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deploy.prototxt
input: "data"
input_shape {
dim: 1
dim: 3
dim: 299
dim: 299
}
layer {
name: "conv1_3x3_s2"
type: "Convolution"
bottom: "data"
top: "conv1_3x3_s2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv1_3x3_s2_bn"
type: "BatchNorm"
bottom: "conv1_3x3_s2"
top: "conv1_3x3_s2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv1_3x3_s2_scale"
type: "Scale"
bottom: "conv1_3x3_s2"
top: "conv1_3x3_s2"
scale_param {
bias_term: true
}
}
layer {
name: "conv1_3x3_relu"
type: "ReLU"
bottom: "conv1_3x3_s2"
top: "conv1_3x3_s2"
}
layer {
name: "conv2_3x3_s1"
type: "Convolution"
bottom: "conv1_3x3_s2"
top: "conv2_3x3_s1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv2_3x3_s1_bn"
type: "BatchNorm"
bottom: "conv2_3x3_s1"
top: "conv2_3x3_s1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv2_3x3_s1_scale"
type: "Scale"
bottom: "conv2_3x3_s1"
top: "conv2_3x3_s1"
scale_param {
bias_term: true
}
}
layer {
name: "conv2_3x3_relu"
type: "ReLU"
bottom: "conv2_3x3_s1"
top: "conv2_3x3_s1"
}
layer {
name: "conv3_3x3_s1"
type: "Convolution"
bottom: "conv2_3x3_s1"
top: "conv3_3x3_s1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv3_3x3_s1_bn"
type: "BatchNorm"
bottom: "conv3_3x3_s1"
top: "conv3_3x3_s1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv3_3x3_s1_scale"
type: "Scale"
bottom: "conv3_3x3_s1"
top: "conv3_3x3_s1"
scale_param {
bias_term: true
}
}
layer {
name: "conv3_3x3_relu"
type: "ReLU"
bottom: "conv3_3x3_s1"
top: "conv3_3x3_s1"
}
layer {
name: "pool1_3x3_s2"
type: "Pooling"
bottom: "conv3_3x3_s1"
top: "pool1_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv4_3x3_reduce"
type: "Convolution"
bottom: "pool1_3x3_s2"
top: "conv4_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 80
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv4_3x3_reduce_bn"
type: "BatchNorm"
bottom: "conv4_3x3_reduce"
top: "conv4_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv4_3x3_reduce_scale"
type: "Scale"
bottom: "conv4_3x3_reduce"
top: "conv4_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "conv4_3x3_reduce_relu"
type: "ReLU"
bottom: "conv4_3x3_reduce"
top: "conv4_3x3_reduce"
}
layer {
name: "conv4_3x3"
type: "Convolution"
bottom: "conv4_3x3_reduce"
top: "conv4_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv4_3x3_bn"
type: "BatchNorm"
bottom: "conv4_3x3"
top: "conv4_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv4_3x3_scale"
type: "Scale"
bottom: "conv4_3x3"
top: "conv4_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "conv4_relu_3x3"
type: "ReLU"
bottom: "conv4_3x3"
top: "conv4_3x3"
}
layer {
name: "pool2_3x3_s2"
type: "Pooling"
bottom: "conv4_3x3"
top: "pool2_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv5_1x1"
type: "Convolution"
bottom: "pool2_3x3_s2"
top: "conv5_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_1x1_bn"
type: "BatchNorm"
bottom: "conv5_1x1"
top: "conv5_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_1x1_scale"
type: "Scale"
bottom: "conv5_1x1"
top: "conv5_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_1x1_relu"
type: "ReLU"
bottom: "conv5_1x1"
top: "conv5_1x1"
}
layer {
name: "conv5_5x5_reduce"
type: "Convolution"
bottom: "pool2_3x3_s2"
top: "conv5_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_5x5_reduce_bn"
type: "BatchNorm"
bottom: "conv5_5x5_reduce"
top: "conv5_5x5_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_5x5_reduce_scale"
type: "Scale"
bottom: "conv5_5x5_reduce"
top: "conv5_5x5_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_5x5_reduce_relu"
type: "ReLU"
bottom: "conv5_5x5_reduce"
top: "conv5_5x5_reduce"
}
layer {
name: "conv5_5x5"
type: "Convolution"
bottom: "conv5_5x5_reduce"
top: "conv5_5x5"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_5x5_bn"
type: "BatchNorm"
bottom: "conv5_5x5"
top: "conv5_5x5"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_5x5_scale"
type: "Scale"
bottom: "conv5_5x5"
top: "conv5_5x5"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_5x5_relu"
type: "ReLU"
bottom: "conv5_5x5"
top: "conv5_5x5"
}
layer {
name: "conv5_3x3_reduce"
type: "Convolution"
bottom: "pool2_3x3_s2"
top: "conv5_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_3x3_reduce_bn"
type: "BatchNorm"
bottom: "conv5_3x3_reduce"
top: "conv5_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_3x3_reduce_scale"
type: "Scale"
bottom: "conv5_3x3_reduce"
top: "conv5_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_3x3_reduce_relu"
type: "ReLU"
bottom: "conv5_3x3_reduce"
top: "conv5_3x3_reduce"
}
layer {
name: "conv5_3x3"
type: "Convolution"
bottom: "conv5_3x3_reduce"
top: "conv5_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_3x3_bn"
type: "BatchNorm"
bottom: "conv5_3x3"
top: "conv5_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_3x3_scale"
type: "Scale"
bottom: "conv5_3x3"
top: "conv5_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_3x3_relu"
type: "ReLU"
bottom: "conv5_3x3"
top: "conv5_3x3"
}
layer {
name: "conv5_3x3_2"
type: "Convolution"
bottom: "conv5_3x3"
top: "conv5_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 96
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_3x3_2_bn"
type: "BatchNorm"
bottom: "conv5_3x3_2"
top: "conv5_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_3x3_2_scale"
type: "Scale"
bottom: "conv5_3x3_2"
top: "conv5_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_3x3_2_relu"
type: "ReLU"
bottom: "conv5_3x3_2"
top: "conv5_3x3_2"
}
layer {
name: "ave_pool"
type: "Pooling"
bottom: "pool2_3x3_s2"
top: "ave_pool"
pooling_param {
pool: AVE
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "conv5_1x1_ave"
type: "Convolution"
bottom: "ave_pool"
top: "conv5_1x1_ave"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv5_1x1_ave_bn"
type: "BatchNorm"
bottom: "conv5_1x1_ave"
top: "conv5_1x1_ave"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv5_1x1_ave_scale"
type: "Scale"
bottom: "conv5_1x1_ave"
top: "conv5_1x1_ave"
scale_param {
bias_term: true
}
}
layer {
name: "conv5_1x1_ave_relu"
type: "ReLU"
bottom: "conv5_1x1_ave"
top: "conv5_1x1_ave"
}
layer {
name: "stem_concat"
type: "Concat"
bottom: "conv5_1x1"
bottom: "conv5_5x5"
bottom: "conv5_3x3_2"
bottom: "conv5_1x1_ave"
top: "stem_concat"
}
layer {
name: "inception_resnet_v2_a1_1x1"
type: "Convolution"
bottom: "stem_concat"
top: "inception_resnet_v2_a1_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a1_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a1_1x1"
top: "inception_resnet_v2_a1_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a1_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a1_1x1"
top: "inception_resnet_v2_a1_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a1_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_1x1"
top: "inception_resnet_v2_a1_1x1"
}
layer {
name: "inception_resnet_v2_a1_3x3_reduce"
type: "Convolution"
bottom: "stem_concat"
top: "inception_resnet_v2_a1_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a1_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a1_3x3_reduce"
top: "inception_resnet_v2_a1_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a1_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a1_3x3_reduce"
top: "inception_resnet_v2_a1_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a1_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_3x3_reduce"
top: "inception_resnet_v2_a1_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a1_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a1_3x3_reduce"
top: "inception_resnet_v2_a1_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a1_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a1_3x3"
top: "inception_resnet_v2_a1_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a1_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a1_3x3"
top: "inception_resnet_v2_a1_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a1_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_3x3"
top: "inception_resnet_v2_a1_3x3"
}
layer {
name: "inception_resnet_v2_a1_3x3_2_reduce"
type: "Convolution"
bottom: "stem_concat"
top: "inception_resnet_v2_a1_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a1_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a1_3x3_2_reduce"
top: "inception_resnet_v2_a1_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a1_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a1_3x3_2_reduce"
top: "inception_resnet_v2_a1_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a1_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_3x3_2_reduce"
top: "inception_resnet_v2_a1_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a1_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a1_3x3_2_reduce"
top: "inception_resnet_v2_a1_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a1_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a1_3x3_2"
top: "inception_resnet_v2_a1_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a1_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a1_3x3_2"
top: "inception_resnet_v2_a1_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a1_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_3x3_2"
top: "inception_resnet_v2_a1_3x3_2"
}
layer {
name: "inception_resnet_v2_a1_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a1_3x3_2"
top: "inception_resnet_v2_a1_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a1_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a1_3x3_3"
top: "inception_resnet_v2_a1_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a1_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a1_3x3_3"
top: "inception_resnet_v2_a1_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a1_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_3x3_3"
top: "inception_resnet_v2_a1_3x3_3"
}
layer {
name: "inception_resnet_v2_a1_concat"
type: "Concat"
bottom: "inception_resnet_v2_a1_1x1"
bottom: "inception_resnet_v2_a1_3x3"
bottom: "inception_resnet_v2_a1_3x3_3"
top: "inception_resnet_v2_a1_concat"
}
layer {
name: "inception_resnet_v2_a1_up"
type: "Convolution"
bottom: "inception_resnet_v2_a1_concat"
top: "inception_resnet_v2_a1_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a1_residual_eltwise"
type: "Eltwise"
bottom: "stem_concat"
bottom: "inception_resnet_v2_a1_up"
top: "inception_resnet_v2_a1_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a1_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a1_residual_eltwise"
top: "inception_resnet_v2_a1_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a2_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a1_residual_eltwise"
top: "inception_resnet_v2_a2_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a2_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a2_1x1"
top: "inception_resnet_v2_a2_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a2_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a2_1x1"
top: "inception_resnet_v2_a2_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a2_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_1x1"
top: "inception_resnet_v2_a2_1x1"
}
layer {
name: "inception_resnet_v2_a2_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a1_residual_eltwise"
top: "inception_resnet_v2_a2_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a2_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a2_3x3_reduce"
top: "inception_resnet_v2_a2_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a2_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a2_3x3_reduce"
top: "inception_resnet_v2_a2_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a2_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_3x3_reduce"
top: "inception_resnet_v2_a2_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a2_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a2_3x3_reduce"
top: "inception_resnet_v2_a2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a2_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a2_3x3"
top: "inception_resnet_v2_a2_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a2_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a2_3x3"
top: "inception_resnet_v2_a2_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a2_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_3x3"
top: "inception_resnet_v2_a2_3x3"
}
layer {
name: "inception_resnet_v2_a2_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a1_residual_eltwise"
top: "inception_resnet_v2_a2_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a2_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a2_3x3_2_reduce"
top: "inception_resnet_v2_a2_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a2_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a2_3x3_2_reduce"
top: "inception_resnet_v2_a2_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a2_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_3x3_2_reduce"
top: "inception_resnet_v2_a2_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a2_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a2_3x3_2_reduce"
top: "inception_resnet_v2_a2_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a2_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a2_3x3_2"
top: "inception_resnet_v2_a2_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a2_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a2_3x3_2"
top: "inception_resnet_v2_a2_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a2_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_3x3_2"
top: "inception_resnet_v2_a2_3x3_2"
}
layer {
name: "inception_resnet_v2_a2_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a2_3x3_2"
top: "inception_resnet_v2_a2_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a2_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a2_3x3_3"
top: "inception_resnet_v2_a2_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a2_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a2_3x3_3"
top: "inception_resnet_v2_a2_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a2_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_3x3_3"
top: "inception_resnet_v2_a2_3x3_3"
}
layer {
name: "inception_resnet_v2_a2_concat"
type: "Concat"
bottom: "inception_resnet_v2_a2_1x1"
bottom: "inception_resnet_v2_a2_3x3"
bottom: "inception_resnet_v2_a2_3x3_3"
top: "inception_resnet_v2_a2_concat"
}
layer {
name: "inception_resnet_v2_a2_up"
type: "Convolution"
bottom: "inception_resnet_v2_a2_concat"
top: "inception_resnet_v2_a2_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a2_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a1_residual_eltwise"
bottom: "inception_resnet_v2_a2_up"
top: "inception_resnet_v2_a2_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a2_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a2_residual_eltwise"
top: "inception_resnet_v2_a2_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a3_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a2_residual_eltwise"
top: "inception_resnet_v2_a3_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a3_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a3_1x1"
top: "inception_resnet_v2_a3_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a3_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a3_1x1"
top: "inception_resnet_v2_a3_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a3_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_1x1"
top: "inception_resnet_v2_a3_1x1"
}
layer {
name: "inception_resnet_v2_a3_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a2_residual_eltwise"
top: "inception_resnet_v2_a3_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a3_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a3_3x3_reduce"
top: "inception_resnet_v2_a3_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a3_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a3_3x3_reduce"
top: "inception_resnet_v2_a3_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a3_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_3x3_reduce"
top: "inception_resnet_v2_a3_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a3_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a3_3x3_reduce"
top: "inception_resnet_v2_a3_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a3_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a3_3x3"
top: "inception_resnet_v2_a3_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a3_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a3_3x3"
top: "inception_resnet_v2_a3_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a3_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_3x3"
top: "inception_resnet_v2_a3_3x3"
}
layer {
name: "inception_resnet_v2_a3_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a2_residual_eltwise"
top: "inception_resnet_v2_a3_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a3_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a3_3x3_2_reduce"
top: "inception_resnet_v2_a3_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a3_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a3_3x3_2_reduce"
top: "inception_resnet_v2_a3_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a3_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_3x3_2_reduce"
top: "inception_resnet_v2_a3_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a3_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a3_3x3_2_reduce"
top: "inception_resnet_v2_a3_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a3_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a3_3x3_2"
top: "inception_resnet_v2_a3_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a3_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a3_3x3_2"
top: "inception_resnet_v2_a3_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a3_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_3x3_2"
top: "inception_resnet_v2_a3_3x3_2"
}
layer {
name: "inception_resnet_v2_a3_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a3_3x3_2"
top: "inception_resnet_v2_a3_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a3_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a3_3x3_3"
top: "inception_resnet_v2_a3_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a3_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a3_3x3_3"
top: "inception_resnet_v2_a3_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a3_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_3x3_3"
top: "inception_resnet_v2_a3_3x3_3"
}
layer {
name: "inception_resnet_v2_a3_concat"
type: "Concat"
bottom: "inception_resnet_v2_a3_1x1"
bottom: "inception_resnet_v2_a3_3x3"
bottom: "inception_resnet_v2_a3_3x3_3"
top: "inception_resnet_v2_a3_concat"
}
layer {
name: "inception_resnet_v2_a3_up"
type: "Convolution"
bottom: "inception_resnet_v2_a3_concat"
top: "inception_resnet_v2_a3_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a3_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a2_residual_eltwise"
