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2335 lines
38 KiB
2335 lines
38 KiB
name: "googlenet"
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input: "data"
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input_dim: 128
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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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input: "label"
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input_dim: 128
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input_dim: 1
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input_dim: 1
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input_dim: 1
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layer {
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name: "conv1/7x7_s2"
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type: "Convolution"
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bottom: "data"
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top: "conv1/7x7_s2"
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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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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 64
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pad: 3
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kernel_size: 7
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stride: 2
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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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value: 0.2
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}
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}
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}
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layer {
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name: "conv1/relu_7x7"
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type: "ReLU"
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bottom: "conv1/7x7_s2"
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top: "conv1/7x7_s2"
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}
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layer {
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name: "pool1/3x3_s2"
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type: "Pooling"
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bottom: "conv1/7x7_s2"
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top: "pool1/3x3_s2"
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pooling_param {
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pool: MAX
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kernel_size: 3
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stride: 2
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}
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}
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#layer {
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# name: "pool1/norm1"
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# type: "LRN"
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# bottom: "pool1/3x3_s2"
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# top: "pool1/norm1"
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# lrn_param {
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# local_size: 5
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# alpha: 0.0001
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# beta: 0.75
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# }
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#}
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layer {
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name: "conv2/3x3_reduce"
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type: "Convolution"
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# bottom: "pool1/norm1"
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bottom: "pool1/3x3_s2"
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top: "conv2/3x3_reduce"
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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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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 64
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kernel_size: 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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value: 0.2
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}
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}
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}
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layer {
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name: "conv2/relu_3x3_reduce"
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type: "ReLU"
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bottom: "conv2/3x3_reduce"
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top: "conv2/3x3_reduce"
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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: "conv2/3x3_reduce"
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top: "conv2/3x3"
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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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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 192
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pad: 1
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kernel_size: 3
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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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value: 0.2
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}
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}
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}
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layer {
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name: "conv2/relu_3x3"
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type: "ReLU"
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bottom: "conv2/3x3"
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top: "conv2/3x3"
