def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 128, 1)
self.conv256_0 = nn.Conv2d(128, 128, 3, padding=1)
self.conv256_1 = nn.Conv2d(128, 128, 3, padding=1)
self.conv256_2 = nn.Conv2d(128, 128, 3, padding=1)
self.conv256_3 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_0 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_1 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_2 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_3 = nn.Conv2d(128, 128, 3, padding=1)
self.conv_down_256_32 = nn.Conv2d(128, 128, 8, 8)
self.conv_down_128_32 = nn.Conv2d(128, 128, 4, 4)
self.conv_down_64_32 = nn.Conv2d(128, 128, 2, 2)
self.gdn_down_256_32 = pytorch_gdn.GDN(128)
self.gdn_down_128_32 = pytorch_gdn.GDN(128)
self.gdn_down_64_32 = pytorch_gdn.GDN(128)
self.conv_down_256_128 = nn.Conv2d(128, 128, 2, 2)
self.conv_down_128_64 = nn.Conv2d(128, 128, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(128)
self.gdn_down_128_64 = pytorch_gdn.GDN(128)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(128, 1, 1)
self.tconv256_0 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv256_1 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv256_2 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv256_3 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_0 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_1 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_2 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_3 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv_up_32_256 = nn.ConvTranspose2d(128, 128, 8, 8)
self.tconv_up_32_128 = nn.ConvTranspose2d(128, 128, 4, 4)
self.tconv_up_32_64 = nn.ConvTranspose2d(128, 128, 2, 2)
self.igdn_up_32_256 = pytorch_gdn.GDN(128, True)
self.igdn_up_32_128 = pytorch_gdn.GDN(128, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(128, True)
self.tconv_up_64_128 = nn.ConvTranspose2d(128, 128, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(128, 128, 2, 2)
self.igdn_up_64_128 = pytorch_gdn.GDN(128, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(128, True)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(64, 1, 1)
self.tconv_up_16_256 = nn.ConvTranspose2d(64, 64, 16, 16)
self.tconv_up_16_128 = nn.ConvTranspose2d(64, 64, 8, 8)
self.tconv_up_16_64 = nn.ConvTranspose2d(64, 64, 4, 4)
self.tconv_up_16_32 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_up_16_256 = pytorch_gdn.GDN(64, True)
self.igdn_up_16_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_16_64 = pytorch_gdn.GDN(64, True)
self.igdn_up_16_32 = pytorch_gdn.GDN(64, True)
self.tconv_up_32_64 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv_up_64_128 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_up_32_64 = pytorch_gdn.GDN(64, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(64, True)
self.tconv_up_32_256 = nn.ConvTranspose2d(64, 64, 8, 8)
self.tconv_up_32_128 = nn.ConvTranspose2d(64, 64, 4, 4)
self.tconv_up_64_256 = nn.ConvTranspose2d(64, 64, 4, 4)
self.igdn_up_32_256 = pytorch_gdn.GDN(64, True)
self.igdn_up_32_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_64_256 = pytorch_gdn.GDN(64, True)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 128, 1)
self.conv1_0 = nn.Conv2d(128, 128, 3, padding=1)
self.conv1_1 = nn.Conv2d(128, 128, 3, padding=1)
self.conv1_2 = nn.Conv2d(128, 128, 3, padding=1)
self.conv1_3 = nn.Conv2d(128, 128, 3, padding=1)
self.conv2_0 = nn.Conv2d(128, 128, 3, padding=1)
self.conv2_1 = nn.Conv2d(128, 128, 3, padding=1)
self.conv2_2 = nn.Conv2d(128, 128, 3, padding=1)
self.conv2_3 = nn.Conv2d(128, 128, 3, padding=1)
self.conv_g1 = nn.Conv2d(128, 128, 8, 8)
self.conv_g2 = nn.Conv2d(128, 128, 4, 4)
self.conv_g3 = nn.Conv2d(128, 128, 2, 2)
self.gdn_g1 = pytorch_gdn.GDN(128)
