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@dudu159632
Created November 12, 2016 15:59
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input: "data"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227
layer {
name: "conv1_7x7_s2"
type: "Convolution"
bottom: "data"
top: "conv1_7x7_s2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 3
kernel_size: 7
stride: 2
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "conv1_7x7_s2_bn"
type: "BatchNorm"
bottom: "conv1_7x7_s2"
top: "conv1_7x7_s2"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "conv1_7x7_relu"
type: "ReLU"
bottom: "conv1_7x7_s2"
top: "conv1_7x7_s2"
}
layer {
name: "pool1_3x3_s2"
type: "Pooling"
bottom: "conv1_7x7_s2"
top: "pool1_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2_3x3_reduce"
type: "Convolution"
bottom: "pool1_3x3_s2"
top: "conv2_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "conv2_3x3_reduce_bn"
type: "BatchNorm"
bottom: "conv2_3x3_reduce"
top: "conv2_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "conv2_3x3_reduce_relu"
type: "ReLU"
bottom: "conv2_3x3_reduce"
top: "conv2_3x3_reduce"
}
layer {
name: "conv2_3x3"
type: "Convolution"
bottom: "conv2_3x3_reduce"
top: "conv2_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "conv2_3x3_bn"
type: "BatchNorm"
bottom: "conv2_3x3"
top: "conv2_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "conv2_3x3_relu"
type: "ReLU"
bottom: "conv2_3x3"
top: "conv2_3x3"
}
layer {
name: "pool2_3x3_s2"
type: "Pooling"
bottom: "conv2_3x3"
top: "pool2_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "inception_3a_1x1"
type: "Convolution"
bottom: "pool2_3x3_s2"
top: "inception_3a_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3a_1x1_bn"
type: "BatchNorm"
bottom: "inception_3a_1x1"
top: "inception_3a_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3a_relu_1x1"
type: "ReLU"
bottom: "inception_3a_1x1"
top: "inception_3a_1x1"
}
layer {
name: "inception_3a_3x3_reduce"
type: "Convolution"
bottom: "pool2_3x3_s2"
top: "inception_3a_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3a_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_3a_3x3_reduce"
top: "inception_3a_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3a_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_3a_3x3_reduce"
top: "inception_3a_3x3_reduce"
}
layer {
name: "inception_3a_3x3"
type: "Convolution"
bottom: "inception_3a_3x3_reduce"
top: "inception_3a_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3a_3x3_bn"
type: "BatchNorm"
bottom: "inception_3a_3x3"
top: "inception_3a_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3a_relu_3x3"
type: "ReLU"
bottom: "inception_3a_3x3"
top: "inception_3a_3x3"
}
layer {
name: "inception_3a_5x5_reduce"
type: "Convolution"
bottom: "pool2_3x3_s2"
top: "inception_3a_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3a_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_3a_5x5_reduce"
top: "inception_3a_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3a_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_3a_5x5_reduce"
top: "inception_3a_5x5_reduce"
}
layer {
name: "inception_3a_5x5"
type: "Convolution"
bottom: "inception_3a_5x5_reduce"
top: "inception_3a_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3a_5x5_bn"
type: "BatchNorm"
bottom: "inception_3a_5x5"
top: "inception_3a_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3a_relu_5x5"
type: "ReLU"
bottom: "inception_3a_5x5"
top: "inception_3a_5x5"
}
layer {
name: "inception_3a_pool"
type: "Pooling"
bottom: "pool2_3x3_s2"
top: "inception_3a_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_3a_pool_proj"
type: "Convolution"
bottom: "inception_3a_pool"
top: "inception_3a_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3a_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_3a_pool_proj"
top: "inception_3a_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3a_relu_pool_proj"
type: "ReLU"
bottom: "inception_3a_pool_proj"
top: "inception_3a_pool_proj"
}
layer {
name: "inception_3a_output"
type: "Concat"
bottom: "inception_3a_1x1"
bottom: "inception_3a_3x3"
bottom: "inception_3a_5x5"
bottom: "inception_3a_pool_proj"
top: "inception_3a_output"
}
layer {
name: "inception_3b_1x1"
type: "Convolution"
bottom: "inception_3a_output"
top: "inception_3b_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3b_1x1_bn"
type: "BatchNorm"
bottom: "inception_3b_1x1"
top: "inception_3b_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3b_relu_1x1"
type: "ReLU"
bottom: "inception_3b_1x1"
