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sriharsha0806/caffe Prototxt

Created October 1, 2018 09:46
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caffe Prototxt
name: "ERFNet"
# initialization is based on Enet (pytorch of ERFNet has its own default initialization method)
layer {
name: "data"
type: "Input"
top: "data"
input_param {
shape {
dim: 1
dim: 3
dim: 512
dim: 1024
}
}
}
layer {
name: "DownsamplerBlock1_conv"
type: "Convolution"
bottom: "data"
top: "DownsamplerBlock1_conv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 13
kernel_size: 3
pad: 1
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "DownsamplerBlock1_pool"
type: "Pooling"
bottom: "data"
top: "DownsamplerBlock1_pool"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "DownsamplerBlock1_concat"
type: "Concat"
bottom: "DownsamplerBlock1_conv"
bottom: "DownsamplerBlock1_pool"
top: "DownsamplerBlock1_concat"
concat_param {
axis: 1
}
}
layer {
name: "DownsamplerBlock1_concat/bn"
type: "BatchNorm"
bottom: "DownsamplerBlock1_concat"
top: "DownsamplerBlock1_concat"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "DownsamplerBlock1_concat/bn"
type: "BatchNorm"
bottom: "DownsamplerBlock1_concat"
top: "DownsamplerBlock1_concat"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "DownsamplerBlock1_concat/scale"
type: "Scale"
bottom: "DownsamplerBlock1_concat"
top: "DownsamplerBlock1_concat"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "DownsamplerBlock1_concat/relu"
type: "ReLU"
bottom: "DownsamplerBlock1_concat"
top: "DownsamplerBlock1_concat"
}
layer {
name: "DownsamplerBlock2_conv"
type: "Convolution"
bottom: "DownsamplerBlock1_concat"
top: "DownsamplerBlock2_conv"
convolution_param {
num_output: 48
kernel_size: 3
pad: 1
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "DownsamplerBlock2_pool"
type: "Pooling"
bottom: "DownsamplerBlock1_concat"
top: "DownsamplerBlock2_pool"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "DownsamplerBlock2_concat"
type: "Concat"
bottom: "DownsamplerBlock2_conv"
bottom: "DownsamplerBlock2_pool"
top: "DownsamplerBlock2_concat"
concat_param {
axis: 1
}
}
layer {
name: "DownsamplerBlock2_concat/bn"
type: "BatchNorm"
bottom: "DownsamplerBlock2_concat"
top: "DownsamplerBlock2_concat"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "DownsamplerBlock2_concat/bn"
type: "BatchNorm"
bottom: "DownsamplerBlock2_concat"
top: "DownsamplerBlock2_concat"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "DownsamplerBlock2_concat/scale"
type: "Scale"
bottom: "DownsamplerBlock2_concat"
top: "DownsamplerBlock2_concat"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "DownsamplerBlock2_concat/relu"
type: "ReLU"
bottom: "DownsamplerBlock2_concat"
top: "DownsamplerBlock2_concat"
}
layer {
name: "NBD3_conv1_3x1"
type: "Convolution"
bottom: "DownsamplerBlock2_concat"
top: "NBD3_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD3_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD3_conv1_3x1"
top: "NBD3_conv1_3x1"
}
layer {
name: "NBD3_conv1_1x3"
type: "Convolution"
bottom: "NBD3_conv1_3x1"
top: "NBD3_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD3_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD3_conv1_1x3"
top: "NBD3_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD3_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD3_conv1_1x3"
top: "NBD3_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD3_conv1_1x3/scale"
type: "Scale"
bottom: "NBD3_conv1_1x3"
top: "NBD3_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD3_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD3_conv1_1x3"
top: "NBD3_conv1_1x3"
}
layer {
name: "NBD3_conv2_3x1"
type: "Convolution"
bottom: "NBD3_conv1_1x3"
top: "NBD3_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD3_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD3_conv2_3x1"
top: "NBD3_conv2_3x1"
}
layer {
name: "NBD3_conv2_1x3"
type: "Convolution"
bottom: "NBD3_conv2_3x1"
top: "NBD3_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD3_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD3_conv2_1x3"
top: "NBD3_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD3_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD3_conv2_1x3"
top: "NBD3_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD3_conv2_1x3/scale"
type: "Scale"
bottom: "NBD3_conv2_1x3"
top: "NBD3_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD3_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD3_conv2_1x3"
top: "NBD3_conv2_1x3"
dropout_param {
dropout_ratio: 0.03
}
}
layer {
name: "NBD3_res"
type: "Eltwise"
bottom: "NBD3_conv2_1x3"
bottom: "DownsamplerBlock2_concat"
top: "NBD3_res"
}
layer {
name: "NBD3_res/relu"
type: "ReLU"
bottom: "NBD3_res"
top: "NBD3_res"
}
layer {
name: "NBD4_conv1_3x1"
type: "Convolution"
bottom: "NBD3_res"
top: "NBD4_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD4_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD4_conv1_3x1"
top: "NBD4_conv1_3x1"
}
layer {
name: "NBD4_conv1_1x3"
type: "Convolution"
bottom: "NBD4_conv1_3x1"
top: "NBD4_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD4_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD4_conv1_1x3"
top: "NBD4_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD4_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD4_conv1_1x3"
top: "NBD4_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD4_conv1_1x3/scale"
type: "Scale"
bottom: "NBD4_conv1_1x3"
top: "NBD4_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD4_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD4_conv1_1x3"
top: "NBD4_conv1_1x3"
}
layer {
name: "NBD4_conv2_3x1"
type: "Convolution"
bottom: "NBD4_conv1_1x3"
