It seems that the discriminator cannot adapt to the size of the input image.

[SwordHolderSH]

Once I set '-- input_scale_size' not to 64, an error will be reported. It seems that the discriminator cannot adapt to the size of the input image. How did you solve the problem?
"ValueError: Target and input must have the same number of elements. target nelement (2) != input nelement (338)"

[SwordHolderSH]

I check the shapes of output tensors.
When input size is 64 *64:
torch.Size([2, 64, 32, 32])
torch.Size([2, 64, 32, 32])
torch.Size([2, 128, 16, 16])
torch.Size([2, 128, 16, 16])
torch.Size([2, 128, 16, 16])
torch.Size([2, 256, 8, 8])
torch.Size([2, 256, 8, 8])
torch.Size([2, 256, 8, 8])
torch.Size([2, 512, 4, 4])
torch.Size([2, 512, 4, 4])
torch.Size([2, 512, 4, 4])
torch.Size([2, 1, 1, 1])
torch.Size([2, 1, 1, 1])

When it is 256*256:
torch.Size([2, 64, 128, 128])
torch.Size([2, 64, 128, 128])
torch.Size([2, 128, 64, 64])
torch.Size([2, 128, 64, 64])
torch.Size([2, 128, 64, 64])
torch.Size([2, 256, 32, 32])
torch.Size([2, 256, 32, 32])
torch.Size([2, 256, 32, 32])
torch.Size([2, 512, 16, 16])
torch.Size([2, 512, 16, 16])
torch.Size([2, 512, 16, 16])
torch.Size([2, 1, 13, 13])
torch.Size([2, 1, 13, 13])

So I add two max-pooling layers, to make it roughly work...