Initial commit

layers/layers-130.cfg

@@ -0,0 +1,605 @@
+[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
+
+[conv1c]
+type=conv
+inputs=data
+channels=3
+filters=32
+padding=0
+stride=4
+filterSize=11
+initW=0.01
+partialSum=5
+sharedBiases=1
+gpu=2
+
+[conv1d]
+type=conv
+inputs=data
+channels=3
+filters=32
+padding=0
+stride=4
+filterSize=11
+initW=0.01
+partialSum=5
+sharedBiases=1
+gpu=3
+
+[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
+
+[pool1c]
+type=pool
+pool=max
+inputs=conv1c
+sizeX=3
+stride=2
+channels=32
+neuron=relu
+
+[pool1d]
+type=pool
+pool=max
+inputs=conv1d
+sizeX=3
+stride=2
+channels=32
+neuron=relu
+
+[rnorm1a]
+type=cmrnorm
+inputs=pool1a
+channels=32
+size=5
+
+[rnorm1b]
+type=cmrnorm
+inputs=pool1b
+channels=32
+size=5
+
+[rnorm1c]
+type=cmrnorm
+inputs=pool1c
+channels=32
+size=5
+
+[rnorm1d]
+type=cmrnorm
+inputs=pool1d
+channels=32
+size=5
+
+[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
+
+[conv2c]
+type=conv
+inputs=nails0,rnorm1c
+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=2
+
+[conv2d]
+type=conv
+inputs=nails0,rnorm1d
+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=3
+
+[rnorm2a]
+type=cmrnorm
+inputs=conv2a
+channels=128
+size=5
+
+[rnorm2b]
+type=cmrnorm
+inputs=conv2b
+channels=128
+size=5
+
+[rnorm2c]
+type=cmrnorm
+inputs=conv2c
+channels=128
+size=5
+
+[rnorm2d]
+type=cmrnorm
+inputs=conv2d
+channels=128
+size=5
+
+[cnorm2a]
+type=cnorm
+inputs=rnorm2a
+channels=128
+size=5
+
+[cnorm2b]
+type=cnorm
+inputs=rnorm2b
+channels=128
+size=5
+
+[cnorm2c]
+type=cnorm
+inputs=rnorm2c
+channels=128
+size=5
+
+[cnorm2d]
+type=cnorm
+inputs=rnorm2d
+channels=128
+size=5
+
+[pool2a]
+type=pool
+pool=max
+inputs=cnorm2a
+sizeX=3
+stride=2
+channels=128
+
+[pool2b]
+type=pool
+pool=max
+inputs=cnorm2b
+sizeX=3
+stride=2
+channels=128
+
+[pool2c]
+type=pool
+pool=max
+inputs=cnorm2c
+sizeX=3
+stride=2
+channels=128
+
+[pool2d]
+type=pool
+pool=max
+inputs=cnorm2d
+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
+
+[conv3c]
+type=conv
+inputs=pool2c,pool2d
+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=2
+
+[conv3d]
+type=conv
+inputs=pool2c,pool2d
+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=3
+
+[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
+
+[conv4c]
+type=conv
+inputs=conv3c
+filters=192
+padding=1
+stride=1
+filterSize=3
+channels=192
+neuron=relu
+initW=0.03
+initB=1
+partialSum=13
+sharedBiases=1
+
+[conv4d]
+type=conv
+inputs=conv3d
+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=64
+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=64
+padding=1
+stride=1
+filterSize=3
+channels=192
+initW=0.03
+initB=1
+partialSum=13
+groups=1
+randSparse=0
+
+[conv5c]
+type=conv
+inputs=conv4c
+filters=64
+padding=1
+stride=1
+filterSize=3
+channels=192
+initW=0.03
+initB=1
+partialSum=13
+groups=1
+randSparse=0
+
+[conv5d]
+type=conv
+inputs=conv4d
+filters=64
+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=64
+neuron=relu
+
+[pool3b]
+type=pool
+pool=max
+inputs=conv5b
+sizeX=3
+stride=2
+channels=64
+neuron=relu
+
+[pool3c]
+type=pool
+pool=max
+inputs=conv5c
+sizeX=3
+stride=2
+channels=64
+neuron=relu
+
+[pool3d]
+type=pool
+pool=max
+inputs=conv5d
+sizeX=3
+stride=2
+channels=64
+neuron=relu
+
+[fc1024-1a]
+type=fc
+inputs=pool3a,pool3b,pool3c,pool3d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=0
+
+[fc1024-1b]
+type=fc
+inputs=pool3a,pool3b,pool3c,pool3d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=1
+
+[fc1024-1c]
+type=fc
+inputs=pool3a,pool3b,pool3c,pool3d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=2
+
+[fc1024-1d]
+type=fc
+inputs=pool3a,pool3b,pool3c,pool3d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=3
+
+[hs1a]
+type=hs
+keep=0.5
+inputs=fc1024-1a
+
+[hs1b]
+type=hs
+keep=0.5
+inputs=fc1024-1b
+
+[hs1c]
+type=hs
+keep=0.5
+inputs=fc1024-1c
+
+[hs1d]
+type=hs
+keep=0.5
+inputs=fc1024-1d
+
+[fc1024-2a]
+type=fc
+inputs=hs1a,hs1b,hs1c,hs1d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=0
+
+[fc1024-2b]
+type=fc
+inputs=hs1a,hs1b,hs1c,hs1d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=1
+
+[fc1024-2c]
+type=fc
+inputs=hs1a,hs1b,hs1c,hs1d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=2
+
+[fc1024-2d]
+type=fc
+inputs=hs1a,hs1b,hs1c,hs1d
+outputs=1024
+initW=0.01,0.01,0.01,0.01
+initB=1
+neuron=relu
+gpu=3
+
+[hs2a]
+type=hs
+keep=0.5
+inputs=fc1024-2a
+
+[hs2b]
+type=hs
+keep=0.5
+inputs=fc1024-2b
+
+[hs2c]
+type=hs
+keep=0.5
+inputs=fc1024-2c
+
+[hs2d]
+type=hs
+keep=0.5
+inputs=fc1024-2d
+
+[fc1000]
+type=fc
+outputs=1000
+inputs=hs2a,hs2b,hs2c,hs2d
+initW=0.01,0.01,0.01,0.01
+gpu=1
+
+[probs]
+type=softmax
+inputs=fc1000
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs
+gpu=1