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Add vector data to model meta after training (see #1457)
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@ -144,7 +144,10 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=30, n_sents=0,
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file_.write(json_dumps(scorer.scores))
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meta_loc = output_path / ('model%d' % i) / 'meta.json'
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meta['accuracy'] = scorer.scores
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meta['speed'] = {'nwords': nwords, 'cpu':cpu_wps, 'gpu': gpu_wps}
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meta['speed'] = {'nwords': nwords, 'cpu': cpu_wps,
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'gpu': gpu_wps}
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meta['vectors'] = {'entries': nlp.vocab.vectors_length,
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'width': 0}
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meta['lang'] = nlp.lang
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meta['pipeline'] = pipeline
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meta['spacy_version'] = '>=%s' % about.__version__
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