top: "NBD4_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD4_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD4_conv2_3x1"
top: "NBD4_conv2_3x1"
}
layer {
name: "NBD4_conv2_1x3"
type: "Convolution"
bottom: "NBD4_conv2_3x1"
top: "NBD4_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD4_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD4_conv2_1x3"
top: "NBD4_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD4_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD4_conv2_1x3"
top: "NBD4_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD4_conv2_1x3/scale"
type: "Scale"
bottom: "NBD4_conv2_1x3"
top: "NBD4_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD4_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD4_conv2_1x3"
top: "NBD4_conv2_1x3"
dropout_param {
dropout_ratio: 0.03
}
}
layer {
name: "NBD4_res"
type: "Eltwise"
bottom: "NBD4_conv2_1x3"
bottom: "NBD3_res"
top: "NBD4_res"
}
layer {
name: "NBD4_res/relu"
type: "ReLU"
bottom: "NBD4_res"
top: "NBD4_res"
}
layer {
name: "NBD5_conv1_3x1"
type: "Convolution"
bottom: "NBD4_res"
top: "NBD5_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD5_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD5_conv1_3x1"
top: "NBD5_conv1_3x1"
}
layer {
name: "NBD5_conv1_1x3"
type: "Convolution"
bottom: "NBD5_conv1_3x1"
top: "NBD5_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD5_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD5_conv1_1x3"
top: "NBD5_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD5_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD5_conv1_1x3"
top: "NBD5_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD5_conv1_1x3/scale"
type: "Scale"
bottom: "NBD5_conv1_1x3"
top: "NBD5_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD5_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD5_conv1_1x3"
top: "NBD5_conv1_1x3"
}
layer {
name: "NBD5_conv2_3x1"
type: "Convolution"
bottom: "NBD5_conv1_1x3"
top: "NBD5_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD5_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD5_conv2_3x1"
top: "NBD5_conv2_3x1"
}
layer {
name: "NBD5_conv2_1x3"
type: "Convolution"
bottom: "NBD5_conv2_3x1"
top: "NBD5_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD5_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD5_conv2_1x3"
top: "NBD5_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD5_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD5_conv2_1x3"
top: "NBD5_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD5_conv2_1x3/scale"
type: "Scale"
bottom: "NBD5_conv2_1x3"
top: "NBD5_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD5_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD5_conv2_1x3"
top: "NBD5_conv2_1x3"
dropout_param {
dropout_ratio: 0.03
}
}
layer {
name: "NBD5_res"
type: "Eltwise"
bottom: "NBD5_conv2_1x3"
bottom: "NBD4_res"
top: "NBD5_res"
}
layer {
name: "NBD5_res/relu"
type: "ReLU"
bottom: "NBD5_res"
top: "NBD5_res"
}
layer {
name: "NBD6_conv1_3x1"
type: "Convolution"
bottom: "NBD5_res"
top: "NBD6_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD6_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD6_conv1_3x1"
top: "NBD6_conv1_3x1"
}
layer {
name: "NBD6_conv1_1x3"
type: "Convolution"
bottom: "NBD6_conv1_3x1"
top: "NBD6_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD6_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD6_conv1_1x3"
top: "NBD6_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD6_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD6_conv1_1x3"
top: "NBD6_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD6_conv1_1x3/scale"
type: "Scale"
bottom: "NBD6_conv1_1x3"
top: "NBD6_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD6_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD6_conv1_1x3"
top: "NBD6_conv1_1x3"
}
layer {
name: "NBD6_conv2_3x1"
type: "Convolution"
bottom: "NBD6_conv1_1x3"
top: "NBD6_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD6_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD6_conv2_3x1"
top: "NBD6_conv2_3x1"
}
layer {
name: "NBD6_conv2_1x3"
type: "Convolution"
bottom: "NBD6_conv2_3x1"
top: "NBD6_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD6_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD6_conv2_1x3"
top: "NBD6_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD6_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD6_conv2_1x3"
top: "NBD6_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD6_conv2_1x3/scale"
type: "Scale"
bottom: "NBD6_conv2_1x3"
top: "NBD6_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD6_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD6_conv2_1x3"
top: "NBD6_conv2_1x3"
dropout_param {
dropout_ratio: 0.03
}
}
layer {
name: "NBD6_res"
type: "Eltwise"
bottom: "NBD6_conv2_1x3"
bottom: "NBD5_res"
top: "NBD6_res"
}
layer {
name: "NBD6_res/relu"
type: "ReLU"
bottom: "NBD6_res"
top: "NBD6_res"
}
layer {
name: "NBD7_conv1_3x1"
type: "Convolution"
bottom: "NBD6_res"
top: "NBD7_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD7_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD7_conv1_3x1"
top: "NBD7_conv1_3x1"
}
layer {
name: "NBD7_conv1_1x3"
type: "Convolution"
bottom: "NBD7_conv1_3x1"
top: "NBD7_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD7_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD7_conv1_1x3"
top: "NBD7_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD7_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD7_conv1_1x3"
top: "NBD7_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD7_conv1_1x3/scale"
type: "Scale"
bottom: "NBD7_conv1_1x3"
top: "NBD7_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD7_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD7_conv1_1x3"
top: "NBD7_conv1_1x3"
}
layer {
name: "NBD7_conv2_3x1"
type: "Convolution"
