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	Move spans2ints to util
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				|  | @ -143,7 +143,7 @@ def create_head_span_idxs(ops, doclen: int): | |||
| 
 | ||||
| 
 | ||||
| def get_clusters_from_doc(doc) -> List[List[Tuple[int, int]]]: | ||||
|     """Given a Doc, convert the cluster spans to simple int tuple lists. The  | ||||
|     """Given a Doc, convert the cluster spans to simple int tuple lists. The | ||||
|     ints are char spans, to be tokenization independent. | ||||
|     """ | ||||
|     out = [] | ||||
|  | @ -203,3 +203,15 @@ def create_gold_scores( | |||
| 
 | ||||
|     # caller needs to convert to array, and add placeholder | ||||
|     return out | ||||
| 
 | ||||
| 
 | ||||
| def spans2ints(doc): | ||||
|     """Convert doc.spans to nested list of ints for comparison. | ||||
|     The ints are token indices. | ||||
| 
 | ||||
|     This is useful for checking consistency of predictions. | ||||
|     """ | ||||
|     out = [] | ||||
|     for key, cluster in doc.spans.items(): | ||||
|         out.append([(ss.start, ss.end) for ss in cluster]) | ||||
|     return out | ||||
|  |  | |||
|  | @ -9,6 +9,7 @@ from spacy.ml.models.coref_util import ( | |||
|     DEFAULT_CLUSTER_PREFIX, | ||||
|     select_non_crossing_spans, | ||||
|     get_sentence_ids, | ||||
|     spans2ints, | ||||
| ) | ||||
| 
 | ||||
| from thinc.util import has_torch | ||||
|  | @ -35,16 +36,6 @@ TRAIN_DATA = [ | |||
| # fmt: on | ||||
| 
 | ||||
| 
 | ||||
| def spans2ints(doc): | ||||
|     """Convert doc.spans to nested list of ints for comparison. | ||||
|     The ints are token indices. | ||||
| 
 | ||||
|     This is useful for checking consistency of predictions. | ||||
|     """ | ||||
|     out = [] | ||||
|     for key, cluster in doc.spans.items(): | ||||
|         out.append([(ss.start, ss.end) for ss in cluster]) | ||||
|     return out | ||||
| 
 | ||||
| 
 | ||||
| @pytest.fixture | ||||
|  |  | |||
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