DRFN.prototxt

name: "DRFN"
layer {
    name: "data"
    type: "HDF5Data"
    top: "data"
    top: "label"
    hdf5_data_param {
        source: "examples/DRFN/train.txt"
        batch_size: 32
        shuffle: true
    }
    include: { phase: TRAIN }
}
layer {
    name: "data"
    type: "HDF5Data"
    top: "data"
    top: "label"
    hdf5_data_param {
        source: "examples/DRFN/test.txt"
        batch_size: 4
        shuffle: true
    }
    include: { phase: TEST }
}
########################  Deconvolution1  #########################################################################################3
layer {
    name: "deconv1"
    type: "Deconvolution"
    bottom: "data"
    top: "deconv1"
    param {
        lr_mult: 0.100000
    }
    param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64  
        kernel_size: 4
        stride: 2
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_deconv1"
    type: "ReLU"
    bottom: "deconv1"
    top: "deconv1"
}
########################  Deconvolution2  #########################################################################################3
layer {
    name: "deconv2"
    type: "Deconvolution"
    bottom: "deconv1"
    top: "deconv2"
    param {
        lr_mult: 0.100000
    }
    param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64  
        kernel_size: 4
        stride: 2
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_deconv2"
    type: "ReLU"
    bottom: "deconv2"
    top: "deconv2"
}
########################  Deconvolution3  #########################################################################################3
# layer {
#     name: "deconv3"
#     type: "Deconvolution"
#     bottom: "deconv2"
#     top: "deconv3"
#     param {
#         lr_mult: 0.100000
#     }
#     param {
#         lr_mult: 0.100000
#     }
#     convolution_param {
#         num_output: 64  
#         kernel_size: 4
#         stride: 2
#         pad: 1
#         weight_filler {
#             type: "msra"
#         }
#         bias_filler {
#             type: "constant"
#             value: 0
#         }
#     }
# }
# layer {
#     name: "relu_deconv3"
#     type: "ReLU"
#     bottom: "deconv3"
#     top: "deconv3"
#     param {
#         lr_mult: 1
#         decay_mult: 0
#     }
#     ReLU_param {
#         filler: {
#         value: 0.33
#         }
#     channel_shared: false
#     }
# }
######################  conv 1   #############################################3
layer {
    name: "conv1"
    type: "Convolution"
    bottom: "deconv2"
    top: "conv1"
    param {
        lr_mult: 1.000000
    }
    param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 16  
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_conv1"
    type: "ReLU"
    bottom: "conv1"
    top: "conv1"
}
##################### RB 1 1---10 #################################3##############
################### 1a #####################
layer {
    name: "conv_1a"
    type: "Convolution"
    bottom: "deconv2"
    top: "conv_1a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_1a"
    type: "ReLU"
    bottom: "conv_1a"
    top: "conv_1a"
}
################### 1b #####################
layer {
    name: "conv_1b"
    type: "Convolution"
    bottom: "conv_1a"
    top: "conv_1b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_1b"
    type: "ReLU"
    bottom: "conv_1b"
    top: "conv_1b"
}
################### 1c ####################
layer {
    name: "conv_1c"
    type: "Convolution"
    bottom: "conv_1b"
    top: "conv_1c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise1"
    type: "Eltwise"
    bottom: "deconv2"
    bottom: "conv_1c"
    top: "eltwise1"
    eltwise_param {
        operation: SUM
    }
}
################### 2a #####################
layer {
    name: "conv_2a"
    type: "Convolution"
    bottom: "eltwise1"
    top: "conv_2a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_2a"
    type: "ReLU"
    bottom: "conv_2a"
    top: "conv_2a"
}
################### 2b #####################
layer {
    name: "conv_2b"
    type: "Convolution"
    bottom: "conv_2a"
    top: "conv_2b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_2b"
    type: "ReLU"
    bottom: "conv_2b"
    top: "conv_2b"
}
################### 2c #####################
layer {
    name: "conv_2c"
    type: "Convolution"
    bottom: "conv_2b"
    top: "conv_2c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise2"
    type: "Eltwise"
    bottom: "eltwise1"
    bottom: "conv_2c"
    top: "eltwise2"
    eltwise_param {
        operation: SUM
    }
}
################### 3a #####################
layer {
