class_docstr: DatasetBuilder for the ProteinNet dataset.
class_docstr_tok: ["DatasetBuilder","for","the","ProteinNet","dataset","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(
      self, dl_manager: tfds.download.DownloadManager
  ) -> Dict[Union[str, tfds.Split], _ExampleIterator]:
      """Returns SplitGenerators."""
      name = (
          self.builder_config.name
      )  # Configurable dataset (config) name.
      path = dl_manager.download_and_extract(
          urllib.parse.urljoin(self.URL, self.FILES[name])
      )
  
      splits = {
          tfds.Split.VALIDATION: self._generate_examples(
              os.path.join(path, name, "validation")
          ),
          tfds.Split.TEST: self._generate_examples(
              os.path.join(path, name, "testing")
          ),
      }
      for threshold in self.THRESHOLDS:  # Train splits.
          split_path = os.path.join(path, name, f"training_{threshold}")
          splits[f"train_{threshold}"] = self._generate_examples(
              split_path
          )
      return splits
  
file_path: datasets/tensorflow_datasets/datasets/protein_net/protein_net_dataset_builder.py
imports: from __future__ import annotations
  import os
  from typing import Dict, Iterator, List, Optional, Sequence, Tuple, Union
  import urllib
  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: splits