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Created September 9, 2016 22:17
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name: "SqueezeNet_Residual"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 227
mean_value: 104
mean_value: 117
mean_value: 123
}
data_param {
source: "/ssd/dataset/ilsvrc12_train_lmdb/"
batch_size: 32
backend: LMDB
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: false
crop_size: 227
mean_value: 104
mean_value: 117
mean_value: 123
}
data_param {
source: "/ssd/dataset/ilsvrc12_val_lmdb/"
batch_size: 50
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output: 96
kernel_size: 7
stride: 2
weight_filler {
type: "xavier"
}
}
}
layer {
name: "relu_conv1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fire2/squeeze1x1"
type: "Convolution"
bottom: "pool1"
top: "fire2/squeeze1x1"
convolution_param {
num_output: 16
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire2/relu_squeeze1x1"
type: "ReLU"
bottom: "fire2/squeeze1x1"
top: "fire2/squeeze1x1"
}
layer {
name: "fire2/expand1x1"
type: "Convolution"
bottom: "fire2/squeeze1x1"
top: "fire2/expand1x1"
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire2/relu_expand1x1"
type: "ReLU"
bottom: "fire2/expand1x1"
top: "fire2/expand1x1"
}
layer {
name: "fire2/expand3x3"
type: "Convolution"
bottom: "fire2/squeeze1x1"
top: "fire2/expand3x3"
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire2/relu_expand3x3"
type: "ReLU"
bottom: "fire2/expand3x3"
top: "fire2/expand3x3"
}
layer {
name: "fire2/concat"
type: "Concat"
bottom: "fire2/expand1x1"
bottom: "fire2/expand3x3"
top: "fire2/concat"
}
#fire2 ends: 128 channels
layer {
name: "fire3/squeeze1x1"
type: "Convolution"
bottom: "fire2/concat"
top: "fire3/squeeze1x1"
convolution_param {
num_output: 16
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire3/relu_squeeze1x1"
type: "ReLU"
bottom: "fire3/squeeze1x1"
top: "fire3/squeeze1x1"
}
layer {
name: "fire3/expand1x1"
type: "Convolution"
bottom: "fire3/squeeze1x1"
top: "fire3/expand1x1"
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire3/relu_expand1x1"
type: "ReLU"
bottom: "fire3/expand1x1"
top: "fire3/expand1x1"
}
layer {
name: "fire3/expand3x3"
type: "Convolution"
bottom: "fire3/squeeze1x1"
top: "fire3/expand3x3"
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire3/relu_expand3x3"
type: "ReLU"
bottom: "fire3/expand3x3"
top: "fire3/expand3x3"
}
layer {
name: "fire3/concat"
type: "Concat"
bottom: "fire3/expand1x1"
bottom: "fire3/expand3x3"
top: "fire3/concat"
}
#fire3 ends: 128 channels
layer {
name: "bypass_23"
type: "Eltwise"
bottom: "fire2/concat"
bottom: "fire3/concat"
top: "fire3_EltAdd"
}
layer {
name: "fire4/squeeze1x1"
type: "Convolution"
bottom: "fire3_EltAdd"
top: "fire4/squeeze1x1"
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire4/relu_squeeze1x1"
type: "ReLU"
bottom: "fire4/squeeze1x1"
top: "fire4/squeeze1x1"
}
layer {
name: "fire4/expand1x1"
type: "Convolution"
bottom: "fire4/squeeze1x1"
top: "fire4/expand1x1"
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire4/relu_expand1x1"
type: "ReLU"
bottom: "fire4/expand1x1"
top: "fire4/expand1x1"
}
layer {
name: "fire4/expand3x3"
type: "Convolution"
bottom: "fire4/squeeze1x1"
