BiLSTM_Model.py 文件源码

def train_epoch(self, X, y, show_bar=True):
        optimizer = optim.Adam(self.parameters())
        if show_bar:
            bar = Progbar(len(X))
        for ix, (elem, tags) in enumerate(zip(X, y)):
            self.zero_grad()
            sentence, feature_vector, sentence_markers = self.get_sentence_feature_vector(elem)
            if self.GPU:
                targets = torch.LongTensor(tags).cuda()
            else:
                targets = torch.LongTensor(tags)
            neg_log_likelihood = self.neg_log_likelihood(sentence, feature_vector, targets)
            neg_log_likelihood.backward()
            optimizer.step()
            if show_bar:
                bar.update(ix + 1)
        if show_bar:
            print ''
        sys.stdout.flush()