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| | """Common functions for ST and MT.""" |
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| | import nltk |
| | import numpy as np |
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|
| | class ErrorCalculator(object): |
| | """Calculate BLEU for ST and MT models during training. |
| | |
| | :param y_hats: numpy array with predicted text |
| | :param y_pads: numpy array with true (target) text |
| | :param char_list: vocabulary list |
| | :param sym_space: space symbol |
| | :param sym_pad: pad symbol |
| | :param report_bleu: report BLUE score if True |
| | """ |
| |
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| | def __init__(self, char_list, sym_space, sym_pad, report_bleu=False): |
| | """Construct an ErrorCalculator object.""" |
| | super(ErrorCalculator, self).__init__() |
| | self.char_list = char_list |
| | self.space = sym_space |
| | self.pad = sym_pad |
| | self.report_bleu = report_bleu |
| | if self.space in self.char_list: |
| | self.idx_space = self.char_list.index(self.space) |
| | else: |
| | self.idx_space = None |
| |
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| | def __call__(self, ys_hat, ys_pad): |
| | """Calculate corpus-level BLEU score. |
| | |
| | :param torch.Tensor ys_hat: prediction (batch, seqlen) |
| | :param torch.Tensor ys_pad: reference (batch, seqlen) |
| | :return: corpus-level BLEU score in a mini-batch |
| | :rtype float |
| | """ |
| | bleu = None |
| | if not self.report_bleu: |
| | return bleu |
| |
|
| | bleu = self.calculate_corpus_bleu(ys_hat, ys_pad) |
| | return bleu |
| |
|
| | def calculate_corpus_bleu(self, ys_hat, ys_pad): |
| | """Calculate corpus-level BLEU score in a mini-batch. |
| | |
| | :param torch.Tensor seqs_hat: prediction (batch, seqlen) |
| | :param torch.Tensor seqs_true: reference (batch, seqlen) |
| | :return: corpus-level BLEU score |
| | :rtype float |
| | """ |
| | seqs_hat, seqs_true = [], [] |
| | for i, y_hat in enumerate(ys_hat): |
| | y_true = ys_pad[i] |
| | eos_true = np.where(y_true == -1)[0] |
| | ymax = eos_true[0] if len(eos_true) > 0 else len(y_true) |
| | |
| | |
| | seq_hat = [self.char_list[int(idx)] for idx in y_hat[:ymax]] |
| | seq_true = [self.char_list[int(idx)] for idx in y_true if int(idx) != -1] |
| | seq_hat_text = "".join(seq_hat).replace(self.space, " ") |
| | seq_hat_text = seq_hat_text.replace(self.pad, "") |
| | seq_true_text = "".join(seq_true).replace(self.space, " ") |
| | seqs_hat.append(seq_hat_text) |
| | seqs_true.append(seq_true_text) |
| | bleu = nltk.bleu_score.corpus_bleu([[ref] for ref in seqs_true], seqs_hat) |
| | return bleu * 100 |
| |
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