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from dataclasses import dataclass |
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import datasets |
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import pytorch_ie.data.builder |
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from pytorch_ie import AnnotationList, LabeledSpan, TextDocument, annotation_field |
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from pytorch_ie.utils.span import bio_tags_to_spans |
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class Conll2003Config(datasets.BuilderConfig): |
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"""BuilderConfig for Conll2003""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig forConll2003. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super().__init__(**kwargs) |
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@dataclass |
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class CoNLL2003Document(TextDocument): |
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entities: AnnotationList[LabeledSpan] = annotation_field(target="text") |
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class Conll2003(pytorch_ie.data.builder.GeneratorBasedBuilder): |
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DOCUMENT_TYPE = CoNLL2003Document |
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BASE_DATASET_PATH = "conll2003" |
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BUILDER_CONFIGS = [ |
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Conll2003Config( |
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name="conll2003", version=datasets.Version("1.0.0"), description="Conll2003 dataset" |
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), |
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] |
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def _generate_document_kwargs(self, dataset): |
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return {"int_to_str": dataset.features["ner_tags"].feature.int2str} |
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def _generate_document(self, example, int_to_str): |
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doc_id = example["id"] |
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tokens = example["tokens"] |
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ner_tags = example["ner_tags"] |
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start = 0 |
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token_offsets = [] |
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tag_sequence = [] |
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for token, tag_id in zip(tokens, ner_tags): |
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end = start + len(token) |
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token_offsets.append((start, end)) |
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tag_sequence.append(int_to_str(tag_id)) |
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start = end + 1 |
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text = " ".join(tokens) |
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spans = bio_tags_to_spans(tag_sequence) |
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document = CoNLL2003Document(text=text, id=doc_id) |
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for label, (start, end) in spans: |
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start_offset = token_offsets[start][0] |
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end_offset = token_offsets[end][1] |
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document.entities.append(LabeledSpan(start=start_offset, end=end_offset, label=label)) |
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return document |
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