import datasets logger = datasets.logging.get_logger(__name__) _CITATION = """\ """ _DESCRIPTION = """\ """ _URL = "https://huggingface.co/datasets/mrojas/finding/resolve/main/data/" _TRAINING_FILE = "Finding_train.conll" _DEV_FILE = "Finding_dev.conll" _TEST_FILE = "Finding_test.conll" class FindingConfig(datasets.BuilderConfig): """BuilderConfig for Finding""" def __init__(self, **kwargs): """BuilderConfig for Finding. Args: **kwargs: keyword arguments forwarded to super. """ super(FindingConfig, self).__init__(**kwargs) class Finding(datasets.GeneratorBasedBuilder): """Finding dataset.""" BUILDER_CONFIGS = [ FindingConfig(name="finding", version=datasets.Version("1.0.0"), description="Finding dataset"), ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "tokens": datasets.Sequence(datasets.Value("string")), "ner_tags": datasets.Sequence( datasets.features.ClassLabel( names=[ "O", "B-Finding", "I-Finding", ] ) ), } ), supervised_keys=None, homepage="", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" urls_to_download = { "train": f"{_URL}{_TRAINING_FILE}", "dev": f"{_URL}{_DEV_FILE}", "test": f"{_URL}{_TEST_FILE}", } downloaded_files = dl_manager.download_and_extract(urls_to_download) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), ] def _generate_examples(self, filepath): logger.info("⏳ Generating examples from = %s", filepath) with open(filepath, encoding="utf-8") as f: id_ = 0 tokens = [] ner_tags = [] for line in f: if line == "" or line == "\n": if tokens: yield id_, { "tokens": tokens, "ner_tags": ner_tags, } id_ += 1 tokens = [] ner_tags = [] else: # conll2003 tokens are space separated splits = line.split(" ") tokens.append(splits[0]) ner_tags.append(splits[1].rstrip()) # last example yield id_, { "tokens": tokens, "ner_tags": ner_tags, }