bottom: "NBD7_conv1_1x3"
top: "NBD7_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD7_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD7_conv2_3x1"
top: "NBD7_conv2_3x1"
}
layer {
name: "NBD7_conv2_1x3"
type: "Convolution"
bottom: "NBD7_conv2_3x1"
top: "NBD7_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD7_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD7_conv2_1x3"
top: "NBD7_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD7_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD7_conv2_1x3"
top: "NBD7_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD7_conv2_1x3/scale"
type: "Scale"
bottom: "NBD7_conv2_1x3"
top: "NBD7_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD7_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD7_conv2_1x3"
top: "NBD7_conv2_1x3"
dropout_param {
dropout_ratio: 0.03
}
}
layer {
name: "NBD7_res"
type: "Eltwise"
bottom: "NBD7_conv2_1x3"
bottom: "NBD6_res"
top: "NBD7_res"
}
layer {
name: "NBD7_res/relu"
type: "ReLU"
bottom: "NBD7_res"
top: "NBD7_res"
}
layer {
name: "DownsamplerBlock8_conv"
type: "Convolution"
bottom: "NBD7_res"
top: "DownsamplerBlock8_conv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "DownsamplerBlock8_pool"
type: "Pooling"
bottom: "NBD7_res"
top: "DownsamplerBlock8_pool"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "DownsamplerBlock8_concat"
type: "Concat"
bottom: "DownsamplerBlock8_conv"
bottom: "DownsamplerBlock8_pool"
top: "DownsamplerBlock8_concat"
concat_param {
axis: 1
}
}
layer {
name: "DownsamplerBlock8_concat/bn"
type: "BatchNorm"
bottom: "DownsamplerBlock8_concat"
top: "DownsamplerBlock8_concat"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "DownsamplerBlock8_concat/bn"
type: "BatchNorm"
bottom: "DownsamplerBlock8_concat"
top: "DownsamplerBlock8_concat"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "DownsamplerBlock8_concat/scale"
type: "Scale"
bottom: "DownsamplerBlock8_concat"
top: "DownsamplerBlock8_concat"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "DownsamplerBlock8_concat/relu"
type: "ReLU"
bottom: "DownsamplerBlock8_concat"
top: "DownsamplerBlock8_concat"
}
layer {
name: "NBD9_conv1_3x1"
type: "Convolution"
bottom: "DownsamplerBlock8_concat"
top: "NBD9_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD9_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD9_conv1_3x1"
top: "NBD9_conv1_3x1"
}
layer {
name: "NBD9_conv1_1x3"
type: "Convolution"
bottom: "NBD9_conv1_3x1"
top: "NBD9_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD9_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD9_conv1_1x3"
top: "NBD9_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD9_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD9_conv1_1x3"
top: "NBD9_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD9_conv1_1x3/scale"
type: "Scale"
bottom: "NBD9_conv1_1x3"
top: "NBD9_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD9_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD9_conv1_1x3"
top: "NBD9_conv1_1x3"
}
layer {
name: "NBD9_conv2_3x1"
type: "Convolution"
bottom: "NBD9_conv1_1x3"
top: "NBD9_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 2
pad_w: 0
stride: 1
dilation:2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD9_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD9_conv2_3x1"
top: "NBD9_conv2_3x1"
}
layer {
name: "NBD9_conv2_1x3"
type: "Convolution"
bottom: "NBD9_conv2_3x1"
top: "NBD9_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 2
stride: 1
dilation:2
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD9_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD9_conv2_1x3"
top: "NBD9_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD9_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD9_conv2_1x3"
top: "NBD9_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD9_conv2_1x3/scale"
type: "Scale"
bottom: "NBD9_conv2_1x3"
top: "NBD9_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD9_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD9_conv2_1x3"
top: "NBD9_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD9_res"
type: "Eltwise"
bottom: "NBD9_conv2_1x3"
bottom: "DownsamplerBlock8_concat"
top: "NBD9_res"
}
layer {
name: "NBD9_res/relu"
type: "ReLU"
bottom: "NBD9_res"
top: "NBD9_res"
}
layer {
name: "NBD10_conv1_3x1"
type: "Convolution"
bottom: "NBD9_res"
top: "NBD10_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD10_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD10_conv1_3x1"
top: "NBD10_conv1_3x1"
}
layer {
name: "NBD10_conv1_1x3"
type: "Convolution"
bottom: "NBD10_conv1_3x1"
top: "NBD10_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD10_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD10_conv1_1x3"
top: "NBD10_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD10_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD10_conv1_1x3"
top: "NBD10_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD10_conv1_1x3/scale"
type: "Scale"
bottom: "NBD10_conv1_1x3"
top: "NBD10_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD10_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD10_conv1_1x3"
top: "NBD10_conv1_1x3"
}
layer {
name: "NBD10_conv2_3x1"
type: "Convolution"
bottom: "NBD10_conv1_1x3"
top: "NBD10_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 4
pad_w: 0
stride: 1
dilation:4
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD10_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD10_conv2_3x1"
top: "NBD10_conv2_3x1"
}
layer {
name: "NBD10_conv2_1x3"
type: "Convolution"
bottom: "NBD10_conv2_3x1"
top: "NBD10_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 4
stride: 1
dilation:4
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD10_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD10_conv2_1x3"
