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