137 lines
1.7 KiB
Plaintext
137 lines
1.7 KiB
Plaintext
name: "LeNet"
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layer {
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name: "input"
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type: "Input"
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top: "data"
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input_param {
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shape {
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dim: 64
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dim: 1
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dim: 28
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dim: 28
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}
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}
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}
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layer {
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name: "conv1"
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type: "Convolution"
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bottom: "data"
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top: "conv1"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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convolution_param {
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num_output: 20
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kernel_size: 5
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "pool1"
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type: "Pooling"
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bottom: "conv1"
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top: "pool1"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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}
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}
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layer {
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name: "conv2"
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type: "Convolution"
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bottom: "pool1"
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top: "conv2"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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convolution_param {
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num_output: 50
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kernel_size: 5
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "pool2"
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type: "Pooling"
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bottom: "conv2"
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top: "pool2"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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}
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}
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layer {
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name: "ip1"
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type: "InnerProduct"
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bottom: "pool2"
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top: "ip1"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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inner_product_param {
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num_output: 500
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "relu1"
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type: "ReLU"
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bottom: "ip1"
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top: "ip1"
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}
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layer {
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name: "ip2"
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type: "InnerProduct"
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bottom: "ip1"
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top: "ip2"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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inner_product_param {
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num_output: 10
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "prob"
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type: "Softmax"
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bottom: "ip2"
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top: "prob"
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}
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