top: "inception_3b_1x1"
}
layer {
name: "inception_3b_3x3_reduce"
type: "Convolution"
bottom: "inception_3a_output"
top: "inception_3b_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3b_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_3b_3x3_reduce"
top: "inception_3b_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3b_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_3b_3x3_reduce"
top: "inception_3b_3x3_reduce"
}
layer {
name: "inception_3b_3x3"
type: "Convolution"
bottom: "inception_3b_3x3_reduce"
top: "inception_3b_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3b_3x3_bn"
type: "BatchNorm"
bottom: "inception_3b_3x3"
top: "inception_3b_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3b_relu_3x3"
type: "ReLU"
bottom: "inception_3b_3x3"
top: "inception_3b_3x3"
}
layer {
name: "inception_3b_5x5_reduce"
type: "Convolution"
bottom: "inception_3a_output"
top: "inception_3b_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3b_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_3b_5x5_reduce"
top: "inception_3b_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3b_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_3b_5x5_reduce"
top: "inception_3b_5x5_reduce"
}
layer {
name: "inception_3b_5x5"
type: "Convolution"
bottom: "inception_3b_5x5_reduce"
top: "inception_3b_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3b_5x5_bn"
type: "BatchNorm"
bottom: "inception_3b_5x5"
top: "inception_3b_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3b_relu_5x5"
type: "ReLU"
bottom: "inception_3b_5x5"
top: "inception_3b_5x5"
}
layer {
name: "inception_3b_pool"
type: "Pooling"
bottom: "inception_3a_output"
top: "inception_3b_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_3b_pool_proj"
type: "Convolution"
bottom: "inception_3b_pool"
top: "inception_3b_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_3b_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_3b_pool_proj"
top: "inception_3b_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_3b_relu_pool_proj"
type: "ReLU"
bottom: "inception_3b_pool_proj"
top: "inception_3b_pool_proj"
}
layer {
name: "inception_3b_output"
type: "Concat"
bottom: "inception_3b_1x1"
bottom: "inception_3b_3x3"
bottom: "inception_3b_5x5"
bottom: "inception_3b_pool_proj"
top: "inception_3b_output"
}
layer {
name: "pool3_3x3_s2"
type: "Pooling"
bottom: "inception_3b_output"
top: "pool3_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "inception_4a_1x1"
type: "Convolution"
bottom: "pool3_3x3_s2"
top: "inception_4a_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4a_1x1_bn"
type: "BatchNorm"
bottom: "inception_4a_1x1"
top: "inception_4a_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4a_relu_1x1"
type: "ReLU"
bottom: "inception_4a_1x1"
top: "inception_4a_1x1"
}
layer {
name: "inception_4a_3x3_reduce"
type: "Convolution"
bottom: "pool3_3x3_s2"
top: "inception_4a_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4a_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_4a_3x3_reduce"
top: "inception_4a_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4a_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_4a_3x3_reduce"
top: "inception_4a_3x3_reduce"
}
layer {
name: "inception_4a_3x3"
type: "Convolution"
bottom: "inception_4a_3x3_reduce"
top: "inception_4a_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 208
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4a_3x3_bn"
type: "BatchNorm"
bottom: "inception_4a_3x3"
top: "inception_4a_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4a_relu_3x3"
type: "ReLU"
bottom: "inception_4a_3x3"
top: "inception_4a_3x3"
}
layer {
name: "inception_4a_5x5_reduce"
type: "Convolution"
bottom: "pool3_3x3_s2"
top: "inception_4a_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4a_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_4a_5x5_reduce"
top: "inception_4a_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4a_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_4a_5x5_reduce"
top: "inception_4a_5x5_reduce"
}
layer {
name: "inception_4a_5x5"
type: "Convolution"
bottom: "inception_4a_5x5_reduce"
top: "inception_4a_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 48
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4a_5x5_bn"
type: "BatchNorm"
bottom: "inception_4a_5x5"
top: "inception_4a_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4a_relu_5x5"
type: "ReLU"
bottom: "inception_4a_5x5"
top: "inception_4a_5x5"
}
layer {
name: "inception_4a_pool"
type: "Pooling"
bottom: "pool3_3x3_s2"
