189 lines
2.8 KiB
Plaintext
189 lines
2.8 KiB
Plaintext
# adapted from https://github.com/lltcggie/waifu2x-caffe
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name: "vgg_7"
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layer {
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name: "input"
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type: "Input"
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top: "input"
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input_param { shape: { dim: 1 dim: 3 dim: 142 dim: 142 } }
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}
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layer {
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name: "conv1_layer"
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type: "Convolution"
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bottom: "input"
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top: "conv1"
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convolution_param {
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num_output: 32
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "conv1_relu_layer"
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type: "ReLU"
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bottom: "conv1"
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top: "conv1"
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relu_param {
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negative_slope: 0.1
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}
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}
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layer {
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name: "conv2_layer"
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type: "Convolution"
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bottom: "conv1"
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top: "conv2"
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convolution_param {
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num_output: 32
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "conv2_relu_layer"
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type: "ReLU"
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bottom: "conv2"
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top: "conv2"
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relu_param {
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negative_slope: 0.1
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}
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}
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layer {
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name: "conv3_layer"
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type: "Convolution"
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bottom: "conv2"
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top: "conv3"
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convolution_param {
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num_output: 64
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "conv3_relu_layer"
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type: "ReLU"
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bottom: "conv3"
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top: "conv3"
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relu_param {
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negative_slope: 0.1
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}
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}
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layer {
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name: "conv4_layer"
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type: "Convolution"
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bottom: "conv3"
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top: "conv4"
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convolution_param {
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num_output: 64
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "conv4_relu_layer"
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type: "ReLU"
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bottom: "conv4"
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top: "conv4"
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relu_param {
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negative_slope: 0.1
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}
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}
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layer {
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name: "conv5_layer"
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type: "Convolution"
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bottom: "conv4"
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top: "conv5"
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convolution_param {
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num_output: 128
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "conv5_relu_layer"
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type: "ReLU"
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bottom: "conv5"
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top: "conv5"
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relu_param {
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negative_slope: 0.1
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}
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}
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layer {
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name: "conv6_layer"
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type: "Convolution"
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bottom: "conv5"
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top: "conv6"
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convolution_param {
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num_output: 128
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "conv6_relu_layer"
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type: "ReLU"
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bottom: "conv6"
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top: "conv6"
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relu_param {
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negative_slope: 0.1
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}
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}
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layer {
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name: "conv7_layer"
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type: "Convolution"
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bottom: "conv6"
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top: "conv7"
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convolution_param {
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num_output: 3
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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}
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}
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layer {
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name: "target"
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type: "MemoryData"
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top: "target"
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top: "dummy_label2"
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memory_data_param {
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batch_size: 1
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channels: 3
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height: 142
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width: 142
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}
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include: { phase: TRAIN }
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}
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layer {
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name: "loss"
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type: "EuclideanLoss"
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bottom: "conv7"
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bottom: "target"
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top: "loss"
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include: { phase: TRAIN }
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}
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