def __init__(self, h, numClasses):
super(CNNFeats, self).__init__()
self.conv1 = utils.Conv2d(h, h, 3)
self.conv2 = utils.Conv2d(h, h, 3)
self.conv3 = utils.Conv2d(h, int(h/2), 3, padding='valid')
self.fc1 = nn.Linear(int(h/2) * 5 * 5, 1024)
self.pool = nn.MaxPool2d(2)
self.fc2 = nn.Linear(1024, numClasses)
def __init__(self, h, numClasses):
super(EngineClassifier, self).__init__()
self.conv1 = utils.Conv2d(h, 4 * h, 1)
self.fc1 = nn.Linear(4 * h * 7 * 7, 1024)
self.pool = nn.MaxPool2d(2)
self.fc2 = nn.Linear(1024, numClasses)
def __init__(self, h):
super(BinaryModule, self).__init__()
self.conv1 = utils.Conv2d(2 * h, h, 1)
self.conv2 = utils.Conv2d(h, h, 3)
self.conv3 = utils.Conv2d(h, h, 3)
def __init__(self, h):
super(CNN, self).__init__()
self.conv1 = utils.Conv2d(1024, h, 3)
self.conv2 = utils.Conv2d(h, h, 3)
def __init__(self):
super(CNN, self).__init__()
self.conv1 = utils.Conv2d(1024, 128, 3)
self.conv2 = utils.Conv2d(128, 128, 3)
def __init__(self):
super(BinaryModule, self).__init__()
self.conv1 = utils.Conv2d(256, 128, 1)
self.conv2 = utils.Conv2d(128, 128, 3)
self.conv3 = utils.Conv2d(128, 128, 3)
def __init__(self, h, k):
super(ConvReluNorm, self).__init__()
self.conv = utils.Conv2d(h, h, k)
self.norm = nn.InstanceNorm2d(h)
def __init__(self, h):
super(UnaryModule, self).__init__()
self.conv1 = utils.Conv2d(h, h, 3)
self.conv2 = utils.Conv2d(h, h, 3)
self.norm2 = nn.InstanceNorm2d(h)
def __init__(self, h):
super(ForkModule, self).__init__()
self.conv1 = utils.Conv2d(2*h, 6*h, 1)
self.conv2 = utils.Conv2d(6*h, 6*h, 3)
self.conv3 = utils.Conv2d(6*h, 6*h, 3)
self.conv4 = utils.Conv2d(6*h, h, 1)
def __init__(self, h):
super(BinForkLarge, self).__init__()
self.conv1 = utils.Conv2d(2*h, 4*h, 1)
self.conv2 = utils.Conv2d(4*h, 4*h, 3)
self.conv3 = utils.Conv2d(4*h, 4*h, 3)
self.conv4 = utils.Conv2d(4*h, h, 1)