fedlab_core.models.pnasnet

PNASNet in PyTorch.

Paper: Progressive Neural Architecture Search

Module Contents

Classes

SepConv	Separable Convolution.
CellA
CellB
PNASNet

Functions

PNASNetA()
PNASNetB()
test()

class fedlab_core.models.pnasnet.SepConv(in_planes, out_planes, kernel_size, stride)

Bases: torch.nn.Module

Separable Convolution.

forward(self, x)

class fedlab_core.models.pnasnet.CellA(in_planes, out_planes, stride=1)

Bases: torch.nn.Module

forward(self, x)

class fedlab_core.models.pnasnet.CellB(in_planes, out_planes, stride=1)

Bases: torch.nn.Module

forward(self, x)

class fedlab_core.models.pnasnet.PNASNet(cell_type, num_cells, num_planes)

Bases: torch.nn.Module

_make_layer(self, planes, num_cells)

_downsample(self, planes)

forward(self, x)

fedlab_core.models.pnasnet.PNASNetA()

fedlab_core.models.pnasnet.PNASNetB()

fedlab_core.models.pnasnet.test()