308 lines
3 KiB
INI
308 lines
3 KiB
INI
[data]
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type=data
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dataIdx=0
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[labels]
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type=data
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dataIdx=1
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[conv1a]
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type=conv
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inputs=data
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channels=3
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filters=48
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padding=0
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stride=4
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filterSize=11
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initW=0.01
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partialSum=11
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sharedBiases=1
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gpu=0
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[conv1b]
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type=conv
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inputs=data
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channels=3
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filters=48
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padding=0
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stride=4
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filterSize=11
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initW=0.01
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partialSum=11
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sharedBiases=1
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gpu=1
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[rnorm1a]
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type=cmrnorm
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inputs=conv1a
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channels=48
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size=5
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[rnorm1b]
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type=cmrnorm
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inputs=conv1b
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channels=48
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size=5
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[pool1a]
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type=pool
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pool=max
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inputs=rnorm1a
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sizeX=3
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stride=2
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channels=48
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neuron=relu
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[pool1b]
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type=pool
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pool=max
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inputs=rnorm1b
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sizeX=3
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stride=2
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channels=48
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neuron=relu
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[conv2a]
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type=conv
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inputs=pool1a
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filters=128
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padding=2
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stride=1
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filterSize=5
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channels=48
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initW=0.01
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initB=1
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partialSum=9
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sharedBiases=1
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neuron=relu
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gpu=0
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[conv2b]
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type=conv
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inputs=pool1b
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filters=128
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padding=2
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stride=1
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filterSize=5
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channels=48
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initW=0.01
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initB=1
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partialSum=9
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sharedBiases=1
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neuron=relu
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gpu=1
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[rnorm2a]
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type=cmrnorm
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inputs=conv2a
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channels=128
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size=5
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[rnorm2b]
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type=cmrnorm
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inputs=conv2b
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channels=128
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size=5
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[cnorm2a]
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type=rnorm
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inputs=rnorm2a
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channels=128
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size=5
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[cnorm2b]
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type=rnorm
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inputs=rnorm2b
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channels=128
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size=5
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[pool2a]
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type=pool
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pool=max
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inputs=cnorm2a
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sizeX=3
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stride=2
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channels=128
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[pool2b]
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type=pool
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pool=max
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inputs=cnorm2b
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sizeX=3
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stride=2
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channels=128
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[conv3a]
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type=conv
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inputs=pool2a,pool2b
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filters=192,192
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padding=1,1
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stride=1,1
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filterSize=3,3
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channels=128,128
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initW=0.03,0.03
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partialSum=13
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sharedBiases=1
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neuron=relu
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gpu=0
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[conv3b]
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type=conv
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inputs=pool2a,pool2b
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filters=192,192
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padding=1,1
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stride=1,1
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filterSize=3,3
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channels=128,128
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initW=0.03,0.03
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partialSum=13
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sharedBiases=1
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neuron=relu
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gpu=1
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[conv4a]
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type=conv
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inputs=conv3a
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filters=192
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padding=1
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stride=1
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filterSize=3
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channels=192
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neuron=relu
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initW=0.03
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initB=1
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partialSum=13
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sharedBiases=1
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[conv4b]
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type=conv
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inputs=conv3b
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filters=192
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padding=1
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stride=1
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filterSize=3
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channels=192
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neuron=relu
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initW=0.03
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initB=1
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partialSum=13
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sharedBiases=1
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[conv5a]
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type=conv
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inputs=conv4a
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filters=128
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padding=1
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stride=1
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filterSize=3
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channels=192
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initW=0.03
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initB=1
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partialSum=13
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groups=1
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randSparse=0
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[conv5b]
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type=conv
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inputs=conv4b
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filters=128
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padding=1
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stride=1
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filterSize=3
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channels=192
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initW=0.03
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initB=1
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partialSum=13
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groups=1
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randSparse=0
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[pool3a]
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type=pool
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pool=max
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inputs=conv5a
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sizeX=3
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stride=2
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channels=128
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neuron=relu
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[pool3b]
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type=pool
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pool=max
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inputs=conv5b
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sizeX=3
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stride=2
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channels=128
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neuron=relu
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[fc2048a]
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type=fc
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inputs=pool3a,pool3b
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outputs=2048
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initW=0.01,0.01
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initB=1
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neuron=relu
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gpu=0
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[fc2048b]
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type=fc
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inputs=pool3a,pool3b
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outputs=2048
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initW=0.01,0.01
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initB=1
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neuron=relu
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gpu=1
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[hs1a]
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type=hs
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keep=0.5
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inputs=fc2048a
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[hs1b]
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type=hs
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keep=0.5
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inputs=fc2048b
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[fc2048ba]
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type=fc
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inputs=hs1a,hs1b
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outputs=2048
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initW=0.01,0.01
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initB=1
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neuron=relu
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gpu=0
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[fc2048bb]
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type=fc
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inputs=hs1b,hs1a
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outputs=2048
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initW=0.01,0.01
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initB=1
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neuron=relu
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gpu=1
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[hs2a]
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type=hs
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keep=0.5
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inputs=fc2048ba
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[hs2b]
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type=hs
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keep=0.5
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inputs=fc2048bb
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[fc1000]
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type=fc
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outputs=1000
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inputs=hs2a,hs2b
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initW=0.01,0.01
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gpu=0
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[probs]
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type=softmax
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inputs=fc1000
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[logprob]
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type=cost.logreg
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inputs=labels,probs
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gpu=0
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