self.gdn_g2 = pytorch_gdn.GDN(128)
self.gdn_g3 = pytorch_gdn.GDN(128)
self.conv_f1 = nn.Conv2d(128, 128, 2, 2)
self.conv_f2 = nn.Conv2d(128, 128, 2, 2)
self.gdn_f1 = pytorch_gdn.GDN(128)
self.gdn_f2 = pytorch_gdn.GDN(128)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(128, 1, 1)
self.tconv1_0 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv1_1 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv1_2 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv1_3 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv2_0 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv2_1 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv2_2 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv2_3 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv_g1 = nn.ConvTranspose2d(128, 128, 8, 8)
self.tconv_g2 = nn.ConvTranspose2d(128, 128, 4, 4)
self.tconv_g3 = nn.ConvTranspose2d(128, 128, 2, 2)
self.igdn_g1 = pytorch_gdn.GDN(128, True)
self.igdn_g2 = pytorch_gdn.GDN(128, True)
self.igdn_g3 = pytorch_gdn.GDN(128, True)
self.tconv_f1 = nn.ConvTranspose2d(128, 128, 2, 2)
self.tconv_f2 = nn.ConvTranspose2d(128, 128, 2, 2)
self.igdn_f1 = pytorch_gdn.GDN(128, True)
self.igdn_f2 = pytorch_gdn.GDN(128, True)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 128, 1)
self.conv_down_256_8 = nn.Conv2d(128, 128, 32, 32)
self.conv_down_128_8 = nn.Conv2d(128, 128, 16, 16)
self.conv_down_64_8 = nn.Conv2d(128, 128, 8, 8)
self.conv_down_32_8 = nn.Conv2d(128, 128, 4, 4)
self.conv_down_16_8 = nn.Conv2d(128, 128, 2, 2)
self.gdn_down_256_8 = pytorch_gdn.GDN(128)
self.gdn_down_128_8 = pytorch_gdn.GDN(128)
self.gdn_down_64_8 = pytorch_gdn.GDN(128)
self.gdn_down_32_8 = pytorch_gdn.GDN(128)
self.gdn_down_16_8 = pytorch_gdn.GDN(128)
self.conv_down_256_128 = nn.Conv2d(128, 128, 2, 2)
self.conv_down_128_64 = nn.Conv2d(128, 128, 2, 2)
self.conv_down_64_32 = nn.Conv2d(128, 128, 2, 2)
self.conv_down_32_16 = nn.Conv2d(128, 128, 2, 2)
self.conv_down_16_8 = nn.Conv2d(128, 128, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(128)
self.gdn_down_128_64 = pytorch_gdn.GDN(128)
self.gdn_down_64_32 = pytorch_gdn.GDN(128)
self.gdn_down_32_16 = pytorch_gdn.GDN(128)
self.gdn_down_16_8 = pytorch_gdn.GDN(128)
def __init__(self,
downSample,
in_channels,
out_channels,
device,
kernel_size=2,
stride=2,
padding=0,
groups=1,
step=2):
super(SampleNet, self).__init__()
self.downSample = downSample
self.step = step
middle_channels = (in_channels + out_channels) // 2
if (self.downSample == True):
if (self.step == 2):
self.convDownX = nn.Conv2d(in_channels,
middle_channels, (kernel_size, 1),
(stride, 1),
groups=groups)
self.convDownY = nn.Conv2d(middle_channels,
out_channels, (1, kernel_size),
(1, stride),
groups=groups)
elif (self.step == 1):
self.convDown = nn.Conv2d(in_channels,
out_channels,
kernel_size,
stride,
groups=groups)
self.gdn = pytorch_gdn.GDN(out_channels,
device=device,
inverse=False)
elif (self.downSample == False):
self.igdn = pytorch_gdn.GDN(in_channels,
device=device,
inverse=True)
if (self.step == 2):
self.tconvUpY = nn.ConvTranspose2d(in_channels,
middle_channels,
(1, kernel_size),
(1, stride),
groups=groups)
self.tconvUpX = nn.ConvTranspose2d(middle_channels,
out_channels,
(kernel_size, 1),
(stride, 1),
groups=groups)
elif (self.step == 1):
self.tconvUp = nn.ConvTranspose2d(in_channels,
out_channels,
kernel_size,
stride,
groups=groups)
def __init__(self):
super(DecodeNet2, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(128, 1, 1)
self.tconv_up_64_128 = nn.ConvTranspose2d(128, 128, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(128, 128, 2, 2)
self.igdn_up_64_128 = pytorch_gdn.GDN(128, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(128, True)