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}
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#layer {
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# name: "conv2/norm2"
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# type: "LRN"
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# bottom: "conv2/3x3"
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# top: "conv2/norm2"
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# lrn_param {
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# local_size: 5
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# alpha: 0.0001
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# beta: 0.75
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# }
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#}
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layer {
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name: "pool2/3x3_s2"
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type: "Pooling"
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# bottom: "conv2/norm2"
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bottom: "conv2/3x3"
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top: "pool2/3x3_s2"
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pooling_param {
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pool: MAX
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kernel_size: 3
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stride: 2
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}
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}
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layer {
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name: "inception_3a/1x1"
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type: "Convolution"
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bottom: "pool2/3x3_s2"
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top: "inception_3a/1x1"
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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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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 64
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kernel_size: 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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value: 0.2
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}
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}
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}
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layer {
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name: "inception_3a/relu_1x1"
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type: "ReLU"
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bottom: "inception_3a/1x1"
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top: "inception_3a/1x1"
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}
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layer {
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name: "inception_3a/3x3_reduce"
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type: "Convolution"
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bottom: "pool2/3x3_s2"
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top: "inception_3a/3x3_reduce"
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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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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 96
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kernel_size: 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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value: 0.2
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}
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}
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}
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layer {
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name: "inception_3a/relu_3x3_reduce"
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|
type: "ReLU"
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bottom: "inception_3a/3x3_reduce"
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top: "inception_3a/3x3_reduce"
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}
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layer {
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name: "inception_3a/3x3"
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type: "Convolution"
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bottom: "inception_3a/3x3_reduce"
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top: "inception_3a/3x3"
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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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param {
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|
lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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num_output: 128
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pad: 1
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kernel_size: 3
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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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value: 0.2
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}
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|
}
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|
}
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layer {
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name: "inception_3a/relu_3x3"
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type: "ReLU"
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bottom: "inception_3a/3x3"
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top: "inception_3a/3x3"
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|
}
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|
layer {
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name: "inception_3a/5x5_reduce"
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type: "Convolution"
