Ops thanks for the solution!
Edited: Now during backprop of the output using that model I get
Expected tensor for 'result' to have the same dimension as tensor for argument #1 'grad_output'; but 4 does not equal 1 (while checking arguments for cudnn_convolution_backward_input)
eg :
output = netd(input)
output.backward( one )
You can probably tell I am using WGAN’s netd with no GP applied.
Edited: I solved this by calling output = output.mean() to get its mean then backprop from there, I don’t know if this is the best way but I am getting generations.