I am a little confused about the padding setting of the torch.nn.ConvTranspose2d.
As I see the document, it seems that the padding of the deconvolution is calculated by some settings of convolution.  padding(deconv) = K(conv) - 1 - padding(conv)
An Example:
If I want to upsample x3 using the deconvolution,  the setting of the convolution is  kernel = 3,  stride = 2,  padding = 0; According to the previous equation, the padding of the deconvolution should be 2;
And by using the this  equation Hout=(Hin−1)∗stride[0]−2∗padding[0]+kernel_size[0]+output_padding[0]
, we can get the setting  of deconvolution, kernel = 7,  stride = 3,  padding = 2;
I don’t know if my understanding is right.  Actually, I don’t know if the first equation is required.  If not, the setting of  kernel = 5,  stride = 3,  padding = 1; also meets the second equation.
Any help would be much appreciated.
It would be better if you could provide some related material.