def __init__(self):
super(EncodeNet2, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 128, 1)
self.conv_down_256_128 = nn.Conv2d(128, 128, 2, 2)
self.conv_down_128_64 = nn.Conv2d(128, 128, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(128)
self.gdn_down_128_64 = pytorch_gdn.GDN(128)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 64, 1)
self.conv_down_256_16 = nn.Conv2d(64, 64, 16, 16)
self.conv_down_128_16 = nn.Conv2d(64, 64, 8, 8)
self.conv_down_64_16 = nn.Conv2d(64, 64, 4, 4)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_16 = pytorch_gdn.GDN(64)
self.gdn_down_128_16 = pytorch_gdn.GDN(64)
self.gdn_down_64_16 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
self.conv_down_256_128 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_128_64 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_64_32 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(64)
self.gdn_down_128_64 = pytorch_gdn.GDN(64)
self.gdn_down_64_32 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
self.conv_down_16_8 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_16_8 = pytorch_gdn.GDN(64)
self.tconv_up_8_16 = nn.ConvTranspose2d(64, 64, 2, 2)
def __init__(self):
super(DecodeNet1, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(32, 1, 1)
self.tconv_up_16_32 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_32_64 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_64_128 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(32, 32, 2, 2)
self.igdn_up_16_32 = pytorch_gdn.GDN(32, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(32, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(32, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(32, True)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 64, 1)
self.conv_down_256_16 = nn.Conv2d(64, 64, 16, 16)
self.conv_down_128_16 = nn.Conv2d(64, 64, 8, 8)
self.conv_down_64_16 = nn.Conv2d(64, 64, 4, 4)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_16 = pytorch_gdn.GDN(64)
self.gdn_down_128_16 = pytorch_gdn.GDN(64)
self.gdn_down_64_16 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
self.conv_down_256_128 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_128_64 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_64_32 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(64)
self.gdn_down_128_64 = pytorch_gdn.GDN(64)
self.gdn_down_64_32 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
self.k1_1 = nn.Parameter(torch.FloatTensor([1]))
self.k1_2 = nn.Parameter(torch.FloatTensor([1]))
self.k1_3 = nn.Parameter(torch.FloatTensor([1]))
self.k2_1 = nn.Parameter(torch.FloatTensor([1]))
self.k2_2 = nn.Parameter(torch.FloatTensor([1]))
self.k2_3 = nn.Parameter(torch.FloatTensor([1]))
self.k3_1 = nn.Parameter(torch.FloatTensor([1]))
self.k3_2 = nn.Parameter(torch.FloatTensor([1]))
self.k3_3 = nn.Parameter(torch.FloatTensor([1]))
self.k4_1 = nn.Parameter(torch.FloatTensor([1]))
self.k4_3 = nn.Parameter(torch.FloatTensor([1]))
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 32, 3, padding=1)
self.conv1 = nn.Conv2d(32, 32, 3, padding=1)
self.conv2 = nn.Conv2d(32, 32, 3, padding=1)
self.conv3 = nn.Conv2d(32, 32, 3, padding=1)
self.conv4 = nn.Conv2d(32, 32, 3, padding=1)
self.conv5 = nn.Conv2d(32, 32, 3, padding=1)
self.conv6 = nn.Conv2d(32, 32, 3, padding=1)
self.conv7 = nn.Conv2d(32, 32, 3, padding=1)
self.conv8 = nn.Conv2d(32, 32, 3, padding=1)
self.conv9 = nn.Conv2d(32, 32, 3, padding=1)
self.conv10 = nn.Conv2d(32, 32, 3, padding=1)
self.conv11 = nn.Conv2d(32, 32, 3, padding=1)
self.conv12 = nn.Conv2d(32, 32, 3, padding=1)
self.conv13 = nn.Conv2d(32, 32, 3, padding=1)
self.conv14 = nn.Conv2d(32, 32, 3, padding=1)
self.conv15 = nn.Conv2d(32, 32, 3, padding=1)