top: "inception_4a_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_4a_pool_proj"
type: "Convolution"
bottom: "inception_4a_pool"
top: "inception_4a_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4a_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_4a_pool_proj"
top: "inception_4a_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4a_relu_pool_proj"
type: "ReLU"
bottom: "inception_4a_pool_proj"
top: "inception_4a_pool_proj"
}
layer {
name: "inception_4a_output"
type: "Concat"
bottom: "inception_4a_1x1"
bottom: "inception_4a_3x3"
bottom: "inception_4a_5x5"
bottom: "inception_4a_pool_proj"
top: "inception_4a_output"
}
layer {
name: "inception_4b_1x1"
type: "Convolution"
bottom: "inception_4a_output"
top: "inception_4b_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4b_1x1_bn"
type: "BatchNorm"
bottom: "inception_4b_1x1"
top: "inception_4b_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4b_relu_1x1"
type: "ReLU"
bottom: "inception_4b_1x1"
top: "inception_4b_1x1"
}
layer {
name: "inception_4b_3x3_reduce"
type: "Convolution"
bottom: "inception_4a_output"
top: "inception_4b_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 112
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4b_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_4b_3x3_reduce"
top: "inception_4b_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4b_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_4b_3x3_reduce"
top: "inception_4b_3x3_reduce"
}
layer {
name: "inception_4b_3x3"
type: "Convolution"
bottom: "inception_4b_3x3_reduce"
top: "inception_4b_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 224
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4b_3x3_bn"
type: "BatchNorm"
bottom: "inception_4b_3x3"
top: "inception_4b_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4b_relu_3x3"
type: "ReLU"
bottom: "inception_4b_3x3"
top: "inception_4b_3x3"
}
layer {
name: "inception_4b_5x5_reduce"
type: "Convolution"
bottom: "inception_4a_output"
top: "inception_4b_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4b_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_4b_5x5_reduce"
top: "inception_4b_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4b_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_4b_5x5_reduce"
top: "inception_4b_5x5_reduce"
}
layer {
name: "inception_4b_5x5"
type: "Convolution"
bottom: "inception_4b_5x5_reduce"
top: "inception_4b_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4b_5x5_bn"
type: "BatchNorm"
bottom: "inception_4b_5x5"
top: "inception_4b_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4b_relu_5x5"
type: "ReLU"
bottom: "inception_4b_5x5"
top: "inception_4b_5x5"
}
layer {
name: "inception_4b_pool"
type: "Pooling"
bottom: "inception_4a_output"
top: "inception_4b_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_4b_pool_proj"
type: "Convolution"
bottom: "inception_4b_pool"
top: "inception_4b_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4b_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_4b_pool_proj"
top: "inception_4b_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4b_relu_pool_proj"
type: "ReLU"
bottom: "inception_4b_pool_proj"
top: "inception_4b_pool_proj"
}
layer {
name: "inception_4b_output"
type: "Concat"
bottom: "inception_4b_1x1"
bottom: "inception_4b_3x3"
bottom: "inception_4b_5x5"
bottom: "inception_4b_pool_proj"
top: "inception_4b_output"
}
layer {
name: "inception_4c_1x1"
type: "Convolution"
bottom: "inception_4b_output"
top: "inception_4c_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4c_1x1_bn"
type: "BatchNorm"
bottom: "inception_4c_1x1"
top: "inception_4c_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4c_relu_1x1"
type: "ReLU"
bottom: "inception_4c_1x1"
top: "inception_4c_1x1"
}
layer {
name: "inception_4c_3x3_reduce"
type: "Convolution"
bottom: "inception_4b_output"
top: "inception_4c_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4c_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_4c_3x3_reduce"
top: "inception_4c_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4c_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_4c_3x3_reduce"
top: "inception_4c_3x3_reduce"
}
layer {
name: "inception_4c_3x3"
type: "Convolution"
bottom: "inception_4c_3x3_reduce"
top: "inception_4c_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4c_3x3_bn"
type: "BatchNorm"
bottom: "inception_4c_3x3"
top: "inception_4c_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4c_relu_3x3"
type: "ReLU"