bottom: "inception_resnet_v2_a3_up"
top: "inception_resnet_v2_a3_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a3_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a3_residual_eltwise"
top: "inception_resnet_v2_a3_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a4_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a3_residual_eltwise"
top: "inception_resnet_v2_a4_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a4_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a4_1x1"
top: "inception_resnet_v2_a4_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a4_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a4_1x1"
top: "inception_resnet_v2_a4_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a4_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_1x1"
top: "inception_resnet_v2_a4_1x1"
}
layer {
name: "inception_resnet_v2_a4_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a3_residual_eltwise"
top: "inception_resnet_v2_a4_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a4_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a4_3x3_reduce"
top: "inception_resnet_v2_a4_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a4_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a4_3x3_reduce"
top: "inception_resnet_v2_a4_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a4_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_3x3_reduce"
top: "inception_resnet_v2_a4_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a4_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a4_3x3_reduce"
top: "inception_resnet_v2_a4_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a4_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a4_3x3"
top: "inception_resnet_v2_a4_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a4_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a4_3x3"
top: "inception_resnet_v2_a4_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a4_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_3x3"
top: "inception_resnet_v2_a4_3x3"
}
layer {
name: "inception_resnet_v2_a4_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a3_residual_eltwise"
top: "inception_resnet_v2_a4_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a4_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a4_3x3_2_reduce"
top: "inception_resnet_v2_a4_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a4_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a4_3x3_2_reduce"
top: "inception_resnet_v2_a4_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a4_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_3x3_2_reduce"
top: "inception_resnet_v2_a4_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a4_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a4_3x3_2_reduce"
top: "inception_resnet_v2_a4_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a4_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a4_3x3_2"
top: "inception_resnet_v2_a4_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a4_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a4_3x3_2"
top: "inception_resnet_v2_a4_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a4_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_3x3_2"
top: "inception_resnet_v2_a4_3x3_2"
}
layer {
name: "inception_resnet_v2_a4_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a4_3x3_2"
top: "inception_resnet_v2_a4_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a4_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a4_3x3_3"
top: "inception_resnet_v2_a4_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a4_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a4_3x3_3"
top: "inception_resnet_v2_a4_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a4_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_3x3_3"
top: "inception_resnet_v2_a4_3x3_3"
}
layer {
name: "inception_resnet_v2_a4_concat"
type: "Concat"
bottom: "inception_resnet_v2_a4_1x1"
bottom: "inception_resnet_v2_a4_3x3"
bottom: "inception_resnet_v2_a4_3x3_3"
top: "inception_resnet_v2_a4_concat"
}
layer {
name: "inception_resnet_v2_a4_up"
type: "Convolution"
bottom: "inception_resnet_v2_a4_concat"
top: "inception_resnet_v2_a4_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a4_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a3_residual_eltwise"
bottom: "inception_resnet_v2_a4_up"
top: "inception_resnet_v2_a4_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a4_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a4_residual_eltwise"
top: "inception_resnet_v2_a4_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a5_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a4_residual_eltwise"
top: "inception_resnet_v2_a5_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a5_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a5_1x1"
top: "inception_resnet_v2_a5_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a5_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a5_1x1"
top: "inception_resnet_v2_a5_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a5_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_1x1"
top: "inception_resnet_v2_a5_1x1"
}
layer {
name: "inception_resnet_v2_a5_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a4_residual_eltwise"
top: "inception_resnet_v2_a5_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a5_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a5_3x3_reduce"
top: "inception_resnet_v2_a5_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a5_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a5_3x3_reduce"
top: "inception_resnet_v2_a5_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a5_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_3x3_reduce"
top: "inception_resnet_v2_a5_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a5_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a5_3x3_reduce"
top: "inception_resnet_v2_a5_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a5_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a5_3x3"
top: "inception_resnet_v2_a5_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a5_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a5_3x3"
top: "inception_resnet_v2_a5_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a5_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_3x3"
top: "inception_resnet_v2_a5_3x3"
}
layer {
name: "inception_resnet_v2_a5_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a4_residual_eltwise"
top: "inception_resnet_v2_a5_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a5_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a5_3x3_2_reduce"
top: "inception_resnet_v2_a5_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a5_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a5_3x3_2_reduce"
top: "inception_resnet_v2_a5_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a5_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_3x3_2_reduce"
top: "inception_resnet_v2_a5_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a5_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a5_3x3_2_reduce"
top: "inception_resnet_v2_a5_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a5_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a5_3x3_2"
top: "inception_resnet_v2_a5_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a5_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a5_3x3_2"
top: "inception_resnet_v2_a5_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a5_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_3x3_2"
top: "inception_resnet_v2_a5_3x3_2"
}
layer {
name: "inception_resnet_v2_a5_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a5_3x3_2"
top: "inception_resnet_v2_a5_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a5_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a5_3x3_3"
top: "inception_resnet_v2_a5_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a5_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a5_3x3_3"
top: "inception_resnet_v2_a5_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a5_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_3x3_3"
top: "inception_resnet_v2_a5_3x3_3"
}
layer {
name: "inception_resnet_v2_a5_concat"
type: "Concat"
bottom: "inception_resnet_v2_a5_1x1"
bottom: "inception_resnet_v2_a5_3x3"
bottom: "inception_resnet_v2_a5_3x3_3"
top: "inception_resnet_v2_a5_concat"
}
layer {
name: "inception_resnet_v2_a5_up"
type: "Convolution"
bottom: "inception_resnet_v2_a5_concat"
top: "inception_resnet_v2_a5_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a5_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a4_residual_eltwise"
bottom: "inception_resnet_v2_a5_up"
top: "inception_resnet_v2_a5_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a5_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a5_residual_eltwise"
top: "inception_resnet_v2_a5_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a6_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a5_residual_eltwise"
top: "inception_resnet_v2_a6_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a6_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a6_1x1"
top: "inception_resnet_v2_a6_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a6_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a6_1x1"
top: "inception_resnet_v2_a6_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a6_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_1x1"
top: "inception_resnet_v2_a6_1x1"
}
layer {
name: "inception_resnet_v2_a6_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a5_residual_eltwise"
top: "inception_resnet_v2_a6_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a6_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a6_3x3_reduce"
top: "inception_resnet_v2_a6_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a6_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a6_3x3_reduce"
top: "inception_resnet_v2_a6_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a6_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_3x3_reduce"
top: "inception_resnet_v2_a6_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a6_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a6_3x3_reduce"
top: "inception_resnet_v2_a6_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a6_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a6_3x3"
top: "inception_resnet_v2_a6_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a6_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a6_3x3"
top: "inception_resnet_v2_a6_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a6_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_3x3"
top: "inception_resnet_v2_a6_3x3"
}
layer {
name: "inception_resnet_v2_a6_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a5_residual_eltwise"
top: "inception_resnet_v2_a6_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a6_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a6_3x3_2_reduce"
top: "inception_resnet_v2_a6_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a6_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a6_3x3_2_reduce"
top: "inception_resnet_v2_a6_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a6_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_3x3_2_reduce"
top: "inception_resnet_v2_a6_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a6_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a6_3x3_2_reduce"
top: "inception_resnet_v2_a6_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a6_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a6_3x3_2"
top: "inception_resnet_v2_a6_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a6_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a6_3x3_2"
top: "inception_resnet_v2_a6_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a6_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_3x3_2"
top: "inception_resnet_v2_a6_3x3_2"
}
layer {
name: "inception_resnet_v2_a6_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a6_3x3_2"
top: "inception_resnet_v2_a6_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a6_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a6_3x3_3"
top: "inception_resnet_v2_a6_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a6_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a6_3x3_3"
top: "inception_resnet_v2_a6_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a6_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_3x3_3"
top: "inception_resnet_v2_a6_3x3_3"
}
layer {
name: "inception_resnet_v2_a6_concat"
type: "Concat"
bottom: "inception_resnet_v2_a6_1x1"
bottom: "inception_resnet_v2_a6_3x3"
bottom: "inception_resnet_v2_a6_3x3_3"
top: "inception_resnet_v2_a6_concat"
}
layer {
name: "inception_resnet_v2_a6_up"
type: "Convolution"
bottom: "inception_resnet_v2_a6_concat"
top: "inception_resnet_v2_a6_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a6_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a5_residual_eltwise"
bottom: "inception_resnet_v2_a6_up"
top: "inception_resnet_v2_a6_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a6_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a6_residual_eltwise"
top: "inception_resnet_v2_a6_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a7_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a6_residual_eltwise"
top: "inception_resnet_v2_a7_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a7_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a7_1x1"
top: "inception_resnet_v2_a7_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a7_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a7_1x1"
top: "inception_resnet_v2_a7_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a7_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_1x1"
top: "inception_resnet_v2_a7_1x1"
}
layer {
name: "inception_resnet_v2_a7_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a6_residual_eltwise"
top: "inception_resnet_v2_a7_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a7_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a7_3x3_reduce"
top: "inception_resnet_v2_a7_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a7_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a7_3x3_reduce"
top: "inception_resnet_v2_a7_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a7_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_3x3_reduce"
top: "inception_resnet_v2_a7_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a7_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a7_3x3_reduce"
top: "inception_resnet_v2_a7_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a7_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a7_3x3"
top: "inception_resnet_v2_a7_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a7_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a7_3x3"
top: "inception_resnet_v2_a7_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a7_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_3x3"
top: "inception_resnet_v2_a7_3x3"
}
layer {
name: "inception_resnet_v2_a7_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a6_residual_eltwise"
top: "inception_resnet_v2_a7_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a7_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a7_3x3_2_reduce"
top: "inception_resnet_v2_a7_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a7_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a7_3x3_2_reduce"
top: "inception_resnet_v2_a7_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a7_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_3x3_2_reduce"
top: "inception_resnet_v2_a7_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a7_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a7_3x3_2_reduce"
top: "inception_resnet_v2_a7_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a7_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a7_3x3_2"
top: "inception_resnet_v2_a7_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a7_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a7_3x3_2"
top: "inception_resnet_v2_a7_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a7_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_3x3_2"
top: "inception_resnet_v2_a7_3x3_2"
}
layer {
name: "inception_resnet_v2_a7_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a7_3x3_2"
top: "inception_resnet_v2_a7_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a7_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a7_3x3_3"
top: "inception_resnet_v2_a7_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a7_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a7_3x3_3"
top: "inception_resnet_v2_a7_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a7_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_3x3_3"
top: "inception_resnet_v2_a7_3x3_3"
}
layer {
name: "inception_resnet_v2_a7_concat"
type: "Concat"
bottom: "inception_resnet_v2_a7_1x1"
bottom: "inception_resnet_v2_a7_3x3"
bottom: "inception_resnet_v2_a7_3x3_3"
top: "inception_resnet_v2_a7_concat"
}
layer {
name: "inception_resnet_v2_a7_up"
type: "Convolution"
bottom: "inception_resnet_v2_a7_concat"
top: "inception_resnet_v2_a7_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a7_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a6_residual_eltwise"
bottom: "inception_resnet_v2_a7_up"
top: "inception_resnet_v2_a7_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a7_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a7_residual_eltwise"
top: "inception_resnet_v2_a7_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a8_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a7_residual_eltwise"
top: "inception_resnet_v2_a8_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a8_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a8_1x1"
top: "inception_resnet_v2_a8_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a8_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a8_1x1"
top: "inception_resnet_v2_a8_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a8_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_1x1"
top: "inception_resnet_v2_a8_1x1"
}
layer {
name: "inception_resnet_v2_a8_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a7_residual_eltwise"
top: "inception_resnet_v2_a8_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a8_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a8_3x3_reduce"
top: "inception_resnet_v2_a8_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a8_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a8_3x3_reduce"
top: "inception_resnet_v2_a8_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a8_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_3x3_reduce"
top: "inception_resnet_v2_a8_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a8_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a8_3x3_reduce"