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bottom: "pool2/3x3_s2"
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top: "inception_3a/5x5_reduce"
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param {
|
|
lr_mult: 1
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|
decay_mult: 1
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|
}
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param {
|
|
lr_mult: 2
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|
decay_mult: 0
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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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|
weight_filler {
|
|
type: "xavier"
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|
}
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|
bias_filler {
|
|
type: "constant"
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|
value: 0.2
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|
}
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}
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|
}
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|
layer {
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name: "inception_3a/relu_5x5_reduce"
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|
type: "ReLU"
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|
bottom: "inception_3a/5x5_reduce"
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|
top: "inception_3a/5x5_reduce"
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|
}
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|
layer {
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name: "inception_3a/5x5"
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|
type: "Convolution"
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|
bottom: "inception_3a/5x5_reduce"
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|
top: "inception_3a/5x5"
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|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 32
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pad: 2
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|
kernel_size: 5
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|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
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|
value: 0.2
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|
}
|
|
}
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}
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|
layer {
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name: "inception_3a/relu_5x5"
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|
type: "ReLU"
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bottom: "inception_3a/5x5"
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top: "inception_3a/5x5"
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|
}
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|
layer {
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name: "inception_3a/pool"
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type: "Pooling"
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bottom: "pool2/3x3_s2"
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top: "inception_3a/pool"
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|
pooling_param {
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pool: MAX
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|
kernel_size: 3
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stride: 1
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pad: 1
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}
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|
}
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layer {
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name: "inception_3a/pool_proj"
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type: "Convolution"
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|
bottom: "inception_3a/pool"
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top: "inception_3a/pool_proj"
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|
param {
|
|
lr_mult: 1
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|
decay_mult: 1
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|
}
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|
param {
|
|
lr_mult: 2
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decay_mult: 0
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|
}
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|
convolution_param {
|
|
num_output: 32
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|
kernel_size: 1
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|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
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}
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}
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}
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layer {
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name: "inception_3a/relu_pool_proj"
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|
type: "ReLU"
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|
bottom: "inception_3a/pool_proj"
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top: "inception_3a/pool_proj"
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}
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layer {
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name: "inception_3a/output"
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type: "Concat"
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bottom: "inception_3a/1x1"
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bottom: "inception_3a/3x3"
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|
bottom: "inception_3a/5x5"
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bottom: "inception_3a/pool_proj"
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top: "inception_3a/output"
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}
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layer {
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name: "inception_3b/1x1"
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type: "Convolution"
