yeah, your code is ok, but my code error is when run resnet.load_state_dict()

resnet define:
class ResNet(nn.Module):
    def __init__(self,block,layers):
        super(ResNet,self).__init__()
        self.inplanes = 64
        self.conv1 = nn.Conv2d(3,64,kernel_size=7,stride=2,padding=3,bias=False)
        self.bn1 = nn.BatchNorm2d(64)
        self.relu = nn.ReLU(inplace=True)
        self.maxpool = nn.MaxPool2d(kernel_size = 3,stride=2,padding=1)

        self.layer1 = self._make_layer(block,64,layers[0])
        self.layer2 = self._make_layer(block,128,layers[1],stride=2)
        self.layer3 = self._make_layer(block,256,layers[2],stride=2)
        self.layer4 = self._make_layer(block,512,layers[3],stride=2)



    
    def _make_layer(self,block,planes,blocks,stride=1):
        downsample = None
        if stride != 1 or self.inplanes != planes * block.expansion:
            downsample = nn.Sequential(conv1x1(self.inplanes,planes * block.expansion,stride),
                                            nn.BatchNorm2d(planes * block.expansion),
                                        )
        
        layers = []
        layers.append(block(self.inplanes,planes,stride,downsample))
        self.inplanes = planes * block.expansion

        for _ in range(1,blocks):
            layers.append(block(self.inplanes,planes))
        
        return nn.Sequential(*layers)

    def forward(self,x):
        sources = []

        x = self.conv1(x)
        x = self.bn1(x)
        x = self.relu(x)
        x = self.maxpool(x)

        x = self.layer1(x)
        sources += [x]

        x = self.layer2(x)
        sources += [x]

        x = self.layer3(x)
        sources += [x]

        x = self.layer4(x)
        sources += [x]

        return sources
​