top: "inception_resnet_v2_a8_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a8_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a8_3x3"
top: "inception_resnet_v2_a8_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a8_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a8_3x3"
top: "inception_resnet_v2_a8_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a8_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_3x3"
top: "inception_resnet_v2_a8_3x3"
}
layer {
name: "inception_resnet_v2_a8_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a7_residual_eltwise"
top: "inception_resnet_v2_a8_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a8_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a8_3x3_2_reduce"
top: "inception_resnet_v2_a8_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a8_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a8_3x3_2_reduce"
top: "inception_resnet_v2_a8_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a8_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_3x3_2_reduce"
top: "inception_resnet_v2_a8_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a8_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a8_3x3_2_reduce"
top: "inception_resnet_v2_a8_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a8_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a8_3x3_2"
top: "inception_resnet_v2_a8_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a8_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a8_3x3_2"
top: "inception_resnet_v2_a8_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a8_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_3x3_2"
top: "inception_resnet_v2_a8_3x3_2"
}
layer {
name: "inception_resnet_v2_a8_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a8_3x3_2"
top: "inception_resnet_v2_a8_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a8_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a8_3x3_3"
top: "inception_resnet_v2_a8_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a8_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a8_3x3_3"
top: "inception_resnet_v2_a8_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a8_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_3x3_3"
top: "inception_resnet_v2_a8_3x3_3"
}
layer {
name: "inception_resnet_v2_a8_concat"
type: "Concat"
bottom: "inception_resnet_v2_a8_1x1"
bottom: "inception_resnet_v2_a8_3x3"
bottom: "inception_resnet_v2_a8_3x3_3"
top: "inception_resnet_v2_a8_concat"
}
layer {
name: "inception_resnet_v2_a8_up"
type: "Convolution"
bottom: "inception_resnet_v2_a8_concat"
top: "inception_resnet_v2_a8_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a8_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a7_residual_eltwise"
bottom: "inception_resnet_v2_a8_up"
top: "inception_resnet_v2_a8_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a8_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a8_residual_eltwise"
top: "inception_resnet_v2_a8_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a9_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a8_residual_eltwise"
top: "inception_resnet_v2_a9_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a9_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a9_1x1"
top: "inception_resnet_v2_a9_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a9_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a9_1x1"
top: "inception_resnet_v2_a9_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a9_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_1x1"
top: "inception_resnet_v2_a9_1x1"
}
layer {
name: "inception_resnet_v2_a9_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a8_residual_eltwise"
top: "inception_resnet_v2_a9_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a9_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a9_3x3_reduce"
top: "inception_resnet_v2_a9_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a9_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a9_3x3_reduce"
top: "inception_resnet_v2_a9_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a9_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_3x3_reduce"
top: "inception_resnet_v2_a9_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a9_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a9_3x3_reduce"
top: "inception_resnet_v2_a9_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a9_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a9_3x3"
top: "inception_resnet_v2_a9_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a9_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a9_3x3"
top: "inception_resnet_v2_a9_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a9_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_3x3"
top: "inception_resnet_v2_a9_3x3"
}
layer {
name: "inception_resnet_v2_a9_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a8_residual_eltwise"
top: "inception_resnet_v2_a9_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a9_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a9_3x3_2_reduce"
top: "inception_resnet_v2_a9_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a9_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a9_3x3_2_reduce"
top: "inception_resnet_v2_a9_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a9_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_3x3_2_reduce"
top: "inception_resnet_v2_a9_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a9_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a9_3x3_2_reduce"
top: "inception_resnet_v2_a9_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a9_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a9_3x3_2"
top: "inception_resnet_v2_a9_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a9_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a9_3x3_2"
top: "inception_resnet_v2_a9_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a9_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_3x3_2"
top: "inception_resnet_v2_a9_3x3_2"
}
layer {
name: "inception_resnet_v2_a9_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a9_3x3_2"
top: "inception_resnet_v2_a9_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a9_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a9_3x3_3"
top: "inception_resnet_v2_a9_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a9_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a9_3x3_3"
top: "inception_resnet_v2_a9_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a9_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_3x3_3"
top: "inception_resnet_v2_a9_3x3_3"
}
layer {
name: "inception_resnet_v2_a9_concat"
type: "Concat"
bottom: "inception_resnet_v2_a9_1x1"
bottom: "inception_resnet_v2_a9_3x3"
bottom: "inception_resnet_v2_a9_3x3_3"
top: "inception_resnet_v2_a9_concat"
}
layer {
name: "inception_resnet_v2_a9_up"
type: "Convolution"
bottom: "inception_resnet_v2_a9_concat"
top: "inception_resnet_v2_a9_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a9_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a8_residual_eltwise"
bottom: "inception_resnet_v2_a9_up"
top: "inception_resnet_v2_a9_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a9_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a9_residual_eltwise"
top: "inception_resnet_v2_a9_residual_eltwise"
}
layer {
name: "inception_resnet_v2_a10_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_a9_residual_eltwise"
top: "inception_resnet_v2_a10_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a10_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a10_1x1"
top: "inception_resnet_v2_a10_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a10_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_a10_1x1"
top: "inception_resnet_v2_a10_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a10_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_1x1"
top: "inception_resnet_v2_a10_1x1"
}
layer {
name: "inception_resnet_v2_a10_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a9_residual_eltwise"
top: "inception_resnet_v2_a10_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a10_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a10_3x3_reduce"
top: "inception_resnet_v2_a10_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a10_3x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a10_3x3_reduce"
top: "inception_resnet_v2_a10_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a10_3x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_3x3_reduce"
top: "inception_resnet_v2_a10_3x3_reduce"
}
layer {
name: "inception_resnet_v2_a10_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a10_3x3_reduce"
top: "inception_resnet_v2_a10_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a10_3x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a10_3x3"
top: "inception_resnet_v2_a10_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a10_3x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a10_3x3"
top: "inception_resnet_v2_a10_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a10_3x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_3x3"
top: "inception_resnet_v2_a10_3x3"
}
layer {
name: "inception_resnet_v2_a10_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a9_residual_eltwise"
top: "inception_resnet_v2_a10_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 32
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a10_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a10_3x3_2_reduce"
top: "inception_resnet_v2_a10_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a10_3x3_2_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_a10_3x3_2_reduce"
top: "inception_resnet_v2_a10_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a10_3x3_2_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_3x3_2_reduce"
top: "inception_resnet_v2_a10_3x3_2_reduce"
}
layer {
name: "inception_resnet_v2_a10_3x3_2"
type: "Convolution"
bottom: "inception_resnet_v2_a10_3x3_2_reduce"
top: "inception_resnet_v2_a10_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 48
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a10_3x3_2_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a10_3x3_2"
top: "inception_resnet_v2_a10_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a10_3x3_2_scale"
type: "Scale"
bottom: "inception_resnet_v2_a10_3x3_2"
top: "inception_resnet_v2_a10_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a10_3x3_2_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_3x3_2"
top: "inception_resnet_v2_a10_3x3_2"
}
layer {
name: "inception_resnet_v2_a10_3x3_3"
type: "Convolution"
bottom: "inception_resnet_v2_a10_3x3_2"
top: "inception_resnet_v2_a10_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_a10_3x3_3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_a10_3x3_3"
top: "inception_resnet_v2_a10_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_a10_3x3_3_scale"
type: "Scale"
bottom: "inception_resnet_v2_a10_3x3_3"
top: "inception_resnet_v2_a10_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_a10_3x3_3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_3x3_3"
top: "inception_resnet_v2_a10_3x3_3"
}
layer {
name: "inception_resnet_v2_a10_concat"
type: "Concat"
bottom: "inception_resnet_v2_a10_1x1"
bottom: "inception_resnet_v2_a10_3x3"
bottom: "inception_resnet_v2_a10_3x3_3"
top: "inception_resnet_v2_a10_concat"
}
layer {
name: "inception_resnet_v2_a10_up"
type: "Convolution"
bottom: "inception_resnet_v2_a10_concat"
top: "inception_resnet_v2_a10_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_a10_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_a9_residual_eltwise"
bottom: "inception_resnet_v2_a10_up"
top: "inception_resnet_v2_a10_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.17
}
}
layer {
name: "inception_resnet_v2_a10_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_a10_residual_eltwise"
top: "inception_resnet_v2_a10_residual_eltwise"
}
layer {
name: "reduction_a_3x3"
type: "Convolution"
bottom: "inception_resnet_v2_a10_residual_eltwise"
top: "reduction_a_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_a_3x3_bn"
type: "BatchNorm"
bottom: "reduction_a_3x3"
top: "reduction_a_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_a_3x3_scale"
type: "Scale"
bottom: "reduction_a_3x3"
top: "reduction_a_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_a_3x3_relu"
type: "ReLU"
bottom: "reduction_a_3x3"
top: "reduction_a_3x3"
}
layer {
name: "reduction_a_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_a10_residual_eltwise"
top: "reduction_a_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_a_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "reduction_a_3x3_2_reduce"
top: "reduction_a_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_a_3x3_2_reduce_scale"
type: "Scale"
bottom: "reduction_a_3x3_2_reduce"
top: "reduction_a_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_a_3x3_2_reduce_relu"
type: "ReLU"
bottom: "reduction_a_3x3_2_reduce"
top: "reduction_a_3x3_2_reduce"
}
layer {
name: "reduction_a_3x3_2"
type: "Convolution"
bottom: "reduction_a_3x3_2_reduce"
top: "reduction_a_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_a_3x3_2_bn"
type: "BatchNorm"
bottom: "reduction_a_3x3_2"
top: "reduction_a_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_a_3x3_2_scale"
type: "Scale"
bottom: "reduction_a_3x3_2"
top: "reduction_a_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_a_3x3_2_relu"
type: "ReLU"
bottom: "reduction_a_3x3_2"
top: "reduction_a_3x3_2"
}
layer {
name: "reduction_a_3x3_3"
type: "Convolution"
bottom: "reduction_a_3x3_2"
top: "reduction_a_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_a_3x3_3_bn"
type: "BatchNorm"
bottom: "reduction_a_3x3_3"
top: "reduction_a_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_a_3x3_3_scale"
type: "Scale"
bottom: "reduction_a_3x3_3"
top: "reduction_a_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_a_3x3_3_relu"
type: "ReLU"
bottom: "reduction_a_3x3_3"
top: "reduction_a_3x3_3"
}
layer {
name: "reduction_a_pool"
type: "Pooling"
bottom: "inception_resnet_v2_a10_residual_eltwise"
top: "reduction_a_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "reduction_a_concat"
type: "Concat"
bottom: "reduction_a_3x3"
bottom: "reduction_a_3x3_3"
bottom: "reduction_a_pool"
top: "reduction_a_concat"
}
layer {
name: "inception_resnet_v2_b1_1x1"
type: "Convolution"
bottom: "reduction_a_concat"
top: "inception_resnet_v2_b1_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b1_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b1_1x1"
top: "inception_resnet_v2_b1_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b1_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b1_1x1"
top: "inception_resnet_v2_b1_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b1_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b1_1x1"
top: "inception_resnet_v2_b1_1x1"
}
layer {
name: "inception_resnet_v2_b1_1x7_reduce"
type: "Convolution"
bottom: "reduction_a_concat"
top: "inception_resnet_v2_b1_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b1_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b1_1x7_reduce"
top: "inception_resnet_v2_b1_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b1_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b1_1x7_reduce"
top: "inception_resnet_v2_b1_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b1_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b1_1x7_reduce"
top: "inception_resnet_v2_b1_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b1_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b1_1x7_reduce"
top: "inception_resnet_v2_b1_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b1_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b1_1x7"
top: "inception_resnet_v2_b1_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b1_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b1_1x7"
top: "inception_resnet_v2_b1_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b1_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b1_1x7"
top: "inception_resnet_v2_b1_1x7"
}
layer {
name: "inception_resnet_v2_b1_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b1_1x7"
top: "inception_resnet_v2_b1_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b1_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b1_7x1"
top: "inception_resnet_v2_b1_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b1_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b1_7x1"
top: "inception_resnet_v2_b1_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b1_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b1_7x1"
top: "inception_resnet_v2_b1_7x1"
}
layer {
name: "inception_resnet_v2_b1_concat"
type: "Concat"
bottom: "inception_resnet_v2_b1_1x1"
bottom: "inception_resnet_v2_b1_7x1"
top: "inception_resnet_v2_b1_concat"
}
layer {
name: "inception_resnet_v2_b1_up"
type: "Convolution"
bottom: "inception_resnet_v2_b1_concat"
top: "inception_resnet_v2_b1_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b1_residual_eltwise"
type: "Eltwise"
bottom: "reduction_a_concat"
bottom: "inception_resnet_v2_b1_up"
top: "inception_resnet_v2_b1_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b1_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b1_residual_eltwise"
top: "inception_resnet_v2_b1_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b2_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b1_residual_eltwise"
top: "inception_resnet_v2_b2_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b2_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b2_1x1"
top: "inception_resnet_v2_b2_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b2_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b2_1x1"
top: "inception_resnet_v2_b2_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b2_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b2_1x1"
top: "inception_resnet_v2_b2_1x1"
}
layer {
name: "inception_resnet_v2_b2_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b1_residual_eltwise"
top: "inception_resnet_v2_b2_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b2_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b2_1x7_reduce"
top: "inception_resnet_v2_b2_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b2_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b2_1x7_reduce"
top: "inception_resnet_v2_b2_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b2_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b2_1x7_reduce"
top: "inception_resnet_v2_b2_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b2_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b2_1x7_reduce"
top: "inception_resnet_v2_b2_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b2_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b2_1x7"
