:py:mod:`neural_compressor.compression.pruner.pruners.basic`
============================================================

.. py:module:: neural_compressor.compression.pruner.pruners.basic

.. autoapi-nested-parse::

   Basic pruner.



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

Classes
~~~~~~~

.. autoapisummary::

   neural_compressor.compression.pruner.pruners.basic.PytorchBasicPruner
   neural_compressor.compression.pruner.pruners.basic.KerasBasicPruner




.. py:class:: PytorchBasicPruner(config, modules)




   Pruning Pruner.

   The class which executes pruning process.
   1. Defines pruning functions called at step begin/end, epoch begin/end.
   2. Defines the pruning criterion.

   :param modules: A dict {"module_name": Tensor} that stores the pruning modules' weights.
   :param config: A config dict object that contains the pruner information.

   .. attribute:: pattern

      A Pattern object that defines pruning weights' arrangements within space.

   .. attribute:: criterion

      A Criterion Object that defines which weights are to be pruned

   .. attribute:: scheduler

      A Scheduler object that defines how the model's sparsity changes as training/pruning proceeds.

   .. attribute:: reg

      A Reg object that defines regulization terms.


.. py:class:: KerasBasicPruner




   Pruning Pruner.

   The class which executes pruning process.
   1. Defines pruning functions called at step begin/end, epoch begin/end.
   2. Defines the pruning criterion.

   :param modules: A dict {"module_name": Tensor} that stores the pruning modules' weights.
   :param config: A config dict object that contains the pruner information.

   .. attribute:: pattern

      A Pattern object that defines pruning weights' arrangements within space.

   .. attribute:: criterion

      A Criterion Object that defines which weights are to be pruned

   .. attribute:: scheduler

      A Scheduler object that defines how the model's sparsity changes as training/pruning proceeds.

   .. attribute:: reg

      A Reg object that defines regulization terms.