class_docstr: The Groove MIDI Dataset (GMD) of drum performances.
class_docstr_tok: ["The","Groove","MIDI","Dataset","(","GMD",")","of","drum","performances","."]
docstr: Returns splits.
docstr_tok: ["Returns","splits","."]
code: def _split_generators(self, dl_manager):
      """Returns splits."""
      # Download data.
      data_dir = os.path.join(
          dl_manager.download_and_extract(
              _DOWNLOAD_URL
              if self._builder_config.include_audio  # pytype: disable=attribute-error  # always-use-return-annotations
              else _DOWNLOAD_URL_MIDI_ONLY
          ),
          "groove",
      )
  
      rows = collections.defaultdict(list)
      with tf.io.gfile.GFile(os.path.join(data_dir, "info.csv")) as f:
          reader = csv.DictReader(f)
          for row in reader:
              rows[row["split"]].append(row)
  
      return [
          tfds.core.SplitGenerator(  # pylint: disable=g-complex-comprehension
              name=split,
              gen_kwargs={"rows": split_rows, "data_dir": data_dir},
          )
          for split, split_rows in rows.items()
      ]
  
file_path: datasets/tensorflow_datasets/datasets/groove/groove_dataset_builder.py
imports: from __future__ import annotations
  import collections
  import copy
  import csv
  import io
  import os
  from absl import logging
  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: unknown