Possibly, how would I do that?  I tried:
self.register_buffer('currentGrad', torch.zeros(1).to(gf.device).double())
in init() and then in the backward hook I do:
def saveGrad(self, grad_input, grad_output):
    if(len(self.currentGrad) == 1):
        self.currentGrad = self.currentGrad.repeat(grad_output[0].shape)
    self.currentGrad = grad_output[0].detach()

But that gives me an error that implies it did not save the modification:
ValueError: not enough values to unpack (expected 4, got 1)
Uncaught exception. Entering post mortem debugging