The Sigmoid layer should have a single output corresponding to whether and image is real or fake. The Softmax layer should output the probabilities for all the 5 classes the fake image might belong to.
I am getting values ranging from 258.514 to 3.999 as an output for the Sigmoid layer.
Shouldn’t this layer constrain the values between 0 and 1? Am I using the layers in the right manner?
Perhaps your second Conv2d after the Sigmoid is getting kernels outside of 0 and 1 during training. Maybe try moving your Sigmoid after that layer and see what happens.
Thanks for your suggestion.
But I am feeding the output of self.conv1 into the Sigmoid layer and the output of self.conv2 into the Softmax layer. Will the second Conv2d still affect the output of the Sigmoid layer?
Anyways, I made the change and tried but its still not working as expected.