Created
May 10, 2018 01:40
-
-
Save northeastsquare/cbb29c2086bf079da666ba1f5568f467 to your computer and use it in GitHub Desktop.
shufflenetSimple1
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
name: "shufflenet" | |
layer { | |
name: "data" | |
type: "Data" | |
top: "data" | |
top: "label" | |
include { | |
phase: TRAIN | |
} | |
data_param { | |
source: "/u02/xchen/char/ImageData/char/gray/lmdb128train/" | |
batch_size: 256 | |
backend: LMDB | |
} | |
} | |
layer { | |
name: "data" | |
type: "Data" | |
top: "data" | |
top: "label" | |
include { | |
phase: TEST | |
} | |
data_param { | |
source: "/u02/xchen/char/ImageData/char/gray/lmdb128val/" | |
batch_size: 1 | |
backend: LMDB | |
} | |
} | |
layer { | |
name: "conv1" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1" | |
convolution_param { | |
num_output: 24 | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv1_bn" | |
type: "BatchNorm" | |
bottom: "conv1" | |
top: "conv1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv1_scale" | |
bottom: "conv1" | |
top: "conv1" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "conv1_relu" | |
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: "resx1_match_conv" | |
type: "Pooling" | |
bottom: "pool1" | |
top: "resx1_match_conv" | |
pooling_param { | |
pool: AVE | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "resx1_conv1" | |
type: "Convolution" | |
bottom: "pool1" | |
top: "resx1_conv1" | |
convolution_param { | |
num_output: 54 | |
kernel_size: 1 | |
stride: 1 | |
pad: 0 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx1_conv1_bn" | |
type: "BatchNorm" | |
bottom: "resx1_conv1" | |
top: "resx1_conv1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx1_conv1_scale" | |
bottom: "resx1_conv1" | |
top: "resx1_conv1" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx1_conv1_relu" | |
type: "ReLU" | |
bottom: "resx1_conv1" | |
top: "resx1_conv1" | |
} | |
layer { | |
name: "resx1_conv2" | |
type: "ConvolutionDepthwise" | |
bottom: "resx1_conv1" | |
top: "resx1_conv2" | |
convolution_param { | |
num_output: 54 | |
kernel_size: 3 | |
stride: 2 | |
pad: 1 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx1_conv2_bn" | |
type: "BatchNorm" | |
bottom: "resx1_conv2" | |
top: "resx1_conv2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx1_conv2_scale" | |
bottom: "resx1_conv2" | |
top: "resx1_conv2" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx1_conv3" | |
type: "Convolution" | |
bottom: "resx1_conv2" | |
top: "resx1_conv3" | |
convolution_param { | |
num_output: 216 | |
kernel_size: 1 | |
stride: 1 | |
pad: 0 | |
group: 3 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx1_conv3_bn" | |
type: "BatchNorm" | |
bottom: "resx1_conv3" | |
top: "resx1_conv3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx1_conv3_scale" | |
bottom: "resx1_conv3" | |
top: "resx1_conv3" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx1_concat" | |
type: "Concat" | |
bottom: "resx1_match_conv" | |
bottom: "resx1_conv3" | |
top: "resx1_concat" | |
} | |
layer { | |
name: "resx1_concat_relu" | |
type: "ReLU" | |
bottom: "resx1_concat" | |
top: "resx1_concat" | |
} | |
layer { | |
name: "resx5_match_conv" | |
type: "Pooling" | |
bottom: "resx1_concat" | |
top: "resx5_match_conv" | |
pooling_param { | |
pool: AVE | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "resx5_conv1" | |
type: "Convolution" | |
bottom: "resx1_concat" | |
top: "resx5_conv1" | |
convolution_param { | |
num_output: 60 | |
kernel_size: 1 | |
stride: 1 | |
pad: 0 | |
group: 3 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx5_conv1_bn" | |
type: "BatchNorm" | |
bottom: "resx5_conv1" | |
top: "resx5_conv1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx5_conv1_scale" | |
bottom: "resx5_conv1" | |
top: "resx5_conv1" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx5_conv1_relu" | |
type: "ReLU" | |
bottom: "resx5_conv1" | |
top: "resx5_conv1" | |
} | |
layer { | |
name: "shuffle5" | |
type: "ShuffleChannel" | |
bottom: "resx5_conv1" | |
top: "shuffle5" | |
shuffle_channel_param { | |
group: 3 | |
} | |
} | |
layer { | |
name: "resx5_conv2" | |
