code: def get_object(obj, predefined_objects=None, default_object=None, kwargs=None):
      
      args = ()
      kwargs = dict() if kwargs is None else kwargs
  
      if isinstance(obj, str) and os.path.isfile(obj):
          with open(obj, 'r') as fp:
              obj = json.load(fp=fp)
      if isinstance(obj, dict):
          kwargs.update(obj)
          obj = kwargs.pop('type', None)
  
      if predefined_objects is not None and obj in predefined_objects:
          obj = predefined_objects[obj]
      elif isinstance(obj, str):
          if obj.find('.') != -1:
              module_name, function_name = obj.rsplit('.', 1)
              module = importlib.import_module(module_name)
              obj = getattr(module, function_name)
          else:
              raise TensorForceError("Error: object {} not found in predefined objects: {}".format(
                  obj,
                  list(predefined_objects or ())
              ))
      elif callable(obj):
          pass
      elif default_object is not None:
          args = (obj,)
          obj = default_object
      else:
          # assumes the object is already instantiated
          return obj
  
      return obj(*args, **kwargs)
docs: Utility method to map some kind of object specification to its content,
      e.g. optimizer or baseline specifications to the respective classes.
  
      Args:
          obj: A specification dict (value for key 'type' optionally specifies
                  the object, options as follows), a module path (e.g.,
                  my_module.MyClass), a key in predefined_objects, or a callable
                  (e.g., the class type object).
          predefined_objects: Dict containing predefined set of objects,
                  accessible via their key
          default_object: Default object is no other is specified
          kwargs: Arguments for object creation
  
      Returns: The retrieved object