y1.set_()
del y1
output = torch.cat([x1, x2], dim=1)
x1.set_()x2.set_()del x1, x2
// save the (empty) input and (non-empty) output variables
cty.save_for_backward(y.data, output)
After Change
with torch.no_grad():
// partition in two equally sized set of channels
y = yin.detach()
y1, y2 = torch.chunk(y, 2, dim=1)
y1, y2 = y1.contiguous(), y2.contiguous()
// compute outputs