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stromnov/MemNet.prototxt

Created August 28, 2017 11:20
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MemNet.prototxt
name: "P40_MemNet_M6R6_80C64"
input: "data"
input_dim: 1
input_dim: 1
input_dim: 144
input_dim: 144
layer {
name: "bn_conv1"
type: "BatchNorm"
bottom: "data"
top: "bn_conv1"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv1"
type: "Scale"
bottom: "bn_conv1"
top: "bn_conv1"
scale_param {
bias_term: true
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "bn_conv1"
top: "bn_conv1"
}
layer {
name: "conv1"
type: "Convolution"
bottom: "bn_conv1"
top: "conv1"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_01_a"
type: "BatchNorm"
bottom: "conv1"
top: "bn_conv01_01_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_01_a"
type: "Scale"
bottom: "bn_conv01_01_a"
top: "bn_conv01_01_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_01_a"
type: "ReLU"
bottom: "bn_conv01_01_a"
top: "bn_conv01_01_a"
}
layer {
name: "conv01_01_a"
type: "Convolution"
bottom: "bn_conv01_01_a"
top: "conv01_01_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_01_b"
type: "BatchNorm"
bottom: "conv01_01_a"
top: "bn_conv01_01_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_01_b"
type: "Scale"
bottom: "bn_conv01_01_b"
top: "bn_conv01_01_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_01_b"
type: "ReLU"
bottom: "bn_conv01_01_b"
top: "bn_conv01_01_b"
}
layer {
name: "conv01_01_b"
type: "Convolution"
bottom: "bn_conv01_01_b"
top: "conv01_01_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise01_01"
type: "Eltwise"
bottom: "conv1"
bottom: "conv01_01_b"
top: "eltwise01_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv01_02_a"
type: "BatchNorm"
bottom: "eltwise01_01"
top: "bn_conv01_02_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_02_a"
type: "Scale"
bottom: "bn_conv01_02_a"
top: "bn_conv01_02_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_02_a"
type: "ReLU"
bottom: "bn_conv01_02_a"
top: "bn_conv01_02_a"
}
layer {
name: "conv01_02_a"
type: "Convolution"
bottom: "bn_conv01_02_a"
top: "conv01_02_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_02_b"
type: "BatchNorm"
bottom: "conv01_02_a"
top: "bn_conv01_02_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_02_b"
type: "Scale"
bottom: "bn_conv01_02_b"
top: "bn_conv01_02_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_02_b"
type: "ReLU"
bottom: "bn_conv01_02_b"
top: "bn_conv01_02_b"
}
layer {
name: "conv01_02_b"
type: "Convolution"
bottom: "bn_conv01_02_b"
top: "conv01_02_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise01_02"
type: "Eltwise"
bottom: "eltwise01_01"
bottom: "conv01_02_b"
top: "eltwise01_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv01_03_a"
type: "BatchNorm"
bottom: "eltwise01_02"
top: "bn_conv01_03_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_03_a"
type: "Scale"
bottom: "bn_conv01_03_a"
top: "bn_conv01_03_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_03_a"
type: "ReLU"
bottom: "bn_conv01_03_a"
top: "bn_conv01_03_a"
}
layer {
name: "conv01_03_a"
type: "Convolution"
bottom: "bn_conv01_03_a"
top: "conv01_03_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_03_b"
type: "BatchNorm"
bottom: "conv01_03_a"
top: "bn_conv01_03_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_03_b"
type: "Scale"
bottom: "bn_conv01_03_b"
top: "bn_conv01_03_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_03_b"
type: "ReLU"
bottom: "bn_conv01_03_b"
top: "bn_conv01_03_b"
}
layer {
name: "conv01_03_b"
type: "Convolution"
bottom: "bn_conv01_03_b"
top: "conv01_03_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise01_03"
type: "Eltwise"
bottom: "eltwise01_02"
bottom: "conv01_03_b"
top: "eltwise01_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv01_04_a"
type: "BatchNorm"
bottom: "eltwise01_03"
top: "bn_conv01_04_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_04_a"
type: "Scale"
bottom: "bn_conv01_04_a"
top: "bn_conv01_04_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_04_a"
type: "ReLU"
bottom: "bn_conv01_04_a"
top: "bn_conv01_04_a"
}
layer {
name: "conv01_04_a"
type: "Convolution"
bottom: "bn_conv01_04_a"
top: "conv01_04_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_04_b"
type: "BatchNorm"
bottom: "conv01_04_a"
top: "bn_conv01_04_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_04_b"
type: "Scale"
bottom: "bn_conv01_04_b"
top: "bn_conv01_04_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_04_b"
type: "ReLU"
bottom: "bn_conv01_04_b"
top: "bn_conv01_04_b"
}
layer {
name: "conv01_04_b"
type: "Convolution"
bottom: "bn_conv01_04_b"
top: "conv01_04_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise01_04"
type: "Eltwise"
bottom: "eltwise01_03"
bottom: "conv01_04_b"
top: "eltwise01_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv01_05_a"
type: "BatchNorm"
bottom: "eltwise01_04"
top: "bn_conv01_05_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_05_a"
type: "Scale"
bottom: "bn_conv01_05_a"
top: "bn_conv01_05_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_05_a"
type: "ReLU"
bottom: "bn_conv01_05_a"
top: "bn_conv01_05_a"
}
layer {
name: "conv01_05_a"
type: "Convolution"
bottom: "bn_conv01_05_a"
top: "conv01_05_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_05_b"
type: "BatchNorm"
bottom: "conv01_05_a"
top: "bn_conv01_05_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_05_b"
type: "Scale"
bottom: "bn_conv01_05_b"
top: "bn_conv01_05_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_05_b"
type: "ReLU"
bottom: "bn_conv01_05_b"
top: "bn_conv01_05_b"
}
layer {
name: "conv01_05_b"
type: "Convolution"
bottom: "bn_conv01_05_b"
top: "conv01_05_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise01_05"
type: "Eltwise"
bottom: "eltwise01_04"
bottom: "conv01_05_b"
top: "eltwise01_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv01_06_a"
type: "BatchNorm"
bottom: "eltwise01_05"
top: "bn_conv01_06_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_06_a"
type: "Scale"
bottom: "bn_conv01_06_a"
top: "bn_conv01_06_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_06_a"
type: "ReLU"