self.conv16 = nn.Conv2d(32, 32, 3, padding=1)
self.bn1 = nn.BatchNorm2d(32)
self.bn2 = nn.BatchNorm2d(32)
self.bn3 = nn.BatchNorm2d(32)
self.bn4 = nn.BatchNorm2d(32)
self.bn5 = nn.BatchNorm2d(32)
self.bn6 = nn.BatchNorm2d(32)
self.bn7 = nn.BatchNorm2d(32)
self.bn8 = nn.BatchNorm2d(32)
self.bn9 = nn.BatchNorm2d(32)
self.bn10 = nn.BatchNorm2d(32)
self.bn11 = nn.BatchNorm2d(32)
self.bn12 = nn.BatchNorm2d(32)
self.bn13 = nn.BatchNorm2d(32)
self.bn14 = nn.BatchNorm2d(32)
self.bn15 = nn.BatchNorm2d(32)
self.bn16 = nn.BatchNorm2d(32)
self.conv_down_256_128 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_128_64 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_64_32 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_32_16 = nn.Conv2d(32, 32, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(32)
self.gdn_down_128_64 = pytorch_gdn.GDN(32)
self.gdn_down_64_32 = pytorch_gdn.GDN(32)
self.gdn_down_32_16 = pytorch_gdn.GDN(32)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 64, 1)
self.conv_down_256_128 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_128_64 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_64_32 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(64)
self.gdn_down_128_64 = pytorch_gdn.GDN(64)
self.gdn_down_64_32 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(32, 1, 5, padding=2)
self.tconv1 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv2 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv3 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv4 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv5 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv6 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv7 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv8 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv9 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv10 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv11 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv12 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv13 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv14 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv15 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.tconv16 = nn.ConvTranspose2d(32, 32, 3, padding=1)
self.bn1 = nn.BatchNorm2d(32)
self.bn2 = nn.BatchNorm2d(32)
self.bn3 = nn.BatchNorm2d(32)
self.bn4 = nn.BatchNorm2d(32)
self.bn5 = nn.BatchNorm2d(32)
self.bn6 = nn.BatchNorm2d(32)
self.bn7 = nn.BatchNorm2d(32)
self.bn8 = nn.BatchNorm2d(32)
self.bn9 = nn.BatchNorm2d(32)
self.bn10 = nn.BatchNorm2d(32)
self.bn11 = nn.BatchNorm2d(32)
self.bn12 = nn.BatchNorm2d(32)
self.bn13 = nn.BatchNorm2d(32)
self.bn14 = nn.BatchNorm2d(32)
self.bn15 = nn.BatchNorm2d(32)
self.bn16 = nn.BatchNorm2d(32)
self.tconv_up_16_32 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_32_64 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_64_128 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(32, 32, 2, 2)
self.igdn_up_16_32 = pytorch_gdn.GDN(32, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(32, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(32, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(32, True)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 64, 1)
self.conv_down_256_16 = nn.Conv2d(64, 64, 16, 16)
self.conv_down_128_16 = nn.Conv2d(64, 64, 8, 8)
self.conv_down_64_16 = nn.Conv2d(64, 64, 4, 4)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_16 = pytorch_gdn.GDN(64)
self.gdn_down_128_16 = pytorch_gdn.GDN(64)
self.gdn_down_64_16 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
self.conv_down_256_128 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_128_64 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_64_32 = nn.Conv2d(64, 64, 2, 2)
