1997 lines
27 KiB
Plaintext
1997 lines
27 KiB
Plaintext
name: "MOBILENET"
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# transform_param {
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# scale: 0.017
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# mirror: false
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# crop_size: 224
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# mean_value: [103.94,116.78,123.68]
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# }
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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: 224
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input_dim: 224
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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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decay_mult: 1
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}
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convolution_param {
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num_output: 32
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bias_term: false
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pad: 1
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kernel_size: 3
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stride: 2
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv1/bn"
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type: "BatchNorm"
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bottom: "conv1"
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top: "conv1"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv1/scale"
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type: "Scale"
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bottom: "conv1"
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top: "conv1"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "conv2_1/dw"
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type: "Convolution"
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bottom: "conv1"
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top: "conv2_1/dw"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 32
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bias_term: false
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pad: 1
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kernel_size: 3
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group: 32
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engine: CAFFE
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stride: 1
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv2_1/dw/bn"
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type: "BatchNorm"
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bottom: "conv2_1/dw"
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top: "conv2_1/dw"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv2_1/dw/scale"
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type: "Scale"
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bottom: "conv2_1/dw"
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top: "conv2_1/dw"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "relu2_1/dw"
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type: "ReLU"
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bottom: "conv2_1/dw"
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top: "conv2_1/dw"
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}
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layer {
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name: "conv2_1/sep"
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type: "Convolution"
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bottom: "conv2_1/dw"
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top: "conv2_1/sep"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 64
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bias_term: false
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pad: 0
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kernel_size: 1
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stride: 1
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv2_1/sep/bn"
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type: "BatchNorm"
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bottom: "conv2_1/sep"
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top: "conv2_1/sep"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv2_1/sep/scale"
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type: "Scale"
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bottom: "conv2_1/sep"
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top: "conv2_1/sep"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "relu2_1/sep"
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type: "ReLU"
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bottom: "conv2_1/sep"
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top: "conv2_1/sep"
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}
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layer {
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name: "conv2_2/dw"
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type: "Convolution"
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bottom: "conv2_1/sep"
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top: "conv2_2/dw"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 64
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bias_term: false
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pad: 1
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kernel_size: 3
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group: 64
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engine: CAFFE
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stride: 2
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv2_2/dw/bn"
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type: "BatchNorm"
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bottom: "conv2_2/dw"
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top: "conv2_2/dw"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv2_2/dw/scale"
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type: "Scale"
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bottom: "conv2_2/dw"
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top: "conv2_2/dw"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "relu2_2/dw"
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type: "ReLU"
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bottom: "conv2_2/dw"
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top: "conv2_2/dw"
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}
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layer {
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name: "conv2_2/sep"
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type: "Convolution"
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bottom: "conv2_2/dw"
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top: "conv2_2/sep"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 128
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bias_term: false
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pad: 0
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kernel_size: 1
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stride: 1
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv2_2/sep/bn"
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type: "BatchNorm"