bottom: "inception_4c_3x3"
top: "inception_4c_3x3"
}
layer {
name: "inception_4c_5x5_reduce"
type: "Convolution"
bottom: "inception_4b_output"
top: "inception_4c_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 24
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4c_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_4c_5x5_reduce"
top: "inception_4c_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4c_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_4c_5x5_reduce"
top: "inception_4c_5x5_reduce"
}
layer {
name: "inception_4c_5x5"
type: "Convolution"
bottom: "inception_4c_5x5_reduce"
top: "inception_4c_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4c_5x5_bn"
type: "BatchNorm"
bottom: "inception_4c_5x5"
top: "inception_4c_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4c_relu_5x5"
type: "ReLU"
bottom: "inception_4c_5x5"
top: "inception_4c_5x5"
}
layer {
name: "inception_4c_pool"
type: "Pooling"
bottom: "inception_4b_output"
top: "inception_4c_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_4c_pool_proj"
type: "Convolution"
bottom: "inception_4c_pool"
top: "inception_4c_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4c_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_4c_pool_proj"
top: "inception_4c_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4c_relu_pool_proj"
type: "ReLU"
bottom: "inception_4c_pool_proj"
top: "inception_4c_pool_proj"
}
layer {
name: "inception_4c_output"
type: "Concat"
bottom: "inception_4c_1x1"
bottom: "inception_4c_3x3"
bottom: "inception_4c_5x5"
bottom: "inception_4c_pool_proj"
top: "inception_4c_output"
}
layer {
name: "inception_4d_1x1"
type: "Convolution"
bottom: "inception_4c_output"
top: "inception_4d_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 112
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4d_1x1_bn"
type: "BatchNorm"
bottom: "inception_4d_1x1"
top: "inception_4d_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4d_relu_1x1"
type: "ReLU"
bottom: "inception_4d_1x1"
top: "inception_4d_1x1"
}
layer {
name: "inception_4d_3x3_reduce"
type: "Convolution"
bottom: "inception_4c_output"
top: "inception_4d_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 144
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4d_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_4d_3x3_reduce"
top: "inception_4d_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4d_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_4d_3x3_reduce"
top: "inception_4d_3x3_reduce"
}
layer {
name: "inception_4d_3x3"
type: "Convolution"
bottom: "inception_4d_3x3_reduce"
top: "inception_4d_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 288
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4d_3x3_bn"
type: "BatchNorm"
bottom: "inception_4d_3x3"
top: "inception_4d_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4d_relu_3x3"
type: "ReLU"
bottom: "inception_4d_3x3"
top: "inception_4d_3x3"
}
layer {
name: "inception_4d_5x5_reduce"
type: "Convolution"
bottom: "inception_4c_output"
top: "inception_4d_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4d_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_4d_5x5_reduce"
top: "inception_4d_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4d_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_4d_5x5_reduce"
top: "inception_4d_5x5_reduce"
}
layer {
name: "inception_4d_5x5"
type: "Convolution"
bottom: "inception_4d_5x5_reduce"
top: "inception_4d_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4d_5x5_bn"
type: "BatchNorm"
bottom: "inception_4d_5x5"
top: "inception_4d_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4d_relu_5x5"
type: "ReLU"
bottom: "inception_4d_5x5"
top: "inception_4d_5x5"
}
layer {
name: "inception_4d_pool"
type: "Pooling"
bottom: "inception_4c_output"
top: "inception_4d_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_4d_pool_proj"
type: "Convolution"
bottom: "inception_4d_pool"
top: "inception_4d_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4d_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_4d_pool_proj"
top: "inception_4d_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4d_relu_pool_proj"
type: "ReLU"
bottom: "inception_4d_pool_proj"
top: "inception_4d_pool_proj"
}
layer {
name: "inception_4d_output"
type: "Concat"
bottom: "inception_4d_1x1"
bottom: "inception_4d_3x3"
bottom: "inception_4d_5x5"
bottom: "inception_4d_pool_proj"
top: "inception_4d_output"
}
layer {
name: "inception_4e_1x1"
type: "Convolution"
bottom: "inception_4d_output"