self.conv_down_32_16 = nn.Conv2d(64, 64, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(64)
self.gdn_down_128_64 = pytorch_gdn.GDN(64)
self.gdn_down_64_32 = pytorch_gdn.GDN(64)
self.gdn_down_32_16 = pytorch_gdn.GDN(64)
self.fc = nn.Linear(64*16*16, 64*16*16)
nn.init.zeros_(self.fc.weight)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up1 = nn.Conv2d(1, 32, 1)
self.conv_channels_up2 = nn.Conv2d(1, 32, 2, 2)
self.conv_channels_up3 = nn.Conv2d(1, 32, 4, 4)
self.conv_channels_up4 = nn.Conv2d(1, 32, 8, 8)
self.conv_down_256_16 = nn.Conv2d(32, 32, 16, 16)
self.conv_down_128_16 = nn.Conv2d(32, 32, 8, 8)
self.conv_down_64_16 = nn.Conv2d(32, 32, 4, 4)
self.conv_down_32_16 = nn.Conv2d(32, 32, 2, 2)
self.gdn_down_256_16 = pytorch_gdn.GDN(32)
self.gdn_down_128_16 = pytorch_gdn.GDN(32)
self.gdn_down_64_16 = pytorch_gdn.GDN(32)
self.gdn_down_32_16 = pytorch_gdn.GDN(32)
self.conv_down_256_128 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_128_64 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_64_32 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_32_16 = nn.Conv2d(32, 32, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(32)
self.gdn_down_128_64 = pytorch_gdn.GDN(32)
self.gdn_down_64_32 = pytorch_gdn.GDN(32)
self.gdn_down_32_16 = pytorch_gdn.GDN(32)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 256, 5, padding=2)
self.conv_down_256_128 = nn.Conv2d(256, 128, 2, 2)
self.conv_down_128_64 = nn.Conv2d(128, 64, 2, 2)
self.conv_down_64_32 = nn.Conv2d(64, 32, 2, 2)
self.conv_down_32_16 = nn.Conv2d(32, 16, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(128)
self.gdn_down_128_64 = pytorch_gdn.GDN(64)
self.gdn_down_64_32 = pytorch_gdn.GDN(32)
self.gdn_down_32_16 = pytorch_gdn.GDN(16)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(256, 1, 5, padding=2)
self.tconv_up_16_32 = nn.ConvTranspose2d(16, 32, 2, 2)
self.tconv_up_32_64 = nn.ConvTranspose2d(32, 64, 2, 2)
self.tconv_up_64_128 = nn.ConvTranspose2d(64, 128, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(128, 256, 2, 2)
self.igdn_up_16_32 = pytorch_gdn.GDN(16, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(32, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(128, True)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(64, 1, 1)
self.tconv_up_16_256 = nn.ConvTranspose2d(64, 64, 16, 16)
self.tconv_up_16_128 = nn.ConvTranspose2d(64, 64, 8, 8)
self.tconv_up_16_64 = nn.ConvTranspose2d(64, 64, 4, 4)
self.tconv_up_16_32 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_up_16_256 = pytorch_gdn.GDN(64, True)
self.igdn_up_16_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_16_64 = pytorch_gdn.GDN(64, True)
self.igdn_up_16_32 = pytorch_gdn.GDN(64, True)
self.tconv_up_32_64 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv_up_64_128 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_up_32_64 = pytorch_gdn.GDN(64, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(64, True)
self.k1_1 = nn.Parameter(torch.FloatTensor([1]))
self.k1_2 = nn.Parameter(torch.FloatTensor([1]))
self.k1_3 = nn.Parameter(torch.FloatTensor([1]))
self.k2_1 = nn.Parameter(torch.FloatTensor([1]))
self.k2_2 = nn.Parameter(torch.FloatTensor([1]))
self.k2_3 = nn.Parameter(torch.FloatTensor([1]))
self.k3_1 = nn.Parameter(torch.FloatTensor([1]))
self.k3_2 = nn.Parameter(torch.FloatTensor([1]))
self.k3_3 = nn.Parameter(torch.FloatTensor([1]))
self.k4_1 = nn.Parameter(torch.FloatTensor([1]))
self.k4_3 = nn.Parameter(torch.FloatTensor([1]))
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(64, 1, 1)
self.tconv_g1 = nn.ConvTranspose2d(64, 64, 8, 8)
self.tconv_g2 = nn.ConvTranspose2d(64, 64, 4, 4)
self.tconv_g3 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_g1 = pytorch_gdn.GDN(64, True)
