[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

[rnorm1a]
type=cmrnorm
inputs=conv1a
channels=48
size=5

[pool1a]
type=pool
pool=max
inputs=rnorm1a
sizeX=3
stride=2
channels=48
neuron=relu

[conv2a]
type=conv
inputs=pool1a
filters=128
padding=2
stride=1
filterSize=5
channels=48
initW=0.01
initB=1
partialSum=3
sharedBiases=1
neuron=relu
gpu=0

[rnorm2a]
type=cmrnorm
inputs=conv2a
channels=128
size=5

[cnorm2a]
type=rnorm
inputs=rnorm2a
channels=128
size=5

[pool2a]
type=pool
pool=max
inputs=cnorm2a
sizeX=3
stride=2
channels=128

[conv3a]
type=conv
inputs=pool2a
filters=192
padding=1
stride=1
filterSize=3
channels=128
initW=0.03
partialSum=13
sharedBiases=1
neuron=relu
gpu=0

[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

[conv5a]
type=conv
inputs=conv4a
filters=256
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=256
neuron=relu

[fc4096a]
type=fc
inputs=pool3a
outputs=4096
initW=0.01
initB=1
neuron=relu
gpu=0

[hs1a]
type=hs
keep=0.5
inputs=fc4096a

[fc4096ba]
type=fc
inputs=hs1a
outputs=4096
initW=0.01
initB=1
neuron=relu
gpu=0

[hs2a]
type=hs
keep=0.5
inputs=fc4096ba

[fc1000]
type=fc
outputs=1000
inputs=hs2a
initW=0.01
gpu=0

[probs]
type=softmax
inputs=fc1000

[logprob]
type=cost.logreg
inputs=labels,probs
gpu=0