99.999% sure it’s 64, as I set batch_size=64 in my DataLoader. The GAN I’m trying to implement has a discriminator with 1024 output filters/channels , so I’m pretty sure self.final_conv = nn.Conv2d(num_disc_filters * 16, 1, 4, 1, 0, bias=False) , but yet that works out to 64x1 in the real_out .
I guess the problem is that my linear layers (supposed to be built on top of the convolutional ones) are wrongly configured? Anything you can see that could be the problem?
Also, what do you think is the simplest way forward?
Many thanks once again!