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import torch |
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import datasets |
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from pathlib import Path |
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from torch.utils.data import Dataset |
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from datasets import load_dataset, Features, Value, ClassLabel, DownloadConfig |
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_DESCRIPTION = """\ |
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""" |
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_CITATION = """\ |
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""" |
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_TRAIN_DOWNLOAD_URL = "train.txt" |
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_VAL_DOWNLOAD_URL = "val.txt" |
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CLASS_NAMES = ["company", "date", "address", "total", "O"] |
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class CustomTokenDataset(datasets.GeneratorBasedBuilder): |
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"""CustomTokenDataset dataset.""" |
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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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"id": datasets.Value("string"), |
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"tokens": datasets.Sequence(datasets.Value("string")), |
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"ner_tags": datasets.Sequence( |
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datasets.features.ClassLabel(names=sorted(list(CLASS_NAMES))) |
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), |
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} |
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), |
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supervised_keys=None, |
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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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"""Returns SplitGenerators.""" |
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urls_to_download = { |
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"train": _TRAIN_DOWNLOAD_URL, |
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"val": _VAL_DOWNLOAD_URL, |
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} |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": downloaded_files["train"]}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"filepath": downloaded_files["val"]}, |
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), |
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] |
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def _generate_examples(self, filepath): |
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with open(filepath, encoding="utf-8") as f: |
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guid = 0 |
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tokens = [] |
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ner_tags = [] |
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for line in f: |
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if line == "" or line == "\n": |
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if tokens: |
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yield guid, { |
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"id": str(guid), |
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"tokens": tokens, |
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"ner_tags": ner_tags, |
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} |
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guid += 1 |
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tokens = [] |
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ner_tags = [] |
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else: |
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splits = line.split(" ") |
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tokens.append(splits[0]) |
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ner_tags.append(splits[1].rstrip()) |
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yield guid, { |
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"id": str(guid), |
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"tokens": tokens, |
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"ner_tags": ner_tags, |
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} |
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