class_docstr: Wrap the target function and operate as ``FunctionNode``
  
  Arguments:
      name (str): name of the function node
      func (func): the target function
      args (list): args for the function
      kwargs (dict): kwargs for the function
      arg_vars (list): list of `chainer.Variable`s in `args` and `kwargs`
      attributes (list): parameters to be set node's attributes
class_docstr_tok: ["Wrap","the","target","function","and","operate","as","``","FunctionNode","``","Arguments",":","name","(","str",")",":","name","of","the","function","node","func","(","func",")",":","the","target","function","args","(","list",")",":","args","for","the","function","kwargs","(","dict",")",":","kwargs","for","the","function","arg_vars","(","list",")",":","list","of","`","chainer.Variable","`","s","in","`","args","`","and","`","kwargs","`","attributes","(","list",")",":","parameters","to","be","set","node","'s","attributes"]
code: def __init__(
      self, name, func, args, kwargs, arg_vars, attributes=None
  ):
      self.custom_function_node_name = name
      self.func = func
      self.args = args
      self.kwargs = kwargs
      self.arg_vars = arg_vars
      self.internal_results = None
  
      if attributes is not None:
          for k, v in attributes.items():
              setattr(self, k, v)
  
file_path: chainer/onnx_chainer/replace_func.py
imports: import inspect
  import chainer
label_desc: Use image node_id 1 to create a new WrappedFunctionNode object from inherited base classes: chainer with example: obj = WrappedFunctionNode(name, func, args, kwargs, arg_vars, attributes)