[data] type=data dataIdx=0 [labels] type=data dataIdx=1 [blur0] type=blur inputs=data stdev=4 filterSize=9 channels=3 gpu=0 [nails0] type=nailbed inputs=blur0 stride=4 channels=3 [conv1a] type=conv inputs=data channels=3 filters=32 padding=0 stride=4 filterSize=11 initW=0.01 partialSum=5 sharedBiases=1 gpu=0 [conv1b] type=conv inputs=data channels=3 filters=32 padding=0 stride=4 filterSize=11 initW=0.01 partialSum=5 sharedBiases=1 gpu=1 [pool1a] type=pool pool=max inputs=conv1a sizeX=3 stride=2 channels=32 neuron=relu [pool1b] type=pool pool=max inputs=conv1b sizeX=3 stride=2 channels=32 neuron=relu [rnorm1a] type=cmrnorm inputs=pool1a channels=32 size=9 [rnorm1b] type=cmrnorm inputs=pool1b channels=32 size=9 [conv2a] type=conv inputs=nails0,rnorm1a filters=128,128 padding=0,2 stride=2,1 filterSize=5,5 channels=3,32 initW=0.01,0.01 initB=1 partialSum=3 sharedBiases=1 neuron=relu gpu=0 [conv2b] type=conv inputs=nails0,rnorm1b filters=128,128 padding=0,2 stride=2,1 filterSize=5,5 channels=3,32 initW=0.01,0.01 initB=1 partialSum=3 sharedBiases=1 neuron=relu gpu=1 [rnorm2a] type=cmrnorm inputs=conv2a channels=128 size=9 [rnorm2b] type=cmrnorm inputs=conv2b channels=128 size=9 [pool2a] type=pool pool=max inputs=rnorm2a sizeX=3 stride=2 channels=128 [pool2b] type=pool pool=max inputs=rnorm2b sizeX=3 stride=2 channels=128 [conv3a] type=conv inputs=pool2a,pool2b filters=192,192 padding=1,1 stride=1,1 filterSize=3,3 channels=128,128 initW=0.03,0.03 partialSum=13 sharedBiases=1 neuron=relu gpu=0 [conv3b] type=conv inputs=pool2a,pool2b filters=192,192 padding=1,1 stride=1,1 filterSize=3,3 channels=128,128 initW=0.03,0.03 partialSum=13 sharedBiases=1 neuron=relu gpu=1 [conv4a] type=conv inputs=conv3a filters=192 padding=1 stride=1 filterSize=3 channels=192 neuron=relu initW=0.03 initB=1 partialSum=13 sharedBiases=1 [conv4b] type=conv inputs=conv3b filters=192 padding=1 stride=1 filterSize=3 channels=192 neuron=relu initW=0.03 initB=1 partialSum=13 sharedBiases=1 [conv5a] type=conv inputs=conv4a filters=128 padding=1 stride=1 filterSize=3 channels=192 initW=0.03 initB=1 partialSum=13 groups=1 randSparse=0 [conv5b] type=conv inputs=conv4b filters=128 padding=1 stride=1 filterSize=3 channels=192 initW=0.03 initB=1 partialSum=13 groups=1 randSparse=0 [pool3a] type=pool pool=max inputs=conv5a sizeX=3 stride=2 channels=128 neuron=relu [pool3b] type=pool pool=max inputs=conv5b sizeX=3 stride=2 channels=128 neuron=relu [fc3072a] type=fc inputs=pool3a,pool3b outputs=3072 initW=0.01,0.01 initB=1 neuron=relu gpu=0 [fc3072b] type=fc inputs=pool3a,pool3b outputs=3072 initW=0.01,0.01 initB=1 neuron=relu gpu=1 [hs1a] type=hs keep=0.5 inputs=fc3072a [hs1b] type=hs keep=0.5 inputs=fc3072b [fc3072ba] type=fc inputs=hs1a,hs1b outputs=3072 initW=0.01,0.01 initB=1 neuron=relu gpu=0 [fc3072bb] type=fc inputs=hs1b,hs1a outputs=3072 initW=0.01,0.01 initB=1 neuron=relu gpu=1 [hs2a] type=hs keep=0.5 inputs=fc3072ba [hs2b] type=hs keep=0.5 inputs=fc3072bb [fc1000] type=fc outputs=1000 inputs=hs2a,hs2b initW=0.01,0.01 gpu=1 [probs] type=softmax inputs=fc1000 [logprob] type=cost.logreg inputs=labels,probs gpu=1