bottom: "bn_conv01_06_a"
top: "bn_conv01_06_a"
}
layer {
name: "conv01_06_a"
type: "Convolution"
bottom: "bn_conv01_06_a"
top: "conv01_06_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv01_06_b"
type: "BatchNorm"
bottom: "conv01_06_a"
top: "bn_conv01_06_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv01_06_b"
type: "Scale"
bottom: "bn_conv01_06_b"
top: "bn_conv01_06_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu01_06_b"
type: "ReLU"
bottom: "bn_conv01_06_b"
top: "bn_conv01_06_b"
}
layer {
name: "conv01_06_b"
type: "Convolution"
bottom: "bn_conv01_06_b"
top: "conv01_06_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise01_06"
type: "Eltwise"
bottom: "eltwise01_05"
bottom: "conv01_06_b"
top: "eltwise01_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "concat01"
type: "Concat"
bottom: "conv1"
bottom: "eltwise01_01"
bottom: "eltwise01_02"
bottom: "eltwise01_03"
bottom: "eltwise01_04"
bottom: "eltwise01_05"
bottom: "eltwise01_06"
top: "concat01"
concat_param {
axis: 1
}
}
layer {
name: "bn_conv_transition_01"
type: "BatchNorm"
bottom: "concat01"
top: "bn_conv_transition_01"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_transition_01"
type: "Scale"
bottom: "bn_conv_transition_01"
top: "bn_conv_transition_01"
scale_param {
bias_term: true
}
}
layer {
name: "relu_transition_01"
type: "ReLU"
bottom: "bn_conv_transition_01"
top: "bn_conv_transition_01"
}
layer {
name: "conv_transition_01"
type: "Convolution"
bottom: "bn_conv_transition_01"
top: "conv_transition_01"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_01_a"
type: "BatchNorm"
bottom: "conv_transition_01"
top: "bn_conv02_01_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_01_a"
type: "Scale"
bottom: "bn_conv02_01_a"
top: "bn_conv02_01_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_01_a"
type: "ReLU"
bottom: "bn_conv02_01_a"
top: "bn_conv02_01_a"
}
layer {
name: "conv02_01_a"
type: "Convolution"
bottom: "bn_conv02_01_a"
top: "conv02_01_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_01_b"
type: "BatchNorm"
bottom: "conv02_01_a"
top: "bn_conv02_01_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_01_b"
type: "Scale"
bottom: "bn_conv02_01_b"
top: "bn_conv02_01_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_01_b"
type: "ReLU"
bottom: "bn_conv02_01_b"
top: "bn_conv02_01_b"
}
layer {
name: "conv02_01_b"
type: "Convolution"
bottom: "bn_conv02_01_b"
top: "conv02_01_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise02_01"
type: "Eltwise"
bottom: "conv_transition_01"
bottom: "conv02_01_b"
top: "eltwise02_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv02_02_a"
type: "BatchNorm"
bottom: "eltwise02_01"
top: "bn_conv02_02_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_02_a"
type: "Scale"
bottom: "bn_conv02_02_a"
top: "bn_conv02_02_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_02_a"
type: "ReLU"
bottom: "bn_conv02_02_a"
top: "bn_conv02_02_a"
}
layer {
name: "conv02_02_a"
type: "Convolution"
bottom: "bn_conv02_02_a"
top: "conv02_02_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_02_b"
type: "BatchNorm"
bottom: "conv02_02_a"
top: "bn_conv02_02_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_02_b"
type: "Scale"
bottom: "bn_conv02_02_b"
top: "bn_conv02_02_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_02_b"
type: "ReLU"
bottom: "bn_conv02_02_b"
top: "bn_conv02_02_b"
}
layer {
name: "conv02_02_b"
type: "Convolution"
bottom: "bn_conv02_02_b"
top: "conv02_02_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise02_02"
type: "Eltwise"
bottom: "eltwise02_01"
bottom: "conv02_02_b"
top: "eltwise02_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv02_03_a"
type: "BatchNorm"
bottom: "eltwise02_02"
top: "bn_conv02_03_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_03_a"
type: "Scale"
bottom: "bn_conv02_03_a"
top: "bn_conv02_03_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_03_a"
type: "ReLU"
bottom: "bn_conv02_03_a"
top: "bn_conv02_03_a"
}
layer {
name: "conv02_03_a"
type: "Convolution"
bottom: "bn_conv02_03_a"
top: "conv02_03_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_03_b"
type: "BatchNorm"
bottom: "conv02_03_a"
top: "bn_conv02_03_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_03_b"
type: "Scale"
bottom: "bn_conv02_03_b"
top: "bn_conv02_03_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_03_b"
type: "ReLU"
bottom: "bn_conv02_03_b"
top: "bn_conv02_03_b"
}
layer {
name: "conv02_03_b"
type: "Convolution"
bottom: "bn_conv02_03_b"
top: "conv02_03_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise02_03"
type: "Eltwise"
bottom: "eltwise02_02"
bottom: "conv02_03_b"
top: "eltwise02_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv02_04_a"
type: "BatchNorm"
bottom: "eltwise02_03"
top: "bn_conv02_04_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_04_a"
type: "Scale"
bottom: "bn_conv02_04_a"
top: "bn_conv02_04_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_04_a"
type: "ReLU"
bottom: "bn_conv02_04_a"
top: "bn_conv02_04_a"
}
layer {
name: "conv02_04_a"
type: "Convolution"
bottom: "bn_conv02_04_a"
top: "conv02_04_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_04_b"
type: "BatchNorm"
bottom: "conv02_04_a"
top: "bn_conv02_04_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_04_b"
type: "Scale"
bottom: "bn_conv02_04_b"
top: "bn_conv02_04_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_04_b"
type: "ReLU"
bottom: "bn_conv02_04_b"
top: "bn_conv02_04_b"
}
layer {
name: "conv02_04_b"
type: "Convolution"
bottom: "bn_conv02_04_b"
top: "conv02_04_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise02_04"
type: "Eltwise"
bottom: "eltwise02_03"
bottom: "conv02_04_b"
top: "eltwise02_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv02_05_a"
type: "BatchNorm"
bottom: "eltwise02_04"
top: "bn_conv02_05_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_05_a"
type: "Scale"
bottom: "bn_conv02_05_a"
top: "bn_conv02_05_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_05_a"
type: "ReLU"
bottom: "bn_conv02_05_a"
top: "bn_conv02_05_a"
}
layer {
name: "conv02_05_a"
type: "Convolution"
bottom: "bn_conv02_05_a"
