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| name: "VDSR" | |
| layer { | |
| name: "data" | |
| type: "HDF5Data" | |
| top: "data" | |
| top: "label" | |
| hdf5_data_param { | |
| source: "examples/VDSR/train.txt" | |
| batch_size: 64 | |
| } | |
| include: { phase: TRAIN } | |
| } | |
| layer { | |
| name: "data" | |
| type: "HDF5Data" | |
| top: "data" | |
| top: "label" | |
| hdf5_data_param { | |
| source: "examples/VDSR/test.txt" | |
| batch_size: 2 | |
| } | |
| include: { phase: TEST } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "conv2" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "conv2" | |
| top: "conv3" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu3" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| top: "conv4" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| } | |
| layer { | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv5" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu5" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| } | |
| layer { | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "conv5" | |
| top: "conv6" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| } | |
| layer { | |
| name: "conv7" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| top: "conv7" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "conv7" | |
| top: "conv7" | |
| } | |
| layer { | |
| name: "conv8" | |
| type: "Convolution" | |
| bottom: "conv7" | |
| top: "conv8" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu8" | |
| type: "ReLU" | |
| bottom: "conv8" | |
| top: "conv8" | |
| } | |
| layer { | |
| name: "conv9" | |
| type: "Convolution" | |
| bottom: "conv8" | |
| top: "conv9" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu9" | |
| type: "ReLU" | |
| bottom: "conv9" | |
| top: "conv9" | |
| } | |
| layer { | |
| name: "conv10" | |
| type: "Convolution" | |
| bottom: "conv9" | |
| top: "conv10" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu10" | |
| type: "ReLU" | |
| bottom: "conv10" | |
| top: "conv10" | |
| } | |
| layer { | |
| name: "conv11" | |
| type: "Convolution" | |
| bottom: "conv10" | |
| top: "conv11" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu11" | |
| type: "ReLU" | |
| bottom: "conv11" | |
| top: "conv11" | |
| } | |
| layer { | |
| name: "conv12" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| top: "conv12" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu12" | |
| type: "ReLU" | |
| bottom: "conv12" | |
| top: "conv12" | |
| } | |
| layer { | |
| name: "conv13" | |
| type: "Convolution" | |
| bottom: "conv12" | |
| top: "conv13" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu13" | |
| type: "ReLU" | |
| bottom: "conv13" | |
| top: "conv13" | |
| } | |
| layer { | |
| name: "conv14" | |
| type: "Convolution" | |
| bottom: "conv13" | |
| top: "conv14" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu14" | |
| type: "ReLU" | |
| bottom: "conv14" | |
| top: "conv14" | |
| } | |
| layer { | |
| name: "conv15" | |
| type: "Convolution" | |
| bottom: "conv14" | |
| top: "conv15" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu15" | |
| type: "ReLU" | |
| bottom: "conv15" | |
| top: "conv15" | |
| } | |
| layer { | |
| name: "conv16" | |
| type: "Convolution" | |
| bottom: "conv15" | |
| top: "conv16" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu16" | |
| type: "ReLU" | |
| bottom: "conv16" | |
| top: "conv16" | |
| } | |
| layer { | |
| name: "conv17" | |
| type: "Convolution" | |
| bottom: "conv16" | |
| top: "conv17" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu17" | |
| type: "ReLU" | |
| bottom: "conv17" | |
| top: "conv17" | |
| } | |
| layer { | |
| name: "conv18" | |
| type: "Convolution" | |
| bottom: "conv17" | |
| top: "conv18" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu18" | |
| type: "ReLU" | |
| bottom: "conv18" | |
| top: "conv18" | |
| } | |
| layer { | |
| name: "conv19" | |
| type: "Convolution" | |
| bottom: "conv18" | |
| top: "conv19" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu19" | |
| type: "ReLU" | |
| bottom: "conv19" | |
| top: "conv19" | |
| } | |
| layer { | |
| name: "conv20" | |
| type: "Convolution" | |
| bottom: "conv19" | |
| top: "conv20" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "sum" | |
| type: "Eltwise" | |
| bottom: "data" | |
| bottom: "conv20" | |
| top: "sum" | |
| eltwise_param { | |
| operation: 1 | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "EuclideanLoss" | |
| bottom: "sum" | |
| bottom: "label" | |
| top: "loss" | |
| } |
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