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Fix #1444: fix pipeline logic and wrong paramater in update call
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@ -56,8 +56,7 @@ def train_ner(nlp, train_data, output_dir):
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losses = {}
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for batch in minibatch(get_gold_parses(nlp.make_doc, train_data), size=3):
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docs, golds = zip(*batch)
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nlp.update(docs, golds, losses=losses, sgd=optimizer, update_shared=True,
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drop=0.35)
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nlp.update(docs, golds, losses=losses, sgd=optimizer, drop=0.35)
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print(losses)
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if not output_dir:
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return
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@ -100,9 +99,10 @@ def main(model_name, output_directory=None):
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)
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]
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nlp.pipeline.append(TokenVectorEncoder(nlp.vocab))
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nlp.pipeline.append(NeuralEntityRecognizer(nlp.vocab))
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nlp.pipeline[-1].add_label('ANIMAL')
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nlp.add_pipe(TokenVectorEncoder(nlp.vocab))
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ner = NeuralEntityRecognizer(nlp.vocab)
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ner.add_label('ANIMAL')
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nlp.add_pipe(ner)
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train_ner(nlp, train_data, output_directory)
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# Test that the entity is recognized
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