code: def patch_attrs(target_obj: object, source_obj: object) -> object:
      """
      Patch attributes of `source_obj` to `target_obj`.
  
      :param target_obj: target object
      :param source_obj: source object
      :return: `target_obj`
      """
      if source_obj is None:
          return target_obj
      if inspect.ismethod(target_obj.__setattr__):
          # `target_obj` has custom `__setattr__`
          wrapper_obj = _ModuleWrapper(target_obj, source_obj)
          return wrapper_obj
      else:
          # `target_obj` has no custom `__setattr__`
          for name in set(dir(source_obj)) - set(dir(target_obj)):
              attr = getattr(source_obj, name)
              if inspect.isfunction(attr):  # static method
                  setattr(target_obj, name, attr)
              elif inspect.ismethod(attr):  # method
                  static_method = getattr(type(source_obj), name)
                  setattr(
                      target_obj,
                      name,
                      _NanoPartial(static_method, target_obj),
                  )
              elif isinstance(
                  attr, _NanoPartial
              ):  # replaced method by Nano
                  static_method = attr.func
                  setattr(
                      target_obj,
                      name,
                      _NanoPartial(static_method, target_obj),
                  )
              else:
                  setattr(target_obj, name, attr)
          return target_obj
  
file_path: BigDL/python/nano/src/bigdl/nano/utils/tf/attributes.py
imports: import inspect
  from functools import partial
  from tensorflow.keras import Model
  from bigdl.nano.utils.common import invalidOperationError
label_desc: Use image node_id 1 for calling a global function with example usage: patch_attrs(target_obj, source_obj) and returns: target_obj, wrapper_obj, target_obj