def __init__(self):
super(SNN, self).__init__()
self.input = nn.Input()
self.fc1 = nn.Linear(in_features=784, out_features=500)
self.active1 = nn.LIF()
self.fc2 = nn.Linear(in_features=500, out_features=150)
self.active2 = nn.LIF()
self.fc3 = nn.Linear(in_features=150, out_features=50)
self.active3 = nn.LIF()
self.fc4 = nn.Linear(in_features=50, out_features=10)
self.output = nn.Output(out_features=10)
def __init__(self):
super(SNN, self).__init__()
self.conv1 = nn.Conv2d(in_channels=1, out_channels=10, kernel_size=5)
self.active1 = nn.LIF()
self.conv2 = nn.Conv2d(in_channels=10, out_channels=20, kernel_size=5)
self.active2 = nn.LIF()
self.pool1 = nn.Pooling(size=2, channel=10)
self.active3 = nn.LIF()
self.pool2 = nn.Pooling(size=2, channel=20)
self.active4 = nn.LIF()
self.fc1 = nn.Linear(out_features=100, in_features=320)
self.active5 = nn.LIF()
self.fc2 = nn.Linear(out_features=50, in_features=100)
self.active6 = nn.LIF()
self.fc3 = nn.Linear(out_features=30, in_features=50)
self.active7 = nn.LIF()
self.fc4 = nn.Linear(out_features=10, in_features=30)
self.output = nn.Output(out_features=10)
