78 lines
2.3 KiB
Lua
78 lines
2.3 KiB
Lua
require './LeakyReLU'
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-- ref: http://arxiv.org/abs/1502.01852
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function nn.SpatialConvolutionMM:reset(stdv)
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stdv = math.sqrt(2 / ((1.0 + 0.1 * 0.1) * self.kW * self.kH * self.nOutputPlane))
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self.weight:normal(0, stdv)
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self.bias:zero()
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end
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-- ref: http://arxiv.org/abs/1501.00092
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local srcnn = {}
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function srcnn.waifu2x(color)
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local model = nn.Sequential()
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local ch = nil
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if color == "rgb" then
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ch = 3
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elseif color == "y" then
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ch = 1
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else
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if color then
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error("unknown color: " .. color)
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else
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error("unknown color: nil")
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end
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end
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-- very deep model
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model:add(nn.SpatialConvolutionMM(ch, 32, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(32, 32, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(32, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(64, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(64, 128, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(128, 128, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(128, ch, 3, 3, 1, 1, 0, 0))
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model:add(nn.View(-1):setNumInputDims(3))
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--model:cuda()
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--print(model:forward(torch.Tensor(32, 1, 92, 92):uniform():cuda()):size())
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return model, 7
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end
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-- current 4x is worse then 2x * 2
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function srcnn.waifu4x(color)
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local model = nn.Sequential()
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local ch = nil
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if color == "rgb" then
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ch = 3
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elseif color == "y" then
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ch = 1
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else
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error("unknown color: " .. color)
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end
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model:add(nn.SpatialConvolutionMM(ch, 32, 9, 9, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(32, 32, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(32, 64, 5, 5, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(64, 64, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(64, 128, 5, 5, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(128, 128, 3, 3, 1, 1, 0, 0))
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model:add(nn.LeakyReLU(0.1))
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model:add(nn.SpatialConvolutionMM(128, ch, 5, 5, 1, 1, 0, 0))
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model:add(nn.View(-1):setNumInputDims(3))
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return model, 13
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end
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return srcnn
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