or ""reverse-mode"" to determine whether the Jacobian will be
        computed with forward or reverse mode AD. Currently,
        ""forward-mode"" requires "vectorized=True". Defaults to
        ""reverse-mode"". If "func" has more outputs than inputs,
        ""forward-mode"" tends to be more performant. Otherwise,
        prefer to use ""reverse-mode"".
Returns:
      if there is a single input and output, this will be a single
      Tensor containing the Jacobian for the linearized inputs and
      output. If one of the two is a tuple, then the Jacobian will be
      a tuple of Tensors. If both of them are tuples, then the
      Jacobian will be a tuple of tuple of Tensors where
      "Jacobian[i][j]" will contain the Jacobian of the "i"th output
      and "j"th input and will have as size the concatenation of the
      sizes of the corresponding output and the corresponding input
      and will have same dtype and device as the corresponding input.