top: "conv02_05_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_05_b"
type: "BatchNorm"
bottom: "conv02_05_a"
top: "bn_conv02_05_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_05_b"
type: "Scale"
bottom: "bn_conv02_05_b"
top: "bn_conv02_05_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_05_b"
type: "ReLU"
bottom: "bn_conv02_05_b"
top: "bn_conv02_05_b"
}
layer {
name: "conv02_05_b"
type: "Convolution"
bottom: "bn_conv02_05_b"
top: "conv02_05_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise02_05"
type: "Eltwise"
bottom: "eltwise02_04"
bottom: "conv02_05_b"
top: "eltwise02_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv02_06_a"
type: "BatchNorm"
bottom: "eltwise02_05"
top: "bn_conv02_06_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_06_a"
type: "Scale"
bottom: "bn_conv02_06_a"
top: "bn_conv02_06_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_06_a"
type: "ReLU"
bottom: "bn_conv02_06_a"
top: "bn_conv02_06_a"
}
layer {
name: "conv02_06_a"
type: "Convolution"
bottom: "bn_conv02_06_a"
top: "conv02_06_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv02_06_b"
type: "BatchNorm"
bottom: "conv02_06_a"
top: "bn_conv02_06_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv02_06_b"
type: "Scale"
bottom: "bn_conv02_06_b"
top: "bn_conv02_06_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu02_06_b"
type: "ReLU"
bottom: "bn_conv02_06_b"
top: "bn_conv02_06_b"
}
layer {
name: "conv02_06_b"
type: "Convolution"
bottom: "bn_conv02_06_b"
top: "conv02_06_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise02_06"
type: "Eltwise"
bottom: "eltwise02_05"
bottom: "conv02_06_b"
top: "eltwise02_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "concat02"
type: "Concat"
bottom: "conv1"
bottom: "conv_transition_01"
bottom: "eltwise02_01"
bottom: "eltwise02_02"
bottom: "eltwise02_03"
bottom: "eltwise02_04"
bottom: "eltwise02_05"
bottom: "eltwise02_06"
top: "concat02"
concat_param {
axis: 1
}
}
layer {
name: "bn_conv_transition_02"
type: "BatchNorm"
bottom: "concat02"
top: "bn_conv_transition_02"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_transition_02"
type: "Scale"
bottom: "bn_conv_transition_02"
top: "bn_conv_transition_02"
scale_param {
bias_term: true
}
}
layer {
name: "relu_transition_02"
type: "ReLU"
bottom: "bn_conv_transition_02"
top: "bn_conv_transition_02"
}
layer {
name: "conv_transition_02"
type: "Convolution"
bottom: "bn_conv_transition_02"
top: "conv_transition_02"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_01_a"
type: "BatchNorm"
bottom: "conv_transition_02"
top: "bn_conv03_01_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_01_a"
type: "Scale"
bottom: "bn_conv03_01_a"
top: "bn_conv03_01_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_01_a"
type: "ReLU"
bottom: "bn_conv03_01_a"
top: "bn_conv03_01_a"
}
layer {
name: "conv03_01_a"
type: "Convolution"
bottom: "bn_conv03_01_a"
top: "conv03_01_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_01_b"
type: "BatchNorm"
bottom: "conv03_01_a"
top: "bn_conv03_01_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_01_b"
type: "Scale"
bottom: "bn_conv03_01_b"
top: "bn_conv03_01_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_01_b"
type: "ReLU"
bottom: "bn_conv03_01_b"
top: "bn_conv03_01_b"
}
layer {
name: "conv03_01_b"
type: "Convolution"
bottom: "bn_conv03_01_b"
top: "conv03_01_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise03_01"
type: "Eltwise"
bottom: "conv_transition_02"
bottom: "conv03_01_b"
top: "eltwise03_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv03_02_a"
type: "BatchNorm"
bottom: "eltwise03_01"
top: "bn_conv03_02_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_02_a"
type: "Scale"
bottom: "bn_conv03_02_a"
top: "bn_conv03_02_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_02_a"
type: "ReLU"
bottom: "bn_conv03_02_a"
top: "bn_conv03_02_a"
}
layer {
name: "conv03_02_a"
type: "Convolution"
bottom: "bn_conv03_02_a"
top: "conv03_02_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_02_b"
type: "BatchNorm"
bottom: "conv03_02_a"
top: "bn_conv03_02_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_02_b"
type: "Scale"
bottom: "bn_conv03_02_b"
top: "bn_conv03_02_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_02_b"
type: "ReLU"
bottom: "bn_conv03_02_b"
top: "bn_conv03_02_b"
}
layer {
name: "conv03_02_b"
type: "Convolution"
bottom: "bn_conv03_02_b"
top: "conv03_02_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise03_02"
type: "Eltwise"
bottom: "eltwise03_01"
bottom: "conv03_02_b"
top: "eltwise03_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv03_03_a"
type: "BatchNorm"
bottom: "eltwise03_02"
top: "bn_conv03_03_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_03_a"
type: "Scale"
bottom: "bn_conv03_03_a"
top: "bn_conv03_03_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_03_a"
type: "ReLU"
bottom: "bn_conv03_03_a"
top: "bn_conv03_03_a"
}
layer {
name: "conv03_03_a"
type: "Convolution"
bottom: "bn_conv03_03_a"
top: "conv03_03_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_03_b"
type: "BatchNorm"
bottom: "conv03_03_a"
top: "bn_conv03_03_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_03_b"
type: "Scale"
bottom: "bn_conv03_03_b"
top: "bn_conv03_03_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_03_b"
type: "ReLU"
bottom: "bn_conv03_03_b"
top: "bn_conv03_03_b"
}
layer {
name: "conv03_03_b"
type: "Convolution"
bottom: "bn_conv03_03_b"
top: "conv03_03_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise03_03"
type: "Eltwise"
bottom: "eltwise03_02"
bottom: "conv03_03_b"
top: "eltwise03_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv03_04_a"
type: "BatchNorm"
bottom: "eltwise03_03"
top: "bn_conv03_04_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_04_a"
type: "Scale"
bottom: "bn_conv03_04_a"
top: "bn_conv03_04_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_04_a"
type: "ReLU"
bottom: "bn_conv03_04_a"
top: "bn_conv03_04_a"
}
layer {
name: "conv03_04_a"
type: "Convolution"
bottom: "bn_conv03_04_a"
top: "conv03_04_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_04_b"
type: "BatchNorm"
bottom: "conv03_04_a"
