Initial commit

example-layers/layer-params-18pct.cfg

@@ -0,0 +1,35 @@
+# 18% error on CIFAR-10 in 20 minutes - layer definition file 
+
+# Reduce all learning rates by factor of 10 after 120 epochs.
+# Then another factor of 10 after 10 more epochs.
+
+[conv1]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[conv2]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[conv3]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[fc10]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=1
+
+[logprob]
+coeff=1

example-layers/layer-params-19pct.cfg

@@ -0,0 +1,33 @@
+# 19% error on CIFAR-10 in 20 minutes - layer parameter file 
+# Set wc to 0 for translations -- 14.2%
+
+[conv1]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[conv2]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[conv3]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[fc10]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=3
+
+[logprob]
+coeff=1

example-layers/layer-params-80sec.cfg

@@ -0,0 +1,39 @@
+# 26% error on CIFAR-10 in 80 seconds - layer parameter file 
+
+[conv1]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[conv2]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[conv3]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[fc64]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=.03
+
+[fc10]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=.03
+
+[logprob]
+coeff=1

example-layers/layer-params-conv-local-12pct.cfg

@@ -0,0 +1,40 @@
+# 12% error on CIFAR-10 - layer parameter file 
+# See methodology: http://code.google.com/p/cuda-convnet/wiki/Methodology
+
+[conv1]
+epsW=0.00001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.00
+
+[conv2]
+epsW=0.00001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.00
+
+[local3]
+epsW=0.00001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[local4]
+epsW=0.00001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[fc10]
+epsW=0.00001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[logprob]
+coeff=1

example-layers/layer-params-conv-local-13pct.cfg

@@ -0,0 +1,40 @@
+# 13% error on CIFAR-10 - layer parameter file 
+# See methodology: http://code.google.com/p/cuda-convnet/wiki/Methodology
+
+[conv1]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.00
+
+[conv2]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.00
+
+[local3]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[local4]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[fc10]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0.004
+
+[logprob]
+coeff=1

example-layers/layer-params-example.cfg

@@ -0,0 +1,44 @@
+[conv32]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[local32]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[fc1024]
+momW=0.9
+momB=0.9
+epsW=0.00001
+epsB=0.00002
+wc=0
+
+[conv32-2]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[conv32-3]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[fc10]
+epsW=0.0001,0.001
+epsB=0.002
+momW=0.5,0.9
+momB=0.9
+wc=0,0
+
+[logprob]
+coeff=1

example-layers/layer-params.gc.cfg

@@ -0,0 +1,66 @@
+[conv32a]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[conv32b]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[conv32c]
+epsW=0.001
+epsB=0.002
+momW=0.9
+momB=0.9
+wc=0
+
+[fc10]
+wc=0
+momB=0
+momW=0
+epsW=0.00001
+epsB=0.00002
+
+[fc16a]
+wc=0,0,0
+momB=0
+momW=0,0,0
+epsW=0.00001,0.1,0.1
+epsB=0.00002
+
+[fc16b]
+wc=0,0,0
+momB=0
+momW=0,0,0
+epsW=0.00001,0.1,0.1
+epsB=0.00002
+
+[fc16c]
+wc=0,0,0
+momB=0
+momW=0,0,0
+epsW=0.00001,0.1,0.1
+epsB=0.00002
+
+[logreg]
+coeff=1
+
+[rnorm1a]
+scale=0.0001
+pow=0.75
+minDiv=0.25
+
+[rnorm1b]
+scale=0.0001
+pow=0.75
+minDiv=0.25
+
+[rnorm1c]
+scale=0.0001
+pow=0.75
+minDiv=0.25

example-layers/layers-18pct.cfg

@@ -0,0 +1,109 @@
+# 18% error on CIFAR-10 in 20 minutes - layer definition file 
+
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv1]
+type=conv
+inputs=data
+channels=3
+filters=32
+padding=2
+stride=1
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=4
+sharedBiases=1
+
+[pool1]
+type=pool
+pool=max
+inputs=conv1
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=32
+
+[rnorm1]
+type=rnorm
+inputs=pool1
+channels=32
+sizeX=3
+scale=0.00005
+pow=.75
+
+[conv2]
+type=conv
+inputs=rnorm1
+filters=32
+padding=2
+stride=1
+filterSize=5
+channels=32
+neuron=relu
+initW=0.01
+partialSum=4
+sharedBiases=1
+
+[pool2]
+type=pool
+pool=avg
+inputs=conv2
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=32
+
+[rnorm2]
+type=rnorm
+inputs=pool2
+channels=32
+sizeX=3
+scale=0.00005
+pow=.75
+
+[conv3]
+type=conv
+inputs=rnorm2
+filters=64
+padding=2
+stride=1
+filterSize=5
+channels=32
+neuron=relu
+initW=0.01
+partialSum=4
+sharedBiases=1
+
+[pool3]
+type=pool
+pool=avg
+inputs=conv3
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[fc10]
+type=fc
+outputs=10
+inputs=pool3
+initW=0.01
+neuron=ident
+
+[probs]
+type=softmax
+inputs=fc10
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs

