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)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 8

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: microsoft/nni
Commit Name: 81fcff86aa30fb188a66aea2bd682dc1ad08ec16
Time: 2019-11-12
Author: 656569648@qq.com
File Name: src/sdk/pynni/nni/compression/torch/compressor.py
Class Name: Compressor
Method Name: compress


Project Name: microsoft/nni
Commit Name: 262fabf111006c99e7415093c78e9c26d3ebe0f0
Time: 2019-11-14
Author: 38930155+chicm-ms@users.noreply.github.com
File Name: src/sdk/pynni/nni/compression/tensorflow/compressor.py
Class Name: Compressor
Method Name: compress