top: "fire4/expand3x3"
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire4/relu_expand3x3"
type: "ReLU"
bottom: "fire4/expand3x3"
top: "fire4/expand3x3"
}
layer {
name: "fire4/concat"
type: "Concat"
bottom: "fire4/expand1x1"
bottom: "fire4/expand3x3"
top: "fire4/concat"
}
#fire4 ends: 256 channels
layer {
name: "pool4"
type: "Pooling"
bottom: "fire4/concat"
top: "pool4"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
#fire4 ends: 256 channels / pooled
layer {
name: "fire5/squeeze1x1"
type: "Convolution"
bottom: "pool4"
top: "fire5/squeeze1x1"
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire5/relu_squeeze1x1"
type: "ReLU"
bottom: "fire5/squeeze1x1"
top: "fire5/squeeze1x1"
}
layer {
name: "fire5/expand1x1"
type: "Convolution"
bottom: "fire5/squeeze1x1"
top: "fire5/expand1x1"
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire5/relu_expand1x1"
type: "ReLU"
bottom: "fire5/expand1x1"
top: "fire5/expand1x1"
}
layer {
name: "fire5/expand3x3"
type: "Convolution"
bottom: "fire5/squeeze1x1"
top: "fire5/expand3x3"
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire5/relu_expand3x3"
type: "ReLU"
bottom: "fire5/expand3x3"
top: "fire5/expand3x3"
}
layer {
name: "fire5/concat"
type: "Concat"
bottom: "fire5/expand1x1"
bottom: "fire5/expand3x3"
top: "fire5/concat"
}
#fire5 ends: 256 channels
layer {
name: "bypass_45"
type: "Eltwise"
bottom: "pool4"
bottom: "fire5/concat"
top: "fire5_EltAdd"
}
layer {
name: "fire6/squeeze1x1"
type: "Convolution"
bottom: "fire5_EltAdd"
top: "fire6/squeeze1x1"
convolution_param {
num_output: 48
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire6/relu_squeeze1x1"
type: "ReLU"
bottom: "fire6/squeeze1x1"
top: "fire6/squeeze1x1"
}
layer {
name: "fire6/expand1x1"
type: "Convolution"
bottom: "fire6/squeeze1x1"
top: "fire6/expand1x1"
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire6/relu_expand1x1"
type: "ReLU"
bottom: "fire6/expand1x1"
top: "fire6/expand1x1"
}
layer {
name: "fire6/expand3x3"
type: "Convolution"
bottom: "fire6/squeeze1x1"
top: "fire6/expand3x3"
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire6/relu_expand3x3"
type: "ReLU"
bottom: "fire6/expand3x3"
top: "fire6/expand3x3"
}
layer {
name: "fire6/concat"
type: "Concat"
bottom: "fire6/expand1x1"
bottom: "fire6/expand3x3"
top: "fire6/concat"
}
#fire6 ends: 384 channels
layer {
name: "fire7/squeeze1x1"
type: "Convolution"
bottom: "fire6/concat"
top: "fire7/squeeze1x1"
convolution_param {
num_output: 48
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire7/relu_squeeze1x1"
type: "ReLU"
bottom: "fire7/squeeze1x1"
top: "fire7/squeeze1x1"
}
layer {
name: "fire7/expand1x1"
type: "Convolution"
bottom: "fire7/squeeze1x1"
top: "fire7/expand1x1"
convolution_param {
num_output: 192
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire7/relu_expand1x1"
type: "ReLU"
bottom: "fire7/expand1x1"
top: "fire7/expand1x1"
}
layer {
name: "fire7/expand3x3"
type: "Convolution"
bottom: "fire7/squeeze1x1"
top: "fire7/expand3x3"
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire7/relu_expand3x3"
type: "ReLU"
bottom: "fire7/expand3x3"
top: "fire7/expand3x3"
}
layer {
name: "fire7/concat"
type: "Concat"
bottom: "fire7/expand1x1"
