seq2seq_mp1.py 文件源码

def evaluate(self):
        bt = time.time()
        with chainer.no_backprop_mode():
            references = []
            hypotheses = []
            observation = {}
            with reporter.report_scope(observation):
                for i in range(0, len(self.test_data), self.batch):
                    src, trg = zip(*self.test_data[i:i + self.batch])
                    references.extend([[t.tolist()] for t in trg])

                    src = [chainer.dataset.to_device(self.device, x)
                           for x in src]

                    if self.comm.rank == 0:
                        self.model.translate(src, self.max_length)

                    elif self.comm.rank == 1:
                        ys = [y.tolist()
                              for y in self.model.translate(
                                  src, self.max_length)]
                        hypotheses.extend(ys)

                if self.comm.rank == 1:
                    bleu = bleu_score.corpus_bleu(
                        references, hypotheses, smoothing_function=bleu_score.
                        SmoothingFunction().method1)
                    reporter.report({'bleu': bleu}, self.model)
        et = time.time()

        if self.comm.rank == 1:
            print("BleuEvaluator(single)::evaluate(): "
                  "took {:.3f} [s]".format(et - bt))
            sys.stdout.flush()
        return observation