sr.prototxt

layer {
 name: "data"
 type: "Input"
 top: "data"
 input_param {
 shape {
 dim: 1
 dim: 1
 dim: 224
 dim: 224
 }
 }
}
layer {
 name: "conv0"
 type: "Convolution"
 bottom: "data"
 top: "conv0"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 32
 bias_term: true
 pad: 1
 kernel_size: 3
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "conv0/lrelu"
 type: "ReLU"
 bottom: "conv0"
 top: "conv0"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db1/reduce"
 type: "Convolution"
 bottom: "conv0"
 top: "db1/reduce"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 8
 bias_term: true
 pad: 0
 kernel_size: 1
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "db1/reduce/lrelu"
 type: "ReLU"
 bottom: "db1/reduce"
 top: "db1/reduce"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db1/3x3"
 type: "Convolution"
 bottom: "db1/reduce"
 top: "db1/3x3"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 8
 bias_term: true
 pad: 1
 kernel_size: 3
 group: 8
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "db1/3x3/lrelu"
 type: "ReLU"
 bottom: "db1/3x3"
 top: "db1/3x3"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db1/1x1"
 type: "Convolution"
 bottom: "db1/3x3"
 top: "db1/1x1"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 32
 bias_term: true
 pad: 0
 kernel_size: 1
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "db1/1x1/lrelu"
 type: "ReLU"
 bottom: "db1/1x1"
 top: "db1/1x1"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db1/concat"
 type: "Concat"
 bottom: "conv0"
 bottom: "db1/1x1"
 top: "db1/concat"
 concat_param {
 axis: 1
 }
}
layer {
 name: "db2/reduce"
 type: "Convolution"
 bottom: "db1/concat"
 top: "db2/reduce"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 8
 bias_term: true
 pad: 0
 kernel_size: 1
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "db2/reduce/lrelu"
 type: "ReLU"
 bottom: "db2/reduce"
 top: "db2/reduce"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db2/3x3"
 type: "Convolution"
 bottom: "db2/reduce"
 top: "db2/3x3"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 8
 bias_term: true
 pad: 1
 kernel_size: 3
 group: 8
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "db2/3x3/lrelu"
 type: "ReLU"
 bottom: "db2/3x3"
 top: "db2/3x3"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db2/1x1"
 type: "Convolution"
 bottom: "db2/3x3"
 top: "db2/1x1"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 32
 bias_term: true
 pad: 0
 kernel_size: 1
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "db2/1x1/lrelu"
 type: "ReLU"
 bottom: "db2/1x1"
 top: "db2/1x1"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "db2/concat"
 type: "Concat"
 bottom: "db1/concat"
 bottom: "db2/1x1"
 top: "db2/concat"
 concat_param {
 axis: 1
 }
}
layer {
 name: "upsample/reduce"
 type: "Convolution"
 bottom: "db2/concat"
 top: "upsample/reduce"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 32
 bias_term: true
 pad: 0
 kernel_size: 1
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "upsample/reduce/lrelu"
 type: "ReLU"
 bottom: "upsample/reduce"
 top: "upsample/reduce"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "upsample/deconv"
 type: "Deconvolution"
 bottom: "upsample/reduce"
 top: "upsample/deconv"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 32
 bias_term: true
 pad: 1
 kernel_size: 3
 group: 32
 stride: 2
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "upsample/lrelu"
 type: "ReLU"
 bottom: "upsample/deconv"
 top: "upsample/deconv"
 relu_param {
 negative_slope: 0.05000000074505806
 }
}
layer {
 name: "upsample/rec"
 type: "Convolution"
 bottom: "upsample/deconv"
 top: "upsample/rec"
 param {
 lr_mult: 1.0
 decay_mult: 1.0
 }
 param {
 lr_mult: 1.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 1
 bias_term: true
 pad: 0
 kernel_size: 1
 group: 1
 stride: 1
 weight_filler {
 type: "msra"
 }
 }
}
layer {
 name: "nearest"
 type: "Deconvolution"
 bottom: "data"
 top: "nearest"
 param {
 lr_mult: 0.0
 decay_mult: 0.0
 }
 convolution_param {
 num_output: 1
 bias_term: false
 pad: 0
 kernel_size: 2
 group: 1
 stride: 2
 weight_filler {
 type: "constant"
 value: 1.0
 }
 }
}
layer {
 name: "Crop1"
 type: "Crop"
 bottom: "nearest"
 bottom: "upsample/rec"
 top: "Crop1"
}
layer {
 name: "fc"
 type: "Eltwise"
 bottom: "Crop1"
 bottom: "upsample/rec"
 top: "fc"
 eltwise_param {
 operation: SUM
 }
}