def __init__(self, inplanes, planes, stride=1, downsample=None):
super(BasicBlock, self).__init__()
self.conv1 = conv3x3(inplanes, planes, stride)
self.bn1 = layer.BatchNorm2d(planes)
self.conv2 = conv3x3(planes, planes)
self.bn2 = layer.BatchNorm2d(planes)
self.relu1 = layer.ReLU()
self.add = layer.Add()
self.relu2 = layer.ReLU()
self.downsample = downsample
self.stride = stride
def __init__(self, inplanes, planes, stride=1, downsample=None):
super(Bottleneck, self).__init__()
self.conv1 = layer.Conv2d(inplanes, planes, 1, bias=False)
self.bn1 = layer.BatchNorm2d(planes)
self.relu1 = layer.ReLU()
self.conv2 = layer.Conv2d(planes,
planes,
3,
stride=stride,
padding=1,
bias=False)
self.bn2 = layer.BatchNorm2d(planes)
self.relu2 = layer.ReLU()
self.conv3 = layer.Conv2d(planes,
planes * self.expansion,
1,
bias=False)
self.bn3 = layer.BatchNorm2d(planes * self.expansion)
self.add = layer.Add()
self.relu3 = layer.ReLU()
self.downsample = downsample
self.stride = stride
def __init__(self,
in_filters,
out_filters,
reps,
strides=1,
padding=0,
start_with_relu=True,
grow_first=True):
super(Block, self).__init__()
if out_filters != in_filters or strides != 1:
self.skip = layer.Conv2d(in_filters,
out_filters,
1,
stride=strides,
padding=padding,
bias=False)
self.skipbn = layer.BatchNorm2d(out_filters)
else:
self.skip = None
self.layers = []
filters = in_filters
if grow_first:
self.layers.append(layer.ReLU())
self.layers.append(
layer.SeparableConv2d(in_filters,
out_filters,
3,
stride=1,
padding=1,
bias=False))
self.layers.append(layer.BatchNorm2d(out_filters))
filters = out_filters
for i in range(reps - 1):
self.layers.append(layer.ReLU())
self.layers.append(
layer.SeparableConv2d(filters,
filters,
3,
stride=1,
padding=1,
bias=False))
self.layers.append(layer.BatchNorm2d(filters))
if not grow_first:
self.layers.append(layer.ReLU())
self.layers.append(
layer.SeparableConv2d(in_filters,
out_filters,
3,
stride=1,
padding=1,
bias=False))
self.layers.append(layer.BatchNorm2d(out_filters))
if not start_with_relu:
self.layers = self.layers[1:]
else:
self.layers[0] = layer.ReLU()
if strides != 1:
self.layers.append(layer.MaxPool2d(3, strides, padding + 1))
self.register_layers(*self.layers)
self.add = layer.Add()