class_docstr: Interface of updater objects for trainers.
  
  :class:`~chainer.training.Updater` implements a training iteration
  as :meth:`update`. Typically, the updating iteration proceeds as follows.
  
  - Fetch a minibatch from :mod:`~chainer.dataset`
    via :class:`~chainer.dataset.Iterator`.
  - Run forward and backward process of :class:`~chainer.Chain`.
  - Update parameters according to their :class:`~chainer.UpdateRule`.
  
  The first line is processed by
  :meth:`Iterator.__next__ <chainer.dataset.Iterator.__next__>`.
  The second and third are processed by
  :meth:`Optimizer.update <chainer.Optimizer.update>`.
  Users can also implement their original updating iteration by overriding
  :meth:`Updater.update <chainer.training.Updater.update>`.
docstr: Updates the parameters of the target model.
  
  This method implements an update formula for the training task,
  including data loading, forward/backward computations, and actual
  updates of parameters.
  
  This method is called once at each iteration of the training loop.
docstr_tok: ["Updates","the","parameters","of","the","target","model",".","This","method","implements","an","update","formula","for","the","training","task",",","including","data","loading",",","forward\/backward","computations",",","and","actual","updates","of","parameters",".","This","method","is","called","once","at","each","iteration","of","the","training","loop","."]
code: def update(self):
      """Updates the parameters of the target model.
  
      This method implements an update formula for the training task,
      including data loading, forward/backward computations, and actual
      updates of parameters.
  
      This method is called once at each iteration of the training loop.
  
      """
      raise NotImplementedError
  
file_path: chainer/chainer/training/_updater.py
label_desc: Use image node_id 5 for calling the Updater obj's underlying member method code with example usage: obj.update() without return types