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bottom: "conv2_2/sep"
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top: "conv2_2/sep"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv2_2/sep/scale"
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type: "Scale"
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bottom: "conv2_2/sep"
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top: "conv2_2/sep"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "relu2_2/sep"
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type: "ReLU"
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bottom: "conv2_2/sep"
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top: "conv2_2/sep"
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}
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layer {
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name: "conv3_1/dw"
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type: "Convolution"
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bottom: "conv2_2/sep"
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top: "conv3_1/dw"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 128
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bias_term: false
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pad: 1
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kernel_size: 3
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group: 128
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engine: CAFFE
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stride: 1
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv3_1/dw/bn"
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type: "BatchNorm"
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bottom: "conv3_1/dw"
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top: "conv3_1/dw"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv3_1/dw/scale"
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type: "Scale"
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bottom: "conv3_1/dw"
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top: "conv3_1/dw"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "relu3_1/dw"
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type: "ReLU"
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bottom: "conv3_1/dw"
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top: "conv3_1/dw"
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}
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layer {
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name: "conv3_1/sep"
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type: "Convolution"
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bottom: "conv3_1/dw"
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top: "conv3_1/sep"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 128
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bias_term: false
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pad: 0
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kernel_size: 1
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stride: 1
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weight_filler {
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type: "msra"
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}
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}
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}
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layer {
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name: "conv3_1/sep/bn"
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type: "BatchNorm"
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bottom: "conv3_1/sep"
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top: "conv3_1/sep"
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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param {
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lr_mult: 0
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decay_mult: 0
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}
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batch_norm_param {
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use_global_stats: true
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eps: 1e-5
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}
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}
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layer {
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name: "conv3_1/sep/scale"
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type: "Scale"
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bottom: "conv3_1/sep"
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top: "conv3_1/sep"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 1
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decay_mult: 0
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}
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scale_param {
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filler {
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value: 1
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}
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bias_term: true
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bias_filler {
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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: "relu3_1/sep"
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type: "ReLU"
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bottom: "conv3_1/sep"
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top: "conv3_1/sep"
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}
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layer {
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name: "conv3_2/dw"
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type: "Convolution"
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bottom: "conv3_1/sep"
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top: "conv3_2/dw"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 128
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bias_term: false
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pad: 1
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kernel_size: 3
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group: 128
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engine: CAFFE
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stride: 2
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weight_filler {
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type: "msra"
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|
}
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}
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}
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layer {
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name: "conv3_2/dw/bn"
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type: "BatchNorm"
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bottom: "conv3_2/dw"
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top: "conv3_2/dw"
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param {
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|
lr_mult: 0
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decay_mult: 0
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|
}
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param {
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lr_mult: 0
