256 lines
3.3 KiB
Plaintext
256 lines
3.3 KiB
Plaintext
name: "Dehaze"
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input: "data"
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input_dim: 1
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input_dim: 3
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input_dim: 16
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input_dim: 16
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layer {
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name: "conv1"
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type: "Convolution"
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bottom: "data"
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top: "conv1"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 0.1
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}
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convolution_param {
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num_output: 20
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kernel_size: 5
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stride: 1
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pad: 0
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weight_filler {
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type: "gaussian"
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std: 0.001
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "relu1"
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type: "ReLU"
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bottom: "conv1"
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top: "conv1"
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}
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layer {
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name: "reshape1"
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type: "Reshape"
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bottom: "conv1"
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top: "reshape1"
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reshape_param {
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shape {
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dim: 0
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dim: 1
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dim: 20
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dim: -1
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}
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}
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}
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layer {
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name: "pool1"
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type: "Pooling"
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bottom: "reshape1"
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top: "pool1"
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pooling_param {
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pool: MAX
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kernel_w: 1
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kernel_h: 5
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stride_w: 1
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stride_h: 5
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}
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}
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layer {
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name: "reshape2"
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type: "Reshape"
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bottom: "pool1"
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top: "reshape2"
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reshape_param {
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shape {
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dim: 0
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dim: 4
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dim: 12
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dim: 12
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}
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}
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}
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layer {
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name: "conv2/1x1"
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type: "Convolution"
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bottom: "reshape2"
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top: "conv2/1x1"
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param {
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lr_mult: 0.1
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}
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param {
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lr_mult: 0.1
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}
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convolution_param {
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num_output: 16
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kernel_size: 1
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stride: 1
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pad: 0
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weight_filler {
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type: "gaussian"
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std: 0.001
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "conv2/3x3"
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type: "Convolution"
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bottom: "reshape2"
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top: "conv2/3x3"
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param {
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lr_mult: 0.1
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}
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param {
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lr_mult: 0.1
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}
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convolution_param {
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num_output: 16
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kernel_size: 3
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stride: 1
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pad: 1
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weight_filler {
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type: "gaussian"
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std: 0.001
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "conv2/5x5"
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type: "Convolution"
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bottom: "reshape2"
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top: "conv2/5x5"
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param {
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lr_mult: 0.1
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}
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param {
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lr_mult: 0.1
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}
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convolution_param {
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num_output: 16
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kernel_size: 5
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stride: 1
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pad: 2
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weight_filler {
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type: "gaussian"
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std: 0.001
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "conv2/7x7"
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type: "Convolution"
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bottom: "reshape2"
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top: "conv2/7x7"
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param {
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lr_mult: 0.1
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}
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param {
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lr_mult: 0.1
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}
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convolution_param {
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num_output: 16
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kernel_size: 7
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stride: 1
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pad: 3
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weight_filler {
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type: "gaussian"
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std: 0.001
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "conv2/output"
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type: "Concat"
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bottom: "conv2/1x1"
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bottom: "conv2/3x3"
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bottom: "conv2/5x5"
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bottom: "conv2/7x7"
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top: "conv2/output"
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concat_param
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{
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axis: 1
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}
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}
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layer {
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name: "relu2"
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type: "ReLU"
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bottom: "conv2/output"
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top: "conv2/output"
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}
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layer {
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name: "pool2"
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type: "Pooling"
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bottom: "conv2/output"
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top: "pool2"
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pooling_param {
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pool: MAX
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kernel_size: 8
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stride: 1
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}
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}
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layer {
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name: "ip1"
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type: "InnerProduct"
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bottom: "pool2"
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top: "ip1"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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inner_product_param {
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num_output: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "drelu1"
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type: "ReLU"
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bottom: "ip1"
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top: "ip1"
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} |