lmflow.optim.yogi
=================

.. py:module:: lmflow.optim.yogi


Classes
-------

.. autoapisummary::

   lmflow.optim.yogi.Yogi


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

.. py:class:: Yogi(params, lr: float = 0.01, betas=(0.9, 0.999), eps: float = 0.001, initial_accumulator: float = 1e-06, weight_decay: float = 0)

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


   
   Implements Yogi Optimizer Algorithm.
   It has been proposed in `Adaptive methods for Nonconvex Optimization`.

   https://papers.nips.cc/paper/8186-adaptive-methods-for-nonconvex-optimization  # noqa

   Note:
       Reference code: https://github.com/4rtemi5/Yogi-Optimizer_Keras















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

      
      Performs a single optimization step.

      Arguments:
          closure: A closure that reevaluates the model and returns the loss.















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