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@walkoncross
Created November 11, 2017 00:02
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sphereface train prototxt (64 layers); netscope: http://ethereon.github.io/netscope/#/gist/fa28659e989e9864df302bbd0678c5e3
name: "SphereFaceNet-64"
layer {
name: "data"
type: "ImageData"
top: "data"
top: "label"
transform_param {
mean_value: 127.5
mean_value: 127.5
mean_value: 127.5
scale: 0.0078125
mirror: true
}
image_data_param {
source: "data/CASIA-WebFace-112X96.txt"
batch_size: 256
shuffle: true
}
}
############## CNN Architecture ###############
layer {
name: "conv1_1"
type: "Convolution"
bottom: "data"
top: "conv1_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_1"
type: "PReLU"
bottom: "conv1_1"
top: "conv1_1"
}
layer {
name: "conv1_2"
type: "Convolution"
bottom: "conv1_1"
top: "conv1_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_2"
type: "PReLU"
bottom: "conv1_2"
top: "conv1_2"
}
layer {
name: "conv1_3"
type: "Convolution"
bottom: "conv1_2"
top: "conv1_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_3"
type: "PReLU"
bottom: "conv1_3"
top: "conv1_3"
}
layer {
name: "res1_3"
type: "Eltwise"
bottom: "conv1_1"
bottom: "conv1_3"
top: "res1_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv1_4"
type: "Convolution"
bottom: "res1_3"
top: "conv1_4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_4"
type: "PReLU"
bottom: "conv1_4"
top: "conv1_4"
}
layer {
name: "conv1_5"
type: "Convolution"
bottom: "conv1_4"
top: "conv1_5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_5"
type: "PReLU"
bottom: "conv1_5"
top: "conv1_5"
}
layer {
name: "res1_5"
type: "Eltwise"
bottom: "res1_3"
bottom: "conv1_5"
top: "res1_5"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv1_6"
type: "Convolution"
bottom: "res1_5"
top: "conv1_6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_6"
type: "PReLU"
bottom: "conv1_6"
top: "conv1_6"
}
layer {
name: "conv1_7"
type: "Convolution"
bottom: "conv1_6"
top: "conv1_7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu1_7"
type: "PReLU"
bottom: "conv1_7"
top: "conv1_7"
}
layer {
name: "res1_7"
type: "Eltwise"
bottom: "res1_5"
bottom: "conv1_7"
top: "res1_7"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_1"
type: "Convolution"
bottom: "res1_7"
top: "conv2_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_1"
type: "PReLU"
bottom: "conv2_1"
top: "conv2_1"
}
layer {
name: "conv2_2"
type: "Convolution"
bottom: "conv2_1"
top: "conv2_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_2"
type: "PReLU"
bottom: "conv2_2"
top: "conv2_2"
}
layer {
name: "conv2_3"
type: "Convolution"
bottom: "conv2_2"
top: "conv2_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_3"
type: "PReLU"
bottom: "conv2_3"
top: "conv2_3"
}
layer {
name: "res2_3"
type: "Eltwise"
bottom: "conv2_1"
bottom: "conv2_3"
top: "res2_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_4"
type: "Convolution"
bottom: "res2_3"
top: "conv2_4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_4"
type: "PReLU"
bottom: "conv2_4"
top: "conv2_4"
}
layer {
name: "conv2_5"
type: "Convolution"
bottom: "conv2_4"
top: "conv2_5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_5"
type: "PReLU"
bottom: "conv2_5"
top: "conv2_5"
}
layer {
name: "res2_5"
type: "Eltwise"
bottom: "res2_3"
bottom: "conv2_5"
top: "res2_5"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_6"
type: "Convolution"
bottom: "res2_5"
top: "conv2_6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_6"
type: "PReLU"
bottom: "conv2_6"
top: "conv2_6"
}
layer {
name: "conv2_7"
type: "Convolution"
bottom: "conv2_6"
top: "conv2_7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_7"
type: "PReLU"
bottom: "conv2_7"
top: "conv2_7"
}
layer {
name: "res2_7"
type: "Eltwise"
bottom: "res2_5"
bottom: "conv2_7"
top: "res2_7"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_8"
type: "Convolution"
bottom: "res2_7"
top: "conv2_8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_8"
type: "PReLU"
bottom: "conv2_8"
top: "conv2_8"
}
layer {
name: "conv2_9"
type: "Convolution"
bottom: "conv2_8"
top: "conv2_9"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_9"
type: "PReLU"
bottom: "conv2_9"
