I think i forgot telling that  I just want to check if weight would vary during training.In the case below I am able to print out the weight.How can I  do it ,Thanks!
class MODEL(nn.Module):
    def __init__(self):
        super().__init__()
        self.conv1 = Conv2d(3,32,kernel_size = 3,padding = 1)
        self.bn1 = BatchNorm2d(32)
        self.pooling1 = MaxPool2d(2,2)
        self.conv2 = Conv2d(32,64,kernel_size = 3,padding = 1)
        self.bn2 = BatchNorm2d(64)
        self.pooling2 = MaxPool2d(2,2)
        self.extra_conv1 = Conv2d(32,32,kernel_size=3,padding=1)
        for module in self.modules():
            if isinstance(module,nn.Conv2d):
                init.ones_(module.weight)
        
    def feature_extractor(self,x):
        out = self.extra_conv1(x)
        return out
    
    def forward(self,x):
        x = self.conv1(x)
        x = self.bn1(x)
        x = F.relu(x)
        x = self.feature_extractor(x)
        x = self.pooling1(x)
        x = self.conv2(x)
        x = self.bn2(x)
        x = F.relu(x)
        x = self.pooling2(x)
        return x
        
class MODEL2(nn.Module):
    def __init__(self,base):
        super().__init__()
        self.base = base
        self.conv1 = Conv2d(64,32,kernel_size = 3,padding = 1)
        self.bn1 = BatchNorm2d(32)
        self.pooling1 = MaxPool2d(2,2)
        self.conv2 = Conv2d(32,16,kernel_size = 3,padding = 1)
        self.bn2 = BatchNorm2d(16)
        self.pooling2 = MaxPool2d(2,2)

    def forward(self,x):
        x = self.base(x)
        x= self.conv1(x)
        x = self.bn1(x)
        x = F.relu(x)
        return x

if __name__=="__main__":
    base = MODEL()
    model = MODEL2(base)

    for name,param in model.named_parameters():
        print(name)
    print(model.base.extra_conv1.weight）