def __init__(self):
super(ReNPN, self).__init__()
self.dropout = args.dropout
self.fc1 = NPNLinear(13, 50, False)
self.relu1 = NPNRelu()
self.fc2 = NPNLinear(50, 1)
def __init__(self):
super(NPNCNN, self).__init__()
self.dropout = args.dropout
self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
self.conv2_drop = nn.Dropout2d()
self.fc1 = NPNLinear(320, 50, dual_input=False)
self.relu1 = NPNRelu()
self.drop1 = NPNDropout(self.dropout)
self.fc2 = NPNLinear(50, 10)
self.sigmoid1 = NPNSigmoid()
def __init__(self):
super(NPNNet, self).__init__()
self.dropout = args.dropout
self.fc1 = NPNLinear(784, 800, False)
self.sigmoid1 = NPNSigmoid()
#self.sigmoid1 = NPNRelu()
self.fc2 = NPNLinear(800, 800)
self.sigmoid2 = NPNSigmoid()
#self.sigmoid2 = NPNRelu()
self.fc3 = NPNLinear(800, 10)
self.sigmoid3 = NPNSigmoid()
self.drop1 = NPNDropout(self.dropout)
self.drop2 = NPNDropout(self.dropout)
self.drop3 = NPNDropout(self.dropout)