Hi - I was experimenting with ConvTranspose2d operation. I took a [2 x 2] random tensor and applied transpose conv on it with and without padding. Both the kernel size and stride are set to 2. When I checked the size of the tensor after the operation I found that the size of the output tensor without padding is bigger than with padding.
Code snippet with padding:
d=torch.randn(1,1,2,2)
deconv2=nn.ConvTranspose2d(1,1,kernel_size=2,stride=2,padding=1)
d1=deconv2(d)
d1.shape ==>> it returns torch.Size([1, 1, 2, 2])
Code snippet without padding:
deconv2=nn.ConvTranspose2d(1,1,kernel_size=2,stride=2,padding=0)
d1=deconv2(d)
d1.shape ==>> it returns torch.Size([1, 1, 4, 4])
I thought that the output tensor size with padding will be bigger than without padding.But it’s not the   case. Can anyone please explain this?
Regards,
Tomojit