example-layers/layers-19pct.cfg

@@ -0,0 +1,93 @@
+# 19% error on CIFAR-10 in 20 minutes - layer definition file 
+
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv1]
+type=conv
+inputs=data
+channels=3
+filters=32
+padding=2
+stride=1
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=1
+sharedBiases=1
+
+[pool1]
+type=pool
+pool=max
+inputs=conv1
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=32
+
+[conv2]
+type=conv
+inputs=pool1
+filters=32
+padding=2
+stride=1
+filterSize=5
+channels=32
+neuron=relu
+initW=0.01
+partialSum=1
+sharedBiases=1
+
+[pool2]
+type=pool
+pool=avg
+inputs=conv2
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=32
+
+[conv3]
+type=conv
+inputs=pool2
+filters=64
+padding=2
+stride=1
+filterSize=5
+channels=32
+neuron=relu
+initW=0.01
+partialSum=1
+sharedBiases=1
+
+[pool3]
+type=pool
+pool=avg
+inputs=conv3
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[fc10]
+type=fc
+outputs=10
+inputs=pool3
+initW=0.01
+neuron=ident
+
+[probs]
+type=softmax
+inputs=fc10
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs

example-layers/layers-80sec.cfg

@@ -0,0 +1,100 @@
+# 26% error on CIFAR-10 in 80 seconds - layer definition file 
+
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv1]
+type=conv
+inputs=data
+channels=3
+filters=32
+padding=2
+stride=1
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=4
+sharedBiases=1
+
+[pool1]
+type=pool
+pool=max
+inputs=conv1
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=32
+
+[conv2]
+type=conv
+inputs=pool1
+filters=32
+padding=2
+stride=1
+filterSize=5
+channels=32
+neuron=relu
+initW=0.01
+partialSum=4
+sharedBiases=1
+
+[pool2]
+type=pool
+pool=avg
+inputs=conv2
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=32
+
+[conv3]
+type=conv
+inputs=pool2
+filters=64
+padding=2
+stride=1
+filterSize=5
+channels=32
+neuron=relu
+initW=0.01
+partialSum=4
+sharedBiases=1
+
+[pool3]
+type=pool
+pool=avg
+inputs=conv3
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[fc64]
+type=fc
+outputs=64
+inputs=pool3
+initW=0.1
+neuron=relu
+
+[fc10]
+type=fc
+outputs=10
+inputs=fc64
+initW=0.1
+neuron=ident
+
+[probs]
+type=softmax
+inputs=fc10
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs

example-layers/layers-conv-local-12pct.cfg

@@ -0,0 +1,92 @@
+# 19% error on CIFAR-10 in 20 minutes - layer definition file 
+
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv1]
+type=conv
+inputs=data
+channels=3
+filters=64
+padding=2
+stride=1
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=4
+sharedBiases=1
+
+[pool1]
+type=pool
+pool=max
+inputs=conv1
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[conv2]
+type=conv
+inputs=pool1
+filters=64
+padding=2
+stride=1
+filterSize=5
+channels=64
+neuron=relu
+initW=0.01
+partialSum=8
+sharedBiases=1
+
+[pool2]
+type=pool
+pool=max
+inputs=conv2
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[local3]
+type=local
+inputs=pool2
+filters=32
+padding=1
+stride=1
+filterSize=3
+channels=64
+neuron=relu
+initW=0.04
+
+[local4]
+type=local
+inputs=local3
+filters=32
+padding=1
+stride=1
+filterSize=3
+channels=32
+neuron=relu
+initW=0.04
+
+[fc10]
+type=fc
+outputs=10
+inputs=local4
+initW=0.01
+neuron=ident
+
+[probs]
+type=softmax
+inputs=fc10
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs

example-layers/layers-conv-local-13pct.cfg

@@ -0,0 +1,93 @@
+# 13% error on CIFAR-10 in 20 minutes - layer definition file 
+# See methodology: http://code.google.com/p/cuda-convnet/wiki/Methodology
+
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv1]
+type=conv
+inputs=data
+channels=3
+filters=64
+padding=2
+stride=1
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=4
+sharedBiases=1
+
+[pool1]
+type=pool
+pool=max
+inputs=conv1
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[conv2]
+type=conv
+inputs=pool1
+filters=64
+padding=2
+stride=1
+filterSize=5
+channels=64
+neuron=relu
+initW=0.01
+partialSum=8
+sharedBiases=1
+
+[pool2]
+type=pool
+pool=max
+inputs=conv2
+start=0
+sizeX=3
+stride=2
+outputsX=0
+channels=64
+
+[local3]
+type=local
+inputs=pool2
+filters=32
+padding=1
+stride=1
+filterSize=3
+channels=64
+neuron=relu
+initW=0.04
+
+[local4]
+type=local
+inputs=local3
+filters=32
+padding=1
+stride=1
+filterSize=3
+channels=32
+neuron=relu
+initW=0.04
+
+[fc10]
+type=fc
+outputs=10
+inputs=local4
+initW=0.01
+neuron=ident
+
+[probs]
+type=softmax
+inputs=fc10
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs

