torch.autograd.Function.jvp
static Function.jvp(ctx, *grad_inputs)
Defines a formula for differentiating the operation with forward
   mode automatic differentiation. This function is to be overridden
   by all subclasses. It must accept a context "ctx" as the first
   argument, followed by as many inputs as the "forward()" got (None
   will be passed in for non tensor inputs of the forward function),
   and it should return as many tensors as there were outputs to
   "forward()". Each argument is the gradient w.r.t the given input,
   and each returned value should be the gradient w.r.t. the
   corresponding output. If an output is not a Tensor or the function
   is not differentiable with respect to that output, you can just
   pass None as a gradient for that input.
You can use the "ctx" object to pass any value from the forward to
   this functions.
Return type:
      Any