仅添加其他参数后，nn.init.normal_结果更改

Question

我创建一个模型并使用nn.init.normal_初始化参数，但是，我添加另一个参数后的权重变化（没有其他操作，包括iNATION）。 该代码在这里，不注重另一种情况。

def __init__(self):
        self.tc_h = torch.nn.Sequential(
            torch.nn.Linear(512, 1024),
            torch.nn.ReLU(),
            torch.nn.Linear(1024, 512)
        )
        self.tg_h = torch.nn.Sequential(
            torch.nn.Linear(512, 1024),
            torch.nn.ReLU(),
            torch.nn.Linear(1024, 512)
        )
        self.vc_h = torch.nn.Sequential(
            torch.nn.Linear(512, 1024),
            torch.nn.ReLU(),
            torch.nn.Linear(1024, 512)
        )
        self.vg_h = torch.nn.Sequential(
            torch.nn.Linear(512, 1024),
            torch.nn.ReLU(),
            torch.nn.Linear(1024, 512)
        )

        #self.tc_Q = torch.nn.Linear(512, 512)
        #self.vc_Q = torch.nn.Linear(512, 512)
        #self.tg_Q = torch.nn.Linear(512, 512)
        #self.vg_Q = torch.nn.Linear(512, 512)

        for layer in [
            self.tc_h, self.tg_h, self.vc_h, self.vg_h,
            #self.tc_Q, self.tg_Q, self.vc_Q, self.vg_Q,
        ]: 
            for name, param in layer.named_parameters():
                if name.endswith('weight'):
                    nn.init.normal_(param, std=1024 ** -0.5)