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handle empty clusters

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This commit is contained in:
Kádár Ákos 2022-03-28 11:29:00 +02:00
parent 4fc40340f9
commit e4b4b67ef6
1 changed files with 21 additions and 20 deletions
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7
spacy/pipeline/coref.py
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@ -458,8 +458,8 @@ class SpanPredictor(TrainablePipe):
out = []
for doc in docs:
# TODO check shape here
span_scores = self.model.predict(doc)
span_scores = span_scores[0]
span_scores = self.model.predict([doc])
if span_scores.size:
# the information about clustering has to come from the input docs
# first let's convert the scores to a list of span idxs
start_scores = span_scores[:, :, 0]
@ -479,6 +479,8 @@ class SpanPredictor(TrainablePipe):
ncluster.append((starts[cidx], ends[cidx]))
cidx += 1
out_clusters.append(ncluster)
else:
out_clusters = []
out.append(out_clusters)
return out
@ -628,7 +630,6 @@ class SpanPredictor(TrainablePipe):
# XXX this is the only different part
p_clusters = doc2clusters(ex.predicted, self.output_prefix)
g_clusters = doc2clusters(ex.reference, self.output_prefix)
cluster_info = get_cluster_info(p_clusters, g_clusters)
evaluator.update(cluster_info)