7b34113cc3b5529a127bd02667de9de0b5b75df9,models/networks_basic.py,PNet,forward,#PNet#Any#Any#Any#,40

Before Change

            if(kk==0):
                val = 1.*cur_score
            else:
                val = val + cur_score
            if(retPerLayer):
                all_scores+=[cur_score]

        if(retPerLayer):
            return (val, all_scores)
        else:
            return val

// Learned perceptual metric
class PNetLin(nn.Module):
    def __init__(self, pnet_type="vgg", pnet_rand=False, pnet_tune=False, use_dropout=True, spatial=False, version="0.1"):

After Change

        elif(self.colorspace=="Lab"):
            value = util.dssim(util.tensor2np(util.tensor2tensorlab(in0.data,to_norm=False)), 
                util.tensor2np(util.tensor2tensorlab(in1.data,to_norm=False)), range=100.).astype("float")
        ret_var = Variable( torch.Tensor((value,) ) )
        if(self.use_gpu):
            ret_var = ret_var.cuda()
        return ret_var

def print_network(net):
    num_params = 0
    for param in net.parameters():

Instances