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removed the net proto test that relies on external data
[platform/upstream/caffeonacl.git]
/
examples
/
imagenet.prototxt
1
name: "CaffeNet"
2
layers {
3
layer {
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name: "data"
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type: "data"
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source: "/home/jiayq/caffe-train-leveldb"
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batchsize: 128
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subtraction: 114
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cropsize: 227
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mirror: true
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}
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top: "data"
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top: "label"
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}
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layers {
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layer {
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name: "conv1"
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type: "conv"
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num_output: 96
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kernelsize: 11
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stride: 4
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "data"
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top: "conv1"
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}
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layers {
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layer {
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name: "relu1"
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type: "relu"
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}
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bottom: "conv1"
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top: "relu1"
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}
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layers {
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layer {
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name: "pool1"
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type: "pool"
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pool: MAX
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kernelsize: 3
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stride: 2
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}
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bottom: "relu1"
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top: "pool1"
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}
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layers {
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layer {
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name: "norm1"
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type: "lrn"
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local_size: 5
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alpha: 0.0001
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beta: 0.75
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}
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bottom: "pool1"
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top: "norm1"
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}
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layers {
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layer {
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name: "pad2"
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type: "padding"
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pad: 2
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}
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bottom: "norm1"
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top: "pad2"
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}
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layers {
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layer {
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name: "conv2"
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type: "conv"
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num_output: 256
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group: 2
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kernelsize: 5
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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value: 1
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "pad2"
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top: "conv2"
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}
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layers {
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layer {
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name: "relu2"
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type: "relu"
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}
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bottom: "conv2"
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top: "relu2"
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}
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layers {
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layer {
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name: "pool2"
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type: "pool"
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pool: MAX
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kernelsize: 3
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stride: 2
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}
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bottom: "relu2"
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top: "pool2"
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}
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layers {
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layer {
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name: "norm2"
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type: "lrn"
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local_size: 5
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alpha: 0.0001
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beta: 0.75
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}
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bottom: "pool2"
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top: "norm2"
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}
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layers {
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layer {
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name: "pad3"
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type: "padding"
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pad: 1
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}
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bottom: "norm2"
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top: "pad3"
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}
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layers {
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layer {
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name: "conv3"
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type: "conv"
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num_output: 384
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kernelsize: 3
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "pad3"
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top: "conv3"
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}
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layers {
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layer {
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name: "relu3"
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type: "relu"
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}
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bottom: "conv3"
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top: "relu3"
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}
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layers {
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layer {
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name: "pad4"
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type: "padding"
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pad: 1
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}
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bottom: "relu3"
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top: "pad4"
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}
172
layers {
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layer {
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name: "conv4"
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type: "conv"
176
num_output: 384
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group: 2
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kernelsize: 3
179
weight_filler {
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type: "gaussian"
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std: 0.01
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}
183
bias_filler {
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type: "constant"
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value: 1
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "pad4"
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top: "conv4"
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}
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layers {
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layer {
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name: "relu4"
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type: "relu"
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}
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bottom: "conv4"
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top: "relu4"
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}
201
layers {
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layer {
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name: "pad5"
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type: "padding"
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pad: 1
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}
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bottom: "relu4"
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top: "pad5"
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}
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layers {
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layer {
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name: "conv5"
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type: "conv"
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num_output: 256
215
group: 2
216
kernelsize: 3
217
weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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value: 1
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "pad5"
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top: "conv5"
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}
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layers {
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layer {
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name: "relu5"
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type: "relu"
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}
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bottom: "conv5"
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top: "relu5"
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}
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layers {
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layer {
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name: "pool5"
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type: "pool"
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kernelsize: 3
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pool: MAX
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stride: 2
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}
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bottom: "relu5"
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top: "pool5"
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}
250
layers {
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layer {
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name: "fc6"
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type: "innerproduct"
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num_output: 4096
255
weight_filler {
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type: "gaussian"
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std: 0.005
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}
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bias_filler {
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type: "constant"
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value: 1
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "pool5"
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top: "fc6"
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}
269
layers {
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layer {
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name: "relu6"
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type: "relu"
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}
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bottom: "fc6"
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top: "relu6"
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}
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layers {
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layer {
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name: "drop6"
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type: "dropout"
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dropout_ratio: 0.5
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}
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bottom: "relu6"
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top: "drop6"
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}
286
layers {
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layer {
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name: "fc7"
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type: "innerproduct"
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num_output: 4096
291
weight_filler {
292
type: "gaussian"
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std: 0.005
294
}
295
bias_filler {
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type: "constant"
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value: 1
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "drop6"
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top: "fc7"
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}
305
layers {
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layer {
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name: "relu7"
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type: "relu"
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}
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bottom: "fc7"
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top: "relu7"
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}
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layers {
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layer {
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name: "drop7"
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type: "dropout"
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dropout_ratio: 0.5
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}
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bottom: "relu7"
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top: "drop7"
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}
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layers {
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layer {
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name: "fc8"
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type: "innerproduct"
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num_output: 1000
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
331
bias_filler {
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type: "constant"
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value: 0
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}
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blobs_lr: 1.
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blobs_lr: 2.
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}
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bottom: "drop7"
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top: "fc8"
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}
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layers {
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layer {
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name: "loss"
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type: "softmax_loss"
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}
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bottom: "fc8"
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bottom: "label"
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}