top: "bn_conv03_04_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_04_b"
type: "Scale"
bottom: "bn_conv03_04_b"
top: "bn_conv03_04_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_04_b"
type: "ReLU"
bottom: "bn_conv03_04_b"
top: "bn_conv03_04_b"
}
layer {
name: "conv03_04_b"
type: "Convolution"
bottom: "bn_conv03_04_b"
top: "conv03_04_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise03_04"
type: "Eltwise"
bottom: "eltwise03_03"
bottom: "conv03_04_b"
top: "eltwise03_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv03_05_a"
type: "BatchNorm"
bottom: "eltwise03_04"
top: "bn_conv03_05_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_05_a"
type: "Scale"
bottom: "bn_conv03_05_a"
top: "bn_conv03_05_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_05_a"
type: "ReLU"
bottom: "bn_conv03_05_a"
top: "bn_conv03_05_a"
}
layer {
name: "conv03_05_a"
type: "Convolution"
bottom: "bn_conv03_05_a"
top: "conv03_05_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_05_b"
type: "BatchNorm"
bottom: "conv03_05_a"
top: "bn_conv03_05_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_05_b"
type: "Scale"
bottom: "bn_conv03_05_b"
top: "bn_conv03_05_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_05_b"
type: "ReLU"
bottom: "bn_conv03_05_b"
top: "bn_conv03_05_b"
}
layer {
name: "conv03_05_b"
type: "Convolution"
bottom: "bn_conv03_05_b"
top: "conv03_05_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise03_05"
type: "Eltwise"
bottom: "eltwise03_04"
bottom: "conv03_05_b"
top: "eltwise03_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv03_06_a"
type: "BatchNorm"
bottom: "eltwise03_05"
top: "bn_conv03_06_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_06_a"
type: "Scale"
bottom: "bn_conv03_06_a"
top: "bn_conv03_06_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_06_a"
type: "ReLU"
bottom: "bn_conv03_06_a"
top: "bn_conv03_06_a"
}
layer {
name: "conv03_06_a"
type: "Convolution"
bottom: "bn_conv03_06_a"
top: "conv03_06_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv03_06_b"
type: "BatchNorm"
bottom: "conv03_06_a"
top: "bn_conv03_06_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv03_06_b"
type: "Scale"
bottom: "bn_conv03_06_b"
top: "bn_conv03_06_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu03_06_b"
type: "ReLU"
bottom: "bn_conv03_06_b"
top: "bn_conv03_06_b"
}
layer {
name: "conv03_06_b"
type: "Convolution"
bottom: "bn_conv03_06_b"
top: "conv03_06_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise03_06"
type: "Eltwise"
bottom: "eltwise03_05"
bottom: "conv03_06_b"
top: "eltwise03_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "concat03"
type: "Concat"
bottom: "conv1"
bottom: "conv_transition_01"
bottom: "conv_transition_02"
bottom: "eltwise03_01"
bottom: "eltwise03_02"
bottom: "eltwise03_03"
bottom: "eltwise03_04"
bottom: "eltwise03_05"
bottom: "eltwise03_06"
top: "concat03"
concat_param {
axis: 1
}
}
layer {
name: "bn_conv_transition_03"
type: "BatchNorm"
bottom: "concat03"
top: "bn_conv_transition_03"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_transition_03"
type: "Scale"
bottom: "bn_conv_transition_03"
top: "bn_conv_transition_03"
scale_param {
bias_term: true
}
}
layer {
name: "relu_transition_03"
type: "ReLU"
bottom: "bn_conv_transition_03"
top: "bn_conv_transition_03"
}
layer {
name: "conv_transition_03"
type: "Convolution"
bottom: "bn_conv_transition_03"
top: "conv_transition_03"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_01_a"
type: "BatchNorm"
bottom: "conv_transition_03"
top: "bn_conv04_01_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_01_a"
type: "Scale"
bottom: "bn_conv04_01_a"
top: "bn_conv04_01_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_01_a"
type: "ReLU"
bottom: "bn_conv04_01_a"
top: "bn_conv04_01_a"
}
layer {
name: "conv04_01_a"
type: "Convolution"
bottom: "bn_conv04_01_a"
top: "conv04_01_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_01_b"
type: "BatchNorm"
bottom: "conv04_01_a"
top: "bn_conv04_01_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_01_b"
type: "Scale"
bottom: "bn_conv04_01_b"
top: "bn_conv04_01_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_01_b"
type: "ReLU"
bottom: "bn_conv04_01_b"
top: "bn_conv04_01_b"
}
layer {
name: "conv04_01_b"
type: "Convolution"
bottom: "bn_conv04_01_b"
top: "conv04_01_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise04_01"
type: "Eltwise"
bottom: "conv_transition_03"
bottom: "conv04_01_b"
top: "eltwise04_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv04_02_a"
type: "BatchNorm"
bottom: "eltwise04_01"
top: "bn_conv04_02_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_02_a"
type: "Scale"
bottom: "bn_conv04_02_a"
top: "bn_conv04_02_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_02_a"
type: "ReLU"
bottom: "bn_conv04_02_a"
top: "bn_conv04_02_a"
}
layer {
name: "conv04_02_a"
type: "Convolution"
bottom: "bn_conv04_02_a"
top: "conv04_02_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_02_b"
type: "BatchNorm"
bottom: "conv04_02_a"
top: "bn_conv04_02_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_02_b"
type: "Scale"
bottom: "bn_conv04_02_b"
top: "bn_conv04_02_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_02_b"
type: "ReLU"
bottom: "bn_conv04_02_b"
top: "bn_conv04_02_b"
}
layer {
name: "conv04_02_b"
type: "Convolution"
bottom: "bn_conv04_02_b"
top: "conv04_02_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise04_02"
type: "Eltwise"
bottom: "eltwise04_01"
bottom: "conv04_02_b"
top: "eltwise04_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv04_03_a"
type: "BatchNorm"
bottom: "eltwise04_02"
top: "bn_conv04_03_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_03_a"
type: "Scale"
bottom: "bn_conv04_03_a"
top: "bn_conv04_03_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_03_a"
type: "ReLU"
bottom: "bn_conv04_03_a"
top: "bn_conv04_03_a"
}
layer {
name: "conv04_03_a"
type: "Convolution"
bottom: "bn_conv04_03_a"
top: "conv04_03_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_03_b"
type: "BatchNorm"
bottom: "conv04_03_a"
top: "bn_conv04_03_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_03_b"
type: "Scale"
bottom: "bn_conv04_03_b"