    name: "conv_3a"
    type: "Convolution"
    bottom: "eltwise2"
    top: "conv_3a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_3a"
    type: "ReLU"
    bottom: "conv_3a"
    top: "conv_3a"
}
################### 3b #####################
layer {
    name: "conv_3b"
    type: "Convolution"
    bottom: "conv_3a"
    top: "conv_3b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_3b"
    type: "ReLU"
    bottom: "conv_3b"
    top: "conv_3b"
}
################### 3c ####################
layer {
    name: "conv_3c"
    type: "Convolution"
    bottom: "conv_3b"
    top: "conv_3c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise3"
    type: "Eltwise"
    bottom: "eltwise2"
    bottom: "conv_3c"
    top: "eltwise3"
    eltwise_param {
        operation: SUM
    }
}
################### 4a #####################
layer {
    name: "conv_4a"
    type: "Convolution"
    bottom: "eltwise3"
    top: "conv_4a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_4a"
    type: "ReLU"
    bottom: "conv_4a"
    top: "conv_4a"
}
################### 4b #####################
layer {
    name: "conv_4b"
    type: "Convolution"
    bottom: "conv_4a"
    top: "conv_4b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_4b"
    type: "ReLU"
    bottom: "conv_4b"
    top: "conv_4b"
}
################### 4c ####################
layer {
    name: "conv_4c"
    type: "Convolution"
    bottom: "conv_4b"
    top: "conv_4c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise4"
    type: "Eltwise"
    bottom: "eltwise3"
    bottom: "conv_4c"
    top: "eltwise4"
    eltwise_param {
        operation: SUM
    }
}
################### 5a #####################
layer {
    name: "conv_5a"
    type: "Convolution"
    bottom: "eltwise4"
    top: "conv_5a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_5a"
    type: "ReLU"
    bottom: "conv_5a"
    top: "conv_5a"
}
################### 5b #####################
layer {
    name: "conv_5b"
    type: "Convolution"
    bottom: "conv_5a"
    top: "conv_5b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_5b"
    type: "ReLU"
    bottom: "conv_5b"
    top: "conv_5b"
}
################### 5c ####################
layer {
    name: "conv_5c"
    type: "Convolution"
    bottom: "conv_5b"
    top: "conv_5c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise5"
    type: "Eltwise"
    bottom: "eltwise4"
    bottom: "conv_5c"
    top: "eltwise5"
    eltwise_param {
        operation: SUM
    }
}

################### 6a #####################
layer {
    name: "conv_6a"
    type: "Convolution"
    bottom: "eltwise5"
    top: "conv_6a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_6a"
    type: "ReLU"
    bottom: "conv_6a"
    top: "conv_6a"
}
################### 6b #####################
layer {
    name: "conv_6b"
    type: "Convolution"
    bottom: "conv_6a"
    top: "conv_6b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_6b"
    type: "ReLU"
    bottom: "conv_6b"
    top: "conv_6b"
}
################### 6c #####################
layer {
    name: "conv_6c"
    type: "Convolution"
    bottom: "conv_6b"
    top: "conv_6c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise6"
    type: "Eltwise"
    bottom: "eltwise5"
    bottom: "conv_6c"
    top: "eltwise6"
    eltwise_param {
        operation: SUM
    }
}
################### 7a #####################
layer {
    name: "conv_7a"
    type: "Convolution"
    bottom: "eltwise6"
    top: "conv_7a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_7a"
    type: "ReLU"
    bottom: "conv_7a"
    top: "conv_7a"
}
################### 7b #####################
layer {
    name: "conv_7b"
    type: "Convolution"
    bottom: "conv_7a"
    top: "conv_7b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_7b"
    type: "ReLU"
    bottom: "conv_7b"
    top: "conv_7b"
}
################### 7c #####################
layer {
    name: "conv_7c"
    type: "Convolution"
    bottom: "conv_7b"
    top: "conv_7c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise7"
    type: "Eltwise"
    bottom: "eltwise6"
    bottom: "conv_7c"
    top: "eltwise7"
    eltwise_param {
        operation: SUM
    }
}
################### 8a #####################
layer {
    name: "conv_8a"
    type: "Convolution"
    bottom: "eltwise7"
    top: "conv_8a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_8a"
    type: "ReLU"
    bottom: "conv_8a"
    top: "conv_8a"
}
################### 8b #####################
layer {
    name: "conv_8b"
    type: "Convolution"
    bottom: "conv_8a"
    top: "conv_8b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_8b"