bottom: "fire7/expand3x3"
top: "fire7/concat"
}
#fire7 ends: 384 channels
layer {
name: "bypass_67"
type: "Eltwise"
bottom: "fire6/concat"
bottom: "fire7/concat"
top: "fire7_EltAdd"
}
layer {
name: "fire8/squeeze1x1"
type: "Convolution"
bottom: "fire7_EltAdd"
top: "fire8/squeeze1x1"
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire8/relu_squeeze1x1"
type: "ReLU"
bottom: "fire8/squeeze1x1"
top: "fire8/squeeze1x1"
}
layer {
name: "fire8/expand1x1"
type: "Convolution"
bottom: "fire8/squeeze1x1"
top: "fire8/expand1x1"
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire8/relu_expand1x1"
type: "ReLU"
bottom: "fire8/expand1x1"
top: "fire8/expand1x1"
}
layer {
name: "fire8/expand3x3"
type: "Convolution"
bottom: "fire8/squeeze1x1"
top: "fire8/expand3x3"
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire8/relu_expand3x3"
type: "ReLU"
bottom: "fire8/expand3x3"
top: "fire8/expand3x3"
}
layer {
name: "fire8/concat"
type: "Concat"
bottom: "fire8/expand1x1"
bottom: "fire8/expand3x3"
top: "fire8/concat"
}
#fire8 ends: 512 channels
layer {
name: "pool8"
type: "Pooling"
bottom: "fire8/concat"
top: "pool8"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
#fire8 ends: 512 channels
layer {
name: "fire9/squeeze1x1"
type: "Convolution"
bottom: "pool8"
top: "fire9/squeeze1x1"
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire9/relu_squeeze1x1"
type: "ReLU"
bottom: "fire9/squeeze1x1"
top: "fire9/squeeze1x1"
}
layer {
name: "fire9/expand1x1"
type: "Convolution"
bottom: "fire9/squeeze1x1"
top: "fire9/expand1x1"
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire9/relu_expand1x1"
type: "ReLU"
bottom: "fire9/expand1x1"
top: "fire9/expand1x1"
}
layer {
name: "fire9/expand3x3"
type: "Convolution"
bottom: "fire9/squeeze1x1"
top: "fire9/expand3x3"
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: "xavier"
}
}
}
layer {
name: "fire9/relu_expand3x3"
type: "ReLU"
bottom: "fire9/expand3x3"
top: "fire9/expand3x3"
}
layer {
name: "fire9/concat"
type: "Concat"
bottom: "fire9/expand1x1"
bottom: "fire9/expand3x3"
top: "fire9/concat"
}
#fire9 ends: 512 channels
layer {
name: "bypass_89"
type: "Eltwise"
bottom: "pool8"
bottom: "fire9/concat"
top: "fire9_EltAdd"
}
layer {
name: "drop9"
type: "Dropout"
bottom: "fire9_EltAdd"
top: "fire9_EltAdd"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "conv10"
type: "Convolution"
bottom: "fire9_EltAdd"
top: "conv10"
convolution_param {
num_output: 1000
pad: 1
kernel_size: 1
weight_filler {
type: "gaussian"
mean: 0.0
std: 0.01
}
}
}
layer {
name: "relu_conv10"
type: "ReLU"
bottom: "conv10"
top: "conv10"
}
layer {
name: "pool10"
type: "Pooling"
bottom: "conv10"
top: "pool10"
pooling_param {
pool: AVE
global_pooling: true
}
}
# loss, top1, top5
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "pool10"
bottom: "label"
top: "loss"
include {
# phase: TRAIN
}
}
layer {
name: "accuracy_top1"
type: "Accuracy"
bottom: "pool10"
bottom: "label"
top: "accuracy_top1"
include {
# phase: TEST
}
accuracy_param {
top_k: 1
}
}
layer {
name: "accuracy_top5"
type: "Accuracy"
bottom: "pool10"
bottom: "label"
top: "accuracy_top5"
include {
# phase: TEST
}
accuracy_param {
top_k: 5
}
}
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