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Temporary work-around for scoring a subset of components (#6090)

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* Try hacking the scorer to work around sentence boundaries

* Upd scorer

* Set dev version

* Upd scorer hack

* Fix version

* Improve comment on hack
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Matthew Honnibal 2020-09-18 14:26:42 +02:00 committed by GitHub
parent d32ce121be
commit bbdb5f62b7
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1 changed files with 12 additions and 0 deletions
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spacy/scorer.py
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@ -270,6 +270,18 @@ class Scorer:
for example in examples: for example in examples:
pred_doc = example.predicted pred_doc = example.predicted
gold_doc = example.reference gold_doc = example.reference
# TODO
# This is a temporary hack to work around the problem that the scorer
# fails if you have examples that are not fully annotated for all
# the tasks in your pipeline. For instance, you might have a corpus
# of NER annotations that does not set sentence boundaries, but the
# pipeline includes a parser or senter, and then the score_weights
# are used to evaluate that component. When the scorer attempts
# to read the sentences from the gold document, it fails.
try:
list(getter(gold_doc, attr))
except ValueError:
continue
# Find all labels in gold and doc # Find all labels in gold and doc
labels = set( labels = set(
[k.label_ for k in getter(gold_doc, attr)] [k.label_ for k in getter(gold_doc, attr)]