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|
bottom: "inception_3a/output"
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top: "inception_3b/1x1"
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param {
|
|
lr_mult: 1
|
|
decay_mult: 1
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|
}
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|
param {
|
|
lr_mult: 2
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|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
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|
kernel_size: 1
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|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
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|
value: 0.2
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}
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|
}
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}
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layer {
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name: "inception_3b/relu_1x1"
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type: "ReLU"
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bottom: "inception_3b/1x1"
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|
top: "inception_3b/1x1"
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|
}
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|
layer {
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|
name: "inception_3b/3x3_reduce"
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|
type: "Convolution"
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|
bottom: "inception_3a/output"
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|
top: "inception_3b/3x3_reduce"
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|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
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|
}
|
|
param {
|
|
lr_mult: 2
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|
decay_mult: 0
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|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
kernel_size: 1
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|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
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|
}
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}
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}
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|
layer {
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name: "inception_3b/relu_3x3_reduce"
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|
type: "ReLU"
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|
bottom: "inception_3b/3x3_reduce"
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|
top: "inception_3b/3x3_reduce"
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|
}
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|
layer {
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name: "inception_3b/3x3"
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|
type: "Convolution"
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|
bottom: "inception_3b/3x3_reduce"
|
|
top: "inception_3b/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 192
|
|
pad: 1
|
|
kernel_size: 3
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|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
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|
}
|
|
}
|
|
}
|
|
layer {
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|
name: "inception_3b/relu_3x3"
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|
type: "ReLU"
|
|
bottom: "inception_3b/3x3"
|
|
top: "inception_3b/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_3b/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_3a/output"
|
|
top: "inception_3b/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 32
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_3b/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_3b/5x5_reduce"
|
|
top: "inception_3b/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_3b/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_3b/5x5_reduce"
|
|
top: "inception_3b/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 96
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_3b/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_3b/5x5"
|
|
top: "inception_3b/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_3b/pool"
|
|
type: "Pooling"
|
|
bottom: "inception_3a/output"
|
|
top: "inception_3b/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_3b/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_3b/pool"
|
|
top: "inception_3b/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_3b/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_3b/pool_proj"
|
|
top: "inception_3b/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_3b/output"
|
|
type: "Concat"
|
|
bottom: "inception_3b/1x1"
|
|
bottom: "inception_3b/3x3"
|
|
bottom: "inception_3b/5x5"
|
|
bottom: "inception_3b/pool_proj"
|
|
top: "inception_3b/output"
|
|
}
|
|
layer {
|
|
name: "pool3/3x3_s2"
|
|
type: "Pooling"
|
|
bottom: "inception_3b/output"
|
|
top: "pool3/3x3_s2"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 2
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/1x1"
|
|
type: "Convolution"
|
|
bottom: "pool3/3x3_s2"
|
|
top: "inception_4a/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 192
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_4a/1x1"
|
|
top: "inception_4a/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_4a/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "pool3/3x3_s2"
|
|
top: "inception_4a/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 96
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4a/3x3_reduce"
|
|
top: "inception_4a/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4a/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_4a/3x3_reduce"
|
|
top: "inception_4a/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 208
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_4a/3x3"
|
|
top: "inception_4a/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_4a/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "pool3/3x3_s2"
|
|