top: "inception_resnet_v2_b2_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b2_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b2_1x7"
top: "inception_resnet_v2_b2_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b2_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b2_1x7"
top: "inception_resnet_v2_b2_1x7"
}
layer {
name: "inception_resnet_v2_b2_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b2_1x7"
top: "inception_resnet_v2_b2_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b2_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b2_7x1"
top: "inception_resnet_v2_b2_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b2_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b2_7x1"
top: "inception_resnet_v2_b2_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b2_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b2_7x1"
top: "inception_resnet_v2_b2_7x1"
}
layer {
name: "inception_resnet_v2_b2_concat"
type: "Concat"
bottom: "inception_resnet_v2_b2_1x1"
bottom: "inception_resnet_v2_b2_7x1"
top: "inception_resnet_v2_b2_concat"
}
layer {
name: "inception_resnet_v2_b2_up"
type: "Convolution"
bottom: "inception_resnet_v2_b2_concat"
top: "inception_resnet_v2_b2_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b2_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b1_residual_eltwise"
bottom: "inception_resnet_v2_b2_up"
top: "inception_resnet_v2_b2_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b2_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b2_residual_eltwise"
top: "inception_resnet_v2_b2_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b3_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b2_residual_eltwise"
top: "inception_resnet_v2_b3_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b3_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b3_1x1"
top: "inception_resnet_v2_b3_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b3_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b3_1x1"
top: "inception_resnet_v2_b3_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b3_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b3_1x1"
top: "inception_resnet_v2_b3_1x1"
}
layer {
name: "inception_resnet_v2_b3_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b2_residual_eltwise"
top: "inception_resnet_v2_b3_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b3_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b3_1x7_reduce"
top: "inception_resnet_v2_b3_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b3_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b3_1x7_reduce"
top: "inception_resnet_v2_b3_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b3_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b3_1x7_reduce"
top: "inception_resnet_v2_b3_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b3_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b3_1x7_reduce"
top: "inception_resnet_v2_b3_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b3_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b3_1x7"
top: "inception_resnet_v2_b3_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b3_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b3_1x7"
top: "inception_resnet_v2_b3_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b3_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b3_1x7"
top: "inception_resnet_v2_b3_1x7"
}
layer {
name: "inception_resnet_v2_b3_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b3_1x7"
top: "inception_resnet_v2_b3_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b3_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b3_7x1"
top: "inception_resnet_v2_b3_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b3_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b3_7x1"
top: "inception_resnet_v2_b3_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b3_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b3_7x1"
top: "inception_resnet_v2_b3_7x1"
}
layer {
name: "inception_resnet_v2_b3_concat"
type: "Concat"
bottom: "inception_resnet_v2_b3_1x1"
bottom: "inception_resnet_v2_b3_7x1"
top: "inception_resnet_v2_b3_concat"
}
layer {
name: "inception_resnet_v2_b3_up"
type: "Convolution"
bottom: "inception_resnet_v2_b3_concat"
top: "inception_resnet_v2_b3_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b3_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b2_residual_eltwise"
bottom: "inception_resnet_v2_b3_up"
top: "inception_resnet_v2_b3_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b3_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b3_residual_eltwise"
top: "inception_resnet_v2_b3_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b4_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b3_residual_eltwise"
top: "inception_resnet_v2_b4_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b4_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b4_1x1"
top: "inception_resnet_v2_b4_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b4_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b4_1x1"
top: "inception_resnet_v2_b4_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b4_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b4_1x1"
top: "inception_resnet_v2_b4_1x1"
}
layer {
name: "inception_resnet_v2_b4_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b3_residual_eltwise"
top: "inception_resnet_v2_b4_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b4_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b4_1x7_reduce"
top: "inception_resnet_v2_b4_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b4_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b4_1x7_reduce"
top: "inception_resnet_v2_b4_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b4_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b4_1x7_reduce"
top: "inception_resnet_v2_b4_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b4_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b4_1x7_reduce"
top: "inception_resnet_v2_b4_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b4_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b4_1x7"
top: "inception_resnet_v2_b4_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b4_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b4_1x7"
top: "inception_resnet_v2_b4_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b4_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b4_1x7"
top: "inception_resnet_v2_b4_1x7"
}
layer {
name: "inception_resnet_v2_b4_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b4_1x7"
top: "inception_resnet_v2_b4_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b4_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b4_7x1"
top: "inception_resnet_v2_b4_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b4_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b4_7x1"
top: "inception_resnet_v2_b4_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b4_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b4_7x1"
top: "inception_resnet_v2_b4_7x1"
}
layer {
name: "inception_resnet_v2_b4_concat"
type: "Concat"
bottom: "inception_resnet_v2_b4_1x1"
bottom: "inception_resnet_v2_b4_7x1"
top: "inception_resnet_v2_b4_concat"
}
layer {
name: "inception_resnet_v2_b4_up"
type: "Convolution"
bottom: "inception_resnet_v2_b4_concat"
top: "inception_resnet_v2_b4_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b4_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b3_residual_eltwise"
bottom: "inception_resnet_v2_b4_up"
top: "inception_resnet_v2_b4_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b4_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b4_residual_eltwise"
top: "inception_resnet_v2_b4_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b5_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b4_residual_eltwise"
top: "inception_resnet_v2_b5_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b5_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b5_1x1"
top: "inception_resnet_v2_b5_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b5_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b5_1x1"
top: "inception_resnet_v2_b5_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b5_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b5_1x1"
top: "inception_resnet_v2_b5_1x1"
}
layer {
name: "inception_resnet_v2_b5_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b4_residual_eltwise"
top: "inception_resnet_v2_b5_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b5_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b5_1x7_reduce"
top: "inception_resnet_v2_b5_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b5_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b5_1x7_reduce"
top: "inception_resnet_v2_b5_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b5_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b5_1x7_reduce"
top: "inception_resnet_v2_b5_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b5_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b5_1x7_reduce"
top: "inception_resnet_v2_b5_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b5_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b5_1x7"
top: "inception_resnet_v2_b5_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b5_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b5_1x7"
top: "inception_resnet_v2_b5_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b5_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b5_1x7"
top: "inception_resnet_v2_b5_1x7"
}
layer {
name: "inception_resnet_v2_b5_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b5_1x7"
top: "inception_resnet_v2_b5_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b5_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b5_7x1"
top: "inception_resnet_v2_b5_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b5_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b5_7x1"
top: "inception_resnet_v2_b5_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b5_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b5_7x1"
top: "inception_resnet_v2_b5_7x1"
}
layer {
name: "inception_resnet_v2_b5_concat"
type: "Concat"
bottom: "inception_resnet_v2_b5_1x1"
bottom: "inception_resnet_v2_b5_7x1"
top: "inception_resnet_v2_b5_concat"
}
layer {
name: "inception_resnet_v2_b5_up"
type: "Convolution"
bottom: "inception_resnet_v2_b5_concat"
top: "inception_resnet_v2_b5_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b5_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b4_residual_eltwise"
bottom: "inception_resnet_v2_b5_up"
top: "inception_resnet_v2_b5_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b5_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b5_residual_eltwise"
top: "inception_resnet_v2_b5_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b6_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b5_residual_eltwise"
top: "inception_resnet_v2_b6_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b6_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b6_1x1"
top: "inception_resnet_v2_b6_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b6_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b6_1x1"
top: "inception_resnet_v2_b6_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b6_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b6_1x1"
top: "inception_resnet_v2_b6_1x1"
}
layer {
name: "inception_resnet_v2_b6_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b5_residual_eltwise"
top: "inception_resnet_v2_b6_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b6_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b6_1x7_reduce"
top: "inception_resnet_v2_b6_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b6_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b6_1x7_reduce"
top: "inception_resnet_v2_b6_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b6_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b6_1x7_reduce"
top: "inception_resnet_v2_b6_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b6_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b6_1x7_reduce"
top: "inception_resnet_v2_b6_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b6_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b6_1x7"
top: "inception_resnet_v2_b6_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b6_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b6_1x7"
top: "inception_resnet_v2_b6_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b6_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b6_1x7"
top: "inception_resnet_v2_b6_1x7"
}
layer {
name: "inception_resnet_v2_b6_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b6_1x7"
top: "inception_resnet_v2_b6_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b6_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b6_7x1"
top: "inception_resnet_v2_b6_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b6_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b6_7x1"
top: "inception_resnet_v2_b6_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b6_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b6_7x1"
top: "inception_resnet_v2_b6_7x1"
}
layer {
name: "inception_resnet_v2_b6_concat"
type: "Concat"
bottom: "inception_resnet_v2_b6_1x1"
bottom: "inception_resnet_v2_b6_7x1"
top: "inception_resnet_v2_b6_concat"
}
layer {
name: "inception_resnet_v2_b6_up"
type: "Convolution"
bottom: "inception_resnet_v2_b6_concat"
top: "inception_resnet_v2_b6_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b6_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b5_residual_eltwise"
bottom: "inception_resnet_v2_b6_up"
top: "inception_resnet_v2_b6_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b6_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b6_residual_eltwise"
top: "inception_resnet_v2_b6_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b7_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b6_residual_eltwise"
top: "inception_resnet_v2_b7_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b7_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b7_1x1"
top: "inception_resnet_v2_b7_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b7_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b7_1x1"
top: "inception_resnet_v2_b7_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b7_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b7_1x1"
top: "inception_resnet_v2_b7_1x1"
}
layer {
name: "inception_resnet_v2_b7_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b6_residual_eltwise"
top: "inception_resnet_v2_b7_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b7_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b7_1x7_reduce"
top: "inception_resnet_v2_b7_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b7_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b7_1x7_reduce"
top: "inception_resnet_v2_b7_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b7_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b7_1x7_reduce"
top: "inception_resnet_v2_b7_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b7_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b7_1x7_reduce"
top: "inception_resnet_v2_b7_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b7_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b7_1x7"
top: "inception_resnet_v2_b7_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b7_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b7_1x7"
top: "inception_resnet_v2_b7_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b7_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b7_1x7"
top: "inception_resnet_v2_b7_1x7"
}
layer {
name: "inception_resnet_v2_b7_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b7_1x7"
top: "inception_resnet_v2_b7_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b7_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b7_7x1"
top: "inception_resnet_v2_b7_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b7_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b7_7x1"
top: "inception_resnet_v2_b7_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b7_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b7_7x1"
top: "inception_resnet_v2_b7_7x1"
}
layer {
name: "inception_resnet_v2_b7_concat"
type: "Concat"
bottom: "inception_resnet_v2_b7_1x1"
bottom: "inception_resnet_v2_b7_7x1"
top: "inception_resnet_v2_b7_concat"
}
layer {
name: "inception_resnet_v2_b7_up"
type: "Convolution"
bottom: "inception_resnet_v2_b7_concat"
top: "inception_resnet_v2_b7_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b7_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b6_residual_eltwise"
bottom: "inception_resnet_v2_b7_up"
top: "inception_resnet_v2_b7_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b7_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b7_residual_eltwise"
top: "inception_resnet_v2_b7_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b8_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b7_residual_eltwise"
top: "inception_resnet_v2_b8_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b8_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b8_1x1"
top: "inception_resnet_v2_b8_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b8_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b8_1x1"
top: "inception_resnet_v2_b8_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b8_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b8_1x1"
top: "inception_resnet_v2_b8_1x1"
}
layer {
name: "inception_resnet_v2_b8_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b7_residual_eltwise"
top: "inception_resnet_v2_b8_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b8_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b8_1x7_reduce"
top: "inception_resnet_v2_b8_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b8_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b8_1x7_reduce"
top: "inception_resnet_v2_b8_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b8_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b8_1x7_reduce"
top: "inception_resnet_v2_b8_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b8_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b8_1x7_reduce"
top: "inception_resnet_v2_b8_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b8_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b8_1x7"
top: "inception_resnet_v2_b8_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b8_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b8_1x7"
top: "inception_resnet_v2_b8_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b8_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b8_1x7"
top: "inception_resnet_v2_b8_1x7"
}
layer {
name: "inception_resnet_v2_b8_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b8_1x7"
