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Simplify input scaling on LeNet network #976

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Aug 22, 2016
Merged

Simplify input scaling on LeNet network #976

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d4f80a6
Simplify input scaling on LeNet network
mpbrigham Aug 15, 2016
2c40306
Scaling factor update for LeNet Torch
mpbrigham Aug 15, 2016
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17 changes: 4 additions & 13 deletions digits/standard-networks/caffe/lenet.prototxt
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Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,8 @@ name: "LeNet"
layer {
name: "train-data"
type: "Data"
top: "scaled"
top: "data"
top: "label"
transform_param {
# 1/(standard deviation)
scale: 0.0125
}
data_param {
batch_size: 64
}
Expand All @@ -17,28 +13,23 @@ layer {
layer {
name: "val-data"
type: "Data"
top: "scaled"
top: "data"
top: "label"
transform_param {
# 1/(standard deviation)
scale: 0.0125
}
data_param {
batch_size: 32
}
include { stage: "val" }
}
layer {
# Use Power layer in deploy phase for input scaling
# Use Power layer for input scaling
name: "scale"
bottom: "data"
top: "scaled"
type: "Power"
power_param {
# 1/(standard deviation)
# 1/(standard deviation on MNIST dataset)
scale: 0.0125
}
include { stage: "deploy" }
}
layer {
name: "conv1"
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2 changes: 1 addition & 1 deletion digits/standard-networks/torch/lenet.lua
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Expand Up @@ -33,7 +33,7 @@ return function(params)
-- -- This is a LeNet model. For more information: http://yann.lecun.com/exdb/lenet/

local lenet = nn.Sequential()
lenet:add(nn.MulConstant(0.00390625))
lenet:add(nn.MulConstant(0.0125)) -- 1/(standard deviation on MNIST dataset)
lenet:add(backend.SpatialConvolution(channels,20,5,5,1,1,0)) -- channels*28*28 -> 20*24*24
lenet:add(backend.SpatialMaxPooling(2, 2, 2, 2)) -- 20*24*24 -> 20*12*12
lenet:add(backend.SpatialConvolution(20,50,5,5,1,1,0)) -- 20*12*12 -> 50*8*8
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