type: "ConvolutionDepthwise" | |
bottom: "shuffle5" | |
top: "resx5_conv2" | |
convolution_param { | |
num_output: 60 | |
kernel_size: 3 | |
stride: 2 | |
pad: 1 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx5_conv2_bn" | |
type: "BatchNorm" | |
bottom: "resx5_conv2" | |
top: "resx5_conv2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx5_conv2_scale" | |
bottom: "resx5_conv2" | |
top: "resx5_conv2" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx5_conv3" | |
type: "Convolution" | |
bottom: "resx5_conv2" | |
top: "resx5_conv3" | |
convolution_param { | |
num_output: 240 | |
kernel_size: 1 | |
stride: 1 | |
pad: 0 | |
group: 3 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx5_conv3_bn" | |
type: "BatchNorm" | |
bottom: "resx5_conv3" | |
top: "resx5_conv3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx5_conv3_scale" | |
bottom: "resx5_conv3" | |
top: "resx5_conv3" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx5_concat" | |
type: "Concat" | |
bottom: "resx5_match_conv" | |
bottom: "resx5_conv3" | |
top: "resx5_concat" | |
} | |
layer { | |
name: "resx5_concat_relu" | |
type: "ReLU" | |
bottom: "resx5_concat" | |
top: "resx5_concat" | |
} | |
layer { | |
name: "resx13_match_conv" | |
type: "Pooling" | |
bottom: "resx5_concat" | |
top: "resx13_match_conv" | |
pooling_param { | |
pool: AVE | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer { | |
name: "resx13_conv1" | |
type: "Convolution" | |
bottom: "resx5_concat" | |
top: "resx13_conv1" | |
convolution_param { | |
num_output: 120 | |
kernel_size: 1 | |
stride: 1 | |
pad: 0 | |
group: 3 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx13_conv1_bn" | |
type: "BatchNorm" | |
bottom: "resx13_conv1" | |
top: "resx13_conv1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx13_conv1_scale" | |
bottom: "resx13_conv1" | |
top: "resx13_conv1" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx13_conv1_relu" | |
type: "ReLU" | |
bottom: "resx13_conv1" | |
top: "resx13_conv1" | |
} | |
layer { | |
name: "shuffle13" | |
type: "ShuffleChannel" | |
bottom: "resx13_conv1" | |
top: "shuffle13" | |
shuffle_channel_param { | |
group: 3 | |
} | |
} | |
layer { | |
name: "resx13_conv2" | |
type: "ConvolutionDepthwise" | |
bottom: "shuffle13" | |
top: "resx13_conv2" | |
convolution_param { | |
num_output: 120 | |
kernel_size: 3 | |
stride: 2 | |
pad: 1 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx13_conv2_bn" | |
type: "BatchNorm" | |
bottom: "resx13_conv2" | |
top: "resx13_conv2" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx13_conv2_scale" | |
bottom: "resx13_conv2" | |
top: "resx13_conv2" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx13_conv3" | |
type: "Convolution" | |
bottom: "resx13_conv2" | |
top: "resx13_conv3" | |
convolution_param { | |
num_output: 480 | |
kernel_size: 1 | |
stride: 1 | |
pad: 0 | |
group: 3 | |
bias_term: false | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "resx13_conv3_bn" | |
type: "BatchNorm" | |
bottom: "resx13_conv3" | |
top: "resx13_conv3" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "resx13_conv3_scale" | |
bottom: "resx13_conv3" | |
top: "resx13_conv3" | |
type: "Scale" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "resx13_concat" | |
type: "Concat" | |
bottom: "resx13_match_conv" | |
bottom: "resx13_conv3" | |
top: "resx13_concat" | |
} | |
layer { | |
name: "resx13_concat_relu" | |
type: "ReLU" | |
bottom: "resx13_concat" | |
top: "resx13_concat" | |
} | |
layer { | |
name: "pool_ave" | |
type: "Pooling" | |
bottom: "resx13_concat" | |
top: "pool_ave" | |
pooling_param { | |
global_pooling : true | |
pool: AVE | |
} | |
} | |
layer { | |
name: "fc7" | |
type: "Convolution" | |
bottom: "pool_ave" | |
top: "fc7" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 7906 | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "loss" | |
type: "SoftmaxWithLoss" | |
bottom: "fc7" | |
bottom: "label" | |
top: "loss" | |
} | |
layer { | |
name: "accuracy" | |
type: "Accuracy" | |
bottom: "fc7" | |
bottom: "label" | |
top: "accuracy" | |
include { | |
phase: TEST | |
} | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment