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@NHZlX
Created August 22, 2017 09:10
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layer {
name: "data"
type: "Input"
top: "data"
input_param { shape: { dim: dim: dim: dim: } }
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output:
kernel_size:
stride:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv1"
type: "BatchNorm"
bottom: "conv1"
top: "conv1"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv1"
type: "Scale"
bottom: "conv1"
top: "conv1"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv2"
type: "Convolution"
bottom: "conv1"
top: "conv2"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv2"
type: "BatchNorm"
bottom: "conv2"
top: "conv2"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv2"
type: "Scale"
bottom: "conv2"
top: "conv2"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size:
stride:
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv3"
type: "BatchNorm"
bottom: "conv3"
top: "conv3"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv3"
type: "Scale"
bottom: "conv3"
top: "conv3"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv4"
type: "BatchNorm"
bottom: "conv4"
top: "conv4"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv4"
type: "Scale"
bottom: "conv4"
top: "conv4"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
convolution_param {
num_output:
kernel_size: 3
pad: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv5"
type: "BatchNorm"
bottom: "conv5"
top: "conv5"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv5"
type: "Scale"
bottom: "conv5"
top: "conv5"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size:
stride:
}
}
layer {
name: "conv6"
type: "Convolution"
bottom: "pool5"
top: "conv6"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv6"
type: "BatchNorm"
bottom: "conv6"
top: "conv6"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv6"
type: "Scale"
bottom: "conv6"
top: "conv6"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv6"
type: "ReLU"
bottom: "conv6"
top: "conv6"
}
layer {
name: "conv7"
type: "Convolution"
bottom: "conv6"
top: "conv7"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv7"
type: "BatchNorm"
bottom: "conv7"
top: "conv7"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv7"
type: "Scale"
bottom: "conv7"
top: "conv7"
scale_param {
bias_term: true
}
}
layer {
name: "relu_con7"
type: "ReLU"
bottom: "conv7"
top: "conv7"
}
layer {
name: "conv8"
type: "Convolution"
bottom: "conv7"
top: "conv8"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv8"
type: "BatchNorm"
bottom: "conv8"
top: "conv8"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv8"
type: "Scale"
bottom: "conv8"
top: "conv8"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv8"
type: "ReLU"
bottom: "conv8"
top: "conv8"
}
layer {
name: "pool8"
type: "Pooling"
bottom: "conv8"
top: "pool8"
pooling_param {
pool: MAX
kernel_size:
stride:
}
}
layer {
name: "conv9"
type: "Convolution"
bottom: "pool8"
top: "conv9"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv9"
type: "BatchNorm"
bottom: "conv9"
top: "conv9"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv9"
type: "Scale"
bottom: "conv9"
top: "conv9"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv9"
type: "ReLU"
bottom: "conv9"
top: "conv9"
}
layer {
name: "conv10"
type: "Convolution"
bottom: "conv9"
top: "conv10"
convolution_param {
num_output:
kernel_size:
pad: 1
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv10"
type: "BatchNorm"
bottom: "conv10"
top: "conv10"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv10"
type: "Scale"
bottom: "conv10"
top: "conv10"
scale_param {
bias_term: true
}
}
layer {
name: "relu_con10"
type: "ReLU"
bottom: "conv10"
top: "conv10"
}
layer {
name: "conv11"
type: "Convolution"
bottom: "conv10"
top: "conv11"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv11"
type: "BatchNorm"
bottom: "conv11"
top: "conv11"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv11"
type: "Scale"
bottom: "conv11"
top: "conv11"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv11"
type: "ReLU"
bottom: "conv11"
top: "conv11"
}
layer {
name: "pool11"
type: "Pooling"
bottom: "conv11"
top: "pool11"
pooling_param {
pool: MAX
kernel_size:
stride:
}
}
layer {
name: "conv12"
type: "Convolution"
bottom: "pool11"
top: "conv12"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv12"
type: "BatchNorm"
bottom: "conv12"
top: "conv12"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv12"
type: "Scale"
bottom: "conv12"
top: "conv12"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv12"
type: "ReLU"
bottom: "conv12"
top: "conv12"
}
layer {
name: "conv13"
type: "Convolution"
bottom: "conv12"
top: "conv13"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv13"
type: "BatchNorm"
bottom: "conv13"
top: "conv13"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv13"
type: "Scale"
bottom: "conv13"
top: "conv13"
scale_param {
bias_term: true
}
}
layer {
name: "relu_con13"
type: "ReLU"
bottom: "conv13"
top: "conv13"
}
layer {
name: "conv14"
type: "Convolution"
bottom: "conv13"
top: "conv14"
convolution_param {
num_output:
kernel_size:
pad:
weight_filler {
type: "xavier"
}
}
}
layer {
name: "bn_conv14"
type: "BatchNorm"
bottom: "conv14"
top: "conv14"
batch_norm_param {
use_global_stats: true
}
include {
phase: TEST
}
}
layer {
name: "scale_conv14"
type: "Scale"
bottom: "conv14"
top: "conv14"
scale_param {
bias_term: true
}
}
layer {
name: "relu_conv14"
type: "ReLU"
bottom: "conv14"
top: "conv14"
}
layer {
name: "conv_final"
type: "Convolution"
bottom: "conv14"
top: "conv_final"
convolution_param {
num_output:
kernel_size:
weight_filler {
type: "gaussian"
mean:
std:
}
}
}
layer {
name: "relu_conv_final"
type: "ReLU"
bottom: "conv_final"
top: "conv_final"
}
layer {
name: "pool_final"
type: "Pooling"
bottom: "conv_final"
top: "pool_final"
pooling_param {
pool: AVE
global_pooling: true
}
}
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