50 lines
1.0 KiB
Lua
50 lines
1.0 KiB
Lua
require 'nn'
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require 'dpnn'
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require 'optim'
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if opt.cuda then
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require 'cunn'
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if opt.cudnn then
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require 'cudnn'
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cudnn.benchmark = false
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cudnn.fastest = true
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cudnn.verbose = false
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end
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end
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paths.dofile('torch-TripletEmbedding/TripletEmbedding.lua')
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if opt.retrain ~= 'none' then
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assert(paths.filep(opt.retrain), 'File not found: ' .. opt.retrain)
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print('Loading model from file: ' .. opt.retrain);
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model = torch.load(opt.retrain)
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else
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paths.dofile(opt.modelDef)
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assert(imgDim, "Model definition must set global variable 'imgDim'")
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assert(imgDim == opt.imgDim, "Model definiton's imgDim must match imgDim option.")
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model = createModel()
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end
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criterion = nn.TripletEmbeddingCriterion(opt.alpha)
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if opt.cuda then
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model = model:cuda()
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if opt.cudnn then
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cudnn.convert(model,cudnn)
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end
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criterion:cuda()
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end
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optimizeNet(model, imgDim)
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print('=> Model')
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print(model)
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print(('Number of Parameters: %d'):format(model:getParameters():size(1)))
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print('=> Criterion')
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print(criterion)
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collectgarbage()
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