I think the thing you need is variable:
a = torch.randn(1, requires_grad=True)
b = a*(a+2)
print (b.grad_fn.next_functions)
print (b.grad_fn.next_functions[1][0].next_functions)
print (b.grad_fn.next_functions[0][0].variable)