| 1234567891011121314151617181920212223242526272829303132 | require 'cunn'require 'cudnn'require './LeakyReLU'function cudnn.SpatialConvolution:reset(stdv)   stdv = math.sqrt(2 / ( self.kW * self.kH * self.nOutputPlane))   self.weight:normal(0, stdv)   self.bias:fill(0)endlocal function create_model()   local model = nn.Sequential()       model:add(cudnn.SpatialConvolution(1, 32, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.LeakyReLU(0.1))      model:add(cudnn.SpatialConvolution(32, 32, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.LeakyReLU(0.1))   model:add(cudnn.SpatialConvolution(32, 64, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.LeakyReLU(0.1))   model:add(cudnn.SpatialConvolution(64, 64, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.LeakyReLU(0.1))   model:add(cudnn.SpatialConvolution(64, 128, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.LeakyReLU(0.1))   model:add(cudnn.SpatialConvolution(128, 128, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.LeakyReLU(0.1))   model:add(cudnn.SpatialConvolution(128, 1, 3, 3, 1, 1, 0, 0):fastest())   model:add(nn.View(-1):setNumInputDims(3))--model:cuda()--print(model:forward(torch.Tensor(32, 1, 92, 92):uniform():cuda()):size())      return model, 7endreturn create_model
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