lmflow.optim.lamb
=================

.. py:module:: lmflow.optim.lamb


Classes
-------

.. autoapisummary::

   lmflow.optim.lamb.Lamb


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

.. py:class:: Lamb(params, lr: float = 0.001, betas=(0.9, 0.999), eps: float = 1e-06, weight_decay: float = 0, clamp_value: float = 10, adam: bool = False, debias: bool = False)

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


   
   Implements Lamb algorithm.

   It has been proposed in `Large Batch Optimization for Deep Learning:
   Training BERT in 76 minutes`
   https://arxiv.org/abs/1904.00962

   Note:
       Reference code: https://github.com/cybertronai/pytorch-lamb















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   .. py:attribute:: clamp_value


   .. py:attribute:: adam


   .. py:attribute:: debias


   .. 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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