top: "NBD10_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD10_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD10_conv2_1x3"
top: "NBD10_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD10_conv2_1x3/scale"
type: "Scale"
bottom: "NBD10_conv2_1x3"
top: "NBD10_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD10_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD10_conv2_1x3"
top: "NBD10_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD10_res"
type: "Eltwise"
bottom: "NBD10_conv2_1x3"
bottom: "NBD9_res"
top: "NBD10_res"
}
layer {
name: "NBD10_res/relu"
type: "ReLU"
bottom: "NBD10_res"
top: "NBD10_res"
}
layer {
name: "NBD11_conv1_3x1"
type: "Convolution"
bottom: "NBD10_res"
top: "NBD11_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD11_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD11_conv1_3x1"
top: "NBD11_conv1_3x1"
}
layer {
name: "NBD11_conv1_1x3"
type: "Convolution"
bottom: "NBD11_conv1_3x1"
top: "NBD11_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD11_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD11_conv1_1x3"
top: "NBD11_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD11_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD11_conv1_1x3"
top: "NBD11_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD11_conv1_1x3/scale"
type: "Scale"
bottom: "NBD11_conv1_1x3"
top: "NBD11_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD11_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD11_conv1_1x3"
top: "NBD11_conv1_1x3"
}
layer {
name: "NBD11_conv2_3x1"
type: "Convolution"
bottom: "NBD11_conv1_1x3"
top: "NBD11_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 8
pad_w: 0
stride: 1
dilation:8
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD11_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD11_conv2_3x1"
top: "NBD11_conv2_3x1"
}
layer {
name: "NBD11_conv2_1x3"
type: "Convolution"
bottom: "NBD11_conv2_3x1"
top: "NBD11_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 8
stride: 1
dilation:8
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD11_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD11_conv2_1x3"
top: "NBD11_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD11_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD11_conv2_1x3"
top: "NBD11_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD11_conv2_1x3/scale"
type: "Scale"
bottom: "NBD11_conv2_1x3"
top: "NBD11_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD11_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD11_conv2_1x3"
top: "NBD11_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD11_res"
type: "Eltwise"
bottom: "NBD11_conv2_1x3"
bottom: "NBD10_res"
top: "NBD11_res"
}
layer {
name: "NBD11_res/relu"
type: "ReLU"
bottom: "NBD11_res"
top: "NBD11_res"
}
layer {
name: "NBD12_conv1_3x1"
type: "Convolution"
bottom: "NBD11_res"
top: "NBD12_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD12_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD12_conv1_3x1"
top: "NBD12_conv1_3x1"
}
layer {
name: "NBD12_conv1_1x3"
type: "Convolution"
bottom: "NBD12_conv1_3x1"
top: "NBD12_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD12_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD12_conv1_1x3"
top: "NBD12_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD12_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD12_conv1_1x3"
top: "NBD12_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD12_conv1_1x3/scale"
type: "Scale"
bottom: "NBD12_conv1_1x3"
top: "NBD12_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD12_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD12_conv1_1x3"
top: "NBD12_conv1_1x3"
}
layer {
name: "NBD12_conv2_3x1"
type: "Convolution"
bottom: "NBD12_conv1_1x3"
top: "NBD12_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 16
pad_w: 0
stride: 1
dilation:16
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD12_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD12_conv2_3x1"
top: "NBD12_conv2_3x1"
}
layer {
name: "NBD12_conv2_1x3"
type: "Convolution"
bottom: "NBD12_conv2_3x1"
top: "NBD12_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 16
stride: 1
dilation:16
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD12_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD12_conv2_1x3"
top: "NBD12_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD12_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD12_conv2_1x3"
top: "NBD12_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD12_conv2_1x3/scale"
type: "Scale"
bottom: "NBD12_conv2_1x3"
top: "NBD12_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD12_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD12_conv2_1x3"
top: "NBD12_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD12_res"
type: "Eltwise"
bottom: "NBD12_conv2_1x3"
bottom: "NBD11_res"
top: "NBD12_res"
}
layer {
name: "NBD12_res/relu"
type: "ReLU"
bottom: "NBD12_res"
top: "NBD12_res"
}
layer {
name: "NBD13_conv1_3x1"
type: "Convolution"
bottom: "NBD12_res"
top: "NBD13_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD13_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD13_conv1_3x1"
top: "NBD13_conv1_3x1"
}
layer {
name: "NBD13_conv1_1x3"
type: "Convolution"
bottom: "NBD13_conv1_3x1"
top: "NBD13_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD13_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD13_conv1_1x3"
top: "NBD13_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD13_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD13_conv1_1x3"
top: "NBD13_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD13_conv1_1x3/scale"
type: "Scale"
bottom: "NBD13_conv1_1x3"
top: "NBD13_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD13_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD13_conv1_1x3"
