def __init__(self):
super(Dis_Tan, self).__init__()
self.complex_conv1 = layers.ComplexConv(1,
20, (5, 5), (2, 2),
num_tied_block=1)
self.complex_conv2 = layers.ComplexConv(20,
20, (5, 5), (2, 2),
num_tied_block=1)
self.distance1 = layers.DifferenceLayer(20, (2, 2), num_tied_block=1)
self.distance2 = layers.DifferenceLayer(20, (2, 2), num_tied_block=1)
self.tangentReLU = layers.tangentRELU()
self.relu = nn.ReLU()
self.linear_1 = layers.DistanceTransform(20, (2, 2), num_tied_block=1)
self.conv_1 = nn.Conv2d(20, 25, (4, 4), (1, 1))
self.mp_1 = nn.MaxPool2d((2, 2))
self.conv_2 = nn.Conv2d(25, 30, (5, 5), (3, 3))
self.bn_1 = nn.BatchNorm2d(25)
self.bn_2 = nn.BatchNorm2d(30)
self.mp_2 = nn.MaxPool2d((3, 3))
self.conv_3 = nn.Conv2d(30, 35, (2, 2), (1, 1))
self.bn_3 = nn.BatchNorm2d(35)
self.linear_2 = nn.Linear(35, 20)
self.linear_4 = nn.Linear(20, 10)
def __init__(self):
super(MoreLayers, self).__init__()
self.complex_conv1 = layers.ComplexConv(1, 20, (5, 5), (2, 2), num_tied_block=1)
self.complex_conv2 = layers.ComplexConv(20, 20, (5, 5), (2, 2), num_tied_block=1)
self.complex_conv3 = layers.ComplexConv(20, 20, (4, 4), (1, 1), num_tied_block=1)
self.proj2 = layers.manifoldReLUv2angle(20)
self.relu = nn.ReLU()
self.linear_1 = layers.DistanceTransform(20, (2, 2), num_tied_block=1)
self.mp_1 = nn.MaxPool2d((2, 2))
self.conv_2 = nn.Conv2d(20, 30, (5, 5), (3, 3))
self.bn_2 = nn.BatchNorm2d(30)
self.mp_2 = nn.MaxPool2d((3, 3))
self.conv_3 = nn.Conv2d(30, 40, (2, 2), (1, 1))
self.bn_3 = nn.BatchNorm2d(40)
self.linear_2 = nn.Linear(40, 20)
self.linear_4 = nn.Linear(20, 10)
def __init__(self):
super(PreviousDisTan, self).__init__()
self.complex_conv1 = layers.ComplexConv(1, 20, (5, 5), (2, 2), num_tied_block=1)
self.complex_conv2 = layers.ComplexConv(20, 20, (5, 5), (2, 2), num_tied_block=1)
self.distance1 = layers.DifferenceLayerUpsample(20, (2, 2), num_tied_block=1)
self.distance2 = layers.DifferenceLayerUpsample(20, (2, 2), num_tied_block=1)
self.tangentReLU = layers.tangentRELU()
self.proj2 = layers.manifoldReLUv2angle(20)
self.relu = nn.ReLU()
self.linear_1 = layers.DistanceTransformUpsample(20, (22, 22), num_tied_block=1)
self.conv_1 = nn.Conv2d(20, 30, (5, 5), (1, 1))
self.mp_1 = nn.MaxPool2d((2, 2))
self.conv_2 = nn.Conv2d(30, 40, (5, 5), (3, 3))
self.bn_1 = nn.BatchNorm2d(30)
self.bn_2 = nn.BatchNorm2d(40)
self.mp_2 = nn.MaxPool2d((3, 3))
self.conv_3 = nn.Conv2d(40, 50, (2, 2), (1, 1))
self.bn_3 = nn.BatchNorm2d(50)
self.linear_2 = nn.Linear(50, 30)
self.linear_4 = nn.Linear(30, 10)
def __init__(self):
super(ManifoldNetComplex, self).__init__()
self.complex_conv1 = layers.ComplexConv(1,
20, (5, 1), (2, 1),
num_tied_block=1)
self.proj1 = layers.manifoldReLUv2angle(20)
self.proj2 = layers.manifoldReLUv2angle(20)
self.complex_conv2 = layers.ComplexConv(20,
20, (5, 1), (2, 1),
num_tied_block=1)
self.relu = nn.ReLU()
self.dropout = nn.Dropout(0.5)
self.linear_1 = layers.DistanceTransform(20, (2, 1), num_tied_block=1)
self.conv_1 = nn.Conv2d(20, 40, (6, 1))
self.mp_1 = nn.MaxPool2d((2, 1))
self.conv_2 = nn.Conv2d(40, 60, (4, 1))
self.mp_2 = nn.MaxPool2d((2, 1))
self.conv_3 = nn.Conv2d(60, 80, (4, 1))
self.bn_1 = nn.BatchNorm2d(40)
self.bn_2 = nn.BatchNorm2d(60)
self.bn_3 = nn.BatchNorm2d(80)
self.linear_2 = nn.Linear(80, 40)
self.linear_3 = nn.Linear(40, 11)
self.name = "Complex"
def __init__(self):
super(LessLayersDis, self).__init__()
self.complex_conv1 = layers.ComplexConv(1, 20, (5, 5), (2, 2), num_tied_block=1)
self.complex_conv2 = nn.Conv2d(20, 30, (5, 5), (2, 2))
self.complex_conv3 = nn.Conv2d(30, 40, (4, 4), (1, 1))
self.relu = nn.ReLU()
self.linear_1 = layers.DistanceTransform(20, (2, 2), num_tied_block=1)
self.distance1 = layers.DifferenceLayerUpsample(20, (2, 2), num_tied_block=1)
self.tangentReLU = layers.tangentRELU()
self.mp_1 = nn.MaxPool2d((2, 2))
self.conv_2 = nn.Conv2d(40, 50, (5, 5), (3, 3))
self.bn_2 = nn.BatchNorm2d(50)
self.mp_2 = nn.MaxPool2d((3, 3))
self.conv_3 = nn.Conv2d(50, 60, (2, 2), (1, 1))
self.bn_3 = nn.BatchNorm2d(60)
self.linear_2 = nn.Linear(60, 40)
self.linear_4 = nn.Linear(40, 10)
