Brian Broll
09b6ca0ad0
WIP #3. Added import tests WIP #3 Added more test-cases WIP #3 Added more tests WIP #3. Fixed concat.lua test WIP #3 minor changes WIP #3 Fixed concat-parallel.lua WIP #3 Added check-model helper WIP #3 Added more tests for model checker WIP #3 Added extra tests WIP #3 Changed check-model to GraphChecker WIP #3. multiple cases fail for ImportTorch... WIP #3 Fixed ImportTorch batch test case running WIP #3 Changed graph checker to use gme path for id WIP #3 Updated tests WIP #3. Tweaked to get all examples working locally w/ 'th' WIP #3 Fixed tests
48 linhas
1.4 KiB
Lua
48 linhas
1.4 KiB
Lua
-- thanks to https://github.com/soumith/imagenet-multiGPU.torch for this example
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require 'nn'
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nClasses = 7
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local features = nn.Sequential()
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features:add(nn.SpatialConvolution(3, 96, 11, 11, 4, 4))
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features:add(nn.ReLU(true))
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features:add(nn.SpatialMaxPooling(2, 2, 2, 2))
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features:add(nn.SpatialConvolution(96, 256, 5, 5, 1, 1))
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features:add(nn.ReLU(true))
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features:add(nn.SpatialMaxPooling(2, 2, 2, 2))
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features:add(nn.SpatialConvolution(256, 512, 3, 3, 1, 1, 1, 1))
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features:add(nn.ReLU(true))
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features:add(nn.SpatialConvolution(512, 1024, 3, 3, 1, 1, 1, 1))
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features:add(nn.ReLU(true))
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features:add(nn.SpatialConvolution(1024, 1024, 3, 3, 1, 1, 1, 1))
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features:add(nn.ReLU(true))
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features:add(nn.SpatialMaxPooling(2, 2, 2, 2))
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-- features:cuda()
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-- features = makeDataParallel(features, nGPU) -- defined in util.lua
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-- 1.3. Create Classifier (fully connected layers)
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local classifier = nn.Sequential()
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classifier:add(nn.View(1024*5*5))
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classifier:add(nn.Dropout(0.5))
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classifier:add(nn.Linear(1024*5*5, 3072))
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classifier:add(nn.Threshold(0, 0.000001))
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classifier:add(nn.Dropout(0.5))
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classifier:add(nn.Linear(3072, 4096))
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classifier:add(nn.Threshold(0, 0.000001))
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classifier:add(nn.Linear(4096, nClasses))
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classifier:add(nn.LogSoftMax())
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-- classifier:cuda()
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-- 1.4. Combine 1.2 and 1.3 to produce final model
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local model = nn.Sequential():add(features):add(classifier)
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model.imageSize = 256
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model.imageCrop = 224
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return model
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