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[WIP] Update
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@ -272,7 +272,7 @@ class SpanCategorizerExclusive(TrainablePipe):
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"""Modify a batch of Doc objects, using pre-computed scores.
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docs (Iterable[Doc]): The documents to modify.
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scores: The scores to set, produced by SpanCategorizer.predict.
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scores: The scores to set, produced by SpanCategorizerExclusive.predict.
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DOCS: https://spacy.io/api/spancategorizerexclusive#set_annotations
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"""
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@ -446,10 +446,12 @@ class SpanCategorizerExclusive(TrainablePipe):
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scores = self.model.ops.to_numpy(scores)
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indices = self.model.ops.to_numpy(indices)
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predicted = scores.argmax(axis=1)
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# Remove samples where the negative label is the argmax
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positive = numpy.where(predicted != self._negative_label)
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predicted = predicted[positive[0]]
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indices = indices[positive[0]]
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# Sort spans according to argmax probability
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if not allow_overlap:
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argmax_probs = numpy.take_along_axis(
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@ -459,16 +461,20 @@ class SpanCategorizerExclusive(TrainablePipe):
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sort_idx = (argmax_probs * -1).argsort()
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predicted = predicted[sort_idx]
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indices = indices[sort_idx]
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seen = Ranges()
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spans = SpanGroup(doc, name=self.key)
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for i in range(len(predicted)):
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label = predicted[i]
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start = indices[i, 0]
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end = indices[i, 1]
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if not allow_overlap:
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if (start, end) in seen:
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continue
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else:
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seen.add(start, end)
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spans.append(Span(doc, start, end, label=labels[label]))
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return spans
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