33 lines
1.2 KiB
Lua
33 lines
1.2 KiB
Lua
require 'cunn'
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require 'cudnn'
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require './LeakyReLU'
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function cudnn.SpatialConvolution:reset(stdv)
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stdv = math.sqrt(2 / ( self.kW * self.kH * self.nOutputPlane))
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self.weight:normal(0, stdv)
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self.bias:fill(0)
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end
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local function create_model()
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local model = nn.Sequential()
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model:add(cudnn.SpatialConvolution(1, 32, 3, 3, 1, 1, 0, 0):fastest())
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model:add(nn.LeakyReLU(0.1))
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model:add(cudnn.SpatialConvolution(32, 32, 3, 3, 1, 1, 0, 0):fastest())
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model:add(nn.LeakyReLU(0.1))
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model:add(cudnn.SpatialConvolution(32, 64, 3, 3, 1, 1, 0, 0):fastest())
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model:add(nn.LeakyReLU(0.1))
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model:add(cudnn.SpatialConvolution(64, 64, 3, 3, 1, 1, 0, 0):fastest())
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model:add(nn.LeakyReLU(0.1))
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model:add(cudnn.SpatialConvolution(64, 128, 3, 3, 1, 1, 0, 0):fastest())
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model:add(nn.LeakyReLU(0.1))
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model:add(cudnn.SpatialConvolution(128, 128, 3, 3, 1, 1, 0, 0):fastest())
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model:add(nn.LeakyReLU(0.1))
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model:add(cudnn.SpatialConvolution(128, 1, 3, 3, 1, 1, 0, 0):fastest())
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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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return create_model
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