super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 6, 3, 1, 1)
        self.conv2 = nn.Conv2d(6,12,3,1,1)
        self.pool1 = nn.MaxPool2d(2)
        self.fc1 = nn.Linear(12*32*32, 20)
        
        self.fc2a = nn.Linear(20, 2) # Regression
        self.fc2b = nn.Linear(20, 1) # Classification

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = self.pool1(x)
        x = F.relu(self.conv2(x))
        x = self.pool1(x)
        x = x.view(x.size(0), -1)
        x = F.relu(self.fc1(x))
        
        x1 = self.fc2a(x)
        #x2 = F.log_softmax(self.fc2b(x), dim=1)
        x2 = F.sigmoid(self.fc2b(x))
        return x1, x2

With the Calculation i get always 32x32 so whats wrong in there?