class PreActBlock(nn.Module):
'''Pre-activation version of the BasicBlock.'''
expansion = 1
def __init__(self, in_planes, planes, stride=1):
super(PreActBlock, self).__init__()
self.actib1 = Hermite()
self.actib1_wts = self.actib1.get_vars(num_pol=NUM_POL)
self.actib2 = Hermite()
self.actib2_wts = self.actib2.get_vars(num_pol=NUM_POL)
self.bn1 = nn.BatchNorm2d(in_planes)
self.conv1 = conv3x3(in_planes, planes, stride)
self.bn2 = nn.BatchNorm2d(planes)
self.conv2 = conv3x3(planes, planes)
if stride != 1 or in_planes != self.expansion * planes:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes,
self.expansion * planes,
kernel_size=1,
stride=stride,
bias=False))
def forward(self, x):
out = F.softsign(
self.actib1.hermite(self.bn1(x), self.actib1_wts, num_pol=NUM_POL))
shortcut = self.shortcut(out) if hasattr(self, 'shortcut') else x
out = self.conv1(out)
# V2L Architecture: Pull Softsign out here
out = F.softsign(
self.conv2(
self.actib2.hermite(self.bn2(out),
self.actib2_wts,
num_pol=NUM_POL)))
out += shortcut
return out
class ResNet(nn.Module):
def __init__(self, block, num_blocks, num_classes=10):
super(ResNet, self).__init__()
self.in_planes = 64
self.actir = Hermite()
self.actir_wts = self.actir.get_vars(num_pol=NUM_POL)
self.conv1 = conv3x3(1, 64) # change to 3 if 3 channel
self.bn1 = nn.BatchNorm2d(64)
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
self.linear = nn.Linear(512 * block.expansion, num_classes)
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1] * (num_blocks - 1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def forward(self, x, out_middle=False, from_middle=False):
if not from_middle:
out = F.softsign(
self.actir.hermite(self.bn1(self.conv1(x)),
self.actir_wts,
num_pol=NUM_POL))
first_layer = self.layer1(out)
out = self.layer2(first_layer)
out = self.layer3(out)
out = self.layer4(out)
out = F.avg_pool2d(out, 4)
feat = out.view(out.size(0), -1)
else:
feat = x
out = self.linear(feat)
if out_middle:
return out, feat
else:
return out