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Add batch size argument to Language.evaluate(). Closes #3263
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@ -573,7 +573,7 @@ class Language(object):
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proc._rehearsal_model = deepcopy(proc.model)
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return self._optimizer
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def evaluate(self, docs_golds, verbose=False):
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def evaluate(self, docs_golds, verbose=False, batch_size=256):
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scorer = Scorer()
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docs, golds = zip(*docs_golds)
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docs = list(docs)
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@ -582,7 +582,7 @@ class Language(object):
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if not hasattr(pipe, "pipe"):
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docs = (pipe(doc) for doc in docs)
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else:
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docs = pipe.pipe(docs, batch_size=256)
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docs = pipe.pipe(docs, batch_size=batch_size)
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for doc, gold in zip(docs, golds):
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if verbose:
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print(doc)
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