Add loading script
Browse files- 2021-punctuation-restoration.py +123 -0
2021-punctuation-restoration.py
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import os
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import datasets
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import pandas as pd
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_CITATION = """"""
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_DESCRIPTION = """\
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This dataset is designed to be used in training models
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that restore punctuation marks from the output of
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Automatic Speech Recognition system for Polish language.
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"""
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_HOMEPAGE = "https://github.com/poleval/2021-punctuation-restoration"
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_URL = "https://huggingface.co/datasets/lruczu/2021-punctuation-restoration/resolve/main"
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_PATHS = {
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"train": os.path.join(_URL, "train"),
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"test-A": os.path.join(_URL, "test-A"),
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}
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class PunctuationDatasetConfig(datasets.BuilderConfig):
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"""BuilderConfig for AfrikaansNerCorpus"""
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def __init__(self, **kwargs):
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"""BuilderConfig for PunctuationDataset.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(PunctuationDatasetConfig, self).__init__(**kwargs)
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class PunctuationDataset(datasets.GeneratorBasedBuilder):
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"""TODO: Short description of my dataset."""
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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PunctuationDatasetConfig(
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name="punctuation_dataset",
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version=datasets.Version("1.0.0"),
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description="PunctuationDataset dataset",
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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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"text_in": datasets.Value("string"),
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"text_out": datasets.Value("string"),
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"tokens": datasets.Sequence(datasets.Value("string")),
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"tags": datasets.Sequence(
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datasets.features.ClassLabel(
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names=[
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'B-.',
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'B-,',
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'B--',
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'B-!',
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'B-?',
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'B-:',
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'B-;',
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'O',
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]
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)
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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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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN, gen_kwargs={"filepath": _PATHS["train"]}
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST, gen_kwargs={"filepath": _PATHS["test-A"]}
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),
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]
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def _generate_examples(self, filepath):
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in_df = pd.read_csv(os.path.join(filepath, "in.tsv"), sep='\t', header=None)
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out_df = pd.read_csv(os.path.join(filepath, 'expected.tsv'), sep='\t', header=None)
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for key, ((_, row_in), (_, row_out)) in enumerate(zip(in_df.iterrows(), out_df.iterrows()), 1):
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text_in = PunctuationDataset._clean_text(row_in[1])
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text_out = PunctuationDataset._clean_text(row_out[0])
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tokens = []
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tags = []
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for token_in, token_out in zip(text_in.split(), text_out.split()):
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assert token_in.lower() in token_out.lower()
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tokens.append(token_in)
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if token_in.lower() == token_out.lower():
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tags.append('O')
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else:
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tags.append(f'B-{token_out[-1]}')
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yield key, {
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"text_in": text_in,
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"text_out": text_out,
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"tokens": tokens,
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"tags": tags
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}
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@staticmethod
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def _clean_text(text: str, lower: bool = False) -> str:
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if lower:
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text = text.lower()
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text = text.replace(' -', '')
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text = text.replace(' .', '')
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text = text.replace(' ,', '')
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text = text.replace(' ', ' ')
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text = text.strip()
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return text
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