top: "NBD13_conv1_1x3"
}
layer {
name: "NBD13_conv2_3x1"
type: "Convolution"
bottom: "NBD13_conv1_1x3"
top: "NBD13_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 2
pad_w: 0
stride: 1
dilation:2
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD13_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD13_conv2_3x1"
top: "NBD13_conv2_3x1"
}
layer {
name: "NBD13_conv2_1x3"
type: "Convolution"
bottom: "NBD13_conv2_3x1"
top: "NBD13_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 2
stride: 1
dilation:2
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD13_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD13_conv2_1x3"
top: "NBD13_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD13_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD13_conv2_1x3"
top: "NBD13_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD13_conv2_1x3/scale"
type: "Scale"
bottom: "NBD13_conv2_1x3"
top: "NBD13_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD13_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD13_conv2_1x3"
top: "NBD13_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD13_res"
type: "Eltwise"
bottom: "NBD13_conv2_1x3"
bottom: "NBD12_res"
top: "NBD13_res"
}
layer {
name: "NBD13_res/relu"
type: "ReLU"
bottom: "NBD13_res"
top: "NBD13_res"
}
layer {
name: "NBD14_conv1_3x1"
type: "Convolution"
bottom: "NBD13_res"
top: "NBD14_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD14_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD14_conv1_3x1"
top: "NBD14_conv1_3x1"
}
layer {
name: "NBD14_conv1_1x3"
type: "Convolution"
bottom: "NBD14_conv1_3x1"
top: "NBD14_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD14_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD14_conv1_1x3"
top: "NBD14_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD14_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD14_conv1_1x3"
top: "NBD14_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD14_conv1_1x3/scale"
type: "Scale"
bottom: "NBD14_conv1_1x3"
top: "NBD14_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD14_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD14_conv1_1x3"
top: "NBD14_conv1_1x3"
}
layer {
name: "NBD14_conv2_3x1"
type: "Convolution"
bottom: "NBD14_conv1_1x3"
top: "NBD14_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 4
pad_w: 0
stride: 1
dilation:4
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD14_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD14_conv2_3x1"
top: "NBD14_conv2_3x1"
}
layer {
name: "NBD14_conv2_1x3"
type: "Convolution"
bottom: "NBD14_conv2_3x1"
top: "NBD14_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 4
stride: 1
dilation:4
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD14_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD14_conv2_1x3"
top: "NBD14_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD14_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD14_conv2_1x3"
top: "NBD14_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD14_conv2_1x3/scale"
type: "Scale"
bottom: "NBD14_conv2_1x3"
top: "NBD14_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD14_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD14_conv2_1x3"
top: "NBD14_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD14_res"
type: "Eltwise"
bottom: "NBD14_conv2_1x3"
bottom: "NBD13_res"
top: "NBD14_res"
}
layer {
name: "NBD14_res/relu"
type: "ReLU"
bottom: "NBD14_res"
top: "NBD14_res"
}
layer {
name: "NBD15_conv1_3x1"
type: "Convolution"
bottom: "NBD14_res"
top: "NBD15_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD15_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD15_conv1_3x1"
top: "NBD15_conv1_3x1"
}
layer {
name: "NBD15_conv1_1x3"
type: "Convolution"
bottom: "NBD15_conv1_3x1"
top: "NBD15_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD15_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD15_conv1_1x3"
top: "NBD15_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD15_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD15_conv1_1x3"
top: "NBD15_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD15_conv1_1x3/scale"
type: "Scale"
bottom: "NBD15_conv1_1x3"
top: "NBD15_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD15_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD15_conv1_1x3"
top: "NBD15_conv1_1x3"
}
layer {
name: "NBD15_conv2_3x1"
type: "Convolution"
bottom: "NBD15_conv1_1x3"
top: "NBD15_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 8
pad_w: 0
stride: 1
dilation:8
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD15_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD15_conv2_3x1"
top: "NBD15_conv2_3x1"
}
layer {
name: "NBD15_conv2_1x3"
type: "Convolution"
bottom: "NBD15_conv2_3x1"
top: "NBD15_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 8
stride: 1
dilation:8
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD15_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD15_conv2_1x3"
top: "NBD15_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD15_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD15_conv2_1x3"
top: "NBD15_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD15_conv2_1x3/scale"
type: "Scale"
bottom: "NBD15_conv2_1x3"
top: "NBD15_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD15_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD15_conv2_1x3"
top: "NBD15_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD15_res"
type: "Eltwise"
bottom: "NBD15_conv2_1x3"
bottom: "NBD14_res"
top: "NBD15_res"
}
layer {
name: "NBD15_res/relu"
type: "ReLU"
bottom: "NBD15_res"
top: "NBD15_res"
}
layer {
name: "NBD16_conv1_3x1"
type: "Convolution"
bottom: "NBD15_res"
