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

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

.. autoapi-nested-parse::

   Dummy Optimizer.

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Classes
-------

.. autoapisummary::

   lmflow.optim.dummy.Dummy


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

.. py:class:: Dummy(params: 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.

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















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

      
      Performs a single optimization step.

      Arguments:
          closure (:obj:`Callable`, `optional`): A closure that reevaluates the model and returns the loss.















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