top: "inception_4e_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4e_1x1_bn"
type: "BatchNorm"
bottom: "inception_4e_1x1"
top: "inception_4e_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4e_relu_1x1"
type: "ReLU"
bottom: "inception_4e_1x1"
top: "inception_4e_1x1"
}
layer {
name: "inception_4e_3x3_reduce"
type: "Convolution"
bottom: "inception_4d_output"
top: "inception_4e_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4e_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_4e_3x3_reduce"
top: "inception_4e_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4e_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_4e_3x3_reduce"
top: "inception_4e_3x3_reduce"
}
layer {
name: "inception_4e_3x3"
type: "Convolution"
bottom: "inception_4e_3x3_reduce"
top: "inception_4e_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4e_3x3_bn"
type: "BatchNorm"
bottom: "inception_4e_3x3"
top: "inception_4e_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4e_relu_3x3"
type: "ReLU"
bottom: "inception_4e_3x3"
top: "inception_4e_3x3"
}
layer {
name: "inception_4e_5x5_reduce"
type: "Convolution"
bottom: "inception_4d_output"
top: "inception_4e_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4e_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_4e_5x5_reduce"
top: "inception_4e_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4e_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_4e_5x5_reduce"
top: "inception_4e_5x5_reduce"
}
layer {
name: "inception_4e_5x5"
type: "Convolution"
bottom: "inception_4e_5x5_reduce"
top: "inception_4e_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4e_5x5_bn"
type: "BatchNorm"
bottom: "inception_4e_5x5"
top: "inception_4e_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4e_relu_5x5"
type: "ReLU"
bottom: "inception_4e_5x5"
top: "inception_4e_5x5"
}
layer {
name: "inception_4e_pool"
type: "Pooling"
bottom: "inception_4d_output"
top: "inception_4e_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_4e_pool_proj"
type: "Convolution"
bottom: "inception_4e_pool"
top: "inception_4e_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_4e_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_4e_pool_proj"
top: "inception_4e_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_4e_relu_pool_proj"
type: "ReLU"
bottom: "inception_4e_pool_proj"
top: "inception_4e_pool_proj"
}
layer {
name: "inception_4e_output"
type: "Concat"
bottom: "inception_4e_1x1"
bottom: "inception_4e_3x3"
bottom: "inception_4e_5x5"
bottom: "inception_4e_pool_proj"
top: "inception_4e_output"
}
layer {
name: "pool4_3x3_s2"
type: "Pooling"
bottom: "inception_4e_output"
top: "pool4_3x3_s2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "inception_5a_1x1"
type: "Convolution"
bottom: "pool4_3x3_s2"
top: "inception_5a_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5a_1x1_bn"
type: "BatchNorm"
bottom: "inception_5a_1x1"
top: "inception_5a_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5a_relu_1x1"
type: "ReLU"
bottom: "inception_5a_1x1"
top: "inception_5a_1x1"
}
layer {
name: "inception_5a_3x3_reduce"
type: "Convolution"
bottom: "pool4_3x3_s2"
top: "inception_5a_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 160
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5a_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_5a_3x3_reduce"
top: "inception_5a_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5a_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_5a_3x3_reduce"
top: "inception_5a_3x3_reduce"
}
layer {
name: "inception_5a_3x3"
type: "Convolution"
bottom: "inception_5a_3x3_reduce"
top: "inception_5a_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 320
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5a_3x3_bn"
type: "BatchNorm"
bottom: "inception_5a_3x3"
top: "inception_5a_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5a_relu_3x3"
type: "ReLU"
bottom: "inception_5a_3x3"
top: "inception_5a_3x3"
}
layer {
name: "inception_5a_5x5_reduce"
type: "Convolution"
bottom: "pool4_3x3_s2"
top: "inception_5a_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5a_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_5a_5x5_reduce"
top: "inception_5a_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5a_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_5a_5x5_reduce"
top: "inception_5a_5x5_reduce"
}
layer {
name: "inception_5a_5x5"
type: "Convolution"
bottom: "inception_5a_5x5_reduce"
top: "inception_5a_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5a_5x5_bn"
type: "BatchNorm"