top: "NBD16_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD16_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD16_conv1_3x1"
top: "NBD16_conv1_3x1"
}
layer {
name: "NBD16_conv1_1x3"
type: "Convolution"
bottom: "NBD16_conv1_3x1"
top: "NBD16_conv1_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD16_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD16_conv1_1x3"
top: "NBD16_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD16_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD16_conv1_1x3"
top: "NBD16_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD16_conv1_1x3/scale"
type: "Scale"
bottom: "NBD16_conv1_1x3"
top: "NBD16_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD16_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD16_conv1_1x3"
top: "NBD16_conv1_1x3"
}
layer {
name: "NBD16_conv2_3x1"
type: "Convolution"
bottom: "NBD16_conv1_1x3"
top: "NBD16_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_h:3
kernel_w:1
pad_h: 16
pad_w: 0
stride: 1
dilation:16
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD16_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD16_conv2_3x1"
top: "NBD16_conv2_3x1"
}
layer {
name: "NBD16_conv2_1x3"
type: "Convolution"
bottom: "NBD16_conv2_3x1"
top: "NBD16_conv2_1x3"
convolution_param {
num_output: 128
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 16
stride: 1
dilation:16
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD16_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD16_conv2_1x3"
top: "NBD16_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD16_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD16_conv2_1x3"
top: "NBD16_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD16_conv2_1x3/scale"
type: "Scale"
bottom: "NBD16_conv2_1x3"
top: "NBD16_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD16_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD16_conv2_1x3"
top: "NBD16_conv2_1x3"
dropout_param {
dropout_ratio: 0.3
}
}
layer {
name: "NBD16_res"
type: "Eltwise"
bottom: "NBD16_conv2_1x3"
bottom: "NBD15_res"
top: "NBD16_res"
}
layer {
name: "NBD16_res/relu"
type: "ReLU"
bottom: "NBD16_res"
top: "NBD16_res"
}
layer {
name: "UpsamplerBlock17_deconv"
type: "Deconvolution"
bottom: "NBD16_res"
top: "UpsamplerBlock17_deconv"
convolution_param {
num_output: 64
kernel_size: 2
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term:false
}
}
layer {
name: "UpsamplerBlock17_deconv/bn"
type: "BatchNorm"
bottom: "UpsamplerBlock17_deconv"
top: "UpsamplerBlock17_deconv"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "UpsamplerBlock17_deconv/bn"
type: "BatchNorm"
bottom: "UpsamplerBlock17_deconv"
top: "UpsamplerBlock17_deconv"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "UpsamplerBlock17_deconv/scale"
type: "Scale"
bottom: "UpsamplerBlock17_deconv"
top: "UpsamplerBlock17_deconv"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "UpsamplerBlock17_deconv/relu"
type: "ReLU"
bottom: "UpsamplerBlock17_deconv"
top: "UpsamplerBlock17_deconv"
}
layer {
name: "NBD18_conv1_3x1"
type: "Convolution"
bottom: "UpsamplerBlock17_deconv"
top: "NBD18_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD18_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD18_conv1_3x1"
top: "NBD18_conv1_3x1"
}
layer {
name: "NBD18_conv1_1x3"
type: "Convolution"
bottom: "NBD18_conv1_3x1"
top: "NBD18_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD18_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD18_conv1_1x3"
top: "NBD18_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD18_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD18_conv1_1x3"
top: "NBD18_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD18_conv1_1x3/scale"
type: "Scale"
bottom: "NBD18_conv1_1x3"
top: "NBD18_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD18_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD18_conv1_1x3"
top: "NBD18_conv1_1x3"
}
layer {
name: "NBD18_conv2_3x1"
type: "Convolution"
bottom: "NBD18_conv1_1x3"
top: "NBD18_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD18_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD18_conv2_3x1"
top: "NBD18_conv2_3x1"
}
layer {
name: "NBD18_conv2_1x3"
type: "Convolution"
bottom: "NBD18_conv2_3x1"
top: "NBD18_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD18_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD18_conv2_1x3"
top: "NBD18_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD18_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD18_conv2_1x3"
top: "NBD18_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD18_conv2_1x3/scale"
type: "Scale"
bottom: "NBD18_conv2_1x3"
top: "NBD18_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD18_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD18_conv2_1x3"
top: "NBD18_conv2_1x3"
dropout_param {
dropout_ratio: 0.1
}
}
layer {
name: "NBD18_res"
type: "Eltwise"
bottom: "NBD18_conv2_1x3"
bottom: "UpsamplerBlock17_deconv"
top: "NBD18_res"
}
layer {
name: "NBD18_res/relu"
type: "ReLU"
bottom: "NBD18_res"
top: "NBD18_res"
}
layer {
name: "NBD19_conv1_3x1"
type: "Convolution"
bottom: "NBD18_res"
top: "NBD19_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD19_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD19_conv1_3x1"
top: "NBD19_conv1_3x1"
}
layer {
name: "NBD19_conv1_1x3"
type: "Convolution"
bottom: "NBD19_conv1_3x1"
top: "NBD19_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD19_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_conv1_1x3"
top: "NBD19_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD19_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_conv1_1x3"
top: "NBD19_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD19_conv1_1x3/scale"
type: "Scale"
bottom: "NBD19_conv1_1x3"