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|
decay_mult: 0
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}
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|
param {
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|
lr_mult: 0
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|
decay_mult: 0
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|
}
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batch_norm_param {
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|
use_global_stats: true
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eps: 1e-5
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|
}
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}
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|
layer {
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name: "conv3_2/dw/scale"
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|
type: "Scale"
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|
bottom: "conv3_2/dw"
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|
top: "conv3_2/dw"
|
|
param {
|
|
lr_mult: 1
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|
decay_mult: 0
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|
}
|
|
param {
|
|
lr_mult: 1
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|
decay_mult: 0
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|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
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|
}
|
|
bias_term: true
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|
bias_filler {
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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: "relu3_2/dw"
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type: "ReLU"
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bottom: "conv3_2/dw"
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top: "conv3_2/dw"
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}
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layer {
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name: "conv3_2/sep"
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|
type: "Convolution"
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|
bottom: "conv3_2/dw"
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|
top: "conv3_2/sep"
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|
param {
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|
lr_mult: 1
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|
decay_mult: 1
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}
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|
convolution_param {
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num_output: 256
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|
bias_term: false
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|
pad: 0
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|
kernel_size: 1
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stride: 1
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|
weight_filler {
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|
type: "msra"
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|
}
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}
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|
}
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|
layer {
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name: "conv3_2/sep/bn"
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type: "BatchNorm"
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bottom: "conv3_2/sep"
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top: "conv3_2/sep"
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|
param {
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|
lr_mult: 0
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|
decay_mult: 0
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|
}
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|
param {
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|
lr_mult: 0
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|
decay_mult: 0
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|
}
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|
param {
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|
lr_mult: 0
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|
decay_mult: 0
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|
}
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|
batch_norm_param {
|
|
use_global_stats: true
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eps: 1e-5
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|
}
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|
}
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|
layer {
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name: "conv3_2/sep/scale"
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|
type: "Scale"
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bottom: "conv3_2/sep"
|
|
top: "conv3_2/sep"
|
|
param {
|
|
lr_mult: 1
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|
decay_mult: 0
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|
}
|
|
param {
|
|
lr_mult: 1
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|
decay_mult: 0
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|
}
|
|
scale_param {
|
|
filler {
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value: 1
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}
|
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bias_term: true
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|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu3_2/sep"
|
|
type: "ReLU"
|
|
bottom: "conv3_2/sep"
|
|
top: "conv3_2/sep"
|
|
}
|
|
layer {
|
|
name: "conv4_1/dw"
|
|
type: "Convolution"
|
|
bottom: "conv3_2/sep"
|
|
top: "conv4_1/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 256
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv4_1/dw"
|
|
top: "conv4_1/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv4_1/dw"
|
|
top: "conv4_1/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu4_1/dw"
|
|
type: "ReLU"
|
|
bottom: "conv4_1/dw"
|
|
top: "conv4_1/dw"
|
|
}
|
|
layer {
|
|
name: "conv4_1/sep"
|
|
type: "Convolution"
|
|
bottom: "conv4_1/dw"
|
|
top: "conv4_1/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv4_1/sep"
|
|
top: "conv4_1/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv4_1/sep"
|
|
top: "conv4_1/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu4_1/sep"
|
|
type: "ReLU"
|
|
bottom: "conv4_1/sep"
|
|
top: "conv4_1/sep"
|
|
}
|
|
layer {
|
|
name: "conv4_2/dw"
|
|
type: "Convolution"
|
|
bottom: "conv4_1/sep"
|
|
top: "conv4_2/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 256
|
|
engine: CAFFE
|
|
stride: 2
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv4_2/dw"
|
|
top: "conv4_2/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv4_2/dw"
|
|
top: "conv4_2/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu4_2/dw"
|
|
type: "ReLU"
|
|
bottom: "conv4_2/dw"
|
|
top: "conv4_2/dw"
|
|
}
|
|
layer {
|
|
name: "conv4_2/sep"
|
|
type: "Convolution"
|
|
bottom: "conv4_2/dw"
|
|
top: "conv4_2/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv4_2/sep"
|
|
top: "conv4_2/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv4_2/sep"
|
|
top: "conv4_2/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu4_2/sep"
|
|
type: "ReLU"
|
|
bottom: "conv4_2/sep"
|
|
top: "conv4_2/sep"
|
|
}
|
|
layer {
|
|
name: "conv5_1/dw"
|
|
type: "Convolution"
|
|
bottom: "conv4_2/sep"
|
|
