code: def _get_one_out_fn(grad_fn, xs, fn_ret):
      out_nested_indices = iter(ivy.all_nested_indices(fn_ret))
  
      def one_out_fn(o):
          out_idx = next(out_nested_indices)
          out_shape = ivy.index_nest(grad_fn(xs), out_idx).shape
          one_arg_fn = _get_jac_one_arg_fn(grad_fn, xs, out_idx)
          jacobian = ivy.nested_map(
              lambda x: jacobian_to_ivy(
                  paddle.incubate.autograd.Jacobian(
                      one_arg_fn, ivy.to_native(x.expand_dims())
                  ),
                  x.shape,
                  out_shape,
              ),
              xs,
              shallow=False,
          )
          return jacobian
  
      return one_out_fn
  
file_path: ivy/ivy/functional/backends/paddle/gradients.py
imports: from typing import Optional, Callable
  import paddle
  import ivy.functional.backends.paddle
  from itertools import chain
  import ivy
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from .None import backend_version
  from ivy.functional.ivy.gradients import _get_required_float_variables, _get_y_and_ret_idxs, _get_native_y, _set_duplicates, _process_func_ret_and_grads
label_desc: Use image node_id 9 for calling a global function with example usage: _get_one_out_fn(grad_fn, xs, fn_ret) and returns: one_out_fn, jacobian