:mod:`fedlab_core.models.shufflenet`
====================================

.. py:module:: fedlab_core.models.shufflenet

.. autoapi-nested-parse::

   ShuffleNet in PyTorch.

   See the paper "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices" for more details.



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

Classes
~~~~~~~

.. autoapisummary::

   fedlab_core.models.shufflenet.ShuffleBlock
   fedlab_core.models.shufflenet.Bottleneck
   fedlab_core.models.shufflenet.ShuffleNet



Functions
~~~~~~~~~

.. autoapisummary::

   fedlab_core.models.shufflenet.ShuffleNetG2
   fedlab_core.models.shufflenet.ShuffleNetG3
   fedlab_core.models.shufflenet.test


.. class:: ShuffleBlock(groups)


   Bases: :class:`torch.nn.Module`

   .. method:: forward(self, x)

      Channel shuffle: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W]



.. class:: Bottleneck(in_planes, out_planes, stride, groups)


   Bases: :class:`torch.nn.Module`

   .. method:: forward(self, x)



.. class:: ShuffleNet(cfg)


   Bases: :class:`torch.nn.Module`

   .. method:: _make_layer(self, out_planes, num_blocks, groups)


   .. method:: forward(self, x)



.. function:: ShuffleNetG2()


.. function:: ShuffleNetG3()


.. function:: test()