top: "conv2_9"
}
layer {
name: "res2_9"
type: "Eltwise"
bottom: "res2_7"
bottom: "conv2_9"
top: "res2_9"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_10"
type: "Convolution"
bottom: "res2_9"
top: "conv2_10"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_10"
type: "PReLU"
bottom: "conv2_10"
top: "conv2_10"
}
layer {
name: "conv2_11"
type: "Convolution"
bottom: "conv2_10"
top: "conv2_11"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_11"
type: "PReLU"
bottom: "conv2_11"
top: "conv2_11"
}
layer {
name: "res2_11"
type: "Eltwise"
bottom: "res2_9"
bottom: "conv2_11"
top: "res2_11"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_12"
type: "Convolution"
bottom: "res2_11"
top: "conv2_12"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_12"
type: "PReLU"
bottom: "conv2_12"
top: "conv2_12"
}
layer {
name: "conv2_13"
type: "Convolution"
bottom: "conv2_12"
top: "conv2_13"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_13"
type: "PReLU"
bottom: "conv2_13"
top: "conv2_13"
}
layer {
name: "res2_13"
type: "Eltwise"
bottom: "res2_11"
bottom: "conv2_13"
top: "res2_13"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_14"
type: "Convolution"
bottom: "res2_13"
top: "conv2_14"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_14"
type: "PReLU"
bottom: "conv2_14"
top: "conv2_14"
}
layer {
name: "conv2_15"
type: "Convolution"
bottom: "conv2_14"
top: "conv2_15"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_15"
type: "PReLU"
bottom: "conv2_15"
top: "conv2_15"
}
layer {
name: "res2_15"
type: "Eltwise"
bottom: "res2_13"
bottom: "conv2_15"
top: "res2_15"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_16"
type: "Convolution"
bottom: "res2_15"
top: "conv2_16"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_16"
type: "PReLU"
bottom: "conv2_16"
top: "conv2_16"
}
layer {
name: "conv2_17"
type: "Convolution"
bottom: "conv2_16"
top: "conv2_17"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu2_17"
type: "PReLU"
bottom: "conv2_17"
top: "conv2_17"
}
layer {
name: "res2_17"
type: "Eltwise"
bottom: "res2_15"
bottom: "conv2_17"
top: "res2_17"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_1"
type: "Convolution"
bottom: "res2_17"
top: "conv3_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_1"
type: "PReLU"
bottom: "conv3_1"
top: "conv3_1"
}
layer {
name: "conv3_2"
type: "Convolution"
bottom: "conv3_1"
top: "conv3_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_2"
type: "PReLU"
bottom: "conv3_2"
top: "conv3_2"
}
layer {
name: "conv3_3"
type: "Convolution"
bottom: "conv3_2"
top: "conv3_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_3"
type: "PReLU"
bottom: "conv3_3"
top: "conv3_3"
}
layer {
name: "res3_3"
type: "Eltwise"
bottom: "conv3_1"
bottom: "conv3_3"
top: "res3_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_4"
type: "Convolution"
bottom: "res3_3"
top: "conv3_4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_4"
type: "PReLU"
bottom: "conv3_4"
top: "conv3_4"
}
layer {
name: "conv3_5"
type: "Convolution"
bottom: "conv3_4"
top: "conv3_5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_5"
type: "PReLU"
bottom: "conv3_5"
top: "conv3_5"
}
layer {
name: "res3_5"
type: "Eltwise"
bottom: "res3_3"
bottom: "conv3_5"
top: "res3_5"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_6"
type: "Convolution"
bottom: "res3_5"
top: "conv3_6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_6"
type: "PReLU"
bottom: "conv3_6"
top: "conv3_6"
}
layer {
name: "conv3_7"
type: "Convolution"
bottom: "conv3_6"
top: "conv3_7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_7"
type: "PReLU"
bottom: "conv3_7"
top: "conv3_7"
}
layer {
name: "res3_7"
type: "Eltwise"
bottom: "res3_5"
bottom: "conv3_7"
top: "res3_7"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_8"
type: "Convolution"
bottom: "res3_7"
top: "conv3_8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_8"
type: "PReLU"
bottom: "conv3_8"
top: "conv3_8"
}
layer {
name: "conv3_9"
type: "Convolution"
bottom: "conv3_8"
top: "conv3_9"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_9"
type: "PReLU"
bottom: "conv3_9"
top: "conv3_9"
}
layer {
name: "res3_9"
type: "Eltwise"
bottom: "res3_7"
bottom: "conv3_9"