top: "NBD19_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD19_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD19_conv1_1x3"
top: "NBD19_conv1_1x3"
}
layer {
name: "NBD19_conv2_3x1"
type: "Convolution"
bottom: "NBD19_conv1_1x3"
top: "NBD19_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD19_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD19_conv2_3x1"
top: "NBD19_conv2_3x1"
}
layer {
name: "NBD19_conv2_1x3"
type: "Convolution"
bottom: "NBD19_conv2_3x1"
top: "NBD19_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD19_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_conv2_1x3"
top: "NBD19_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD19_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_conv2_1x3"
top: "NBD19_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD19_conv2_1x3/scale"
type: "Scale"
bottom: "NBD19_conv2_1x3"
top: "NBD19_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD19_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD19_conv2_1x3"
top: "NBD19_conv2_1x3"
dropout_param {
dropout_ratio: 0.1
}
}
layer {
name: "NBD19_res"
type: "Eltwise"
bottom: "NBD19_conv2_1x3"
bottom: "NBD18_res"
top: "NBD19_res"
}
layer {
name: "NBD19_res/relu"
type: "ReLU"
bottom: "NBD19_res"
top: "NBD19_res"
}
layer {
name: "NBD19_add_conv1_3x1"
type: "Convolution"
bottom: "NBD19_res"
top: "NBD19_add_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD19_add_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD19_add_conv1_3x1"
top: "NBD19_add_conv1_3x1"
}
layer {
name: "NBD19_add_conv1_1x3"
type: "Convolution"
bottom: "NBD19_add_conv1_3x1"
top: "NBD19_add_conv1_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD19_add_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_add_conv1_1x3"
top: "NBD19_add_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD19_add_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_add_conv1_1x3"
top: "NBD19_add_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD19_add_conv1_1x3/scale"
type: "Scale"
bottom: "NBD19_add_conv1_1x3"
top: "NBD19_add_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD19_add_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD19_add_conv1_1x3"
top: "NBD19_add_conv1_1x3"
}
layer {
name: "NBD19_add_conv2_3x1"
type: "Convolution"
bottom: "NBD19_add_conv1_1x3"
top: "NBD19_add_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD19_add_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD19_add_conv2_3x1"
top: "NBD19_add_conv2_3x1"
}
layer {
name: "NBD19_add_conv2_1x3"
type: "Convolution"
bottom: "NBD19_add_conv2_3x1"
top: "NBD19_add_conv2_1x3"
convolution_param {
num_output: 64
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD19_add_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_add_conv2_1x3"
top: "NBD19_add_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD19_add_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD19_add_conv2_1x3"
top: "NBD19_add_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD19_add_conv2_1x3/scale"
type: "Scale"
bottom: "NBD19_add_conv2_1x3"
top: "NBD19_add_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD19_add_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD19_add_conv2_1x3"
top: "NBD19_add_conv2_1x3"
dropout_param {
dropout_ratio: 0.1
}
}
layer {
name: "NBD19_add_res"
type: "Eltwise"
bottom: "NBD19_add_conv2_1x3"
bottom: "NBD19_res"
top: "NBD19_add_res"
}
layer {
name: "NBD19_add_res/relu"
type: "ReLU"
bottom: "NBD19_add_res"
top: "NBD19_add_res"
}
layer {
name: "UpsamplerBlock20_deconv"
type: "Deconvolution"
bottom: "NBD19_add_res"
top: "UpsamplerBlock20_deconv"
convolution_param {
num_output: 16
kernel_size: 2
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "UpsamplerBlock20_deconv/bn"
type: "BatchNorm"
bottom: "UpsamplerBlock20_deconv"
top: "UpsamplerBlock20_deconv"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "UpsamplerBlock20_deconv/bn"
type: "BatchNorm"
bottom: "UpsamplerBlock20_deconv"
top: "UpsamplerBlock20_deconv"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "UpsamplerBlock20_deconv/scale"
type: "Scale"
bottom: "UpsamplerBlock20_deconv"
top: "UpsamplerBlock20_deconv"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "UpsamplerBlock20_deconv/relu"
type: "ReLU"
bottom: "UpsamplerBlock20_deconv"
top: "UpsamplerBlock20_deconv"
}
layer {
name: "NBD21_conv1_3x1"
type: "Convolution"
bottom: "UpsamplerBlock20_deconv"
top: "NBD21_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD21_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD21_conv1_3x1"
top: "NBD21_conv1_3x1"
}
layer {
name: "NBD21_conv1_1x3"
type: "Convolution"
bottom: "NBD21_conv1_3x1"
top: "NBD21_conv1_1x3"
convolution_param {
num_output: 16
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD21_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD21_conv1_1x3"
top: "NBD21_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD21_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD21_conv1_1x3"
top: "NBD21_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD21_conv1_1x3/scale"
type: "Scale"
bottom: "NBD21_conv1_1x3"
top: "NBD21_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD21_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD21_conv1_1x3"
top: "NBD21_conv1_1x3"
}
layer {
name: "NBD21_conv2_3x1"
type: "Convolution"
bottom: "NBD21_conv1_1x3"
top: "NBD21_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD21_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD21_conv2_3x1"
top: "NBD21_conv2_3x1"
}
layer {
name: "NBD21_conv2_1x3"
type: "Convolution"
bottom: "NBD21_conv2_3x1"
top: "NBD21_conv2_1x3"
convolution_param {
num_output: 16
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD21_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD21_conv2_1x3"
