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from sftp import SpanPredictor |
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def print_children(sentence, boundary, labels, _): |
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print('Sentence:', ' '.join(sentence)) |
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for (start_idx, end_idx), lbl in zip(boundary, labels): |
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print(' '.join(sentence[start_idx:end_idx+1]), ':', lbl) |
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print('='*20) |
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def example(): |
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print("Loading predictor...") |
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predictor = SpanPredictor.from_path( |
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"/data/p289731/cloned/lome-models/models/spanfinder/model.mod.tar.gz", |
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cuda_device=-1 |
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) |
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print("Predicting for sentence..") |
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sentence = ['Tom', 'eats', 'an', 'apple', 'and', 'he', 'wakes', 'up', '.'] |
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p1 = predictor.force_decode(sentence) |
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print_children(sentence, *p1) |
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p2 = predictor.force_decode(sentence, parent_span=(1, 1), parent_label='Ingestion') |
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print_children(sentence, *p2) |
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p3 = predictor.force_decode(sentence, child_spans=[(0, 0), (2, 3)], parent_span=(1, 1), parent_label='Ingestion') |
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print_children(sentence, *p3) |
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if __name__ == '__main__': |
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example() |
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