network.py 文件源码

def weights_normal_init(model, dev=0.01):
    if isinstance(model, list):
        for m in model:
            weights_normal_init(m, dev)
    else:
        for m in model.modules():
            if isinstance(m, nn.Conv2d):                
                #print torch.sum(m.weight)
                m.weight.data.normal_(0.0, dev)
                if m.bias is not None:
                    m.bias.data.fill_(0.0)
            elif isinstance(m, nn.Linear):
                m.weight.data.normal_(0.0, dev)