top: "bn_conv04_03_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_03_b"
type: "ReLU"
bottom: "bn_conv04_03_b"
top: "bn_conv04_03_b"
}
layer {
name: "conv04_03_b"
type: "Convolution"
bottom: "bn_conv04_03_b"
top: "conv04_03_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise04_03"
type: "Eltwise"
bottom: "eltwise04_02"
bottom: "conv04_03_b"
top: "eltwise04_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv04_04_a"
type: "BatchNorm"
bottom: "eltwise04_03"
top: "bn_conv04_04_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_04_a"
type: "Scale"
bottom: "bn_conv04_04_a"
top: "bn_conv04_04_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_04_a"
type: "ReLU"
bottom: "bn_conv04_04_a"
top: "bn_conv04_04_a"
}
layer {
name: "conv04_04_a"
type: "Convolution"
bottom: "bn_conv04_04_a"
top: "conv04_04_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_04_b"
type: "BatchNorm"
bottom: "conv04_04_a"
top: "bn_conv04_04_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_04_b"
type: "Scale"
bottom: "bn_conv04_04_b"
top: "bn_conv04_04_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_04_b"
type: "ReLU"
bottom: "bn_conv04_04_b"
top: "bn_conv04_04_b"
}
layer {
name: "conv04_04_b"
type: "Convolution"
bottom: "bn_conv04_04_b"
top: "conv04_04_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise04_04"
type: "Eltwise"
bottom: "eltwise04_03"
bottom: "conv04_04_b"
top: "eltwise04_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv04_05_a"
type: "BatchNorm"
bottom: "eltwise04_04"
top: "bn_conv04_05_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_05_a"
type: "Scale"
bottom: "bn_conv04_05_a"
top: "bn_conv04_05_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_05_a"
type: "ReLU"
bottom: "bn_conv04_05_a"
top: "bn_conv04_05_a"
}
layer {
name: "conv04_05_a"
type: "Convolution"
bottom: "bn_conv04_05_a"
top: "conv04_05_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_05_b"
type: "BatchNorm"
bottom: "conv04_05_a"
top: "bn_conv04_05_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_05_b"
type: "Scale"
bottom: "bn_conv04_05_b"
top: "bn_conv04_05_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_05_b"
type: "ReLU"
bottom: "bn_conv04_05_b"
top: "bn_conv04_05_b"
}
layer {
name: "conv04_05_b"
type: "Convolution"
bottom: "bn_conv04_05_b"
top: "conv04_05_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise04_05"
type: "Eltwise"
bottom: "eltwise04_04"
bottom: "conv04_05_b"
top: "eltwise04_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv04_06_a"
type: "BatchNorm"
bottom: "eltwise04_05"
top: "bn_conv04_06_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_06_a"
type: "Scale"
bottom: "bn_conv04_06_a"
top: "bn_conv04_06_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_06_a"
type: "ReLU"
bottom: "bn_conv04_06_a"
top: "bn_conv04_06_a"
}
layer {
name: "conv04_06_a"
type: "Convolution"
bottom: "bn_conv04_06_a"
top: "conv04_06_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv04_06_b"
type: "BatchNorm"
bottom: "conv04_06_a"
top: "bn_conv04_06_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv04_06_b"
type: "Scale"
bottom: "bn_conv04_06_b"
top: "bn_conv04_06_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu04_06_b"
type: "ReLU"
bottom: "bn_conv04_06_b"
top: "bn_conv04_06_b"
}
layer {
name: "conv04_06_b"
type: "Convolution"
bottom: "bn_conv04_06_b"
top: "conv04_06_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise04_06"
type: "Eltwise"
bottom: "eltwise04_05"
bottom: "conv04_06_b"
top: "eltwise04_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "concat04"
type: "Concat"
bottom: "conv1"
bottom: "conv_transition_01"
bottom: "conv_transition_02"
bottom: "conv_transition_03"
bottom: "eltwise04_01"
bottom: "eltwise04_02"
bottom: "eltwise04_03"
bottom: "eltwise04_04"
bottom: "eltwise04_05"
bottom: "eltwise04_06"
top: "concat04"
concat_param {
axis: 1
}
}
layer {
name: "bn_conv_transition_04"
type: "BatchNorm"
bottom: "concat04"
top: "bn_conv_transition_04"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_transition_04"
type: "Scale"
bottom: "bn_conv_transition_04"
top: "bn_conv_transition_04"
scale_param {
bias_term: true
}
}
layer {
name: "relu_transition_04"
type: "ReLU"
bottom: "bn_conv_transition_04"
top: "bn_conv_transition_04"
}
layer {
name: "conv_transition_04"
type: "Convolution"
bottom: "bn_conv_transition_04"
top: "conv_transition_04"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_01_a"
type: "BatchNorm"
bottom: "conv_transition_04"
top: "bn_conv05_01_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_01_a"
type: "Scale"
bottom: "bn_conv05_01_a"
top: "bn_conv05_01_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_01_a"
type: "ReLU"
bottom: "bn_conv05_01_a"
top: "bn_conv05_01_a"
}
layer {
name: "conv05_01_a"
type: "Convolution"
bottom: "bn_conv05_01_a"
top: "conv05_01_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_01_b"
type: "BatchNorm"
bottom: "conv05_01_a"
top: "bn_conv05_01_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_01_b"
type: "Scale"
bottom: "bn_conv05_01_b"
top: "bn_conv05_01_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_01_b"
type: "ReLU"
bottom: "bn_conv05_01_b"
top: "bn_conv05_01_b"
}
layer {
name: "conv05_01_b"
type: "Convolution"
bottom: "bn_conv05_01_b"
top: "conv05_01_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise05_01"
type: "Eltwise"
bottom: "conv_transition_04"
bottom: "conv05_01_b"
top: "eltwise05_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv05_02_a"
type: "BatchNorm"
bottom: "eltwise05_01"
top: "bn_conv05_02_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_02_a"
type: "Scale"
bottom: "bn_conv05_02_a"
top: "bn_conv05_02_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_02_a"
type: "ReLU"
bottom: "bn_conv05_02_a"
top: "bn_conv05_02_a"
}
layer {
name: "conv05_02_a"
type: "Convolution"
bottom: "bn_conv05_02_a"
top: "conv05_02_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_02_b"
type: "BatchNorm"
bottom: "conv05_02_a"
top: "bn_conv05_02_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_02_b"
type: "Scale"
bottom: "bn_conv05_02_b"
top: "bn_conv05_02_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_02_b"