top: "res3_9"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_10"
type: "Convolution"
bottom: "res3_9"
top: "conv3_10"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_10"
type: "PReLU"
bottom: "conv3_10"
top: "conv3_10"
}
layer {
name: "conv3_11"
type: "Convolution"
bottom: "conv3_10"
top: "conv3_11"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_11"
type: "PReLU"
bottom: "conv3_11"
top: "conv3_11"
}
layer {
name: "res3_11"
type: "Eltwise"
bottom: "res3_9"
bottom: "conv3_11"
top: "res3_11"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_12"
type: "Convolution"
bottom: "res3_11"
top: "conv3_12"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_12"
type: "PReLU"
bottom: "conv3_12"
top: "conv3_12"
}
layer {
name: "conv3_13"
type: "Convolution"
bottom: "conv3_12"
top: "conv3_13"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_13"
type: "PReLU"
bottom: "conv3_13"
top: "conv3_13"
}
layer {
name: "res3_13"
type: "Eltwise"
bottom: "res3_11"
bottom: "conv3_13"
top: "res3_13"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_14"
type: "Convolution"
bottom: "res3_13"
top: "conv3_14"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_14"
type: "PReLU"
bottom: "conv3_14"
top: "conv3_14"
}
layer {
name: "conv3_15"
type: "Convolution"
bottom: "conv3_14"
top: "conv3_15"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_15"
type: "PReLU"
bottom: "conv3_15"
top: "conv3_15"
}
layer {
name: "res3_15"
type: "Eltwise"
bottom: "res3_13"
bottom: "conv3_15"
top: "res3_15"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_16"
type: "Convolution"
bottom: "res3_15"
top: "conv3_16"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_16"
type: "PReLU"
bottom: "conv3_16"
top: "conv3_16"
}
layer {
name: "conv3_17"
type: "Convolution"
bottom: "conv3_16"
top: "conv3_17"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_17"
type: "PReLU"
bottom: "conv3_17"
top: "conv3_17"
}
layer {
name: "res3_17"
type: "Eltwise"
bottom: "res3_15"
bottom: "conv3_17"
top: "res3_17"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_18"
type: "Convolution"
bottom: "res3_17"
top: "conv3_18"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_18"
type: "PReLU"
bottom: "conv3_18"
top: "conv3_18"
}
layer {
name: "conv3_19"
type: "Convolution"
bottom: "conv3_18"
top: "conv3_19"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_19"
type: "PReLU"
bottom: "conv3_19"
top: "conv3_19"
}
layer {
name: "res3_19"
type: "Eltwise"
bottom: "res3_17"
bottom: "conv3_19"
top: "res3_19"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_20"
type: "Convolution"
bottom: "res3_19"
top: "conv3_20"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_20"
type: "PReLU"
bottom: "conv3_20"
top: "conv3_20"
}
layer {
name: "conv3_21"
type: "Convolution"
bottom: "conv3_20"
top: "conv3_21"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_21"
type: "PReLU"
bottom: "conv3_21"
top: "conv3_21"
}
layer {
name: "res3_21"
type: "Eltwise"
bottom: "res3_19"
bottom: "conv3_21"
top: "res3_21"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_22"
type: "Convolution"
bottom: "res3_21"
top: "conv3_22"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_22"
type: "PReLU"
bottom: "conv3_22"
top: "conv3_22"
}
layer {
name: "conv3_23"
type: "Convolution"
bottom: "conv3_22"
top: "conv3_23"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_23"
type: "PReLU"
bottom: "conv3_23"
top: "conv3_23"
}
layer {
name: "res3_23"
type: "Eltwise"
bottom: "res3_21"
bottom: "conv3_23"
top: "res3_23"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_24"
type: "Convolution"
bottom: "res3_23"
top: "conv3_24"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_24"
type: "PReLU"
bottom: "conv3_24"
top: "conv3_24"
}
layer {
name: "conv3_25"
type: "Convolution"
bottom: "conv3_24"
top: "conv3_25"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_25"
type: "PReLU"
bottom: "conv3_25"
top: "conv3_25"
}
layer {
name: "res3_25"
type: "Eltwise"
bottom: "res3_23"
bottom: "conv3_25"
top: "res3_25"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_26"
type: "Convolution"
bottom: "res3_25"
top: "conv3_26"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_26"
type: "PReLU"
bottom: "conv3_26"
top: "conv3_26"
