fc8951bbd36b14099e41fe171ab57e9f3937fe4f,congan_train.py,,train,#,191

Before Change

            gen_cost, gen_aux_output = aD(fake_data)

            //aux_label = Variable(torch.LongTensor(BATCH_SIZE), requires_grad=True).data.resize_(BATCH_SIZE).copy_(torch.from_numpy(f_label))
            aux_label = autograd.Variable(torch.from_numpy(f_label).long().cuda())
            aux_errG = aux_criterion(gen_aux_output, aux_label).mean()
            gen_cost = -gen_cost.mean()
            g_cost = ACGAN_SCALE_G*aux_errG + gen_cost

After Change

            fake_data = aG(noise)
            gen_cost, gen_aux_output = aD(fake_data)

            aux_label = torch.from_numpy(f_label).long()
            if cuda_available:
                aux_label = aux_label.cuda()
            aux_errG = aux_criterion(gen_aux_output, aux_label).mean()
            gen_cost = -gen_cost.mean()
            g_cost = ACGAN_SCALE_G*aux_errG + gen_cost

Instances