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