top: "conv5_1/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 512
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_1/dw"
|
|
top: "conv5_1/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_1/dw"
|
|
top: "conv5_1/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_1/dw"
|
|
type: "ReLU"
|
|
bottom: "conv5_1/dw"
|
|
top: "conv5_1/dw"
|
|
}
|
|
layer {
|
|
name: "conv5_1/sep"
|
|
type: "Convolution"
|
|
bottom: "conv5_1/dw"
|
|
top: "conv5_1/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_1/sep"
|
|
top: "conv5_1/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_1/sep"
|
|
top: "conv5_1/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_1/sep"
|
|
type: "ReLU"
|
|
bottom: "conv5_1/sep"
|
|
top: "conv5_1/sep"
|
|
}
|
|
layer {
|
|
name: "conv5_2/dw"
|
|
type: "Convolution"
|
|
bottom: "conv5_1/sep"
|
|
top: "conv5_2/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 512
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_2/dw"
|
|
top: "conv5_2/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_2/dw"
|
|
top: "conv5_2/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_2/dw"
|
|
type: "ReLU"
|
|
bottom: "conv5_2/dw"
|
|
top: "conv5_2/dw"
|
|
}
|
|
layer {
|
|
name: "conv5_2/sep"
|
|
type: "Convolution"
|
|
bottom: "conv5_2/dw"
|
|
top: "conv5_2/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_2/sep"
|
|
top: "conv5_2/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_2/sep"
|
|
top: "conv5_2/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_2/sep"
|
|
type: "ReLU"
|
|
bottom: "conv5_2/sep"
|
|
top: "conv5_2/sep"
|
|
}
|
|
layer {
|
|
name: "conv5_3/dw"
|
|
type: "Convolution"
|
|
bottom: "conv5_2/sep"
|
|
top: "conv5_3/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 512
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_3/dw"
|
|
top: "conv5_3/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_3/dw"
|
|
top: "conv5_3/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_3/dw"
|
|
type: "ReLU"
|
|
bottom: "conv5_3/dw"
|
|
top: "conv5_3/dw"
|
|
}
|
|
layer {
|
|
name: "conv5_3/sep"
|
|
type: "Convolution"
|
|
bottom: "conv5_3/dw"
|
|
top: "conv5_3/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_3/sep"
|
|
top: "conv5_3/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_3/sep"
|
|
top: "conv5_3/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_3/sep"
|
|
type: "ReLU"
|
|
bottom: "conv5_3/sep"
|
|
top: "conv5_3/sep"
|
|
}
|
|
layer {
|
|
name: "conv5_4/dw"
|
|
type: "Convolution"
|
|
bottom: "conv5_3/sep"
|
|
top: "conv5_4/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 512
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_4/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_4/dw"
|
|
top: "conv5_4/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_4/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_4/dw"
|
|
top: "conv5_4/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_4/dw"
|
|
type: "ReLU"
|
|
bottom: "conv5_4/dw"
|
|
top: "conv5_4/dw"
|
|
}
|
|
layer {
|
|
name: "conv5_4/sep"
|
|
type: "Convolution"
|
|
bottom: "conv5_4/dw"
|
|
top: "conv5_4/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_4/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_4/sep"
|
|
top: "conv5_4/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_4/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_4/sep"
|
|
top: "conv5_4/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_4/sep"
|
|
type: "ReLU"
|
|
bottom: "conv5_4/sep"
|
|
top: "conv5_4/sep"
|
|
}
|
|
layer {
|
|
name: "conv5_5/dw"
|
|
type: "Convolution"
|
|
bottom: "conv5_4/sep"
|
|
top: "conv5_5/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 512
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_5/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_5/dw"
|
|
top: "conv5_5/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_5/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_5/dw"
|
|
top: "conv5_5/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_5/dw"
|
|
type: "ReLU"
|
|
bottom: "conv5_5/dw"
|
|
top: "conv5_5/dw"
|
|
}
|
|
layer {
|
|
name: "conv5_5/sep"
|
|
type: "Convolution"
|
|
bottom: "conv5_5/dw"
|
|
top: "conv5_5/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_5/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_5/sep"
|
|
top: "conv5_5/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_5/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_5/sep"
|
|
top: "conv5_5/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_5/sep"
|
|
type: "ReLU"
|
|
bottom: "conv5_5/sep"
|
|
top: "conv5_5/sep"
|
|
}
|
|
layer {
|
|
name: "conv5_6/dw"
|
|
type: "Convolution"
|
|
bottom: "conv5_5/sep"
|
|
top: "conv5_6/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 512
|
|
engine: CAFFE
|
|
stride: 2
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_6/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_6/dw"
|
|
top: "conv5_6/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_6/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_6/dw"
|
|
top: "conv5_6/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_6/dw"
|
|
type: "ReLU"
|
|
bottom: "conv5_6/dw"
|
|
top: "conv5_6/dw"
|
|
}
|
|
layer {
|
|
name: "conv5_6/sep"
|
|
type: "Convolution"
|
|
bottom: "conv5_6/dw"
|
|
top: "conv5_6/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_6/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv5_6/sep"
|
|
top: "conv5_6/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_6/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv5_6/sep"
|
|
top: "conv5_6/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu5_6/sep"
|
|
type: "ReLU"
|
|
bottom: "conv5_6/sep"
|
|
top: "conv5_6/sep"
|
|
}
|
|
layer {
|
|
name: "conv6/dw"
|
|
type: "Convolution"
|
|
bottom: "conv5_6/sep"
|
|
top: "conv6/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
bias_term: false
|
|
pad: 1
|
|
kernel_size: 3
|
|
group: 1024
|
|
engine: CAFFE
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv6/dw/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv6/dw"
|
|
top: "conv6/dw"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv6/dw/scale"
|
|
type: "Scale"
|
|
bottom: "conv6/dw"
|
|
top: "conv6/dw"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu6/dw"
|
|
type: "ReLU"
|
|
bottom: "conv6/dw"
|
|
top: "conv6/dw"
|
|
}
|
|
layer {
|
|
name: "conv6/sep"
|
|
type: "Convolution"
|
|
bottom: "conv6/dw"
|
|
top: "conv6/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
bias_term: false
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv6/sep/bn"
|
|
type: "BatchNorm"
|
|
bottom: "conv6/sep"
|
|
top: "conv6/sep"
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
batch_norm_param {
|
|
use_global_stats: true
|
|
eps: 1e-5
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv6/sep/scale"
|
|
type: "Scale"
|
|
bottom: "conv6/sep"
|
|
top: "conv6/sep"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
scale_param {
|
|
filler {
|
|
value: 1
|
|
}
|
|
bias_term: true
|
|
bias_filler {
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "relu6/sep"
|
|
type: "ReLU"
|
|
bottom: "conv6/sep"
|
|
top: "conv6/sep"
|
|
}
|
|
layer {
|
|
name: "pool6"
|
|
type: "Pooling"
|
|
bottom: "conv6/sep"
|
|
top: "pool6"
|
|
pooling_param {
|
|
pool: AVE
|
|
global_pooling: true
|
|
}
|
|
}
|
|
layer {
|
|
name: "fc7"
|
|
type: "Convolution"
|
|
bottom: "pool6"
|
|
top: "fc7"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 1000
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "prob"
|
|
type: "Softmax"
|
|
bottom: "fc7"
|
|
top: "prob"
|
|
}
|