type: "ReLU"
bottom: "bn_conv05_02_b"
top: "bn_conv05_02_b"
}
layer {
name: "conv05_02_b"
type: "Convolution"
bottom: "bn_conv05_02_b"
top: "conv05_02_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise05_02"
type: "Eltwise"
bottom: "eltwise05_01"
bottom: "conv05_02_b"
top: "eltwise05_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv05_03_a"
type: "BatchNorm"
bottom: "eltwise05_02"
top: "bn_conv05_03_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_03_a"
type: "Scale"
bottom: "bn_conv05_03_a"
top: "bn_conv05_03_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_03_a"
type: "ReLU"
bottom: "bn_conv05_03_a"
top: "bn_conv05_03_a"
}
layer {
name: "conv05_03_a"
type: "Convolution"
bottom: "bn_conv05_03_a"
top: "conv05_03_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_03_b"
type: "BatchNorm"
bottom: "conv05_03_a"
top: "bn_conv05_03_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_03_b"
type: "Scale"
bottom: "bn_conv05_03_b"
top: "bn_conv05_03_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_03_b"
type: "ReLU"
bottom: "bn_conv05_03_b"
top: "bn_conv05_03_b"
}
layer {
name: "conv05_03_b"
type: "Convolution"
bottom: "bn_conv05_03_b"
top: "conv05_03_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise05_03"
type: "Eltwise"
bottom: "eltwise05_02"
bottom: "conv05_03_b"
top: "eltwise05_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv05_04_a"
type: "BatchNorm"
bottom: "eltwise05_03"
top: "bn_conv05_04_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_04_a"
type: "Scale"
bottom: "bn_conv05_04_a"
top: "bn_conv05_04_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_04_a"
type: "ReLU"
bottom: "bn_conv05_04_a"
top: "bn_conv05_04_a"
}
layer {
name: "conv05_04_a"
type: "Convolution"
bottom: "bn_conv05_04_a"
top: "conv05_04_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_04_b"
type: "BatchNorm"
bottom: "conv05_04_a"
top: "bn_conv05_04_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_04_b"
type: "Scale"
bottom: "bn_conv05_04_b"
top: "bn_conv05_04_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_04_b"
type: "ReLU"
bottom: "bn_conv05_04_b"
top: "bn_conv05_04_b"
}
layer {
name: "conv05_04_b"
type: "Convolution"
bottom: "bn_conv05_04_b"
top: "conv05_04_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise05_04"
type: "Eltwise"
bottom: "eltwise05_03"
bottom: "conv05_04_b"
top: "eltwise05_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv05_05_a"
type: "BatchNorm"
bottom: "eltwise05_04"
top: "bn_conv05_05_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_05_a"
type: "Scale"
bottom: "bn_conv05_05_a"
top: "bn_conv05_05_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_05_a"
type: "ReLU"
bottom: "bn_conv05_05_a"
top: "bn_conv05_05_a"
}
layer {
name: "conv05_05_a"
type: "Convolution"
bottom: "bn_conv05_05_a"
top: "conv05_05_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_05_b"
type: "BatchNorm"
bottom: "conv05_05_a"
top: "bn_conv05_05_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_05_b"
type: "Scale"
bottom: "bn_conv05_05_b"
top: "bn_conv05_05_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_05_b"
type: "ReLU"
bottom: "bn_conv05_05_b"
top: "bn_conv05_05_b"
}
layer {
name: "conv05_05_b"
type: "Convolution"
bottom: "bn_conv05_05_b"
top: "conv05_05_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise05_05"
type: "Eltwise"
bottom: "eltwise05_04"
bottom: "conv05_05_b"
top: "eltwise05_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv05_06_a"
type: "BatchNorm"
bottom: "eltwise05_05"
top: "bn_conv05_06_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_06_a"
type: "Scale"
bottom: "bn_conv05_06_a"
top: "bn_conv05_06_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_06_a"
type: "ReLU"
bottom: "bn_conv05_06_a"
top: "bn_conv05_06_a"
}
layer {
name: "conv05_06_a"
type: "Convolution"
bottom: "bn_conv05_06_a"
top: "conv05_06_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv05_06_b"
type: "BatchNorm"
bottom: "conv05_06_a"
top: "bn_conv05_06_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv05_06_b"
type: "Scale"
bottom: "bn_conv05_06_b"
top: "bn_conv05_06_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu05_06_b"
type: "ReLU"
bottom: "bn_conv05_06_b"
top: "bn_conv05_06_b"
}
layer {
name: "conv05_06_b"
type: "Convolution"
bottom: "bn_conv05_06_b"
top: "conv05_06_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise05_06"
type: "Eltwise"
bottom: "eltwise05_05"
bottom: "conv05_06_b"
top: "eltwise05_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "concat05"
type: "Concat"
bottom: "conv1"
bottom: "conv_transition_01"
bottom: "conv_transition_02"
bottom: "conv_transition_03"
bottom: "conv_transition_04"
bottom: "eltwise05_01"
bottom: "eltwise05_02"
bottom: "eltwise05_03"
bottom: "eltwise05_04"
bottom: "eltwise05_05"
bottom: "eltwise05_06"
top: "concat05"
concat_param {
axis: 1
}
}
layer {
name: "bn_conv_transition_05"
type: "BatchNorm"
bottom: "concat05"
top: "bn_conv_transition_05"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_transition_05"
type: "Scale"
bottom: "bn_conv_transition_05"
top: "bn_conv_transition_05"
scale_param {
bias_term: true
}
}
layer {
name: "relu_transition_05"
type: "ReLU"
bottom: "bn_conv_transition_05"
top: "bn_conv_transition_05"
}
layer {
name: "conv_transition_05"
type: "Convolution"
bottom: "bn_conv_transition_05"
top: "conv_transition_05"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_01_a"
type: "BatchNorm"
bottom: "conv_transition_05"
top: "bn_conv06_01_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_01_a"
type: "Scale"
bottom: "bn_conv06_01_a"
top: "bn_conv06_01_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_01_a"
type: "ReLU"
bottom: "bn_conv06_01_a"
top: "bn_conv06_01_a"
}
layer {
name: "conv06_01_a"
type: "Convolution"
bottom: "bn_conv06_01_a"
top: "conv06_01_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_01_b"
type: "BatchNorm"
bottom: "conv06_01_a"
top: "bn_conv06_01_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_01_b"
type: "Scale"
bottom: "bn_conv06_01_b"
top: "bn_conv06_01_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_01_b"
type: "ReLU"
