code: def outputs_to_frontend_arrays(fn: Callable) -> Callable:
      @functools.wraps(fn)
      def new_fn(*args, **kwargs):
          """Convert `ivy.Array` into `Tensor` instances.
  
          Call the function, and then convert all `ivy.Array` instances returned by the
          function into `Tensor` instances.
          """
          # call unmodified function
          # ToDo: Remove this default dtype setting
          #  once frontend specific backend setting is added
          # ivy.set_default_int_dtype("int64")
          # ivy.set_default_float_dtype(paddle_frontend.get_default_dtype())
          try:
              ret = fn(*args, **kwargs)
          finally:
              ivy.unset_default_int_dtype()
              ivy.unset_default_float_dtype()
          # convert all arrays in the return to `paddle_frontend.Tensor` instances
          return _from_ivy_array_to_paddle_frontend_tensor(
              ret, nested=True, include_derived={"tuple": True}
          )
  
      return new_fn
  
file_path: ivy/ivy/functional/frontends/paddle/func_wrapper.py
imports: from typing import Callable
  import functools
  import ivy
  import ivy.functional.frontends.paddle
label_desc: Use image node_id 4 for calling a global function with example usage: outputs_to_frontend_arrays(fn) and returns: new_fn, _from_ivy_array_to_paddle_frontend_tensor