autograd_subtensor.lua

grad = require 'autograd'
torch = require 'torch'

params={
  W=torch.range(0, 8):view(3, 3),
  storage=torch.zeros(3, 3)
}

function f(params, x)
  params.storage[2] = params.W * x
  return torch.mean(params.storage)
end

grad, _ = grad(f)(params, torch.ones(3))
print(grad.W)
print(grad.storage)

--[[
This gives a zero gradient to W, which is incorrect.

 0  0  0
 0  0  0
 0  0  0
[torch.DoubleTensor of size 3x3]

 0.1111  0.1111  0.1111
 0.0000  0.0000  0.0000
 0.1111  0.1111  0.1111
[torch.DoubleTensor of size 3x3]

--]]