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: Gets the optimizer of given name.
  
  Updater holds one or more optimizers with names. They can be retrieved
  by this method.
  
  Args:
      name (str): Name of the optimizer.
  
  Returns:
      ~chainer.Optimizer: Optimizer of the name.
docstr_tok: ["Gets","the","optimizer","of","given","name",".","Updater","holds","one","or","more","optimizers","with","names",".","They","can","be","retrieved","by","this","method",".","Args",":","name","(","str",")",":","Name","of","the","optimizer",".","Returns",":","~chainer.Optimizer",":","Optimizer","of","the","name","."]
code: def get_optimizer(self, name):
      """Gets the optimizer of given name.
  
      Updater holds one or more optimizers with names. They can be retrieved
      by this method.
  
      Args:
          name (str): Name of the optimizer.
  
      Returns:
          ~chainer.Optimizer: Optimizer of the name.
  
      """
      raise NotImplementedError
  
file_path: chainer/chainer/training/_updater.py
label_desc: Use image node_id 3 for calling the Updater obj's underlying member method code with example usage: obj.get_optimizer(name) without return types