self.igdn_g2 = pytorch_gdn.GDN(64, True)
self.igdn_g3 = pytorch_gdn.GDN(64, True)
self.tconv_f1 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv_f2 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_f1 = pytorch_gdn.GDN(64, True)
self.igdn_f2 = pytorch_gdn.GDN(64, True)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 64, 1)
self.conv_g1 = nn.Conv2d(64, 64, 8, 8)
self.conv_g2 = nn.Conv2d(64, 64, 4, 4)
self.conv_g3 = nn.Conv2d(64, 64, 2, 2)
self.gdn_g1 = pytorch_gdn.GDN(64)
self.gdn_g2 = pytorch_gdn.GDN(64)
self.gdn_g3 = pytorch_gdn.GDN(64)
self.conv_f1 = nn.Conv2d(64, 64, 2, 2)
self.conv_f2 = nn.Conv2d(64, 64, 2, 2)
self.gdn_f1 = pytorch_gdn.GDN(64)
self.gdn_f2 = pytorch_gdn.GDN(64)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down_1 = nn.ConvTranspose2d(32, 1, 1)
self.tconv_channels_down_3 = nn.ConvTranspose2d(32, 1, 3, padding=1)
self.tconv_channels_down_5 = nn.ConvTranspose2d(32, 1, 5, padding=2)
self.tconv_channels_down_7 = nn.ConvTranspose2d(32, 1, 7, padding=3)
self.tconv_channels_down_9 = nn.ConvTranspose2d(32, 1, 9, padding=4)
self.tconv_up_16_32 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_32_64 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_64_128 = nn.ConvTranspose2d(32, 32, 2, 2)
self.tconv_up_128_256 = nn.ConvTranspose2d(32, 32, 2, 2)
self.igdn_up_16_32 = pytorch_gdn.GDN(32, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(32, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(32, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(32, True)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv0 = nn.ConvTranspose2d(128, 1, 9, padding=4)
self.tconv_up_0 = nn.ConvTranspose2d(128, 128, 4, 4) # 升采样
self.igdn128_0 = pytorch_gdn.GDN(128, True)
self.tconv1 = nn.ConvTranspose2d(128, 128, 5, padding=2)
self.tconv_up_1 = nn.ConvTranspose2d(128, 128, 2, 2) # 升采样
self.igdn128_1 = pytorch_gdn.GDN(128, True)
self.tconv2 = nn.ConvTranspose2d(128, 128, 5, padding=2)
self.tconv_up_2 = nn.ConvTranspose2d(128, 128, 2, 2) # 升采样
self.igdn128_2 = pytorch_gdn.GDN(128, True)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv0 = nn.Conv2d(1, 128, 9, padding=4)
self.conv_down_0 = nn.Conv2d(128, 128, 4, 4) # 降采样
self.gdn128_0 = pytorch_gdn.GDN(128)
self.conv1 = nn.Conv2d(128, 128, 5, padding=2)
self.conv_down_1 = nn.Conv2d(128, 128, 2, 2) # 降采样
self.gdn128_1 = pytorch_gdn.GDN(128)
self.conv2 = nn.Conv2d(128, 128, 5, padding=2)
self.conv_down_2 = nn.Conv2d(128, 128, 2, 2) # 降采样
self.gdn128_2 = pytorch_gdn.GDN(128)
def __init__(self):
super(EncodeNet, self).__init__()
self.conv_channels_up_1 = nn.Conv2d(1, 32, 1)
self.conv_channels_up_3 = nn.Conv2d(1, 32, 3, padding=1)
self.conv_channels_up_5 = nn.Conv2d(1, 32, 5, padding=2)
self.conv_channels_up_7 = nn.Conv2d(1, 32, 7, padding=3)
self.conv_channels_up_9 = nn.Conv2d(1, 32, 9, padding=4)
self.conv_down_256_128 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_128_64 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_64_32 = nn.Conv2d(32, 32, 2, 2)
self.conv_down_32_16 = nn.Conv2d(32, 32, 2, 2)
self.gdn_down_256_128 = pytorch_gdn.GDN(32)
self.gdn_down_128_64 = pytorch_gdn.GDN(32)
self.gdn_down_64_32 = pytorch_gdn.GDN(32)
self.gdn_down_32_16 = pytorch_gdn.GDN(32)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(64, 1, 1)
self.tconv3_16 = nn.ConvTranspose2d(64, 64, 3, 1, padding=1)
self.tconv_up_16_32 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv3_32 = nn.ConvTranspose2d(64, 64, 3, 1, padding=1)
self.tconv_up_32_64 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv3_64 = nn.ConvTranspose2d(64, 64, 3, 1, padding=1)
self.tconv_up_64_128 = nn.ConvTranspose2d(64, 64, 2, 2)
