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Add speed benchmarks to metadata
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@ -114,15 +114,33 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=10, n_sents=0,
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nlp.to_disk(epoch_model_path)
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nlp_loaded = lang_class(pipeline=pipeline)
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nlp_loaded = nlp_loaded.from_disk(epoch_model_path)
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scorer = nlp_loaded.evaluate(
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list(corpus.dev_docs(
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dev_docs = list(corpus.dev_docs(
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nlp_loaded,
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gold_preproc=gold_preproc)))
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gold_preproc=gold_preproc))
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nwords = sum(len(doc_gold[0]) for doc_gold in dev_docs)
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start_time = timer()
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scorer = nlp_loaded.evaluate(dev_docs)
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end_time = timer()
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if use_gpu < 0:
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gpu_wps = None
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cpu_wps = nwords/(end_time-start_time)
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else:
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gpu_wps = nwords/(end_time-start_time)
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with Model.use_device('cpu'):
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nlp_loaded = lang_class(pipeline=pipeline)
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nlp_loaded = nlp_loaded.from_disk(epoch_model_path)
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dev_docs = list(corpus.dev_docs(
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nlp_loaded, gold_preproc=gold_preproc))
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start_time = timer()
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scorer = nlp_loaded.evaluate(dev_docs)
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end_time = timer()
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cpu_wps = nwords/(end_time-start_time)
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acc_loc =(output_path / ('model%d' % i) / 'accuracy.json')
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with acc_loc.open('w') as file_:
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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['lang'] = nlp.lang
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meta['pipeline'] = pipeline
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meta['spacy_version'] = '>=%s' % about.__version__
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@ -132,7 +150,7 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=10, n_sents=0,
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with meta_loc.open('w') as file_:
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file_.write(json_dumps(meta))
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util.set_env_log(True)
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print_progress(i, losses, scorer.scores)
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print_progress(i, losses, scorer.scores, cpu_wps=cpu_wps, gpu_wps=gpu_wps)
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finally:
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print("Saving model...")
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try:
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@ -153,16 +171,18 @@ def _render_parses(i, to_render):
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file_.write(html)
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def print_progress(itn, losses, dev_scores, wps=0.0):
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def print_progress(itn, losses, dev_scores, cpu_wps=0.0, gpu_wps=0.0):
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print(locals())
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scores = {}
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for col in ['dep_loss', 'tag_loss', 'uas', 'tags_acc', 'token_acc',
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'ents_p', 'ents_r', 'ents_f', 'wps']:
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'ents_p', 'ents_r', 'ents_f', 'cpu_wps', 'gpu_wps']:
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scores[col] = 0.0
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scores['dep_loss'] = losses.get('parser', 0.0)
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scores['ner_loss'] = losses.get('ner', 0.0)
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scores['tag_loss'] = losses.get('tagger', 0.0)
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scores.update(dev_scores)
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scores['wps'] = wps
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scores['cpu_wps'] = cpu_wps
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scores['gpu_wps'] = gpu_wps or 0.0
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tpl = '\t'.join((
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'{:d}',
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'{dep_loss:.3f}',
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@ -173,7 +193,9 @@ def print_progress(itn, losses, dev_scores, wps=0.0):
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'{ents_f:.3f}',
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'{tags_acc:.3f}',
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'{token_acc:.3f}',
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'{wps:.1f}'))
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'{cpu_wps:.1f}',
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'{gpu_wps:.1f}',
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))
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print(tpl.format(itn, **scores))
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