Tensor of zeros as the hessian for said inputs, which is the
        expected mathematical value. Defaults to "False".
  * **vectorize** (*bool**, **optional*) -- This feature is
    experimental. Please consider using "torch.func.hessian()"
    instead if you are looking for something less experimental and
    more performant. When computing the hessian, usually we invoke
    "autograd.grad" once per row of the hessian. If this flag is
    "True", we use the vmap prototype feature as the backend to
    vectorize calls to "autograd.grad" so we only invoke it once
    instead of once per row. This should lead to performance
    improvements in many use cases, however, due to this feature
    being incomplete, there may be performance cliffs. Please use
    *torch._C._debug_only_display_vmap_fallback_warnings(True)* to
    show any performance warnings and file us issues if warnings
    exist for your use case. Defaults to "False".