self.tconv3_128 = nn.ConvTranspose2d(64, 64, 3, 1, padding=1)
self.tconv_up_128_256 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_up_16_32 = pytorch_gdn.GDN(64, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(64, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(64, True)
def __init__(self):
super(DecodeNet, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(64, 1, 1)
self.dropout16 = nn.Dropout2d(0.5)
self.tconv_up_16_32 = nn.ConvTranspose2d(64, 64, 2, 2)
self.dropout32 = nn.Dropout2d(0.5)
self.tconv_up_32_64 = nn.ConvTranspose2d(64, 64, 2, 2)
self.dropout64 = nn.Dropout2d(0.5)
self.tconv_up_64_128 = nn.ConvTranspose2d(64, 64, 2, 2)
self.dropout128 = nn.Dropout2d(0.5)
self.tconv_up_128_256 = nn.ConvTranspose2d(64, 64, 2, 2)
self.igdn_up_16_32 = pytorch_gdn.GDN(64, True)
self.igdn_up_32_64 = pytorch_gdn.GDN(64, True)
self.igdn_up_64_128 = pytorch_gdn.GDN(64, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(64, True)
def __init__(self):
super(EncodeNet2, self).__init__()
self.conv_channels_up = nn.Conv2d(1, 128, 1)
self.conv_down_256_128 = nn.Conv2d(128, 128, 2, 2)
self.conv128_1 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_2 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_3 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_4 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_5 = nn.Conv2d(128, 128, 3, padding=1)
self.conv128_6 = nn.Conv2d(128, 128, 3, padding=1)
self.bn128_1 = nn.BatchNorm2d(128)
self.bn128_2 = nn.BatchNorm2d(128)
self.bn128_3 = nn.BatchNorm2d(128)
self.bn128_4 = nn.BatchNorm2d(128)
self.bn128_5 = nn.BatchNorm2d(128)
self.bn128_6 = nn.BatchNorm2d(128)
self.conv_down_128_64 = nn.Conv2d(128, 128, 2, 2)
self.conv64_1 = nn.Conv2d(128, 128, 3, padding=1)
self.conv64_2 = nn.Conv2d(128, 128, 3, padding=1)
self.conv64_3 = nn.Conv2d(128, 128, 3, padding=1)
self.conv64_4 = nn.Conv2d(128, 128, 3, padding=1)
self.conv64_5 = nn.Conv2d(128, 128, 3, padding=1)
self.conv64_6 = nn.Conv2d(128, 128, 3, padding=1)
self.bn64_1 = nn.BatchNorm2d(128)
self.bn64_2 = nn.BatchNorm2d(128)
self.bn64_3 = nn.BatchNorm2d(128)
self.bn64_4 = nn.BatchNorm2d(128)
self.bn64_5 = nn.BatchNorm2d(128)
self.bn64_6 = nn.BatchNorm2d(128)
self.gdn_down_256_128 = pytorch_gdn.GDN(128)
self.gdn_down_128_64 = pytorch_gdn.GDN(128)
def __init__(self):
super(DecodeNet2, self).__init__()
self.tconv_channels_down = nn.ConvTranspose2d(128, 1, 1)
self.tconv64_1 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv64_2 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv64_3 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv64_4 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv64_5 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv64_6 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.bn64_1 = nn.BatchNorm2d(128)
self.bn64_2 = nn.BatchNorm2d(128)
self.bn64_3 = nn.BatchNorm2d(128)
self.bn64_4 = nn.BatchNorm2d(128)
self.bn64_5 = nn.BatchNorm2d(128)
self.bn64_6 = nn.BatchNorm2d(128)
self.tconv_up_64_128 = nn.ConvTranspose2d(128, 128, 2, 2)
self.tconv128_1 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_2 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_3 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_4 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_5 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.tconv128_6 = nn.ConvTranspose2d(128, 128, 3, padding=1)
self.bn128_1 = nn.BatchNorm2d(128)
self.bn128_2 = nn.BatchNorm2d(128)
self.bn128_3 = nn.BatchNorm2d(128)
self.bn128_4 = nn.BatchNorm2d(128)
self.bn128_5 = nn.BatchNorm2d(128)
self.bn128_6 = nn.BatchNorm2d(128)
self.tconv_up_128_256 = nn.ConvTranspose2d(128, 128, 2, 2)
self.igdn_up_64_128 = pytorch_gdn.GDN(128, True)
self.igdn_up_128_256 = pytorch_gdn.GDN(128, True)
