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change weight initialization and upconv_7

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nagadomi 2016-06-08 06:58:46 +09:00
parent 307ae40883
commit 51914b894a
1 changed files with 24 additions and 46 deletions
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70
lib/srcnn.lua
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@ -5,23 +5,31 @@ require 'w2nn'
local srcnn = {}
function nn.SpatialConvolutionMM:reset(stdv)
stdv = math.sqrt(2 / ((1.0 + 0.1 * 0.1) * self.kW * self.kH * self.nOutputPlane))
local fin = self.kW * self.kH * self.nInputPlane
local fout = self.kW * self.kH * self.nOutputPlane
stdv = math.sqrt(4 / ((1.0 + 0.1 * 0.1) * (fin + fout)))
self.weight:normal(0, stdv)
self.bias:zero()
end
function nn.SpatialFullConvolution:reset(stdv)
stdv = math.sqrt(2 / ((1.0 + 0.1 * 0.1) * self.kW * self.kH * self.nOutputPlane))
local fin = self.kW * self.kH * self.nInputPlane
local fout = self.kW * self.kH * self.nOutputPlane
stdv = math.sqrt(4 / ((1.0 + 0.1 * 0.1) * (fin + fout)))
self.weight:normal(0, stdv)
self.bias:zero()
end
if cudnn and cudnn.SpatialConvolution then
function cudnn.SpatialConvolution:reset(stdv)
stdv = math.sqrt(2 / ((1.0 + 0.1 * 0.1) * self.kW * self.kH * self.nOutputPlane))
local fin = self.kW * self.kH * self.nInputPlane
local fout = self.kW * self.kH * self.nOutputPlane
stdv = math.sqrt(4 / ((1.0 + 0.1 * 0.1) * (fin + fout)))
self.weight:normal(0, stdv)
self.bias:zero()
end
function cudnn.SpatialFullConvolution:reset(stdv)
stdv = math.sqrt(2 / ((1.0 + 0.1 * 0.1) * self.kW * self.kH * self.nOutputPlane))
local fin = self.kW * self.kH * self.nInputPlane
local fout = self.kW * self.kH * self.nOutputPlane
stdv = math.sqrt(4 / ((1.0 + 0.1 * 0.1) * (fin + fout)))
self.weight:normal(0, stdv)
self.bias:zero()
end
@ -119,9 +127,9 @@ local function SpatialConvolution(backend, nInputPlane, nOutputPlane, kW, kH, dW
error("unsupported backend:" .. backend)
end
end
local function SpatialFullConvolution(backend, nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH)
local function SpatialFullConvolution(backend, nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH, adjW, adjH)
if backend == "cunn" then
return nn.SpatialFullConvolution(nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH)
return nn.SpatialFullConvolution(nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH, adjW, adjH)
elseif backend == "cudnn" then
return cudnn.SpatialFullConvolution(nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH)
else
@ -225,26 +233,26 @@ function srcnn.dilated_7(backend, ch)
return model
end
-- Up Convolution
-- Upconvolution
function srcnn.upconv_7(backend, ch)
local model = nn.Sequential()
model:add(SpatialConvolution(backend, ch, 32, 3, 3, 1, 1, 0, 0))
model:add(SpatialConvolution(backend, ch, 16, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 32, 32, 3, 3, 1, 1, 0, 0))
model:add(SpatialConvolution(backend, 16, 32, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 32, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 128, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 128, 128, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 128, ch, 4, 4, 2, 2, 1, 1))
model:add(SpatialConvolution(backend, 128, 256, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 256, ch, 4, 4, 2, 2, 3, 3))
model:add(nn.View(-1):setNumInputDims(3))
model.w2nn_arch_name = "upconv_7"
model.w2nn_offset = 12
model.w2nn_offset = 14
model.w2nn_scale_factor = 2
model.w2nn_resize = true
model.w2nn_channels = ch
@ -254,36 +262,6 @@ function srcnn.upconv_7(backend, ch)
return model
end
function srcnn.upconv_8_4x(backend, ch)
local model = nn.Sequential()
model:add(SpatialFullConvolution(backend, ch, 32, 4, 4, 2, 2, 1, 1))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 32, 32, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 32, 32, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 32, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 64, 3, 4, 4, 2, 2, 1, 1))
model.w2nn_arch_name = "upconv_8_4x"
model.w2nn_offset = 12
model.w2nn_scale_factor = 4
model.w2nn_resize = true
model.w2nn_channels = ch
--model:cuda()
--print(model:forward(torch.Tensor(32, ch, 92, 92):uniform():cuda()):size())
return model
end
function srcnn.create(model_name, backend, color)
model_name = model_name or "vgg_7"
backend = backend or "cunn"
@ -298,14 +276,14 @@ function srcnn.create(model_name, backend, color)
end
if srcnn[model_name] then
local model = srcnn[model_name](backend, ch)
assert(model.w2nn_offset == (model.w2nn_offset / model.w2nn_scale_factor) * model.w2nn_scale_factor)
assert(model.w2nn_offset % model.w2nn_scale_factor == 0)
return model
else
error("unsupported model_name: " .. model_name)
end
end
--local model = srcnn.upconv_8_4x("cunn", 3):cuda()
--local model = srcnn.upconv_6("cunn", 3):cuda()
--print(model:forward(torch.Tensor(1, 3, 64, 64):zero():cuda()):size())
return srcnn