:py:mod:`neural_compressor.compression.pruner.patterns.nxm`
===========================================================

.. py:module:: neural_compressor.compression.pruner.patterns.nxm

.. autoapi-nested-parse::

   NxM patterns.



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

Classes
~~~~~~~

.. autoapisummary::

   neural_compressor.compression.pruner.patterns.nxm.PytorchPatternNxM
   neural_compressor.compression.pruner.patterns.nxm.KerasPatternNxM




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




   Pruning Pattern.

   A Pattern class derived from BasePattern. In this pattern, the weights in a NxM block will be pruned or kept
   during one pruning step.

   :param config: A config dict object that contains the pattern information.

   .. attribute:: block_size

      A list of two integers representing the height and width of the block.

   .. attribute:: Please note that the vertical direction of a Linear layer's weight refers to the output channel.

      because PyTorch's tensor matmul has a hidden transpose operation.


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




   Pruning Pattern.

   A Pattern class derived from BasePattern. In this pattern, the weights in a NxM block will be pruned or kept
   during one pruning step.

   :param config: A config dict object that contains the pattern information.

   .. attribute:: block_size

      A list of two integers representing the height and width of the block.

   .. attribute:: Please note that the vertical direction of a Linear layer's weight refers to the output channel.

      because PyTorch's tensor matmul has a hidden transpose operation.