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| """TODO: Add a description here.""" |
|
|
| import datasets |
| import gzip |
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
| |
| |
| _CITATION = """\ |
| @InProceedings{huggingface:dataset, |
| title = {A great new dataset}, |
| author={huggingface, Inc. |
| }, |
| year={2020} |
| } |
| """ |
|
|
| _VERSION= "1.1.0" |
|
|
| |
| |
| _DESCRIPTION = """\ |
| BSBasque dataset. The text is extracted from the following domains: |
| |
| https://www.berria.eus |
| https://eu.wikipedia.org |
| https://goiena.eus |
| https://www.argia.eus |
| https://goierri.hitza.eus |
| |
| """ |
|
|
| |
| _HOMEPAGE = "to.be.announced.eus" |
|
|
| |
| _LICENSE = "CC BY-SA 4.0" |
|
|
| _BASE_DATA_URL_STR = ( |
| "https://ixa2.si.ehu.es/~ccpsoeta/bsbasque/" |
| ) |
| _BASE_CHECKSUM_FILE_NAME = "bsbasque_sha256.txt" |
|
|
| class BsBasqueConfig(datasets.BuilderConfig): |
| "BsBasque corpus." |
|
|
| def __init__(self, **kwargs): |
| """BuilderConfig for BsBasque. |
| |
| Args: |
| **kwargs: Keyword arguments forwarded to super. |
| """ |
|
|
| |
| name = "bsbasque" |
| description = "BsBasque dataset" |
| super(BsBasqueConfig, self).__init__(name=name, description=description, **kwargs) |
|
|
| |
| self.base_data_url = _BASE_DATA_URL_STR |
|
|
|
|
| |
| class BSBasque(datasets.GeneratorBasedBuilder): |
| """TODO: Short description of my dataset.""" |
|
|
| BUILDER_CONFIGS = [ |
| BsBasqueConfig(version=datasets.Version(_VERSION)) |
| ] |
| BUILDER_CONFIG_CLASS = BsBasqueConfig |
|
|
| def _info(self): |
| |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features({"id": datasets.Value("int64"), "text": datasets.Value("string")}), |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| checksum_url = self.config.base_data_url + _BASE_CHECKSUM_FILE_NAME |
| checksum_file = dl_manager.download(checksum_url) |
| with open(checksum_file, encoding="utf-8") as f: |
| data_filenames = [line.split("\t")[0] for line in f if line] |
| data_urls = [self.config.base_data_url + data_filename for data_filename in data_filenames] |
| downloaded_files = dl_manager.download(data_urls) |
| return [ |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files}), |
| ] |
|
|
| def _generate_examples(self, filepaths): |
| """This function returns the examples in the raw (text) form by iterating on all the files.""" |
| id_ = 0 |
| for filepath in filepaths: |
| logger.info("generating examples from = %s", filepath) |
| with gzip.open(filepath, "rt") as f: |
| for line in f: |
| feature = id_, {"id": id_, "text": "".join(line).rstrip()} |
| yield feature |
| id_ += 1 |
|
|