| |
| import datasets |
| import json |
| try: |
| import lzma as xz |
| except ImportError: |
| import pylzma as xz |
|
|
| datasets.logging.set_verbosity_info() |
| logger = datasets.logging.get_logger(__name__) |
|
|
| _DESCRIPTION = """\ |
| """ |
|
|
| _HOMEPAGE = "https://skatinger.github.io/master_thesis/", |
|
|
| _LICENSE = "" |
|
|
| _CITATION = "" |
|
|
| _TYPES = ["original", "paraphrased"] |
|
|
| _SIZES = [4096, 512] |
|
|
| _URLS = { |
| "original_4096": "data/original_4096.jsonl.xz", |
| "original_512": "data/original_512.jsonl.xz", |
| "paraphrased_4096": "data/paraphrased_4096.jsonl.xz", |
| "paraphrased_512": "data/paraphrased_512.jsonl.xz" |
| } |
|
|
|
|
| class WikipediaForMaskFillingConfig(datasets.BuilderConfig): |
| """BuilderConfig for WikipediaForMaskFilling. |
| |
| features: *list[string]*, list of the features that will appear in the |
| feature dict. Should not include "label". |
| **kwargs: keyword arguments forwarded to super |
| """ |
|
|
| def __init__(self, type:str, size=4096, **kwargs): |
| """BuilderConfig for WikipediaForMaskFilling. |
| |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
|
|
| |
| |
| super(WikipediaForMaskFillingConfig, self).__init__(**kwargs) |
| self.size = size |
| self.type = type |
|
|
|
|
| class WikipediaForMaskFilling(datasets.GeneratorBasedBuilder): |
| """WikipediaForMaskFilling dataset.""" |
|
|
| BUILDER_CONFIGS = [ |
| WikipediaForMaskFillingConfig( |
| name="original_4096", |
| version=datasets.Version("1.0.0"), |
| description="Part of the dataset with original texts and masks, with text chunks split into size of max 4096 tokens (Longformer).", |
| size=4096, |
| type="original" |
| ), |
| WikipediaForMaskFillingConfig( |
| name="original_512", |
| version=datasets.Version("1.0.0"), |
| description="text chunks split into size of max 512 tokens (roberta).", |
| size=512, |
| type="original" |
| ), |
| WikipediaForMaskFillingConfig( |
| name="paraphrased_4096", |
| version=datasets.Version("1.0.0"), |
| description="Part of the dataset with paraphrased texts and masks, with text chunks split into size of max 4096 tokens (Longformer).", |
| size=4096, |
| type="paraphrased" |
| ), |
| WikipediaForMaskFillingConfig( |
| name="paraphrased_512", |
| version=datasets.Version("1.0.0"), |
| description="Paraphrased text chunks split into size of max 512 tokens (roberta).", |
| size=512, |
| type="paraphrased" |
| ) |
| ] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "id": datasets.Value("int32"), |
| "sequence_number": datasets.Value("int32"), |
| "title": datasets.Value("string"), |
| "type": datasets.Value("string"), |
| "size": datasets.Value("int32"), |
| "texts": datasets.Value("string"), |
| "masks": datasets.Sequence(datasets.Value("string")), |
| } |
| ), |
| |
| |
| supervised_keys=None, |
| homepage=_HOMEPAGE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| type = self.config.type |
| size = self.config.size |
| filepath = dl_manager.download(f"data/{type}_{size}.jsonl.xz") |
|
|
| return [ |
| datasets.SplitGenerator(name='train', gen_kwargs={"filepath": filepath}), |
| ] |
|
|
| def _generate_examples(self, filepath): |
| id_ = 0 |
| if filepath: |
| logger.info("Generating examples from = %s", filepath) |
| try: |
| with xz.open(open(filepath,'rb'), 'rt', encoding='utf-8') as f: |
| json_list = list(f) |
| |
| for json_str in json_list: |
| data = json.loads(json_str) |
| if data is not None and isinstance(data, dict): |
| yield id_, { |
| "id": data["id"], |
| "sequence_number": data["sequence_number"], |
| "title": data["title"], |
| "type": data["type"], |
| "size": data["size"], |
| "texts": data["texts"], |
| "masks": data["masks"] |
| } |
| id_ +=1 |
|
|
| except Exception: |
| logger.exception("Error while processing file %s", filepath) |
|
|
