It’s dearly missed, but can be hacked together… I’m not sure on the most efficient way though, I’ve seen several “solutions” to this.
For example, I use this method straight from the backend:
arguments: input, weight, bias, kH, kW, strideH, strideW, padH, padW, inH, inW, outH, outW
conv2Dlocal = torch.nn.backends.thnn.backend.SpatialConvolutionLocal.apply
I find it strange there is still no supported solution for this (should easily be in the functional sub-lib at least).