bottom: "bn_conv06_01_b"
top: "bn_conv06_01_b"
}
layer {
name: "conv06_01_b"
type: "Convolution"
bottom: "bn_conv06_01_b"
top: "conv06_01_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise06_01"
type: "Eltwise"
bottom: "conv_transition_05"
bottom: "conv06_01_b"
top: "eltwise06_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv06_02_a"
type: "BatchNorm"
bottom: "eltwise06_01"
top: "bn_conv06_02_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_02_a"
type: "Scale"
bottom: "bn_conv06_02_a"
top: "bn_conv06_02_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_02_a"
type: "ReLU"
bottom: "bn_conv06_02_a"
top: "bn_conv06_02_a"
}
layer {
name: "conv06_02_a"
type: "Convolution"
bottom: "bn_conv06_02_a"
top: "conv06_02_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_02_b"
type: "BatchNorm"
bottom: "conv06_02_a"
top: "bn_conv06_02_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_02_b"
type: "Scale"
bottom: "bn_conv06_02_b"
top: "bn_conv06_02_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_02_b"
type: "ReLU"
bottom: "bn_conv06_02_b"
top: "bn_conv06_02_b"
}
layer {
name: "conv06_02_b"
type: "Convolution"
bottom: "bn_conv06_02_b"
top: "conv06_02_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise06_02"
type: "Eltwise"
bottom: "eltwise06_01"
bottom: "conv06_02_b"
top: "eltwise06_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv06_03_a"
type: "BatchNorm"
bottom: "eltwise06_02"
top: "bn_conv06_03_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_03_a"
type: "Scale"
bottom: "bn_conv06_03_a"
top: "bn_conv06_03_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_03_a"
type: "ReLU"
bottom: "bn_conv06_03_a"
top: "bn_conv06_03_a"
}
layer {
name: "conv06_03_a"
type: "Convolution"
bottom: "bn_conv06_03_a"
top: "conv06_03_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_03_b"
type: "BatchNorm"
bottom: "conv06_03_a"
top: "bn_conv06_03_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_03_b"
type: "Scale"
bottom: "bn_conv06_03_b"
top: "bn_conv06_03_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_03_b"
type: "ReLU"
bottom: "bn_conv06_03_b"
top: "bn_conv06_03_b"
}
layer {
name: "conv06_03_b"
type: "Convolution"
bottom: "bn_conv06_03_b"
top: "conv06_03_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise06_03"
type: "Eltwise"
bottom: "eltwise06_02"
bottom: "conv06_03_b"
top: "eltwise06_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv06_04_a"
type: "BatchNorm"
bottom: "eltwise06_03"
top: "bn_conv06_04_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_04_a"
type: "Scale"
bottom: "bn_conv06_04_a"
top: "bn_conv06_04_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_04_a"
type: "ReLU"
bottom: "bn_conv06_04_a"
top: "bn_conv06_04_a"
}
layer {
name: "conv06_04_a"
type: "Convolution"
bottom: "bn_conv06_04_a"
top: "conv06_04_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_04_b"
type: "BatchNorm"
bottom: "conv06_04_a"
top: "bn_conv06_04_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_04_b"
type: "Scale"
bottom: "bn_conv06_04_b"
top: "bn_conv06_04_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_04_b"
type: "ReLU"
bottom: "bn_conv06_04_b"
top: "bn_conv06_04_b"
}
layer {
name: "conv06_04_b"
type: "Convolution"
bottom: "bn_conv06_04_b"
top: "conv06_04_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise06_04"
type: "Eltwise"
bottom: "eltwise06_03"
bottom: "conv06_04_b"
top: "eltwise06_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv06_05_a"
type: "BatchNorm"
bottom: "eltwise06_04"
top: "bn_conv06_05_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_05_a"
type: "Scale"
bottom: "bn_conv06_05_a"
top: "bn_conv06_05_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_05_a"
type: "ReLU"
bottom: "bn_conv06_05_a"
top: "bn_conv06_05_a"
}
layer {
name: "conv06_05_a"
type: "Convolution"
bottom: "bn_conv06_05_a"
top: "conv06_05_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_05_b"
type: "BatchNorm"
bottom: "conv06_05_a"
top: "bn_conv06_05_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_05_b"
type: "Scale"
bottom: "bn_conv06_05_b"
top: "bn_conv06_05_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_05_b"
type: "ReLU"
bottom: "bn_conv06_05_b"
top: "bn_conv06_05_b"
}
layer {
name: "conv06_05_b"
type: "Convolution"
bottom: "bn_conv06_05_b"
top: "conv06_05_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise06_05"
type: "Eltwise"
bottom: "eltwise06_04"
bottom: "conv06_05_b"
top: "eltwise06_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "bn_conv06_06_a"
type: "BatchNorm"
bottom: "eltwise06_05"
top: "bn_conv06_06_a"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_06_a"
type: "Scale"
bottom: "bn_conv06_06_a"
top: "bn_conv06_06_a"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_06_a"
type: "ReLU"
bottom: "bn_conv06_06_a"
top: "bn_conv06_06_a"
}
layer {
name: "conv06_06_a"
type: "Convolution"
bottom: "bn_conv06_06_a"
top: "conv06_06_a"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv06_06_b"
type: "BatchNorm"
bottom: "conv06_06_a"
top: "bn_conv06_06_b"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv06_06_b"
type: "Scale"
bottom: "bn_conv06_06_b"
top: "bn_conv06_06_b"
scale_param {
bias_term: true
}
}
layer {
name: "relu06_06_b"
type: "ReLU"
bottom: "bn_conv06_06_b"
top: "bn_conv06_06_b"
}
layer {
name: "conv06_06_b"
type: "Convolution"
bottom: "bn_conv06_06_b"
top: "conv06_06_b"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "eltwise06_06"
type: "Eltwise"
bottom: "eltwise06_05"
bottom: "conv06_06_b"
top: "eltwise06_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "concat06"
type: "Concat"
bottom: "conv1"
bottom: "conv_transition_01"
bottom: "conv_transition_02"
bottom: "conv_transition_03"
bottom: "conv_transition_04"
bottom: "conv_transition_05"
bottom: "eltwise06_01"
bottom: "eltwise06_02"
bottom: "eltwise06_03"
bottom: "eltwise06_04"
bottom: "eltwise06_05"
bottom: "eltwise06_06"
top: "concat06"
concat_param {
axis: 1
}
}
layer {
name: "bn_conv_transition_06"
type: "BatchNorm"
bottom: "concat06"
top: "bn_conv_transition_06"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_transition_06"
type: "Scale"
