Created
August 22, 2017 09:10
-
-
Save NHZlX/243aea9ec3f22e3e2cfbb50b05cede93 to your computer and use it in GitHub Desktop.
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
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 | |
} | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment