:mod:`fedlab_core.models.resnext`
=================================

.. py:module:: fedlab_core.models.resnext

.. autoapi-nested-parse::

   ResNeXt in PyTorch.

   See the paper "Aggregated Residual Transformations for Deep Neural Networks" for more details.



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

Classes
~~~~~~~

.. autoapisummary::

   fedlab_core.models.resnext.Block
   fedlab_core.models.resnext.ResNeXt



Functions
~~~~~~~~~

.. autoapisummary::

   fedlab_core.models.resnext.ResNeXt29_2x64d
   fedlab_core.models.resnext.ResNeXt29_4x64d
   fedlab_core.models.resnext.ResNeXt29_8x64d
   fedlab_core.models.resnext.ResNeXt29_32x4d
   fedlab_core.models.resnext.test_resnext


.. class:: Block(in_planes, cardinality=32, bottleneck_width=4, stride=1)


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

   Grouped convolution block.

   .. attribute:: expansion
      :annotation: = 2

      

   .. method:: forward(self, x)



.. class:: ResNeXt(num_blocks, cardinality, bottleneck_width, num_classes=10)


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

   .. method:: _make_layer(self, num_blocks, stride)


   .. method:: forward(self, x)



.. function:: ResNeXt29_2x64d()


.. function:: ResNeXt29_4x64d()


.. function:: ResNeXt29_8x64d()


.. function:: ResNeXt29_32x4d()


.. function:: test_resnext()