top: "inception_resnet_v2_b8_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b8_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b8_7x1"
top: "inception_resnet_v2_b8_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b8_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b8_7x1"
top: "inception_resnet_v2_b8_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b8_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b8_7x1"
top: "inception_resnet_v2_b8_7x1"
}
layer {
name: "inception_resnet_v2_b8_concat"
type: "Concat"
bottom: "inception_resnet_v2_b8_1x1"
bottom: "inception_resnet_v2_b8_7x1"
top: "inception_resnet_v2_b8_concat"
}
layer {
name: "inception_resnet_v2_b8_up"
type: "Convolution"
bottom: "inception_resnet_v2_b8_concat"
top: "inception_resnet_v2_b8_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b8_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b7_residual_eltwise"
bottom: "inception_resnet_v2_b8_up"
top: "inception_resnet_v2_b8_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b8_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b8_residual_eltwise"
top: "inception_resnet_v2_b8_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b9_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b8_residual_eltwise"
top: "inception_resnet_v2_b9_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b9_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b9_1x1"
top: "inception_resnet_v2_b9_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b9_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b9_1x1"
top: "inception_resnet_v2_b9_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b9_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b9_1x1"
top: "inception_resnet_v2_b9_1x1"
}
layer {
name: "inception_resnet_v2_b9_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b8_residual_eltwise"
top: "inception_resnet_v2_b9_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b9_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b9_1x7_reduce"
top: "inception_resnet_v2_b9_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b9_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b9_1x7_reduce"
top: "inception_resnet_v2_b9_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b9_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b9_1x7_reduce"
top: "inception_resnet_v2_b9_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b9_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b9_1x7_reduce"
top: "inception_resnet_v2_b9_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b9_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b9_1x7"
top: "inception_resnet_v2_b9_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b9_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b9_1x7"
top: "inception_resnet_v2_b9_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b9_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b9_1x7"
top: "inception_resnet_v2_b9_1x7"
}
layer {
name: "inception_resnet_v2_b9_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b9_1x7"
top: "inception_resnet_v2_b9_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b9_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b9_7x1"
top: "inception_resnet_v2_b9_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b9_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b9_7x1"
top: "inception_resnet_v2_b9_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b9_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b9_7x1"
top: "inception_resnet_v2_b9_7x1"
}
layer {
name: "inception_resnet_v2_b9_concat"
type: "Concat"
bottom: "inception_resnet_v2_b9_1x1"
bottom: "inception_resnet_v2_b9_7x1"
top: "inception_resnet_v2_b9_concat"
}
layer {
name: "inception_resnet_v2_b9_up"
type: "Convolution"
bottom: "inception_resnet_v2_b9_concat"
top: "inception_resnet_v2_b9_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b9_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b8_residual_eltwise"
bottom: "inception_resnet_v2_b9_up"
top: "inception_resnet_v2_b9_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b9_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b9_residual_eltwise"
top: "inception_resnet_v2_b9_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b10_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b9_residual_eltwise"
top: "inception_resnet_v2_b10_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b10_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b10_1x1"
top: "inception_resnet_v2_b10_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b10_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b10_1x1"
top: "inception_resnet_v2_b10_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b10_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b10_1x1"
top: "inception_resnet_v2_b10_1x1"
}
layer {
name: "inception_resnet_v2_b10_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b9_residual_eltwise"
top: "inception_resnet_v2_b10_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b10_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b10_1x7_reduce"
top: "inception_resnet_v2_b10_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b10_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b10_1x7_reduce"
top: "inception_resnet_v2_b10_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b10_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b10_1x7_reduce"
top: "inception_resnet_v2_b10_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b10_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b10_1x7_reduce"
top: "inception_resnet_v2_b10_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b10_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b10_1x7"
top: "inception_resnet_v2_b10_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b10_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b10_1x7"
top: "inception_resnet_v2_b10_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b10_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b10_1x7"
top: "inception_resnet_v2_b10_1x7"
}
layer {
name: "inception_resnet_v2_b10_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b10_1x7"
top: "inception_resnet_v2_b10_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b10_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b10_7x1"
top: "inception_resnet_v2_b10_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b10_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b10_7x1"
top: "inception_resnet_v2_b10_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b10_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b10_7x1"
top: "inception_resnet_v2_b10_7x1"
}
layer {
name: "inception_resnet_v2_b10_concat"
type: "Concat"
bottom: "inception_resnet_v2_b10_1x1"
bottom: "inception_resnet_v2_b10_7x1"
top: "inception_resnet_v2_b10_concat"
}
layer {
name: "inception_resnet_v2_b10_up"
type: "Convolution"
bottom: "inception_resnet_v2_b10_concat"
top: "inception_resnet_v2_b10_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b10_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b9_residual_eltwise"
bottom: "inception_resnet_v2_b10_up"
top: "inception_resnet_v2_b10_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b10_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b10_residual_eltwise"
top: "inception_resnet_v2_b10_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b11_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b10_residual_eltwise"
top: "inception_resnet_v2_b11_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b11_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b11_1x1"
top: "inception_resnet_v2_b11_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b11_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b11_1x1"
top: "inception_resnet_v2_b11_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b11_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b11_1x1"
top: "inception_resnet_v2_b11_1x1"
}
layer {
name: "inception_resnet_v2_b11_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b10_residual_eltwise"
top: "inception_resnet_v2_b11_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b11_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b11_1x7_reduce"
top: "inception_resnet_v2_b11_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b11_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b11_1x7_reduce"
top: "inception_resnet_v2_b11_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b11_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b11_1x7_reduce"
top: "inception_resnet_v2_b11_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b11_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b11_1x7_reduce"
top: "inception_resnet_v2_b11_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b11_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b11_1x7"
top: "inception_resnet_v2_b11_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b11_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b11_1x7"
top: "inception_resnet_v2_b11_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b11_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b11_1x7"
top: "inception_resnet_v2_b11_1x7"
}
layer {
name: "inception_resnet_v2_b11_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b11_1x7"
top: "inception_resnet_v2_b11_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b11_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b11_7x1"
top: "inception_resnet_v2_b11_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b11_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b11_7x1"
top: "inception_resnet_v2_b11_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b11_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b11_7x1"
top: "inception_resnet_v2_b11_7x1"
}
layer {
name: "inception_resnet_v2_b11_concat"
type: "Concat"
bottom: "inception_resnet_v2_b11_1x1"
bottom: "inception_resnet_v2_b11_7x1"
top: "inception_resnet_v2_b11_concat"
}
layer {
name: "inception_resnet_v2_b11_up"
type: "Convolution"
bottom: "inception_resnet_v2_b11_concat"
top: "inception_resnet_v2_b11_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b11_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b10_residual_eltwise"
bottom: "inception_resnet_v2_b11_up"
top: "inception_resnet_v2_b11_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b11_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b11_residual_eltwise"
top: "inception_resnet_v2_b11_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b12_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b11_residual_eltwise"
top: "inception_resnet_v2_b12_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b12_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b12_1x1"
top: "inception_resnet_v2_b12_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b12_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b12_1x1"
top: "inception_resnet_v2_b12_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b12_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b12_1x1"
top: "inception_resnet_v2_b12_1x1"
}
layer {
name: "inception_resnet_v2_b12_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b11_residual_eltwise"
top: "inception_resnet_v2_b12_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b12_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b12_1x7_reduce"
top: "inception_resnet_v2_b12_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b12_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b12_1x7_reduce"
top: "inception_resnet_v2_b12_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b12_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b12_1x7_reduce"
top: "inception_resnet_v2_b12_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b12_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b12_1x7_reduce"
top: "inception_resnet_v2_b12_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b12_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b12_1x7"
top: "inception_resnet_v2_b12_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b12_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b12_1x7"
top: "inception_resnet_v2_b12_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b12_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b12_1x7"
top: "inception_resnet_v2_b12_1x7"
}
layer {
name: "inception_resnet_v2_b12_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b12_1x7"
top: "inception_resnet_v2_b12_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b12_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b12_7x1"
top: "inception_resnet_v2_b12_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b12_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b12_7x1"
top: "inception_resnet_v2_b12_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b12_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b12_7x1"
top: "inception_resnet_v2_b12_7x1"
}
layer {
name: "inception_resnet_v2_b12_concat"
type: "Concat"
bottom: "inception_resnet_v2_b12_1x1"
bottom: "inception_resnet_v2_b12_7x1"
top: "inception_resnet_v2_b12_concat"
}
layer {
name: "inception_resnet_v2_b12_up"
type: "Convolution"
bottom: "inception_resnet_v2_b12_concat"
top: "inception_resnet_v2_b12_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b12_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b11_residual_eltwise"
bottom: "inception_resnet_v2_b12_up"
top: "inception_resnet_v2_b12_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b12_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b12_residual_eltwise"
top: "inception_resnet_v2_b12_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b13_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b12_residual_eltwise"
top: "inception_resnet_v2_b13_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b13_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b13_1x1"
top: "inception_resnet_v2_b13_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b13_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b13_1x1"
top: "inception_resnet_v2_b13_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b13_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b13_1x1"
top: "inception_resnet_v2_b13_1x1"
}
layer {
name: "inception_resnet_v2_b13_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b12_residual_eltwise"
top: "inception_resnet_v2_b13_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b13_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b13_1x7_reduce"
top: "inception_resnet_v2_b13_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b13_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b13_1x7_reduce"
top: "inception_resnet_v2_b13_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b13_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b13_1x7_reduce"
top: "inception_resnet_v2_b13_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b13_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b13_1x7_reduce"
top: "inception_resnet_v2_b13_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b13_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b13_1x7"
top: "inception_resnet_v2_b13_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b13_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b13_1x7"
top: "inception_resnet_v2_b13_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b13_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b13_1x7"
top: "inception_resnet_v2_b13_1x7"
}
layer {
name: "inception_resnet_v2_b13_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b13_1x7"
top: "inception_resnet_v2_b13_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b13_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b13_7x1"
top: "inception_resnet_v2_b13_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b13_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b13_7x1"
top: "inception_resnet_v2_b13_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b13_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b13_7x1"
top: "inception_resnet_v2_b13_7x1"
}
layer {
name: "inception_resnet_v2_b13_concat"
type: "Concat"
bottom: "inception_resnet_v2_b13_1x1"
bottom: "inception_resnet_v2_b13_7x1"
top: "inception_resnet_v2_b13_concat"
}
layer {
name: "inception_resnet_v2_b13_up"
type: "Convolution"
bottom: "inception_resnet_v2_b13_concat"
top: "inception_resnet_v2_b13_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b13_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b12_residual_eltwise"
bottom: "inception_resnet_v2_b13_up"
top: "inception_resnet_v2_b13_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b13_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b13_residual_eltwise"
top: "inception_resnet_v2_b13_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b14_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b13_residual_eltwise"
top: "inception_resnet_v2_b14_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b14_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b14_1x1"
top: "inception_resnet_v2_b14_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b14_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b14_1x1"
top: "inception_resnet_v2_b14_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b14_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b14_1x1"
top: "inception_resnet_v2_b14_1x1"
}
layer {
name: "inception_resnet_v2_b14_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b13_residual_eltwise"
top: "inception_resnet_v2_b14_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b14_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b14_1x7_reduce"
top: "inception_resnet_v2_b14_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b14_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b14_1x7_reduce"
top: "inception_resnet_v2_b14_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b14_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b14_1x7_reduce"
top: "inception_resnet_v2_b14_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b14_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b14_1x7_reduce"
top: "inception_resnet_v2_b14_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b14_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b14_1x7"
top: "inception_resnet_v2_b14_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b14_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b14_1x7"
top: "inception_resnet_v2_b14_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b14_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b14_1x7"
top: "inception_resnet_v2_b14_1x7"
}
layer {
name: "inception_resnet_v2_b14_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b14_1x7"
top: "inception_resnet_v2_b14_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b14_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b14_7x1"