top: "inception_4a/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 16
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4a/5x5_reduce"
|
|
top: "inception_4a/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4a/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_4a/5x5_reduce"
|
|
top: "inception_4a/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 48
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_4a/5x5"
|
|
top: "inception_4a/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_4a/pool"
|
|
type: "Pooling"
|
|
bottom: "pool3/3x3_s2"
|
|
top: "inception_4a/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_4a/pool"
|
|
top: "inception_4a/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4a/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_4a/pool_proj"
|
|
top: "inception_4a/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_4a/output"
|
|
type: "Concat"
|
|
bottom: "inception_4a/1x1"
|
|
bottom: "inception_4a/3x3"
|
|
bottom: "inception_4a/5x5"
|
|
bottom: "inception_4a/pool_proj"
|
|
top: "inception_4a/output"
|
|
}
|
|
#layer {
|
|
# name: "loss1/ave_pool"
|
|
# type: "Pooling"
|
|
# bottom: "inception_4a/output"
|
|
# top: "loss1/ave_pool"
|
|
# pooling_param {
|
|
# pool: AVE
|
|
# kernel_size: 5
|
|
# stride: 3
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss1/conv"
|
|
# type: "Convolution"
|
|
# bottom: "loss1/ave_pool"
|
|
# top: "loss1/conv"
|
|
# param {
|
|
# lr_mult: 1
|
|
# decay_mult: 1
|
|
# }
|
|
# param {
|
|
# lr_mult: 2
|
|
# decay_mult: 0
|
|
# }
|
|
# convolution_param {
|
|
# num_output: 128
|
|
# kernel_size: 1
|
|
# weight_filler {
|
|
# type: "xavier"
|
|
# }
|
|
# bias_filler {
|
|
# type: "constant"
|
|
# value: 0.2
|
|
# }
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss1/relu_conv"
|
|
# type: "ReLU"
|
|
# bottom: "loss1/conv"
|
|
# top: "loss1/conv"
|
|
#}
|
|
#layer {
|
|
# name: "loss1/fc"
|
|
# type: "InnerProduct"
|
|
# bottom: "loss1/conv"
|
|
# top: "loss1/fc"
|
|
# param {
|
|
# lr_mult: 1
|
|
# decay_mult: 1
|
|
# }
|
|
# param {
|
|
# lr_mult: 2
|
|
# decay_mult: 0
|
|
# }
|
|
# inner_product_param {
|
|
# num_output: 1024
|
|
# weight_filler {
|
|
# type: "xavier"
|
|
# }
|
|
# bias_filler {
|
|
# type: "constant"
|
|
# value: 0.2
|
|
# }
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss1/relu_fc"
|
|
# type: "ReLU"
|
|
# bottom: "loss1/fc"
|
|
# top: "loss1/fc"
|
|
#}
|
|
#layer {
|
|
# name: "loss1/drop_fc"
|
|
# type: "Dropout"
|
|
# bottom: "loss1/fc"
|
|
# top: "loss1/fc"
|
|
# dropout_param {
|
|
# dropout_ratio: 0.7
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss1/classifier"
|
|
# type: "InnerProduct"
|
|
# bottom: "loss1/fc"
|
|
# top: "loss1/classifier"
|
|
# param {
|
|
# lr_mult: 1
|
|
# decay_mult: 1
|
|
# }
|
|
# param {
|
|
# lr_mult: 2
|
|
# decay_mult: 0
|
|
# }
|
|
# inner_product_param {
|
|
# num_output: 1000
|
|
# weight_filler {
|
|
# type: "xavier"
|
|
# }
|
|
# bias_filler {
|
|
# type: "constant"
|
|
# value: 0
|
|
# }
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss1/loss"
|
|
# type: "SoftmaxWithLoss"
|
|
# bottom: "loss1/classifier"
|
|
# bottom: "label"
|
|
# top: "loss1/loss1"
|
|
# loss_weight: 0.3
|
|
#}
|
|
layer {
|
|
name: "inception_4b/1x1"
|
|
type: "Convolution"
|
|
bottom: "inception_4a/output"
|
|
top: "inception_4b/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 160
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_4b/1x1"
|
|
top: "inception_4b/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_4b/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4a/output"
|
|
top: "inception_4b/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 112
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4b/3x3_reduce"
|
|
top: "inception_4b/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4b/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_4b/3x3_reduce"
|
|
top: "inception_4b/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 224
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_4b/3x3"
|
|
top: "inception_4b/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_4b/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4a/output"
|
|
top: "inception_4b/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 24
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4b/5x5_reduce"
|
|
top: "inception_4b/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4b/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_4b/5x5_reduce"
|
|
top: "inception_4b/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_4b/5x5"
|
|
top: "inception_4b/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_4b/pool"
|
|
type: "Pooling"
|
|
bottom: "inception_4a/output"
|
|
top: "inception_4b/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_4b/pool"
|
|
top: "inception_4b/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4b/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_4b/pool_proj"
|
|
top: "inception_4b/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_4b/output"
|
|
type: "Concat"
|
|
bottom: "inception_4b/1x1"
|
|
bottom: "inception_4b/3x3"
|
|
bottom: "inception_4b/5x5"
|
|
bottom: "inception_4b/pool_proj"
|
|
top: "inception_4b/output"
|
|
}
|
|
layer {
|
|
name: "inception_4c/1x1"
|
|
type: "Convolution"
|
|
bottom: "inception_4b/output"
|
|
top: "inception_4c/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_4c/1x1"
|
|
top: "inception_4c/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_4c/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4b/output"
|
|
top: "inception_4c/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4c/3x3_reduce"
|
|
top: "inception_4c/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4c/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_4c/3x3_reduce"
|
|
top: "inception_4c/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_4c/3x3"
|
|
top: "inception_4c/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_4c/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4b/output"
|
|
top: "inception_4c/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 24
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4c/5x5_reduce"
|
|
top: "inception_4c/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4c/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_4c/5x5_reduce"