top: "NBD21_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD21_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD21_conv2_1x3"
top: "NBD21_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD21_conv2_1x3/scale"
type: "Scale"
bottom: "NBD21_conv2_1x3"
top: "NBD21_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD21_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD21_conv2_1x3"
top: "NBD21_conv2_1x3"
dropout_param {
dropout_ratio: 0.1
}
}
layer {
name: "NBD21_res"
type: "Eltwise"
bottom: "NBD21_conv2_1x3"
bottom: "UpsamplerBlock20_deconv"
top: "NBD21_res"
}
layer {
name: "NBD21_res/relu"
type: "ReLU"
bottom: "NBD21_res"
top: "NBD21_res"
}
layer {
name: "NBD22_conv1_3x1"
type: "Convolution"
bottom: "NBD21_res"
top: "NBD22_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD22_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD22_conv1_3x1"
top: "NBD22_conv1_3x1"
}
layer {
name: "NBD22_conv1_1x3"
type: "Convolution"
bottom: "NBD22_conv1_3x1"
top: "NBD22_conv1_1x3"
convolution_param {
num_output: 16
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD22_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_conv1_1x3"
top: "NBD22_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD22_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_conv1_1x3"
top: "NBD22_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD22_conv1_1x3/scale"
type: "Scale"
bottom: "NBD22_conv1_1x3"
top: "NBD22_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD22_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD22_conv1_1x3"
top: "NBD22_conv1_1x3"
}
layer {
name: "NBD22_conv2_3x1"
type: "Convolution"
bottom: "NBD22_conv1_1x3"
top: "NBD22_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD22_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD22_conv2_3x1"
top: "NBD22_conv2_3x1"
}
layer {
name: "NBD22_conv2_1x3"
type: "Convolution"
bottom: "NBD22_conv2_3x1"
top: "NBD22_conv2_1x3"
convolution_param {
num_output: 16
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD22_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_conv2_1x3"
top: "NBD22_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD22_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_conv2_1x3"
top: "NBD22_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD22_conv2_1x3/scale"
type: "Scale"
bottom: "NBD22_conv2_1x3"
top: "NBD22_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD22_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD22_conv2_1x3"
top: "NBD22_conv2_1x3"
dropout_param {
dropout_ratio: 0.1
}
}
layer {
name: "NBD22_res"
type: "Eltwise"
bottom: "NBD22_conv2_1x3"
bottom: "NBD21_res"
top: "NBD22_res"
}
layer {
name: "NBD22_res/relu"
type: "ReLU"
bottom: "NBD22_res"
top: "NBD22_res"
}
layer {
name: "NBD22_add_conv1_3x1"
type: "Convolution"
bottom: "NBD22_res"
top: "NBD22_add_conv1_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD22_add_conv1_3x1/relu"
type: "ReLU"
bottom: "NBD22_add_conv1_3x1"
top: "NBD22_add_conv1_3x1"
}
layer {
name: "NBD22_add_conv1_1x3"
type: "Convolution"
bottom: "NBD22_add_conv1_3x1"
top: "NBD22_add_conv1_1x3"
convolution_param {
num_output: 16
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD22_add_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_add_conv1_1x3"
top: "NBD22_add_conv1_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD22_add_conv1_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_add_conv1_1x3"
top: "NBD22_add_conv1_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD22_add_conv1_1x3/scale"
type: "Scale"
bottom: "NBD22_add_conv1_1x3"
top: "NBD22_add_conv1_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD22_add_conv1_1x3/relu"
type: "ReLU"
bottom: "NBD22_add_conv1_1x3"
top: "NBD22_add_conv1_1x3"
}
layer {
name: "NBD22_add_conv2_3x1"
type: "Convolution"
bottom: "NBD22_add_conv1_1x3"
top: "NBD22_add_conv2_3x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_h:3
kernel_w:1
pad_h: 1
pad_w: 0
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: true
}
}
layer {
name: "NBD22_add_conv2_3x1/relu"
type: "ReLU"
bottom: "NBD22_add_conv2_3x1"
top: "NBD22_add_conv2_3x1"
}
layer {
name: "NBD22_add_conv2_1x3"
type: "Convolution"
bottom: "NBD22_add_conv2_3x1"
top: "NBD22_add_conv2_1x3"
convolution_param {
num_output: 16
kernel_h:1
kernel_w:3
pad_h: 0
pad_w: 1
stride: 1
dilation:1
weight_filler {
type: "msra"
}
bias_term: false
}
}
layer {
name: "NBD22_add_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_add_conv2_1x3"
top: "NBD22_add_conv2_1x3"
batch_norm_param {
use_global_stats: false
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TRAIN
}
}
layer {
name: "NBD22_add_conv2_1x3/bn"
type: "BatchNorm"
bottom: "NBD22_add_conv2_1x3"
top: "NBD22_add_conv2_1x3"
batch_norm_param {
use_global_stats: true
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
include {
phase: TEST
}
}
layer {
name: "NBD22_add_conv2_1x3/scale"
type: "Scale"
bottom: "NBD22_add_conv2_1x3"
top: "NBD22_add_conv2_1x3"
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 1
decay_mult: 0
}
scale_param {
bias_term: true
}
}
layer {
name: "NBD22_add_conv2_1x3/dropout"
type: "Dropout"
bottom: "NBD22_add_conv2_1x3"
top: "NBD22_add_conv2_1x3"
dropout_param {
dropout_ratio: 0.1
}
}
layer {
name: "NBD22_add_res"
type: "Eltwise"
bottom: "NBD22_add_conv2_1x3"
bottom: "NBD22_res"
top: "NBD22_add_res"
}
layer {
name: "NBD22_add_res/relu"
type: "ReLU"
bottom: "NBD22_add_res"
top: "NBD22_add_res"
}
layer {
name: "Deconvolution23_deconv"
type: "Deconvolution"
bottom: "NBD22_add_res"
top: "Deconvolution23_deconv"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 19
kernel_size: 2
stride: 2
weight_filler {
type: "msra"
}
bias_term: true
}
}
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