bottom: "bn_conv_transition_06"
top: "bn_conv_transition_06"
scale_param {
bias_term: true
}
}
layer {
name: "relu_transition_06"
type: "ReLU"
bottom: "bn_conv_transition_06"
top: "bn_conv_transition_06"
}
layer {
name: "conv_transition_06"
type: "Convolution"
bottom: "bn_conv_transition_06"
top: "conv_transition_06"
param {
lr_mult: 1.000000
}
param {
lr_mult: 0.100000
}
convolution_param {
num_output: 64
kernel_size: 1
stride: 1
pad: 0
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bn_conv_end_01"
type: "BatchNorm"
bottom: "conv_transition_01"
top: "bn_conv_end_01"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_end_01"
type: "Scale"
bottom: "bn_conv_end_01"
top: "bn_conv_end_01"
scale_param {
bias_term: true
}
}
layer {
name: "relu_end_01"
type: "ReLU"
bottom: "bn_conv_end_01"
top: "bn_conv_end_01"
}
layer {
name: "conv_end_01"
type: "Convolution"
bottom: "bn_conv_end_01"
top: "conv_end_01"
param {
name: "Recon_w"
lr_mult: 1.000000
}
param {
name: "Recon_b"
lr_mult: 0.100000
}
convolution_param {
num_output: 1
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "HR_recovery_01"
type: "Eltwise"
bottom: "data"
bottom: "conv_end_01"
top: "HR_recovery_01"
eltwise_param {
operation: SUM
}
}
layer {
name: "weight_output_end_01"
type: "Scale"
bottom: "HR_recovery_01"
top: "weight_output_end_01"
scale_param {
bias_term: false
}
}
layer {
name: "bn_conv_end_02"
type: "BatchNorm"
bottom: "conv_transition_02"
top: "bn_conv_end_02"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_end_02"
type: "Scale"
bottom: "bn_conv_end_02"
top: "bn_conv_end_02"
scale_param {
bias_term: true
}
}
layer {
name: "relu_end_02"
type: "ReLU"
bottom: "bn_conv_end_02"
top: "bn_conv_end_02"
}
layer {
name: "conv_end_02"
type: "Convolution"
bottom: "bn_conv_end_02"
top: "conv_end_02"
param {
name: "Recon_w"
lr_mult: 1.000000
}
param {
name: "Recon_b"
lr_mult: 0.100000
}
convolution_param {
num_output: 1
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "HR_recovery_02"
type: "Eltwise"
bottom: "data"
bottom: "conv_end_02"
top: "HR_recovery_02"
eltwise_param {
operation: SUM
}
}
layer {
name: "weight_output_end_02"
type: "Scale"
bottom: "HR_recovery_02"
top: "weight_output_end_02"
scale_param {
bias_term: false
}
}
layer {
name: "bn_conv_end_03"
type: "BatchNorm"
bottom: "conv_transition_03"
top: "bn_conv_end_03"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_end_03"
type: "Scale"
bottom: "bn_conv_end_03"
top: "bn_conv_end_03"
scale_param {
bias_term: true
}
}
layer {
name: "relu_end_03"
type: "ReLU"
bottom: "bn_conv_end_03"
top: "bn_conv_end_03"
}
layer {
name: "conv_end_03"
type: "Convolution"
bottom: "bn_conv_end_03"
top: "conv_end_03"
param {
name: "Recon_w"
lr_mult: 1.000000
}
param {
name: "Recon_b"
lr_mult: 0.100000
}
convolution_param {
num_output: 1
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "HR_recovery_03"
type: "Eltwise"
bottom: "data"
bottom: "conv_end_03"
top: "HR_recovery_03"
eltwise_param {
operation: SUM
}
}
layer {
name: "weight_output_end_03"
type: "Scale"
bottom: "HR_recovery_03"
top: "weight_output_end_03"
scale_param {
bias_term: false
}
}
layer {
name: "bn_conv_end_04"
type: "BatchNorm"
bottom: "conv_transition_04"
top: "bn_conv_end_04"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_end_04"
type: "Scale"
bottom: "bn_conv_end_04"
top: "bn_conv_end_04"
scale_param {
bias_term: true
}
}
layer {
name: "relu_end_04"
type: "ReLU"
bottom: "bn_conv_end_04"
top: "bn_conv_end_04"
}
layer {
name: "conv_end_04"
type: "Convolution"
bottom: "bn_conv_end_04"
top: "conv_end_04"
param {
name: "Recon_w"
lr_mult: 1.000000
}
param {
name: "Recon_b"
lr_mult: 0.100000
}
convolution_param {
num_output: 1
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "HR_recovery_04"
type: "Eltwise"
bottom: "data"
bottom: "conv_end_04"
top: "HR_recovery_04"
eltwise_param {
operation: SUM
}
}
layer {
name: "weight_output_end_04"
type: "Scale"
bottom: "HR_recovery_04"
top: "weight_output_end_04"
scale_param {
bias_term: false
}
}
layer {
name: "bn_conv_end_05"
type: "BatchNorm"
bottom: "conv_transition_05"
top: "bn_conv_end_05"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_end_05"
type: "Scale"
bottom: "bn_conv_end_05"
top: "bn_conv_end_05"
scale_param {
bias_term: true
}
}
layer {
name: "relu_end_05"
type: "ReLU"
bottom: "bn_conv_end_05"
top: "bn_conv_end_05"
}
layer {
name: "conv_end_05"
type: "Convolution"
bottom: "bn_conv_end_05"
top: "conv_end_05"
param {
name: "Recon_w"
lr_mult: 1.000000
}
param {
name: "Recon_b"
lr_mult: 0.100000
}
convolution_param {
num_output: 1
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "HR_recovery_05"
type: "Eltwise"
bottom: "data"
bottom: "conv_end_05"
top: "HR_recovery_05"
eltwise_param {
operation: SUM
}
}
layer {
name: "weight_output_end_05"
type: "Scale"
bottom: "HR_recovery_05"
top: "weight_output_end_05"
scale_param {
bias_term: false
}
}
layer {
name: "bn_conv_end_06"
type: "BatchNorm"
bottom: "conv_transition_06"
top: "bn_conv_end_06"
param {
lr_mult: 0
}
param {
lr_mult: 0
}
param {
lr_mult: 0
}
}
layer {
name: "scale_conv_end_06"
type: "Scale"
bottom: "bn_conv_end_06"
top: "bn_conv_end_06"
scale_param {
bias_term: true
}
}
layer {
name: "relu_end_06"
type: "ReLU"
bottom: "bn_conv_end_06"
top: "bn_conv_end_06"
}
layer {
name: "conv_end_06"
type: "Convolution"
bottom: "bn_conv_end_06"
top: "conv_end_06"
param {
name: "Recon_w"
lr_mult: 1.000000
}
param {
name: "Recon_b"
lr_mult: 0.100000
}
convolution_param {
num_output: 1
kernel_size: 3
stride: 1
pad: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "HR_recovery_06"
type: "Eltwise"
bottom: "data"
bottom: "conv_end_06"
top: "HR_recovery_06"
eltwise_param {
operation: SUM
}
}
layer {
name: "weight_output_end_06"
type: "Scale"
bottom: "HR_recovery_06"
top: "weight_output_end_06"
scale_param {
bias_term: false
}
}
layer {
name: "HR_recovery"
type: "Eltwise"
bottom: "weight_output_end_01"
bottom: "weight_output_end_02"
bottom: "weight_output_end_03"
bottom: "weight_output_end_04"
bottom: "weight_output_end_05"
bottom: "weight_output_end_06"
top: "HR_recovery"
eltwise_param {
operation: SUM
}
}
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