dart.py
imports: from __future__ import annotations
  import json
  import os
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Dart obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: dict