lmflow.optim.dummy
==================

.. py:module:: lmflow.optim.dummy

.. autoapi-nested-parse::

   Dummy Optimizer.



Classes
-------

.. autoapisummary::

   lmflow.optim.dummy.Dummy


Module Contents
---------------

.. py:class:: Dummy(params: collections.abc.Iterable[torch.nn.parameter.Parameter], lr: float = 0.0, betas: tuple[float, float] = (0.9, 0.999), weight_decay: float = 0.0)

   Bases: :py:obj:`torch.optim.Optimizer`


   An dummy optimizer that does nothing.

   :param params: Iterable of parameters to optimize or dictionaries defining parameter groups.
   :type params: :obj:`Iterable[nn.parameter.Parameter]`
   :param lr: The learning rate to use.
   :type lr: :obj:`float`, `optional`, defaults to 0


   .. py:method:: step(closure: Callable = None)

      Performs a single optimization step.

      :param closure: A closure that reevaluates the model and returns the loss.
      :type closure: :obj:`Callable`, `optional`