class GaborNN(nn.Module):
def init(self):
super(GaborNN, self).init()
#Gabor Convolution 1
self.g0 = GaborConv2d(in_channels=1, out_channels=128, kernel_size=11,stride=1,padding=2)
self.relu1=nn.ReLU()
print(self.g0.weight.shape)
    #Max Pool 1
    self.maxpool1=nn.MaxPool2d(2)
  
    #Convolution 2
    self.c1 = nn.Conv2d(in_channels=128, out_channels=384, kernel_size=11,stride=1,padding=2)
    self.relu2=nn.ReLU()
    print(self.c1.weight.shape)
    #Max Pool 2
    self.maxpool1=nn.MaxPool2d(2)
    #print(self.maxpool1.shape)
    self.fc1 = nn.Linear(384*8*8, 100)
    print(self.fc1.weight.shape)
    self.fc2 = nn.Linear(100, 1)
    #print(self.fc1.weight.shape)
    #self.fc2 = nn.Linear(64, 2)
    #print(self.fc2.weight.shape)

def forward(self, x):
    ##Convolution 1
    out=self.g0(x)
    out=self.relu1(out)
    #Max Pool 1
    out=self.maxpool1(out)
    #Convolution 2
    out=self.c1(x)
    out=self.relu2(out)
    #Max Pool 2
    out=self.maxpool2(out)
    #print(out.size)
    out=out.view(out.size(0),-1)
    out=self.fc1(out)
    out=self.fc2(out)
    print(out)
    return out

during training i got stucked with this error
RuntimeError: Given groups=1, weight of size [128, 128, 11, 11], expected input[128, 1, 32, 32] to have 128 channels, but got 1 channels instead… If such an error occurs where should i modify my code .