bottom: "inception_5a_5x5"
top: "inception_5a_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5a_relu_5x5"
type: "ReLU"
bottom: "inception_5a_5x5"
top: "inception_5a_5x5"
}
layer {
name: "inception_5a_pool"
type: "Pooling"
bottom: "pool4_3x3_s2"
top: "inception_5a_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_5a_pool_proj"
type: "Convolution"
bottom: "inception_5a_pool"
top: "inception_5a_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5a_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_5a_pool_proj"
top: "inception_5a_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5a_relu_pool_proj"
type: "ReLU"
bottom: "inception_5a_pool_proj"
top: "inception_5a_pool_proj"
}
layer {
name: "inception_5a_output"
type: "Concat"
bottom: "inception_5a_1x1"
bottom: "inception_5a_3x3"
bottom: "inception_5a_5x5"
bottom: "inception_5a_pool_proj"
top: "inception_5a_output"
}
layer {
name: "inception_5b_1x1"
type: "Convolution"
bottom: "inception_5a_output"
top: "inception_5b_1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5b_1x1_bn"
type: "BatchNorm"
bottom: "inception_5b_1x1"
top: "inception_5b_1x1"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5b_relu_1x1"
type: "ReLU"
bottom: "inception_5b_1x1"
top: "inception_5b_1x1"
}
layer {
name: "inception_5b_3x3_reduce"
type: "Convolution"
bottom: "inception_5a_output"
top: "inception_5b_3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 192
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5b_3x3_reduce_bn"
type: "BatchNorm"
bottom: "inception_5b_3x3_reduce"
top: "inception_5b_3x3_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5b_relu_3x3_reduce"
type: "ReLU"
bottom: "inception_5b_3x3_reduce"
top: "inception_5b_3x3_reduce"
}
layer {
name: "inception_5b_3x3"
type: "Convolution"
bottom: "inception_5b_3x3_reduce"
top: "inception_5b_3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5b_3x3_bn"
type: "BatchNorm"
bottom: "inception_5b_3x3"
top: "inception_5b_3x3"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5b_relu_3x3"
type: "ReLU"
bottom: "inception_5b_3x3"
top: "inception_5b_3x3"
}
layer {
name: "inception_5b_5x5_reduce"
type: "Convolution"
bottom: "inception_5a_output"
top: "inception_5b_5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 48
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5b_5x5_reduce_bn"
type: "BatchNorm"
bottom: "inception_5b_5x5_reduce"
top: "inception_5b_5x5_reduce"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5b_relu_5x5_reduce"
type: "ReLU"
bottom: "inception_5b_5x5_reduce"
top: "inception_5b_5x5_reduce"
}
layer {
name: "inception_5b_5x5"
type: "Convolution"
bottom: "inception_5b_5x5_reduce"
top: "inception_5b_5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 2
kernel_size: 5
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5b_5x5_bn"
type: "BatchNorm"
bottom: "inception_5b_5x5"
top: "inception_5b_5x5"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5b_relu_5x5"
type: "ReLU"
bottom: "inception_5b_5x5"
top: "inception_5b_5x5"
}
layer {
name: "inception_5b_pool"
type: "Pooling"
bottom: "inception_5a_output"
top: "inception_5b_pool"
pooling_param {
pool: MAX
kernel_size: 3
stride: 1
pad: 1
}
}
layer {
name: "inception_5b_pool_proj"
type: "Convolution"
bottom: "inception_5b_pool"
top: "inception_5b_pool_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
std: 1
}
bias_filler {
type: "constant"
value: 0.2
}
}
}
layer {
name: "inception_5b_pool_proj_bn"
type: "BatchNorm"
bottom: "inception_5b_pool_proj"
top: "inception_5b_pool_proj"
batch_norm_param {
use_global_stats: true
}
}
layer {
name: "inception_5b_relu_pool_proj"
type: "ReLU"
bottom: "inception_5b_pool_proj"
top: "inception_5b_pool_proj"
}
layer {
name: "inception_5b_output"
type: "Concat"
bottom: "inception_5b_1x1"
bottom: "inception_5b_3x3"
bottom: "inception_5b_5x5"
bottom: "inception_5b_pool_proj"
top: "inception_5b_output"
}
layer {
name: "pool5_7x7_s1"
type: "Pooling"
bottom: "inception_5b_output"
top: "pool5_7x7_s1"
pooling_param {
pool: AVE
kernel_size: 7
stride: 1
}
}
layer {
name: "pool5_drop_7x7_s1"
type: "Dropout"
bottom: "pool5_7x7_s1"
top: "pool5_7x7_s1"
dropout_param {
dropout_ratio: 0.4
}
}
layer {
name: "loss3_classifier"
type: "InnerProduct"
bottom: "pool5_7x7_s1"
top: "loss3_classifier"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 1000
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "prob"
type: "Softmax"
bottom: "loss3_classifier"
top: "prob"
}
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