top: "inception_resnet_v2_b14_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b14_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b14_7x1"
top: "inception_resnet_v2_b14_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b14_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b14_7x1"
top: "inception_resnet_v2_b14_7x1"
}
layer {
name: "inception_resnet_v2_b14_concat"
type: "Concat"
bottom: "inception_resnet_v2_b14_1x1"
bottom: "inception_resnet_v2_b14_7x1"
top: "inception_resnet_v2_b14_concat"
}
layer {
name: "inception_resnet_v2_b14_up"
type: "Convolution"
bottom: "inception_resnet_v2_b14_concat"
top: "inception_resnet_v2_b14_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b14_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b13_residual_eltwise"
bottom: "inception_resnet_v2_b14_up"
top: "inception_resnet_v2_b14_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b14_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b14_residual_eltwise"
top: "inception_resnet_v2_b14_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b15_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b14_residual_eltwise"
top: "inception_resnet_v2_b15_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b15_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b15_1x1"
top: "inception_resnet_v2_b15_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b15_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b15_1x1"
top: "inception_resnet_v2_b15_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b15_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b15_1x1"
top: "inception_resnet_v2_b15_1x1"
}
layer {
name: "inception_resnet_v2_b15_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b14_residual_eltwise"
top: "inception_resnet_v2_b15_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b15_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b15_1x7_reduce"
top: "inception_resnet_v2_b15_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b15_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b15_1x7_reduce"
top: "inception_resnet_v2_b15_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b15_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b15_1x7_reduce"
top: "inception_resnet_v2_b15_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b15_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b15_1x7_reduce"
top: "inception_resnet_v2_b15_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b15_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b15_1x7"
top: "inception_resnet_v2_b15_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b15_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b15_1x7"
top: "inception_resnet_v2_b15_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b15_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b15_1x7"
top: "inception_resnet_v2_b15_1x7"
}
layer {
name: "inception_resnet_v2_b15_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b15_1x7"
top: "inception_resnet_v2_b15_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b15_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b15_7x1"
top: "inception_resnet_v2_b15_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b15_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b15_7x1"
top: "inception_resnet_v2_b15_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b15_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b15_7x1"
top: "inception_resnet_v2_b15_7x1"
}
layer {
name: "inception_resnet_v2_b15_concat"
type: "Concat"
bottom: "inception_resnet_v2_b15_1x1"
bottom: "inception_resnet_v2_b15_7x1"
top: "inception_resnet_v2_b15_concat"
}
layer {
name: "inception_resnet_v2_b15_up"
type: "Convolution"
bottom: "inception_resnet_v2_b15_concat"
top: "inception_resnet_v2_b15_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b15_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b14_residual_eltwise"
bottom: "inception_resnet_v2_b15_up"
top: "inception_resnet_v2_b15_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b15_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b15_residual_eltwise"
top: "inception_resnet_v2_b15_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b16_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b15_residual_eltwise"
top: "inception_resnet_v2_b16_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b16_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b16_1x1"
top: "inception_resnet_v2_b16_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b16_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b16_1x1"
top: "inception_resnet_v2_b16_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b16_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b16_1x1"
top: "inception_resnet_v2_b16_1x1"
}
layer {
name: "inception_resnet_v2_b16_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b15_residual_eltwise"
top: "inception_resnet_v2_b16_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b16_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b16_1x7_reduce"
top: "inception_resnet_v2_b16_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b16_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b16_1x7_reduce"
top: "inception_resnet_v2_b16_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b16_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b16_1x7_reduce"
top: "inception_resnet_v2_b16_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b16_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b16_1x7_reduce"
top: "inception_resnet_v2_b16_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b16_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b16_1x7"
top: "inception_resnet_v2_b16_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b16_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b16_1x7"
top: "inception_resnet_v2_b16_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b16_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b16_1x7"
top: "inception_resnet_v2_b16_1x7"
}
layer {
name: "inception_resnet_v2_b16_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b16_1x7"
top: "inception_resnet_v2_b16_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b16_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b16_7x1"
top: "inception_resnet_v2_b16_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b16_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b16_7x1"
top: "inception_resnet_v2_b16_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b16_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b16_7x1"
top: "inception_resnet_v2_b16_7x1"
}
layer {
name: "inception_resnet_v2_b16_concat"
type: "Concat"
bottom: "inception_resnet_v2_b16_1x1"
bottom: "inception_resnet_v2_b16_7x1"
top: "inception_resnet_v2_b16_concat"
}
layer {
name: "inception_resnet_v2_b16_up"
type: "Convolution"
bottom: "inception_resnet_v2_b16_concat"
top: "inception_resnet_v2_b16_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b16_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b15_residual_eltwise"
bottom: "inception_resnet_v2_b16_up"
top: "inception_resnet_v2_b16_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b16_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b16_residual_eltwise"
top: "inception_resnet_v2_b16_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b17_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b16_residual_eltwise"
top: "inception_resnet_v2_b17_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b17_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b17_1x1"
top: "inception_resnet_v2_b17_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b17_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b17_1x1"
top: "inception_resnet_v2_b17_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b17_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b17_1x1"
top: "inception_resnet_v2_b17_1x1"
}
layer {
name: "inception_resnet_v2_b17_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b16_residual_eltwise"
top: "inception_resnet_v2_b17_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b17_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b17_1x7_reduce"
top: "inception_resnet_v2_b17_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b17_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b17_1x7_reduce"
top: "inception_resnet_v2_b17_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b17_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b17_1x7_reduce"
top: "inception_resnet_v2_b17_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b17_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b17_1x7_reduce"
top: "inception_resnet_v2_b17_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b17_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b17_1x7"
top: "inception_resnet_v2_b17_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b17_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b17_1x7"
top: "inception_resnet_v2_b17_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b17_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b17_1x7"
top: "inception_resnet_v2_b17_1x7"
}
layer {
name: "inception_resnet_v2_b17_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b17_1x7"
top: "inception_resnet_v2_b17_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b17_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b17_7x1"
top: "inception_resnet_v2_b17_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b17_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b17_7x1"
top: "inception_resnet_v2_b17_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b17_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b17_7x1"
top: "inception_resnet_v2_b17_7x1"
}
layer {
name: "inception_resnet_v2_b17_concat"
type: "Concat"
bottom: "inception_resnet_v2_b17_1x1"
bottom: "inception_resnet_v2_b17_7x1"
top: "inception_resnet_v2_b17_concat"
}
layer {
name: "inception_resnet_v2_b17_up"
type: "Convolution"
bottom: "inception_resnet_v2_b17_concat"
top: "inception_resnet_v2_b17_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b17_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b16_residual_eltwise"
bottom: "inception_resnet_v2_b17_up"
top: "inception_resnet_v2_b17_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b17_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b17_residual_eltwise"
top: "inception_resnet_v2_b17_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b18_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b17_residual_eltwise"
top: "inception_resnet_v2_b18_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b18_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b18_1x1"
top: "inception_resnet_v2_b18_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b18_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b18_1x1"
top: "inception_resnet_v2_b18_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b18_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b18_1x1"
top: "inception_resnet_v2_b18_1x1"
}
layer {
name: "inception_resnet_v2_b18_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b17_residual_eltwise"
top: "inception_resnet_v2_b18_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b18_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b18_1x7_reduce"
top: "inception_resnet_v2_b18_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b18_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b18_1x7_reduce"
top: "inception_resnet_v2_b18_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b18_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b18_1x7_reduce"
top: "inception_resnet_v2_b18_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b18_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b18_1x7_reduce"
top: "inception_resnet_v2_b18_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b18_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b18_1x7"
top: "inception_resnet_v2_b18_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b18_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b18_1x7"
top: "inception_resnet_v2_b18_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b18_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b18_1x7"
top: "inception_resnet_v2_b18_1x7"
}
layer {
name: "inception_resnet_v2_b18_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b18_1x7"
top: "inception_resnet_v2_b18_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b18_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b18_7x1"
top: "inception_resnet_v2_b18_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b18_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b18_7x1"
top: "inception_resnet_v2_b18_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b18_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b18_7x1"
top: "inception_resnet_v2_b18_7x1"
}
layer {
name: "inception_resnet_v2_b18_concat"
type: "Concat"
bottom: "inception_resnet_v2_b18_1x1"
bottom: "inception_resnet_v2_b18_7x1"
top: "inception_resnet_v2_b18_concat"
}
layer {
name: "inception_resnet_v2_b18_up"
type: "Convolution"
bottom: "inception_resnet_v2_b18_concat"
top: "inception_resnet_v2_b18_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b18_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b17_residual_eltwise"
bottom: "inception_resnet_v2_b18_up"
top: "inception_resnet_v2_b18_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b18_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b18_residual_eltwise"
top: "inception_resnet_v2_b18_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b19_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b18_residual_eltwise"
top: "inception_resnet_v2_b19_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b19_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b19_1x1"
top: "inception_resnet_v2_b19_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b19_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b19_1x1"
top: "inception_resnet_v2_b19_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b19_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b19_1x1"
top: "inception_resnet_v2_b19_1x1"
}
layer {
name: "inception_resnet_v2_b19_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b18_residual_eltwise"
top: "inception_resnet_v2_b19_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b19_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b19_1x7_reduce"
top: "inception_resnet_v2_b19_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b19_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b19_1x7_reduce"
top: "inception_resnet_v2_b19_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b19_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b19_1x7_reduce"
top: "inception_resnet_v2_b19_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b19_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b19_1x7_reduce"
top: "inception_resnet_v2_b19_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b19_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b19_1x7"
top: "inception_resnet_v2_b19_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b19_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b19_1x7"
top: "inception_resnet_v2_b19_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b19_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b19_1x7"
top: "inception_resnet_v2_b19_1x7"
}
layer {
name: "inception_resnet_v2_b19_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b19_1x7"
top: "inception_resnet_v2_b19_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b19_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b19_7x1"
top: "inception_resnet_v2_b19_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b19_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b19_7x1"
top: "inception_resnet_v2_b19_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b19_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b19_7x1"
top: "inception_resnet_v2_b19_7x1"
}
layer {
name: "inception_resnet_v2_b19_concat"
type: "Concat"
bottom: "inception_resnet_v2_b19_1x1"
bottom: "inception_resnet_v2_b19_7x1"
top: "inception_resnet_v2_b19_concat"
}
layer {
name: "inception_resnet_v2_b19_up"
type: "Convolution"
bottom: "inception_resnet_v2_b19_concat"
top: "inception_resnet_v2_b19_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b19_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b18_residual_eltwise"
bottom: "inception_resnet_v2_b19_up"
top: "inception_resnet_v2_b19_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b19_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b19_residual_eltwise"
top: "inception_resnet_v2_b19_residual_eltwise"
}
layer {
name: "inception_resnet_v2_b20_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_b19_residual_eltwise"
top: "inception_resnet_v2_b20_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b20_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b20_1x1"
top: "inception_resnet_v2_b20_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b20_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b20_1x1"
top: "inception_resnet_v2_b20_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b20_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b20_1x1"
top: "inception_resnet_v2_b20_1x1"
}
layer {
name: "inception_resnet_v2_b20_1x7_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b19_residual_eltwise"
top: "inception_resnet_v2_b20_1x7_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_b20_1x7_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b20_1x7_reduce"
top: "inception_resnet_v2_b20_1x7_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b20_1x7_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_b20_1x7_reduce"
top: "inception_resnet_v2_b20_1x7_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b20_1x7_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b20_1x7_reduce"
top: "inception_resnet_v2_b20_1x7_reduce"
}
layer {
name: "inception_resnet_v2_b20_1x7"
type: "Convolution"
bottom: "inception_resnet_v2_b20_1x7_reduce"
top: "inception_resnet_v2_b20_1x7"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 160
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 3
kernel_h: 1
kernel_w: 7
}
}
layer {
name: "inception_resnet_v2_b20_1x7_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b20_1x7"
top: "inception_resnet_v2_b20_1x7"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b20_1x7_scale"
type: "Scale"
bottom: "inception_resnet_v2_b20_1x7"
top: "inception_resnet_v2_b20_1x7"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b20_1x7_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b20_1x7"
top: "inception_resnet_v2_b20_1x7"
}
layer {
name: "inception_resnet_v2_b20_7x1"
type: "Convolution"
bottom: "inception_resnet_v2_b20_1x7"
top: "inception_resnet_v2_b20_7x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 3
pad_w: 0
kernel_h: 7
