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Allow batch size to be set for evaluation in spacy train

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Matthw Honnibal 2020-07-01 15:04:36 +02:00
parent f5532757a3
commit c5d12d1a22
1 changed files with 3 additions and 2 deletions
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5
spacy/cli/train.py
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@ -332,13 +332,14 @@ def create_evaluation_callback(nlp, optimizer, corpus, cfg):
) )
n_words = sum(len(ex.predicted) for ex in dev_examples) n_words = sum(len(ex.predicted) for ex in dev_examples)
batch_size = cfg.get("evaluation_batch_size", 128)
start_time = timer() start_time = timer()
if optimizer.averages: if optimizer.averages:
with nlp.use_params(optimizer.averages): with nlp.use_params(optimizer.averages):
scorer = nlp.evaluate(dev_examples, batch_size=32) scorer = nlp.evaluate(dev_examples, batch_size=eval_batch_size)
else: else:
scorer = nlp.evaluate(dev_examples, batch_size=32) scorer = nlp.evaluate(dev_examples, batch_size=eval_batch_size)
end_time = timer() end_time = timer()
wps = n_words / (end_time - start_time) wps = n_words / (end_time - start_time)
scores = scorer.scores scores = scorer.scores