def backward(ctx, graddist, gradidx):
xyz1, xyz2, assignment = ctx.saved_tensors
graddist = graddist.contiguous()
gradxyz1 = torch.zeros(xyz1.size(), device='cuda').contiguous()
gradxyz2 = torch.zeros(xyz2.size(), device='cuda').contiguous()
emd.backward(xyz1, xyz2, gradxyz1, graddist, assignment)
return gradxyz1, gradxyz2, None, None
def backward(ctx, gradcost):
xyz1, xyz2, match = ctx.saved_tensors
gradxyz1 = torch.zeros(xyz1.size()).cuda()
gradxyz2 = torch.zeros(xyz2.size()).cuda()
emd.backward(xyz1, xyz2, gradxyz1, gradxyz2, match)
return gradxyz1, gradxyz2