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_b20_7x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_b20_7x1"
top: "inception_resnet_v2_b20_7x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_b20_7x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_b20_7x1"
top: "inception_resnet_v2_b20_7x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_b20_7x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b20_7x1"
top: "inception_resnet_v2_b20_7x1"
}
layer {
name: "inception_resnet_v2_b20_concat"
type: "Concat"
bottom: "inception_resnet_v2_b20_1x1"
bottom: "inception_resnet_v2_b20_7x1"
top: "inception_resnet_v2_b20_concat"
}
layer {
name: "inception_resnet_v2_b20_up"
type: "Convolution"
bottom: "inception_resnet_v2_b20_concat"
top: "inception_resnet_v2_b20_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 1088
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_b20_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_b19_residual_eltwise"
bottom: "inception_resnet_v2_b20_up"
top: "inception_resnet_v2_b20_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.1
}
}
layer {
name: "inception_resnet_v2_b20_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_b20_residual_eltwise"
top: "inception_resnet_v2_b20_residual_eltwise"
}
layer {
name: "reduction_b_3x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b20_residual_eltwise"
top: "reduction_b_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_reduce_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3_reduce"
top: "reduction_b_3x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_reduce_scale"
type: "Scale"
bottom: "reduction_b_3x3_reduce"
top: "reduction_b_3x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_reduce_relu"
type: "ReLU"
bottom: "reduction_b_3x3_reduce"
top: "reduction_b_3x3_reduce"
}
layer {
name: "reduction_b_3x3"
type: "Convolution"
bottom: "reduction_b_3x3_reduce"
top: "reduction_b_3x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 384
bias_term: false
pad: 0
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3"
top: "reduction_b_3x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_scale"
type: "Scale"
bottom: "reduction_b_3x3"
top: "reduction_b_3x3"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_relu"
type: "ReLU"
bottom: "reduction_b_3x3"
top: "reduction_b_3x3"
}
layer {
name: "reduction_b_3x3_2_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b20_residual_eltwise"
top: "reduction_b_3x3_2_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_2_reduce_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3_2_reduce"
top: "reduction_b_3x3_2_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_2_reduce_scale"
type: "Scale"
bottom: "reduction_b_3x3_2_reduce"
top: "reduction_b_3x3_2_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_2_reduce_relu"
type: "ReLU"
bottom: "reduction_b_3x3_2_reduce"
top: "reduction_b_3x3_2_reduce"
}
layer {
name: "reduction_b_3x3_2"
type: "Convolution"
bottom: "reduction_b_3x3_2_reduce"
top: "reduction_b_3x3_2"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 288
bias_term: false
pad: 0
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_2_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3_2"
top: "reduction_b_3x3_2"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_2_scale"
type: "Scale"
bottom: "reduction_b_3x3_2"
top: "reduction_b_3x3_2"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_2_relu"
type: "ReLU"
bottom: "reduction_b_3x3_2"
top: "reduction_b_3x3_2"
}
layer {
name: "reduction_b_3x3_3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_b20_residual_eltwise"
top: "reduction_b_3x3_3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_3_reduce_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3_3_reduce"
top: "reduction_b_3x3_3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_3_reduce_scale"
type: "Scale"
bottom: "reduction_b_3x3_3_reduce"
top: "reduction_b_3x3_3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_3_reduce_relu"
type: "ReLU"
bottom: "reduction_b_3x3_3_reduce"
top: "reduction_b_3x3_3_reduce"
}
layer {
name: "reduction_b_3x3_3"
type: "Convolution"
bottom: "reduction_b_3x3_3_reduce"
top: "reduction_b_3x3_3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 288
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_3_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3_3"
top: "reduction_b_3x3_3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_3_scale"
type: "Scale"
bottom: "reduction_b_3x3_3"
top: "reduction_b_3x3_3"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_3_relu"
type: "ReLU"
bottom: "reduction_b_3x3_3"
top: "reduction_b_3x3_3"
}
layer {
name: "reduction_b_3x3_4"
type: "Convolution"
bottom: "reduction_b_3x3_3"
top: "reduction_b_3x3_4"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 320
bias_term: false
pad: 0
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "reduction_b_3x3_4_bn"
type: "BatchNorm"
bottom: "reduction_b_3x3_4"
top: "reduction_b_3x3_4"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "reduction_b_3x3_4_scale"
type: "Scale"
bottom: "reduction_b_3x3_4"
top: "reduction_b_3x3_4"
scale_param {
bias_term: true
}
}
layer {
name: "reduction_b_3x3_4_relu"
type: "ReLU"
bottom: "reduction_b_3x3_4"
top: "reduction_b_3x3_4"
}
layer {
name: "reduction_b_pool"
type: "Pooling"
bottom: "inception_resnet_v2_b20_residual_eltwise"
top: "reduction_b_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "reduction_b_concat"
type: "Concat"
bottom: "reduction_b_3x3"
bottom: "reduction_b_3x3_2"
bottom: "reduction_b_3x3_4"
bottom: "reduction_b_pool"
top: "reduction_b_concat"
}
layer {
name: "inception_resnet_v2_c1_1x1"
type: "Convolution"
bottom: "reduction_b_concat"
top: "inception_resnet_v2_c1_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c1_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c1_1x1"
top: "inception_resnet_v2_c1_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c1_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c1_1x1"
top: "inception_resnet_v2_c1_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c1_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c1_1x1"
top: "inception_resnet_v2_c1_1x1"
}
layer {
name: "inception_resnet_v2_c1_1x3_reduce"
type: "Convolution"
bottom: "reduction_b_concat"
top: "inception_resnet_v2_c1_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c1_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c1_1x3_reduce"
top: "inception_resnet_v2_c1_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c1_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c1_1x3_reduce"
top: "inception_resnet_v2_c1_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c1_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c1_1x3_reduce"
top: "inception_resnet_v2_c1_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c1_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c1_1x3_reduce"
top: "inception_resnet_v2_c1_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c1_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c1_1x3"
top: "inception_resnet_v2_c1_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c1_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c1_1x3"
top: "inception_resnet_v2_c1_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c1_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c1_1x3"
top: "inception_resnet_v2_c1_1x3"
}
layer {
name: "inception_resnet_v2_c1_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c1_1x3"
top: "inception_resnet_v2_c1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c1_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c1_3x1"
top: "inception_resnet_v2_c1_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c1_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c1_3x1"
top: "inception_resnet_v2_c1_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c1_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c1_3x1"
top: "inception_resnet_v2_c1_3x1"
}
layer {
name: "inception_resnet_v2_c1_concat"
type: "Concat"
bottom: "inception_resnet_v2_c1_1x1"
bottom: "inception_resnet_v2_c1_3x1"
top: "inception_resnet_v2_c1_concat"
}
layer {
name: "inception_resnet_v2_c1_up"
type: "Convolution"
bottom: "inception_resnet_v2_c1_concat"
top: "inception_resnet_v2_c1_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c1_residual_eltwise"
type: "Eltwise"
bottom: "reduction_b_concat"
bottom: "inception_resnet_v2_c1_up"
top: "inception_resnet_v2_c1_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c1_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c1_residual_eltwise"
top: "inception_resnet_v2_c1_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c2_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c1_residual_eltwise"
top: "inception_resnet_v2_c2_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c2_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c2_1x1"
top: "inception_resnet_v2_c2_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c2_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c2_1x1"
top: "inception_resnet_v2_c2_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c2_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c2_1x1"
top: "inception_resnet_v2_c2_1x1"
}
layer {
name: "inception_resnet_v2_c2_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c1_residual_eltwise"
top: "inception_resnet_v2_c2_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c2_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c2_1x3_reduce"
top: "inception_resnet_v2_c2_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c2_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c2_1x3_reduce"
top: "inception_resnet_v2_c2_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c2_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c2_1x3_reduce"
top: "inception_resnet_v2_c2_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c2_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c2_1x3_reduce"
top: "inception_resnet_v2_c2_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c2_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c2_1x3"
top: "inception_resnet_v2_c2_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c2_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c2_1x3"
top: "inception_resnet_v2_c2_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c2_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c2_1x3"
top: "inception_resnet_v2_c2_1x3"
}
layer {
name: "inception_resnet_v2_c2_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c2_1x3"
top: "inception_resnet_v2_c2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c2_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c2_3x1"
top: "inception_resnet_v2_c2_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c2_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c2_3x1"
top: "inception_resnet_v2_c2_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c2_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c2_3x1"
top: "inception_resnet_v2_c2_3x1"
}
layer {
name: "inception_resnet_v2_c2_concat"
type: "Concat"
bottom: "inception_resnet_v2_c2_1x1"
bottom: "inception_resnet_v2_c2_3x1"
top: "inception_resnet_v2_c2_concat"
}
layer {
name: "inception_resnet_v2_c2_up"
type: "Convolution"
bottom: "inception_resnet_v2_c2_concat"
top: "inception_resnet_v2_c2_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c2_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c1_residual_eltwise"
bottom: "inception_resnet_v2_c2_up"
top: "inception_resnet_v2_c2_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c2_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c2_residual_eltwise"
top: "inception_resnet_v2_c2_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c3_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c2_residual_eltwise"
top: "inception_resnet_v2_c3_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c3_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c3_1x1"
top: "inception_resnet_v2_c3_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c3_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c3_1x1"
top: "inception_resnet_v2_c3_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c3_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c3_1x1"
top: "inception_resnet_v2_c3_1x1"
}
layer {
name: "inception_resnet_v2_c3_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c2_residual_eltwise"
top: "inception_resnet_v2_c3_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c3_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c3_1x3_reduce"
top: "inception_resnet_v2_c3_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c3_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c3_1x3_reduce"
top: "inception_resnet_v2_c3_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c3_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c3_1x3_reduce"
top: "inception_resnet_v2_c3_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c3_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c3_1x3_reduce"
top: "inception_resnet_v2_c3_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c3_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c3_1x3"
top: "inception_resnet_v2_c3_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c3_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c3_1x3"
top: "inception_resnet_v2_c3_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c3_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c3_1x3"
top: "inception_resnet_v2_c3_1x3"
}
layer {
name: "inception_resnet_v2_c3_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c3_1x3"
top: "inception_resnet_v2_c3_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c3_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c3_3x1"
top: "inception_resnet_v2_c3_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c3_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c3_3x1"
top: "inception_resnet_v2_c3_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c3_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c3_3x1"
top: "inception_resnet_v2_c3_3x1"
}
layer {
name: "inception_resnet_v2_c3_concat"
type: "Concat"
bottom: "inception_resnet_v2_c3_1x1"
bottom: "inception_resnet_v2_c3_3x1"
top: "inception_resnet_v2_c3_concat"
}
layer {
name: "inception_resnet_v2_c3_up"
type: "Convolution"
bottom: "inception_resnet_v2_c3_concat"
top: "inception_resnet_v2_c3_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c3_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c2_residual_eltwise"
bottom: "inception_resnet_v2_c3_up"
top: "inception_resnet_v2_c3_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c3_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c3_residual_eltwise"
top: "inception_resnet_v2_c3_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c4_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c3_residual_eltwise"
top: "inception_resnet_v2_c4_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c4_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c4_1x1"
top: "inception_resnet_v2_c4_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c4_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c4_1x1"
top: "inception_resnet_v2_c4_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c4_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c4_1x1"
top: "inception_resnet_v2_c4_1x1"
}
layer {
name: "inception_resnet_v2_c4_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c3_residual_eltwise"
top: "inception_resnet_v2_c4_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c4_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c4_1x3_reduce"
top: "inception_resnet_v2_c4_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c4_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c4_1x3_reduce"
top: "inception_resnet_v2_c4_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c4_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c4_1x3_reduce"
top: "inception_resnet_v2_c4_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c4_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c4_1x3_reduce"
top: "inception_resnet_v2_c4_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c4_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c4_1x3"
top: "inception_resnet_v2_c4_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c4_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c4_1x3"
top: "inception_resnet_v2_c4_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c4_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c4_1x3"
top: "inception_resnet_v2_c4_1x3"
}
layer {
name: "inception_resnet_v2_c4_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c4_1x3"
top: "inception_resnet_v2_c4_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c4_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c4_3x1"
top: "inception_resnet_v2_c4_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c4_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c4_3x1"
top: "inception_resnet_v2_c4_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c4_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c4_3x1"
top: "inception_resnet_v2_c4_3x1"
}
layer {
name: "inception_resnet_v2_c4_concat"
type: "Concat"
bottom: "inception_resnet_v2_c4_1x1"
bottom: "inception_resnet_v2_c4_3x1"
top: "inception_resnet_v2_c4_concat"
}
layer {
name: "inception_resnet_v2_c4_up"
type: "Convolution"
bottom: "inception_resnet_v2_c4_concat"
top: "inception_resnet_v2_c4_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c4_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c3_residual_eltwise"
bottom: "inception_resnet_v2_c4_up"
top: "inception_resnet_v2_c4_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c4_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c4_residual_eltwise"
top: "inception_resnet_v2_c4_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c5_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c4_residual_eltwise"
top: "inception_resnet_v2_c5_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c5_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c5_1x1"
top: "inception_resnet_v2_c5_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c5_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c5_1x1"
top: "inception_resnet_v2_c5_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c5_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c5_1x1"
top: "inception_resnet_v2_c5_1x1"
}
layer {
name: "inception_resnet_v2_c5_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c4_residual_eltwise"
top: "inception_resnet_v2_c5_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c5_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c5_1x3_reduce"
top: "inception_resnet_v2_c5_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c5_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c5_1x3_reduce"
