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