:py:mod:`neural_compressor.compression.pruner.tf_criteria`
==========================================================

.. py:module:: neural_compressor.compression.pruner.tf_criteria

.. autoapi-nested-parse::

   Tensorflow pruning criterion.



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

Classes
~~~~~~~

.. autoapisummary::

   neural_compressor.compression.pruner.tf_criteria.PruningCriterion
   neural_compressor.compression.pruner.tf_criteria.MagnitudeCriterion



Functions
~~~~~~~~~

.. autoapisummary::

   neural_compressor.compression.pruner.tf_criteria.register_criterion
   neural_compressor.compression.pruner.tf_criteria.get_tf_criterion



.. py:function:: register_criterion(name)

   Register a criterion to the registry.


.. py:function:: get_tf_criterion(config, modules)

   Get registered criterion class.


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


   Pruning base criterion.

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

   .. attribute:: scores

      A dict {"module_name": Tensor} that stores the scores of pruning modules.


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




   Pruning criterion.

   The magnitude criterion_class is derived from PruningCriterion.
   The magnitude value is used to score and determine if a weight is to be pruned.

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

   .. attribute:: scores

      A dict {"module_name": Tensor} that stores the scores of pruning modules.