train2_paired.py 文件源码

def loss_gen(self, gen, G_p_rough, D_p_rough, p_line, batchsize, alpha=0.1):
        xp = self.gen.xp
        loss_L = F.mean_squared_error(G_p_rough, p_line) * G_p_rough.data.shape[0]
        loss_adv = F.softmax_cross_entropy(D_p_rough, Variable(xp.zeros(batchsize, dtype=np.int32)))
        #loss_line = self.line_loss(G_p_rough, p_line)
        loss = loss_L + alpha * loss_adv #+ loss_line
        chainer.report({'loss': loss, "loss_L": loss_L, 'loss_adv': loss_adv}, gen)
        return loss