torch.autograd.functional.jacobian
torch.autograd.functional.jacobian(func, inputs, create_graph=False, strict=False, vectorize=False, strategy='reverse-mode')
Function that computes the Jacobian of a given function.
Parameters:
      * func (function) -- a Python function that takes Tensor
        inputs and returns a tuple of Tensors or a Tensor.
  * **inputs** (*tuple of Tensors** or **Tensor*) -- inputs to the
    function "func".

  * **create_graph** (*bool**, **optional*) -- If "True", the
    Jacobian will be computed in a differentiable manner. Note
    that when "strict" is "False", the result can not require
    gradients or be disconnected from the inputs.  Defaults to
    "False".

  * **strict** (*bool**, **optional*) -- If "True", an error will
    be raised when we detect that there exists an input such that
    all the outputs are independent of it. If "False", we return a
