[data] type=data dataIdx=0 [labels] type=data dataIdx=1 [conv1a] type=conv inputs=data channels=3 filters=48 padding=0 stride=4 filterSize=11 initW=0.01 partialSum=5 sharedBiases=1 gpu=0 [conv1b] type=conv inputs=data channels=3 filters=48 padding=0 stride=4 filterSize=11 initW=0.01 partialSum=5 sharedBiases=1 gpu=1 [rnorm1a] type=cmrnorm inputs=conv1a channels=48 size=5 [rnorm1b] type=cmrnorm inputs=conv1b channels=48 size=5 [pool1a] type=pool pool=max inputs=rnorm1a sizeX=3 stride=2 channels=48 neuron=relu [pool1b] type=pool pool=max inputs=rnorm1b sizeX=3 stride=2 channels=48 neuron=relu [conv2a] type=conv inputs=pool1a filters=160 padding=2 stride=1 filterSize=5 channels=48 initW=0.01 initB=1 partialSum=3 sharedBiases=1 neuron=relu gpu=0 [conv2b] type=conv inputs=pool1b filters=160 padding=2 stride=1 filterSize=5 channels=48 initW=0.01 initB=1 partialSum=3 sharedBiases=1 neuron=relu gpu=1 [rnorm2a] type=cmrnorm inputs=conv2a channels=160 size=5 [rnorm2b] type=cmrnorm inputs=conv2b channels=160 size=5 [cnorm2a] type=rnorm inputs=rnorm2a channels=160 size=5 [cnorm2b] type=rnorm inputs=rnorm2b channels=160 size=5 [pool2a] type=pool pool=max inputs=cnorm2a sizeX=3 stride=2 channels=160 [pool2b] type=pool pool=max inputs=cnorm2b sizeX=3 stride=2 channels=160 [conv3a] type=conv inputs=pool2a filters=192 padding=1 stride=1 filterSize=3 channels=160 initW=0.03 partialSum=13 sharedBiases=1 neuron=relu gpu=0 [conv3b] type=conv inputs=pool2b filters=192 padding=1 stride=1 filterSize=3 channels=160 initW=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 [fc4096a] type=fc inputs=pool3a outputs=4096 initW=0.01 initB=1 neuron=relu gpu=0 [fc4096b] type=fc inputs=pool3b outputs=4096 initW=0.01 initB=1 neuron=relu gpu=1 [hs1a] type=hs keep=0.5 inputs=fc4096a [hs1b] type=hs keep=0.5 inputs=fc4096b [fc2048ba] type=fc inputs=hs1a outputs=2048 initW=0.01 initB=1 neuron=relu gpu=0 [fc2048bb] type=fc inputs=hs1b outputs=2048 initW=0.01 initB=1 neuron=relu gpu=1 [hs2a] type=hs keep=0.5 inputs=fc2048ba [hs2b] type=hs keep=0.5 inputs=fc2048bb [fc1000] type=fc outputs=1000 inputs=hs2a,hs2b initW=0.01,0.01 gpu=0 [probs] type=softmax inputs=fc1000 [logprob] type=cost.logreg inputs=labels,probs gpu=0