63871d5ab3301d015805abddd8f4259680d6a24a,translate.py,,main,#,68
Before Change
if opt.verbose:
words = []
for f in src_sent:
word = translator.fields["src"].vocab.itos[f]
if word == onmt.IO.PAD_WORD:
break
words.append(word)
os.write(1, bytes("\nSENT %d: %s\n" %
(count, " ".join(words)), "UTF-8"))
index += 1
After Change
(sent.squeeze(1) for sent in src.split(1, dim=1)))
for pred_sents, gold_sent, pred_score, gold_score, src_sent in z_batch:
n_best_preds = [" ".join(pred) for pred in pred_sents[:opt.n_best]]
count += 1
out_file.write("\n".join(n_best_preds))
out_file.write("\n")
out_file.flush()
if opt.verbose:
words = get_src_words(
src_sent, translator.fields["src"].vocab.itos)
os.write(1, bytes("\nSENT %d: %s\n" %
(count, words), "UTF-8"))
index += 1
best_pred = n_best_preds[0]
best_score = pred_score[0]
os.write(1, bytes("PRED %d: %s\n" %
(count, best_pred), "UTF-8"))
print("PRED SCORE: %.4f" % best_score)
if opt.tgt:
tgt_sent = " ".join(gold_sent)
os.write(1, bytes("GOLD %d: %s\n" %
(count, tgt_sent), "UTF-8"))
print("GOLD SCORE: %.4f" % gold_score)
if opt.n_best > 1:
print("\nBEST HYP:")
for score, sent in zip(pred_score, n_best_preds):
os.write(1, bytes("[%.4f] %s\n" % (score, sent),
"UTF-8"))
report_score("PRED", pred_score_total, pred_words_total)
if opt.tgt:
report_score("GOLD", gold_score_total, gold_words_total)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 7
Instances
Project Name: OpenNMT/OpenNMT-py
Commit Name: 63871d5ab3301d015805abddd8f4259680d6a24a
Time: 2017-09-21
Author: bpeters@coli.uni-saarland.de
File Name: translate.py
Class Name:
Method Name: main
Project Name: ClimbsRocks/auto_ml
Commit Name: a23afcd39cc364f17e1adefc1a4309e99c4a3d7d
Time: 2017-05-19
Author: ClimbsBytes@gmail.com
File Name: auto_ml/utils_model_training.py
Class Name: FinalModelATC
Method Name: predict_uncertainty
Project Name: OpenNMT/OpenNMT-py
Commit Name: 13bbee615c87c812ddcfff73746cd504222e3fb0
Time: 2017-08-30
Author: nasa4836@gmail.com
File Name: onmt/Models.py
Class Name:
Method Name: make_base_model