af79a5c7760057a7dec1b68b97639cc69f40c3ea,train.py,,evaluate,#,26

Before Change

    for b, batch in enumerate(val_iter):
        src, len_src = batch.src
        trg, len_trg = batch.trg
        src, trg = src.cuda(), trg.cuda()
        output = model(src, trg)
        loss = F.cross_entropy(output.view(-1, vocab_size),
                               trg.contiguous().view(-1), ignore_index=pad)

After Change

        src, len_src = batch.src
        trg, len_trg = batch.trg
        src = Variable(src.data.cuda(), volatile=True)
        trg = Variable(trg.data.cuda(), volatile=True)
        output = model(src, trg)
        loss = F.cross_entropy(output.view(-1, vocab_size),
                               trg.contiguous().view(-1), ignore_index=pad)
        total_loss += loss.data[0]

Instances