def _split_generators(self, dl_manager: tfds.download.DownloadManager):
"""Returns SplitGenerators."""
# TODO(financial_sentiment_dataset): Downloads the data and defines the splits
path = dl_manager.download_kaggle_data(
'ankurzing/sentiment-analysis-for-financial-news')
# TODO(financial_sentiment_dataset): Returns the Dict[split names, Iterator[Key, Example]]
return {
'train':
self._generate_examples(path=os.path.join(path, 'all-data.csv')),
}
def _split_generators(
dl_manager: tfds.download.DownloadManager,
) -> Dict[str, Iterator[Tuple[str, Dict[str, Union[Path, str]]]]]:
"""Returns SplitGenerators."""
path = dl_manager.download_kaggle_data(_KAGGLE_DATA)
path /= "MURA-v1.1"
return {
"train": Mura._generate_examples(path / "train"),
"valid": Mura._generate_examples(path / "valid"),
}