class_docstr: CheXpert 2019.
class_docstr_tok: ["CheXpert","2019","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      path = dl_manager.manual_dir
      train_path = os.path.join(path, _TRAIN_DIR)
      val_path = os.path.join(path, _VALIDATION_DIR)
  
      if not tf.io.gfile.exists(train_path) or not tf.io.gfile.exists(
          val_path
      ):
          msg = (
              "You must download the dataset folder from CheXpert"
              "website manually and place it into %s." % path
          )
          raise AssertionError(msg)
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={
                  "imgs_path": path,  # Relative img path is provided in csv
                  "csv_path": os.path.join(path, _TRAIN_LABELS_FNAME),
              },
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs={
                  "imgs_path": path,
                  "csv_path": os.path.join(
                      path, _VALIDATION_LABELS_FNAME
                  ),
              },
          ),
      ]
  
file_path: datasets/tensorflow_datasets/image_classification/chexpert.py
imports: import collections
  import csv
  import os
  from etils import epath
  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 Chexpert obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list