code: def previous_backend():
      """Unset the current global backend, and adjusts the ivy dict such that
      either a previously set global backend is then used as the backend,
      otherwise we return to Ivy's implementations.
  
      Returns
      -------
      ret
          the backend that was unset, or None if there was no set global backend.
  
      Examples
      --------
      Torch is the last set backend hence is the backend used in the first examples.
      However, as seen in the example after, if `previous_backend` is called before
      `ivy.native_array` then tensorflow will become the current backend and any
      torch backend implementations in the Ivy dict will be swapped with the
      tensorflow implementation::
  
      >>> ivy.set_backend("tensorflow")
      >>> ivy.set_backend("torch")
      >>> x = ivy.native_array([1])
      >>> print(type(x))
      <class 'torch.Tensor'>
  
      >>> ivy.set_backend("tensorflow")
      >>> ivy.set_backend("torch")
      >>> ivy.previous_backend()
      >>> x = ivy.native_array([1])
      >>> print(type(x))
      <class'tensorflow.python.framework.ops.EagerTensor'>
      """  # noqa
      backend = None
      # if the backend stack is empty, nothing is done then we just return `None`
      if backend_stack:
          backend = backend_stack.pop(
              -1
          )  # remove last backend from the stack
          if backend.current_backend_str() == "numpy":
              ivy.unset_default_device()
          elif backend.current_backend_str() == "jax":
              ivy.del_global_attr("RNG")
          # the new backend is the backend that was set before the one
          # we just removed from the stack, or Ivy if there was no
          # previously set backend
          if backend_stack:
              new_backend = backend_stack[-1]
              if new_backend.current_backend_str() == "numpy":
                  ivy.set_default_device("cpu")
              elif new_backend.current_backend_str() == "jax":
                  ivy.set_global_attr(
                      "RNG", ivy.functional.backends.jax.random.RNG
                  )
          new_backend_dict = (
              backend_stack[-1].__dict__
              if backend_stack
              else ivy_original_dict
          )
          # wrap backend functions if there still is a backend, and add functions
          # to ivy namespace
          for k, v in new_backend_dict.items():
              if k in ivy.GLOBAL_PROPS:
                  continue
              if backend_stack and k in ivy_original_dict:
                  v = _wrap_function(k, v, ivy_original_dict[k])
              if k in ivy_original_dict:
                  ivy.__dict__[k] = v
              if k in ivy.functional.__dict__ and not k.startswith(
                  "__"
              ):
                  ivy.functional.__dict__[k] = v
      if verbosity.level > 0:
          verbosity.cprint(f"backend stack: {backend_stack}")
      _handle_inplace_mode()
      return backend
  
imports: import os
  import copy
  import types
  import ivy
  import importlib
  import functools
  import numpy
  import gc
  from ivy.utils import _importlib, verbosity
  from ivy.func_wrapper import _wrap_function
  from ivy.utils.backend.sub_backend_handler import _clear_current_sub_backends, fn_name_from_version_specific_fn_name
  from ivy.utils.exceptions import _handle_inplace_mode
label_desc: Use image node_id 17 for calling a global function with example usage: previous_backend() and returns: backend