|
|
top: "inception_4c/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_4c/5x5"
|
|
top: "inception_4c/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_4c/pool"
|
|
type: "Pooling"
|
|
bottom: "inception_4b/output"
|
|
top: "inception_4c/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_4c/pool"
|
|
top: "inception_4c/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4c/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_4c/pool_proj"
|
|
top: "inception_4c/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_4c/output"
|
|
type: "Concat"
|
|
bottom: "inception_4c/1x1"
|
|
bottom: "inception_4c/3x3"
|
|
bottom: "inception_4c/5x5"
|
|
bottom: "inception_4c/pool_proj"
|
|
top: "inception_4c/output"
|
|
}
|
|
layer {
|
|
name: "inception_4d/1x1"
|
|
type: "Convolution"
|
|
bottom: "inception_4c/output"
|
|
top: "inception_4d/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 112
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_4d/1x1"
|
|
top: "inception_4d/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_4d/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4c/output"
|
|
top: "inception_4d/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 144
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4d/3x3_reduce"
|
|
top: "inception_4d/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4d/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_4d/3x3_reduce"
|
|
top: "inception_4d/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 288
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_4d/3x3"
|
|
top: "inception_4d/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_4d/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4c/output"
|
|
top: "inception_4d/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 32
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4d/5x5_reduce"
|
|
top: "inception_4d/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4d/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_4d/5x5_reduce"
|
|
top: "inception_4d/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_4d/5x5"
|
|
top: "inception_4d/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_4d/pool"
|
|
type: "Pooling"
|
|
bottom: "inception_4c/output"
|
|
top: "inception_4d/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_4d/pool"
|
|
top: "inception_4d/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4d/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_4d/pool_proj"
|
|
top: "inception_4d/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_4d/output"
|
|
type: "Concat"
|
|
bottom: "inception_4d/1x1"
|
|
bottom: "inception_4d/3x3"
|
|
bottom: "inception_4d/5x5"
|
|
bottom: "inception_4d/pool_proj"
|
|
top: "inception_4d/output"
|
|
}
|
|
#layer {
|
|
# name: "loss2/ave_pool"
|
|
# type: "Pooling"
|
|
# bottom: "inception_4d/output"
|
|
# top: "loss2/ave_pool"
|
|
# pooling_param {
|
|
# pool: AVE
|
|
# kernel_size: 5
|
|
# stride: 3
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss2/conv"
|
|
# type: "Convolution"
|
|
# bottom: "loss2/ave_pool"
|
|
# top: "loss2/conv"
|
|
# param {
|
|
# lr_mult: 1
|
|
# decay_mult: 1
|
|
# }
|
|
# param {
|
|
# lr_mult: 2
|
|
# decay_mult: 0
|
|
# }
|
|
# convolution_param {
|
|
# num_output: 128
|
|
# kernel_size: 1
|
|
# weight_filler {
|
|
# type: "xavier"
|
|
# }
|
|
# bias_filler {
|
|
# type: "constant"
|
|
# value: 0.2
|
|
# }
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss2/relu_conv"
|
|
# type: "ReLU"
|
|
# bottom: "loss2/conv"
|
|
# top: "loss2/conv"
|
|
#}
|
|
#layer {
|
|
# name: "loss2/fc"
|
|
# type: "InnerProduct"
|
|
# bottom: "loss2/conv"
|
|
# top: "loss2/fc"
|
|
# param {
|
|
# lr_mult: 1
|
|
# decay_mult: 1
|
|
# }
|
|
# param {
|
|
# lr_mult: 2
|
|
# decay_mult: 0
|
|
# }
|
|
# inner_product_param {
|
|
# num_output: 1024
|
|
# weight_filler {
|
|
# type: "xavier"
|
|
# }
|
|
# bias_filler {
|
|
# type: "constant"
|
|
# value: 0.2
|
|
# }
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss2/relu_fc"
|
|
# type: "ReLU"
|
|
# bottom: "loss2/fc"
|
|
# top: "loss2/fc"
|
|
#}
|
|
#layer {
|
|
# name: "loss2/drop_fc"
|
|
# type: "Dropout"
|
|
# bottom: "loss2/fc"
|
|
# top: "loss2/fc"
|
|
# dropout_param {
|
|
# dropout_ratio: 0.7
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss2/classifier"
|
|
# type: "InnerProduct"
|
|
# bottom: "loss2/fc"
|
|
# top: "loss2/classifier"
|
|
# param {
|
|
# lr_mult: 1
|
|
# decay_mult: 1
|
|
# }
|
|
# param {
|
|
# lr_mult: 2
|
|
# decay_mult: 0
|
|
# }
|
|
# inner_product_param {
|
|
# num_output: 1000
|
|
# weight_filler {
|
|
# type: "xavier"
|
|
# }
|
|
# bias_filler {
|
|
# type: "constant"
|
|
# value: 0
|
|
# }
|
|
# }
|
|
#}
|
|
#layer {
|
|
# name: "loss2/loss"
|
|
# type: "SoftmaxWithLoss"
|
|
# bottom: "loss2/classifier"
|
|
# bottom: "label"
|
|
# top: "loss2/loss1"
|
|
# loss_weight: 0.3
|
|
#}
|
|
layer {
|
|
name: "inception_4e/1x1"
|
|
type: "Convolution"
|
|
bottom: "inception_4d/output"
|
|
top: "inception_4e/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_4e/1x1"
|
|
top: "inception_4e/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_4e/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4d/output"
|
|
top: "inception_4e/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 160
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4e/3x3_reduce"
|
|
top: "inception_4e/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4e/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_4e/3x3_reduce"
|
|
top: "inception_4e/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 320
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_4e/3x3"
|
|
top: "inception_4e/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_4e/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_4d/output"
|
|
top: "inception_4e/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 32
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_4e/5x5_reduce"
|
|
top: "inception_4e/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_4e/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_4e/5x5_reduce"
|
|
top: "inception_4e/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_4e/5x5"
|
|