top: "inception_resnet_v2_c5_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c5_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c5_1x3_reduce"
top: "inception_resnet_v2_c5_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c5_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c5_1x3_reduce"
top: "inception_resnet_v2_c5_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c5_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c5_1x3"
top: "inception_resnet_v2_c5_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c5_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c5_1x3"
top: "inception_resnet_v2_c5_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c5_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c5_1x3"
top: "inception_resnet_v2_c5_1x3"
}
layer {
name: "inception_resnet_v2_c5_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c5_1x3"
top: "inception_resnet_v2_c5_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c5_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c5_3x1"
top: "inception_resnet_v2_c5_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c5_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c5_3x1"
top: "inception_resnet_v2_c5_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c5_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c5_3x1"
top: "inception_resnet_v2_c5_3x1"
}
layer {
name: "inception_resnet_v2_c5_concat"
type: "Concat"
bottom: "inception_resnet_v2_c5_1x1"
bottom: "inception_resnet_v2_c5_3x1"
top: "inception_resnet_v2_c5_concat"
}
layer {
name: "inception_resnet_v2_c5_up"
type: "Convolution"
bottom: "inception_resnet_v2_c5_concat"
top: "inception_resnet_v2_c5_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c5_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c4_residual_eltwise"
bottom: "inception_resnet_v2_c5_up"
top: "inception_resnet_v2_c5_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c5_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c5_residual_eltwise"
top: "inception_resnet_v2_c5_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c6_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c5_residual_eltwise"
top: "inception_resnet_v2_c6_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c6_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c6_1x1"
top: "inception_resnet_v2_c6_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c6_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c6_1x1"
top: "inception_resnet_v2_c6_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c6_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c6_1x1"
top: "inception_resnet_v2_c6_1x1"
}
layer {
name: "inception_resnet_v2_c6_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c5_residual_eltwise"
top: "inception_resnet_v2_c6_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c6_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c6_1x3_reduce"
top: "inception_resnet_v2_c6_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c6_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c6_1x3_reduce"
top: "inception_resnet_v2_c6_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c6_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c6_1x3_reduce"
top: "inception_resnet_v2_c6_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c6_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c6_1x3_reduce"
top: "inception_resnet_v2_c6_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c6_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c6_1x3"
top: "inception_resnet_v2_c6_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c6_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c6_1x3"
top: "inception_resnet_v2_c6_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c6_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c6_1x3"
top: "inception_resnet_v2_c6_1x3"
}
layer {
name: "inception_resnet_v2_c6_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c6_1x3"
top: "inception_resnet_v2_c6_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c6_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c6_3x1"
top: "inception_resnet_v2_c6_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c6_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c6_3x1"
top: "inception_resnet_v2_c6_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c6_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c6_3x1"
top: "inception_resnet_v2_c6_3x1"
}
layer {
name: "inception_resnet_v2_c6_concat"
type: "Concat"
bottom: "inception_resnet_v2_c6_1x1"
bottom: "inception_resnet_v2_c6_3x1"
top: "inception_resnet_v2_c6_concat"
}
layer {
name: "inception_resnet_v2_c6_up"
type: "Convolution"
bottom: "inception_resnet_v2_c6_concat"
top: "inception_resnet_v2_c6_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c6_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c5_residual_eltwise"
bottom: "inception_resnet_v2_c6_up"
top: "inception_resnet_v2_c6_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c6_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c6_residual_eltwise"
top: "inception_resnet_v2_c6_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c7_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c6_residual_eltwise"
top: "inception_resnet_v2_c7_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c7_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c7_1x1"
top: "inception_resnet_v2_c7_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c7_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c7_1x1"
top: "inception_resnet_v2_c7_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c7_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c7_1x1"
top: "inception_resnet_v2_c7_1x1"
}
layer {
name: "inception_resnet_v2_c7_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c6_residual_eltwise"
top: "inception_resnet_v2_c7_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c7_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c7_1x3_reduce"
top: "inception_resnet_v2_c7_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c7_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c7_1x3_reduce"
top: "inception_resnet_v2_c7_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c7_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c7_1x3_reduce"
top: "inception_resnet_v2_c7_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c7_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c7_1x3_reduce"
top: "inception_resnet_v2_c7_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c7_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c7_1x3"
top: "inception_resnet_v2_c7_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c7_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c7_1x3"
top: "inception_resnet_v2_c7_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c7_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c7_1x3"
top: "inception_resnet_v2_c7_1x3"
}
layer {
name: "inception_resnet_v2_c7_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c7_1x3"
top: "inception_resnet_v2_c7_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c7_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c7_3x1"
top: "inception_resnet_v2_c7_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c7_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c7_3x1"
top: "inception_resnet_v2_c7_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c7_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c7_3x1"
top: "inception_resnet_v2_c7_3x1"
}
layer {
name: "inception_resnet_v2_c7_concat"
type: "Concat"
bottom: "inception_resnet_v2_c7_1x1"
bottom: "inception_resnet_v2_c7_3x1"
top: "inception_resnet_v2_c7_concat"
}
layer {
name: "inception_resnet_v2_c7_up"
type: "Convolution"
bottom: "inception_resnet_v2_c7_concat"
top: "inception_resnet_v2_c7_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c7_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c6_residual_eltwise"
bottom: "inception_resnet_v2_c7_up"
top: "inception_resnet_v2_c7_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c7_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c7_residual_eltwise"
top: "inception_resnet_v2_c7_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c8_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c7_residual_eltwise"
top: "inception_resnet_v2_c8_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c8_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c8_1x1"
top: "inception_resnet_v2_c8_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c8_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c8_1x1"
top: "inception_resnet_v2_c8_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c8_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c8_1x1"
top: "inception_resnet_v2_c8_1x1"
}
layer {
name: "inception_resnet_v2_c8_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c7_residual_eltwise"
top: "inception_resnet_v2_c8_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c8_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c8_1x3_reduce"
top: "inception_resnet_v2_c8_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c8_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c8_1x3_reduce"
top: "inception_resnet_v2_c8_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c8_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c8_1x3_reduce"
top: "inception_resnet_v2_c8_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c8_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c8_1x3_reduce"
top: "inception_resnet_v2_c8_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c8_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c8_1x3"
top: "inception_resnet_v2_c8_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c8_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c8_1x3"
top: "inception_resnet_v2_c8_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c8_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c8_1x3"
top: "inception_resnet_v2_c8_1x3"
}
layer {
name: "inception_resnet_v2_c8_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c8_1x3"
top: "inception_resnet_v2_c8_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c8_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c8_3x1"
top: "inception_resnet_v2_c8_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c8_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c8_3x1"
top: "inception_resnet_v2_c8_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c8_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c8_3x1"
top: "inception_resnet_v2_c8_3x1"
}
layer {
name: "inception_resnet_v2_c8_concat"
type: "Concat"
bottom: "inception_resnet_v2_c8_1x1"
bottom: "inception_resnet_v2_c8_3x1"
top: "inception_resnet_v2_c8_concat"
}
layer {
name: "inception_resnet_v2_c8_up"
type: "Convolution"
bottom: "inception_resnet_v2_c8_concat"
top: "inception_resnet_v2_c8_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c8_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c7_residual_eltwise"
bottom: "inception_resnet_v2_c8_up"
top: "inception_resnet_v2_c8_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c8_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c8_residual_eltwise"
top: "inception_resnet_v2_c8_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c9_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c8_residual_eltwise"
top: "inception_resnet_v2_c9_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c9_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c9_1x1"
top: "inception_resnet_v2_c9_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c9_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c9_1x1"
top: "inception_resnet_v2_c9_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c9_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c9_1x1"
top: "inception_resnet_v2_c9_1x1"
}
layer {
name: "inception_resnet_v2_c9_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c8_residual_eltwise"
top: "inception_resnet_v2_c9_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c9_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c9_1x3_reduce"
top: "inception_resnet_v2_c9_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c9_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c9_1x3_reduce"
top: "inception_resnet_v2_c9_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c9_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c9_1x3_reduce"
top: "inception_resnet_v2_c9_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c9_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c9_1x3_reduce"
top: "inception_resnet_v2_c9_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c9_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c9_1x3"
top: "inception_resnet_v2_c9_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c9_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c9_1x3"
top: "inception_resnet_v2_c9_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c9_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c9_1x3"
top: "inception_resnet_v2_c9_1x3"
}
layer {
name: "inception_resnet_v2_c9_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c9_1x3"
top: "inception_resnet_v2_c9_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c9_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c9_3x1"
top: "inception_resnet_v2_c9_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c9_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c9_3x1"
top: "inception_resnet_v2_c9_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c9_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c9_3x1"
top: "inception_resnet_v2_c9_3x1"
}
layer {
name: "inception_resnet_v2_c9_concat"
type: "Concat"
bottom: "inception_resnet_v2_c9_1x1"
bottom: "inception_resnet_v2_c9_3x1"
top: "inception_resnet_v2_c9_concat"
}
layer {
name: "inception_resnet_v2_c9_up"
type: "Convolution"
bottom: "inception_resnet_v2_c9_concat"
top: "inception_resnet_v2_c9_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c9_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c8_residual_eltwise"
bottom: "inception_resnet_v2_c9_up"
top: "inception_resnet_v2_c9_residual_eltwise"
eltwise_param {
operation: SUM
coeff: 1
coeff: 0.2
}
}
layer {
name: "inception_resnet_v2_c9_residual_eltwise_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c9_residual_eltwise"
top: "inception_resnet_v2_c9_residual_eltwise"
}
layer {
name: "inception_resnet_v2_c10_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c9_residual_eltwise"
top: "inception_resnet_v2_c10_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c10_1x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c10_1x1"
top: "inception_resnet_v2_c10_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c10_1x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c10_1x1"
top: "inception_resnet_v2_c10_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c10_1x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c10_1x1"
top: "inception_resnet_v2_c10_1x1"
}
layer {
name: "inception_resnet_v2_c10_1x3_reduce"
type: "Convolution"
bottom: "inception_resnet_v2_c9_residual_eltwise"
top: "inception_resnet_v2_c10_1x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 192
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "inception_resnet_v2_c10_1x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c10_1x3_reduce"
top: "inception_resnet_v2_c10_1x3_reduce"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c10_1x3_reduce_scale"
type: "Scale"
bottom: "inception_resnet_v2_c10_1x3_reduce"
top: "inception_resnet_v2_c10_1x3_reduce"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c10_1x3_reduce_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c10_1x3_reduce"
top: "inception_resnet_v2_c10_1x3_reduce"
}
layer {
name: "inception_resnet_v2_c10_1x3"
type: "Convolution"
bottom: "inception_resnet_v2_c10_1x3_reduce"
top: "inception_resnet_v2_c10_1x3"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 224
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 0
pad_w: 1
kernel_h: 1
kernel_w: 3
}
}
layer {
name: "inception_resnet_v2_c10_1x3_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c10_1x3"
top: "inception_resnet_v2_c10_1x3"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c10_1x3_scale"
type: "Scale"
bottom: "inception_resnet_v2_c10_1x3"
top: "inception_resnet_v2_c10_1x3"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c10_1x3_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c10_1x3"
top: "inception_resnet_v2_c10_1x3"
}
layer {
name: "inception_resnet_v2_c10_3x1"
type: "Convolution"
bottom: "inception_resnet_v2_c10_1x3"
top: "inception_resnet_v2_c10_3x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
pad_h: 1
pad_w: 0
kernel_h: 3
kernel_w: 1
}
}
layer {
name: "inception_resnet_v2_c10_3x1_bn"
type: "BatchNorm"
bottom: "inception_resnet_v2_c10_3x1"
top: "inception_resnet_v2_c10_3x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "inception_resnet_v2_c10_3x1_scale"
type: "Scale"
bottom: "inception_resnet_v2_c10_3x1"
top: "inception_resnet_v2_c10_3x1"
scale_param {
bias_term: true
}
}
layer {
name: "inception_resnet_v2_c10_3x1_relu"
type: "ReLU"
bottom: "inception_resnet_v2_c10_3x1"
top: "inception_resnet_v2_c10_3x1"
}
layer {
name: "inception_resnet_v2_c10_concat"
type: "Concat"
bottom: "inception_resnet_v2_c10_1x1"
bottom: "inception_resnet_v2_c10_3x1"
top: "inception_resnet_v2_c10_concat"
}
layer {
name: "inception_resnet_v2_c10_up"
type: "Convolution"
bottom: "inception_resnet_v2_c10_concat"
top: "inception_resnet_v2_c10_up"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 2080
kernel_size: 1
weight_filler {
type: "xavier"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_resnet_v2_c10_residual_eltwise"
type: "Eltwise"
bottom: "inception_resnet_v2_c9_residual_eltwise"
bottom: "inception_resnet_v2_c10_up"
top: "inception_resnet_v2_c10_residual_eltwise"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv6_1x1"
type: "Convolution"
bottom: "inception_resnet_v2_c10_residual_eltwise"
top: "conv6_1x1"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1536
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 0.01
}
}
}
layer {
name: "conv6_1x1_bn"
type: "BatchNorm"
bottom: "conv6_1x1"
top: "conv6_1x1"
batch_norm_param {
use_global_stats: true
eps: 0.001
}
}
layer {
name: "conv6_1x1_scale"
type: "Scale"
bottom: "conv6_1x1"
top: "conv6_1x1"
scale_param {
bias_term: true
}
}
layer {
name: "conv6_1x1_relu"
type: "ReLU"
bottom: "conv6_1x1"
top: "conv6_1x1"
}
layer {
name: "pool_8x8_s1"
type: "Pooling"
bottom: "conv6_1x1"
top: "pool_8x8_s1"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "classifier_new"
type: "InnerProduct"
bottom: "pool_8x8_s1"
top: "classifier_new"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prob"
type: "Softmax"
bottom: "classifier_new"
top: "prob"
}
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