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rm component function
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@ -1007,21 +1007,6 @@ def _get_labels_from_spancat(nlp: Language) -> Dict[str, Set[str]]:
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return labels
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def _get_labels_from_trainable_lemmatizer(nlp: Language) -> Set[str]:
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pipe_names = [
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pipe_name
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for pipe_name in nlp.pipe_names
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if nlp.get_pipe_meta(pipe_name).factory == "trainable_lemmatizer"
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]
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labels: Set[str] = set()
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for pipe_name in pipe_names:
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pipe = nlp.get_pipe(pipe_name)
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# This gets lemmatization trees and no partial subtrees
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for tree_id in pipe.tree2label.keys():
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labels.add(pipe.trees.tree_to_str(tree_id))
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return labels
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def _gmean(l: List) -> float:
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"""Compute geometric mean of a list"""
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return math.exp(math.fsum(math.log(i) for i in l) / len(l))
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