def __init__(self, N=192, **kwargs):
super().__init__(N=N, **kwargs)
self.g_a = nn.Sequential(
ResidualBlockWithStride(3, N, stride=2),
ResidualBlock(N, N),
ResidualBlockWithStride(N, N, stride=2),
AttentionBlock(N),
ResidualBlock(N, N),
ResidualBlockWithStride(N, N, stride=2),
ResidualBlock(N, N),
conv3x3(N, N, stride=2),
AttentionBlock(N),
)
self.g_s = nn.Sequential(
AttentionBlock(N),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
AttentionBlock(N),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
subpel_conv3x3(N, 3, 2),
)
def __init__(self, N=192, **kwargs):
super().__init__(N=N, M=N, **kwargs)
self.g_a = nn.Sequential(
ResidualBlockWithStride(3, N, stride=2),
ResidualBlock(N, N),
ResidualBlockWithStride(N, N, stride=2),
ResidualBlock(N, N),
ResidualBlockWithStride(N, N, stride=2),
ResidualBlock(N, N),
conv3x3(N, N, stride=2),
)
self.h_a = nn.Sequential(
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
conv3x3(N, N, stride=2),
nn.LeakyReLU(inplace=True),
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
conv3x3(N, N, stride=2),
)
self.h_s = nn.Sequential(
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
subpel_conv3x3(N, N, 2),
nn.LeakyReLU(inplace=True),
conv3x3(N, N * 3 // 2),
nn.LeakyReLU(inplace=True),
subpel_conv3x3(N * 3 // 2, N * 3 // 2, 2),
nn.LeakyReLU(inplace=True),
conv3x3(N * 3 // 2, N * 2),
)
self.g_s = nn.Sequential(
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
subpel_conv3x3(N, 3, 2),
)
def __init__(self, N=192, **kwargs):
super().__init__(N=N, M=N, **kwargs)
self.g_a = nn.Sequential(
ResidualBlockWithStride(3, N, stride=2),
ResidualBlock(N, N),
ResidualBlockWithStride(N, N, stride=2),
ResidualBlock(N, N),
ResidualBlockWithStride(N, N, stride=2),
ResidualBlock(N, N),
conv3x3(N, N, stride=2),
)
self.g_a_b = copy.deepcopy(self.g_a)
self.h_a = nn.Sequential(
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
conv3x3(N, N, stride=2),
nn.LeakyReLU(inplace=True),
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
conv3x3(N, N, stride=2),
)
self.h_a_b = copy.deepcopy(self.h_a)
self.h_s = nn.Sequential(
conv3x3(N, N),
nn.LeakyReLU(inplace=True),
subpel_conv3x3(N, N, 2),
nn.LeakyReLU(inplace=True),
conv3x3(N, N * 3 // 2),
nn.LeakyReLU(inplace=True),
subpel_conv3x3(N * 3 // 2, N * 3 // 2, 2),
nn.LeakyReLU(inplace=True),
conv3x3(N * 3 // 2, N * 2),
)
self.h_s_b = copy.deepcopy(self.h_s)
self.g_s = nn.Sequential(
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
ResidualBlockUpsample(N, N, 2),
ResidualBlock(N, N),
subpel_conv3x3(N, 3, 2),
)
self.g_s_b = copy.deepcopy(self.g_s)
self.entropy_parameters = nn.Sequential(
nn.Conv2d(N * 4, 640, 3, padding=1),
nn.LeakyReLU(inplace=True),
nn.Conv2d(640, 640, 3, padding=1),
nn.LeakyReLU(inplace=True),
nn.Conv2d(640, N * 9, 3, padding=1),
)
self.context_prediction = MaskedConv2d(N,
2 * N,
kernel_size=5,
padding=2,
stride=1)
self.Quantization = Quantization()