top: "inception_4e/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_4e/pool"
|
|
type: "Pooling"
|
|
bottom: "inception_4d/output"
|
|
top: "inception_4e/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_4e/pool"
|
|
top: "inception_4e/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_4e/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_4e/pool_proj"
|
|
top: "inception_4e/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_4e/output"
|
|
type: "Concat"
|
|
bottom: "inception_4e/1x1"
|
|
bottom: "inception_4e/3x3"
|
|
bottom: "inception_4e/5x5"
|
|
bottom: "inception_4e/pool_proj"
|
|
top: "inception_4e/output"
|
|
}
|
|
layer {
|
|
name: "pool4/3x3_s2"
|
|
type: "Pooling"
|
|
bottom: "inception_4e/output"
|
|
top: "pool4/3x3_s2"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 2
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/1x1"
|
|
type: "Convolution"
|
|
bottom: "pool4/3x3_s2"
|
|
top: "inception_5a/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_5a/1x1"
|
|
top: "inception_5a/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_5a/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "pool4/3x3_s2"
|
|
top: "inception_5a/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 160
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_5a/3x3_reduce"
|
|
top: "inception_5a/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_5a/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_5a/3x3_reduce"
|
|
top: "inception_5a/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 320
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_5a/3x3"
|
|
top: "inception_5a/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_5a/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "pool4/3x3_s2"
|
|
top: "inception_5a/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 32
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_5a/5x5_reduce"
|
|
top: "inception_5a/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_5a/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_5a/5x5_reduce"
|
|
top: "inception_5a/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_5a/5x5"
|
|
top: "inception_5a/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_5a/pool"
|
|
type: "Pooling"
|
|
bottom: "pool4/3x3_s2"
|
|
top: "inception_5a/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_5a/pool"
|
|
top: "inception_5a/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5a/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_5a/pool_proj"
|
|
top: "inception_5a/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_5a/output"
|
|
type: "Concat"
|
|
bottom: "inception_5a/1x1"
|
|
bottom: "inception_5a/3x3"
|
|
bottom: "inception_5a/5x5"
|
|
bottom: "inception_5a/pool_proj"
|
|
top: "inception_5a/output"
|
|
}
|
|
layer {
|
|
name: "inception_5b/1x1"
|
|
type: "Convolution"
|
|
bottom: "inception_5a/output"
|
|
top: "inception_5b/1x1"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 384
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/relu_1x1"
|
|
type: "ReLU"
|
|
bottom: "inception_5b/1x1"
|
|
top: "inception_5b/1x1"
|
|
}
|
|
layer {
|
|
name: "inception_5b/3x3_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_5a/output"
|
|
top: "inception_5b/3x3_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 192
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/relu_3x3_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_5b/3x3_reduce"
|
|
top: "inception_5b/3x3_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_5b/3x3"
|
|
type: "Convolution"
|
|
bottom: "inception_5b/3x3_reduce"
|
|
top: "inception_5b/3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 384
|
|
pad: 1
|
|
kernel_size: 3
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/relu_3x3"
|
|
type: "ReLU"
|
|
bottom: "inception_5b/3x3"
|
|
top: "inception_5b/3x3"
|
|
}
|
|
layer {
|
|
name: "inception_5b/5x5_reduce"
|
|
type: "Convolution"
|
|
bottom: "inception_5a/output"
|
|
top: "inception_5b/5x5_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 48
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/relu_5x5_reduce"
|
|
type: "ReLU"
|
|
bottom: "inception_5b/5x5_reduce"
|
|
top: "inception_5b/5x5_reduce"
|
|
}
|
|
layer {
|
|
name: "inception_5b/5x5"
|
|
type: "Convolution"
|
|
bottom: "inception_5b/5x5_reduce"
|
|
top: "inception_5b/5x5"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 2
|
|
kernel_size: 5
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/relu_5x5"
|
|
type: "ReLU"
|
|
bottom: "inception_5b/5x5"
|
|
top: "inception_5b/5x5"
|
|
}
|
|
layer {
|
|
name: "inception_5b/pool"
|
|
type: "Pooling"
|
|
bottom: "inception_5a/output"
|
|
top: "inception_5b/pool"
|
|
pooling_param {
|
|
pool: MAX
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/pool_proj"
|
|
type: "Convolution"
|
|
bottom: "inception_5b/pool"
|
|
top: "inception_5b/pool_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
kernel_size: 1
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0.2
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "inception_5b/relu_pool_proj"
|
|
type: "ReLU"
|
|
bottom: "inception_5b/pool_proj"
|
|
top: "inception_5b/pool_proj"
|
|
}
|
|
layer {
|
|
name: "inception_5b/output"
|
|
type: "Concat"
|
|
bottom: "inception_5b/1x1"
|
|
bottom: "inception_5b/3x3"
|
|
bottom: "inception_5b/5x5"
|
|
bottom: "inception_5b/pool_proj"
|
|
top: "inception_5b/output"
|
|
}
|
|
layer {
|
|
name: "pool5/7x7_s1"
|
|
type: "Pooling"
|
|
bottom: "inception_5b/output"
|
|
top: "pool5/7x7_s1"
|
|
pooling_param {
|
|
pool: AVE
|
|
kernel_size: 7
|
|
stride: 1
|
|
}
|
|
}
|
|
layer {
|
|
name: "pool5/drop_7x7_s1"
|
|
type: "Dropout"
|
|
bottom: "pool5/7x7_s1"
|
|
top: "pool5/7x7_s1"
|
|
dropout_param {
|
|
dropout_ratio: 0.4
|
|
}
|
|
}
|
|
layer {
|
|
name: "loss3/classifier"
|
|
type: "InnerProduct"
|
|
bottom: "pool5/7x7_s1"
|
|
top: "loss3/classifier"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 2
|
|
decay_mult: 0
|
|
}
|
|
inner_product_param {
|
|
num_output: 1000
|
|
weight_filler {
|
|
type: "xavier"
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "loss3/loss3"
|
|
type: "SoftmaxWithLoss"
|
|
bottom: "loss3/classifier"
|
|
bottom: "label"
|
|
top: "loss3/loss3"
|
|
loss_weight: 1
|
|
}
|