example-layers/layers-example.cfg

@@ -0,0 +1,115 @@
+# This is a layer configuration file that contains all the 
+# layer types supported by this code. It's not actually good for anything
+# other than demonstrating how layers are specified and connected to one another.
+
+# Note: this file has gotten so big that the resultant net will not run on anything short of a 3GB GTX 580.
+# But there's no particular reason to run the net specified by this file. It's not actually good.
+
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv32]
+type=conv
+inputs=data
+channels=3
+filters=32
+padding=4
+stride=1
+filterSize=9
+neuron=logistic
+initW=0.00001
+partialSum=1
+sharedBiases=true
+
+[local32]
+type=local
+inputs=conv32
+channels=32
+filters=32
+padding=4
+stride=1
+filterSize=9
+neuron=logistic
+initW=0.00001
+
+[fc1024]
+type=fc
+outputs=1024
+inputs=data
+initW=0.001
+neuron=relu
+
+[maxpool]
+type=pool
+pool=max
+inputs=local32
+start=0
+sizeX=4
+stride=2
+outputsX=0
+channels=32
+
+[rnorm1]
+type=rnorm
+inputs=maxpool
+channels=32
+sizeX=5
+scale=0.0000125
+pow=0.75
+
+[cnorm1]
+type=cnorm
+inputs=rnorm1
+channels=32
+sizeX=7
+scale=0.001
+pow=0.5
+
+[conv32-2]
+type=conv
+inputs=cnorm1
+groups=4
+channels=32
+filters=32
+padding=2
+stride=1
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=1
+sharedBiases=false
+
+[conv32-3]
+type=conv
+inputs=conv32-2
+groups=4
+channels=128
+filters=32
+padding=2
+stride=2
+filterSize=5
+neuron=relu
+initW=0.0001
+partialSum=1
+randSparse=true
+filterChannels=64
+
+[fc10]
+type=fc
+outputs=10
+inputs=conv32-3,fc1024
+initW=0.0001,0.0001
+neuron=ident
+
+[probs]
+type=softmax
+inputs=fc10
+
+[logprob]
+type=cost.logreg
+inputs=labels,probs

example-layers/layers.gc.cfg

@@ -0,0 +1,112 @@
+[data]
+type=data
+dataIdx=0
+
+[labels]
+type=data
+dataIdx=1
+
+[conv32a]
+type=conv
+inputs=data
+filters=16
+padding=0
+stride=1
+filterSize=3
+channels=3
+neuron=relu
+initW=0.3
+initB=1
+partialSum=1
+sharedBiases=true
+gpu=0
+
+[conv32b]
+type=conv
+inputs=data
+filters=16
+padding=0
+stride=1
+filterSize=3
+channels=3
+neuron=relu
+initW=0.3
+initB=1
+partialSum=1
+sharedBiases=true
+gpu=1
+
+[conv32c]
+type=conv
+inputs=data
+filters=16
+padding=0
+stride=1
+filterSize=3
+channels=3
+neuron=relu
+initW=0.3
+initB=1
+partialSum=1
+sharedBiases=true
+gpu=2
+
+[rnorm1a]
+type=cmrnorm
+inputs=conv32a
+channels=16
+size=5
+
+[rnorm1b]
+type=cmrnorm
+inputs=conv32b
+channels=16
+size=5
+
+[rnorm1c]
+type=cmrnorm
+inputs=conv32c
+channels=16
+size=5
+
+[fc16a]
+type=fc
+outputs=16
+inputs=rnorm1a,rnorm1b,rnorm1c
+initW=0.1,0.1,0.1
+gpu=0
+
+[fc16b]
+type=fc
+outputs=16
+inputs=rnorm1b,rnorm1c,rnorm1a
+initW=0.1,0.1,0.1
+gpu=1
+
+[fc16c]
+type=fc
+outputs=16
+inputs=rnorm1c,rnorm1a,rnorm1a
+initW=0.1,0.1,0.1
+gpu=2
+
+[concat]
+type=concat
+inputs=fc16a,fc16c,fc16b
+
+[fc10]
+type=fc
+inputs=concat
+outputs=10
+initW=0.08
+gpu=0
+
+[probs]
+type=softmax
+inputs=fc10
+gpu=0
+
+[logreg]
+type=cost.logreg
+inputs=labels,probs
+gpu=0