torch.func.hessian
torch.func.hessian(func, argnums=0)
Computes the Hessian of "func" with respect to the arg(s) at index
   "argnum" via a forward-over-reverse strategy.
The forward-over-reverse strategy (composing
   "jacfwd(jacrev(func))") is a good default for good performance. It
   is possible to compute Hessians through other compositions of
   "jacfwd()" and "jacrev()" like "jacfwd(jacfwd(func))" or
   "jacrev(jacrev(func))".
Parameters:
      * func (function) -- A Python function that takes one or
        more arguments, one of which must be a Tensor, and returns one
        or more Tensors
  * **argnums** (*int** or **Tuple**[**int**]*) -- Optional,
    integer or tuple of integers, saying which arguments to get
    the Hessian with respect to. Default: 0.

Returns:
      Returns a function that takes in the same inputs as "func" and
      returns the Hessian of "func" with respect to the arg(s) at
      "argnums".
Note: