code: def test_compute_split_info(tmp_path):
      builder = testing.DummyDataset(data_dir=tmp_path)
      builder.download_and_prepare()
  
      filename_template = naming.ShardedFileTemplate(
          dataset_name=builder.name,
          data_dir=builder.data_dir,
          filetype_suffix=builder.info.file_format.file_suffix,
      )
      split_infos = compute_split_utils.compute_split_info(
          out_dir=tmp_path,
          filename_template=filename_template,
      )
  
      assert [s.to_proto() for s in split_infos] == [
          s.to_proto() for s in builder.info.splits.values()
      ]
  
      # Split info are correctly saved
      filename_template = filename_template.replace(
          data_dir=tmp_path, split="train"
      )
      split_info = compute_split_utils._split_info_from_path(
          filename_template
      )
      assert (
          builder.info.splits["train"].to_proto()
          == split_info.to_proto()
      )
  
imports: import pytest
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import naming
  from tensorflow_datasets.core.folder_dataset import compute_split_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_compute_split_info(tmp_path) without return types