:mod:`fedlab_core.models.pnasnet`
=================================

.. py:module:: fedlab_core.models.pnasnet

.. autoapi-nested-parse::

   PNASNet in PyTorch.

   Paper: Progressive Neural Architecture Search



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

Classes
~~~~~~~

.. autoapisummary::

   fedlab_core.models.pnasnet.SepConv
   fedlab_core.models.pnasnet.CellA
   fedlab_core.models.pnasnet.CellB
   fedlab_core.models.pnasnet.PNASNet



Functions
~~~~~~~~~

.. autoapisummary::

   fedlab_core.models.pnasnet.PNASNetA
   fedlab_core.models.pnasnet.PNASNetB
   fedlab_core.models.pnasnet.test


.. class:: SepConv(in_planes, out_planes, kernel_size, stride)


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

   Separable Convolution.

   .. method:: forward(self, x)



.. class:: CellA(in_planes, out_planes, stride=1)


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

   .. method:: forward(self, x)



.. class:: CellB(in_planes, out_planes, stride=1)


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

   .. method:: forward(self, x)



.. class:: PNASNet(cell_type, num_cells, num_planes)


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

   .. method:: _make_layer(self, planes, num_cells)


   .. method:: _downsample(self, planes)


   .. method:: forward(self, x)



.. function:: PNASNetA()


.. function:: PNASNetB()


.. function:: test()