can anyone help i develop cnn and this error pop up and i have no idea what went wrog or how to fix it can annyone help
class gface1(nn.Module):
    def __init__(self, bottleneck_setting=MobiFace_bottleneck_setting, final=False):
        super(gface1, self).__init__()
        self.final = final

        self.conv1 = ConvBlock(3, 64, 3, 2, 1)

        self.dw_conv1 = ConvBlock(64, 64, 3, 1, 1, dw=True)

      
        self.conv4= ConvBlock6(64,128,3, 1, 1)

        self.conv5= ConvBlock6(128,256,3, 1, 1)

        self.conv6= ConvBlock6(256,512,3, 1, 1)

        #self.conv7 = ConvBlock(512, 512, 1, 1, 0, linear=True)

        #self.linear1 = nn.Linear(512*7*7, 512)

        #self.linear7 = ConvBlock4(512, 512, (7, 6), 1, 0, dw=True, linear=True)

        #self.linear1 = ConvBlock4(512, 128, 1, 1, 0, linear=True)

        #self.prelu1 = nn.PReLU()



    def forward(self, x):
        x = self.conv1(x)
        x = self.dw_conv1(x)
        #x= self.conv3(x)
        x=self.conv4(x)
        x= self.conv5(x)
        x=self.conv6(x)
        #x=self.conv7(x)
        #x = x.view(x.size(0), -1)
        #x = self.linear1(x)
        #if self.final is False:
         # x = self.prelu1(x)
        #x = self.linear7(x)
        #x = self.linear1(x)
        #x = x.view(x.size(0), -1)
        return x
        
        



class ConvBlock6(nn.Module):
    def __init__(self, inp, oup, k, s, p, dw=False, linear=False):
        super(ConvBlock6, self).__init__()
        self.linear = linear
        self.conv = nn.Conv2d(inp, oup, k, s, p, groups=inp, bias=False)
        self.batch1 = nn.BatchNorm2d(oup)
        self.PRelu1=nn.PReLU(oup)
        self.max1= nn.MaxPool2d((2, 2), 2)


        self.dw_conv2=nn.Conv2d(oup, oup, k, s, p,groups=inp * 2, bias=False)
        self.batch2=nn.BatchNorm2d(oup)
        self.PRelu2=nn.PReLU(oup)
        self.max2=  nn.MaxPool2d((2, 2), 2)
        

        self.conv3= nn.Conv2d(oup, oup, 1, 1, 0, bias=False)
        self.batch3=nn.BatchNorm2d(oup)


        

        #self.maxP = x

    def forward(self, x):
        x = self.conv(x)
        x = self.batch1(x)
        x=self.PRelu1(x)
        x= self.max1(x)
        x=self.dw_conv2(x)
        x=self.batch2(x)
        x=self.PRelu2(x)
        x=self.max2(x)
        x=self.conv3(x)
        x=self.batch3(x)
        return self.conv3(x)