class_docstr: Covid19sum Dataset.
class_docstr_tok: ["Covid19sum","Dataset","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(
      self, dl_manager: tfds.download.DownloadManager
  ) -> List[tfds.core.SplitGenerator]:
      """Returns SplitGenerators."""
      extracted_path = dl_manager.extract(
          os.path.join(
              dl_manager.manual_dir, "CORD-19-research-challenge.zip"
          )
      )
      pd = tfds.core.lazy_imports.pandas
      df = pd.read_csv(
          os.path.join(extracted_path, "metadata.csv"),
          header=0,
          names=_ALL_COLUMNS,
      ).fillna("")
      data_paths = []
      for _, row in df.iterrows():
          file_dir = row["full_text_file"]
          if row["has_full_text"] and _has_abstract(row) and file_dir:
              d = {
                  k: row[k] for k in _ADDITIONAL_FEATURES + [_ABSTRACT]
              }
              d["path"] = os.path.join(
                  extracted_path,
                  file_dir,
                  file_dir,
                  row[_SHA] + ".json",
              )
              data_paths.append(d)
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={"data_paths": data_paths},
          )
      ]
  
file_path: datasets/tensorflow_datasets/summarization/covid19sum.py
imports: from __future__ import annotations
  import json
  import os
  from typing import Any, Dict, Iterator, List, Optional, Text, Tuple
  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 Covid19sum obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list