}
layer {
name: "conv3_27"
type: "Convolution"
bottom: "conv3_26"
top: "conv3_27"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_27"
type: "PReLU"
bottom: "conv3_27"
top: "conv3_27"
}
layer {
name: "res3_27"
type: "Eltwise"
bottom: "res3_25"
bottom: "conv3_27"
top: "res3_27"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_28"
type: "Convolution"
bottom: "res3_27"
top: "conv3_28"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_28"
type: "PReLU"
bottom: "conv3_28"
top: "conv3_28"
}
layer {
name: "conv3_29"
type: "Convolution"
bottom: "conv3_28"
top: "conv3_29"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_29"
type: "PReLU"
bottom: "conv3_29"
top: "conv3_29"
}
layer {
name: "res3_29"
type: "Eltwise"
bottom: "res3_27"
bottom: "conv3_29"
top: "res3_29"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_30"
type: "Convolution"
bottom: "res3_29"
top: "conv3_30"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_30"
type: "PReLU"
bottom: "conv3_30"
top: "conv3_30"
}
layer {
name: "conv3_31"
type: "Convolution"
bottom: "conv3_30"
top: "conv3_31"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_31"
type: "PReLU"
bottom: "conv3_31"
top: "conv3_31"
}
layer {
name: "res3_31"
type: "Eltwise"
bottom: "res3_29"
bottom: "conv3_31"
top: "res3_31"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_32"
type: "Convolution"
bottom: "res3_31"
top: "conv3_32"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_32"
type: "PReLU"
bottom: "conv3_32"
top: "conv3_32"
}
layer {
name: "conv3_33"
type: "Convolution"
bottom: "conv3_32"
top: "conv3_33"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu3_33"
type: "PReLU"
bottom: "conv3_33"
top: "conv3_33"
}
layer {
name: "res3_33"
type: "Eltwise"
bottom: "res3_31"
bottom: "conv3_33"
top: "res3_33"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_1"
type: "Convolution"
bottom: "res3_33"
top: "conv4_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_1"
type: "PReLU"
bottom: "conv4_1"
top: "conv4_1"
}
layer {
name: "conv4_2"
type: "Convolution"
bottom: "conv4_1"
top: "conv4_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_2"
type: "PReLU"
bottom: "conv4_2"
top: "conv4_2"
}
layer {
name: "conv4_3"
type: "Convolution"
bottom: "conv4_2"
top: "conv4_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_3"
type: "PReLU"
bottom: "conv4_3"
top: "conv4_3"
}
layer {
name: "res4_3"
type: "Eltwise"
bottom: "conv4_1"
bottom: "conv4_3"
top: "res4_3"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_4"
type: "Convolution"
bottom: "res4_3"
top: "conv4_4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_4"
type: "PReLU"
bottom: "conv4_4"
top: "conv4_4"
}
layer {
name: "conv4_5"
type: "Convolution"
bottom: "conv4_4"
top: "conv4_5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_5"
type: "PReLU"
bottom: "conv4_5"
top: "conv4_5"
}
layer {
name: "res4_5"
type: "Eltwise"
bottom: "res4_3"
bottom: "conv4_5"
top: "res4_5"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv4_6"
type: "Convolution"
bottom: "res4_5"
top: "conv4_6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_6"
type: "PReLU"
bottom: "conv4_6"
top: "conv4_6"
}
layer {
name: "conv4_7"
type: "Convolution"
bottom: "conv4_6"
top: "conv4_7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 0
decay_mult: 0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prelu4_7"
type: "PReLU"
bottom: "conv4_7"
top: "conv4_7"
}
layer {
name: "res4_7"
type: "Eltwise"
bottom: "res4_5"
bottom: "conv4_7"
top: "res4_7"
eltwise_param {
operation: SUM
}
}
layer {
name: "fc5"
type: "InnerProduct"
bottom: "res4_7"
top: "fc5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 512
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
############### A-Softmax Loss ##############
layer {
name: "fc6"
type: "MarginInnerProduct"
bottom: "fc5"
bottom: "label"
top: "fc6"
top: "lambda"
param {
lr_mult: 1
decay_mult: 1
}
margin_inner_product_param {
num_output: 10572
type: QUADRUPLE
weight_filler {
type: "xavier"
}
base: 1000
gamma: 0.12
power: 1
lambda_min: 5
iteration: 0
}
}
layer {
name: "softmax_loss"
type: "SoftmaxWithLoss"
bottom: "fc6"
bottom: "label"
top: "softmax_loss"
}
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