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squeezenet 1.1
# please cite:
# @article{SqueezeNet,
# Author = {Forrest N. Iandola and Matthew W. Moskewicz and Khalid Ashraf and Song Han and William J. Dally and Kurt Keutzer},
# Title = {SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $<$1MB model size},
# Journal = {arXiv:1602.07360},
# Year = {2016}
# }
name: "SqueezeNet_1.1"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
crop_size: 227
mean_value: 104
mean_value: 117
mean_value: 123
}
data_param {
source: "examples/imagenet/ilsvrc12_train_lmdb"
batch_size: 32
backend: LMDB
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
crop_size: 227
mean_value: 104
mean_value: 117
mean_value: 123
}
data_param {
source: "examples/imagenet/ilsvrc12_val_lmdb"
batch_size: 25 #not *iter_size
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output: 64
kernel_size: 3
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"
}
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"
}
layer {
name: "pool3"
type: "Pooling"
bottom: "fire3/concat"
top: "pool3"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fire4/squeeze1x1"
type: "Convolution"
bottom: "pool3"
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"
}
layer {
name: "fire5/squeeze1x1"
type: "Convolution"
bottom: "fire4/concat"
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"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "fire5/concat"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fire6/squeeze1x1"
type: "Convolution"
bottom: "pool5"
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"
}
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"
}
layer {
name: "fire8/squeeze1x1"
type: "Convolution"
bottom: "fire7/concat"
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"
}
layer {
name: "fire9/squeeze1x1"
type: "Convolution"
bottom: "fire8/concat"
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"
}
layer {
name: "drop9"
type: "Dropout"
bottom: "fire9/concat"
top: "fire9/concat"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "conv10"
type: "Convolution"
bottom: "fire9/concat"
top: "conv10"
convolution_param {
num_output: 1000
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
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "pool10"
bottom: "label"
top: "loss"
#include {
# phase: TRAIN
#}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "pool10"
bottom: "label"
top: "accuracy"
#include {
# phase: TEST
#}
}
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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