| import datasets |
|
|
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
|
|
| _CITATION = """\ |
| |
| """ |
|
|
| _DESCRIPTION = """\ |
| |
| |
| """ |
|
|
| _URL = "https://huggingface.co/datasets/mrojas/shared-task/resolve/main/data/" |
| _TRAINING_FILE = "train.conll" |
| _DEV_FILE = "dev.conll" |
| _TEST_FILE = "test.conll" |
|
|
|
|
| class SharedConfig(datasets.BuilderConfig): |
| """BuilderConfig for Shared Task""" |
|
|
| def __init__(self, **kwargs): |
| """BuilderConfig for Shared Task. |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super(SharedConfig, self).__init__(**kwargs) |
|
|
|
|
| class Shared(datasets.GeneratorBasedBuilder): |
| """Shared dataset.""" |
|
|
| BUILDER_CONFIGS = [ |
| SharedConfig(name="Shared", version=datasets.Version("1.0.0"), description="Shared 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=[ |
| "B-EXPLORATION", |
| "I-EXPLORATION", |
| "B-PRESENT_ILLNESS", |
| "I-PRESENT_ILLNESS", |
| "B-TREATMENT", |
| "I-TREATMENT", |
| "B-EVOLUTION", |
| "I-EVOLUTION", |
| "B-PAST_MEDICAL_HISTORY", |
| "I-PAST_MEDICAL_HISTORY", |
| "B-DERIVED_FROM/TO", |
| "I-DERIVED_FROM/TO", |
| "B-FAMILY_HISTORY", |
| "I-FAMILY_HISTORY", |
| ] |
| ) |
| ), |
| } |
| ), |
| 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: |
| |
| splits = line.split(" ") |
| tokens.append(splits[0]) |
| ner_tags.append(splits[1].rstrip()) |
| |
| yield id_, { |
| "tokens": tokens, |
| "ner_tags": ner_tags, |
| } |
