44 lines
1.4 KiB
Lua
44 lines
1.4 KiB
Lua
require 'pl'
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local __FILE__ = (function() return string.gsub(debug.getinfo(2, 'S').source, "^@", "") end)()
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package.path = path.join(path.dirname(__FILE__), "..", "lib", "?.lua;") .. package.path
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require 'os'
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require 'w2nn'
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local srcnn = require 'srcnn'
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local function cunn2cudnn(cunn_model)
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local cudnn_model = srcnn.waifu2x_cudnn(srcnn.channels(cunn_model))
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local weight_from = cunn_model:findModules("nn.SpatialConvolutionMM")
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local weight_to = cudnn_model:findModules("cudnn.SpatialConvolution")
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assert(#weight_from == #weight_to)
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for i = 1, #weight_from do
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local from = weight_from[i]
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local to = weight_to[i]
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to.weight:copy(from.weight)
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to.bias:copy(from.bias)
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end
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cudnn_model:cuda()
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cudnn_model:evaluate()
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return cudnn_model
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end
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local cmd = torch.CmdLine()
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cmd:text()
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cmd:text("waifu2x cunn model to cudnn model converter")
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cmd:text("Options:")
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cmd:option("-i", "", 'Specify the input cudnn model')
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cmd:option("-o", "", 'Specify the output cunn model')
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cmd:option("-iformat", "ascii", 'Specify the input format (ascii|binary)')
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cmd:option("-oformat", "ascii", 'Specify the output format (ascii|binary)')
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local opt = cmd:parse(arg)
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if not path.isfile(opt.i) then
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cmd:help()
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os.exit(-1)
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end
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local cunn_model = torch.load(opt.i, opt.iformat)
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local cudnn_model = cunn2cudnn(cunn_model)
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torch.save(opt.o, cudnn_model, opt.oformat)
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