    type: "ReLU"
    bottom: "conv_8b"
    top: "conv_8b"
}
################### 8c #####################
layer {
    name: "conv_8c"
    type: "Convolution"
    bottom: "conv_8b"
    top: "conv_8c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise8"
    type: "Eltwise"
    bottom: "eltwise7"
    bottom: "conv_8c"
    top: "eltwise8"
    eltwise_param {
        operation: SUM
    }
}
################### 9a #####################
layer {
    name: "conv_9a"
    type: "Convolution"
    bottom: "eltwise8"
    top: "conv_9a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_9a"
    type: "ReLU"
    bottom: "conv_9a"
    top: "conv_9a"
}
################### 9b #####################
layer {
    name: "conv_9b"
    type: "Convolution"
    bottom: "conv_9a"
    top: "conv_9b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_9b"
    type: "ReLU"
    bottom: "conv_9b"
    top: "conv_9b"
}
################### 9c #####################
layer {
    name: "conv_9c"
    type: "Convolution"
    bottom: "conv_9b"
    top: "conv_9c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise9"
    type: "Eltwise"
    bottom: "eltwise8"
    bottom: "conv_9c"
    top: "eltwise9"
    eltwise_param {
        operation: SUM
    }
}################### 10a #####################
layer {
    name: "conv_10a"
    type: "Convolution"
    bottom: "eltwise9"
    top: "conv_10a"
    param {
        name: "RB1_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_10a"
    type: "ReLU"
    bottom: "conv_10a"
    top: "conv_10a"
}
################### 10b #####################
layer {
    name: "conv_10b"
    type: "Convolution"
    bottom: "conv_10a"
    top: "conv_10b"
    param {
        name: "RB1_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_10b"
    type: "ReLU"
    bottom: "conv_10b"
    top: "conv_10b"
}
################### 10c #####################
layer {
    name: "conv_10c"
    type: "Convolution"
    bottom: "conv_10b"
    top: "conv_10c"
    param {
        name: "RB1_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB1_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise10"
    type: "Eltwise"
    bottom: "eltwise9"
    bottom: "conv_10c"
    top: "eltwise10"
    eltwise_param {
        operation: SUM
    }
}

################# conv 2  ###########################################################
layer {
    name: "conv2"
    type: "Convolution"
    bottom: "eltwise10"
    top: "conv2"
    param {
        lr_mult: 1.000000
    }
    param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 32  
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_conv2"
    type: "ReLU"
    bottom: "conv2"
    top: "conv2"
}
##################### RB 2 three  10---20 #################################3##############

################### 11a #####################
layer {
    name: "conv_11a"
    type: "Convolution"
    bottom: "eltwise10"
    top: "conv_11a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_11a"
    type: "ReLU"
    bottom: "conv_11a"
    top: "conv_11a"
}
################### 11b #####################
layer {
    name: "conv_11b"
    type: "Convolution"
    bottom: "conv_11a"
    top: "conv_11b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_11b"
    type: "ReLU"
    bottom: "conv_11b"
    top: "conv_11b"
}
################### 11c ####################
layer {
    name: "conv_11c"
    type: "Convolution"
    bottom: "conv_11b"
    top: "conv_11c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise11"
    type: "Eltwise"
    bottom: "eltwise10"
    bottom: "conv_11c"
    top: "eltwise11"
    eltwise_param {
        operation: SUM
    }
}
################### 12a #####################
layer {
    name: "conv_12a"
    type: "Convolution"
    bottom: "eltwise11"
    top: "conv_12a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_12a"
    type: "ReLU"
    bottom: "conv_12a"
    top: "conv_12a"
}
################### 12b #####################
layer {
    name: "conv_12b"
    type: "Convolution"
    bottom: "conv_12a"
    top: "conv_12b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_12b"
    type: "ReLU"
    bottom: "conv_12b"
    top: "conv_12b"
}
################### 12c #####################
layer {
    name: "conv_12c"
    type: "Convolution"
    bottom: "conv_12b"
    top: "conv_12c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise12"
    type: "Eltwise"
    bottom: "eltwise11"
    bottom: "conv_12c"
    top: "eltwise12"
    eltwise_param {
        operation: SUM
    }
}
################### 13a #####################
layer {
    name: "conv_13a"
    type: "Convolution"
    bottom: "eltwise12"
    top: "conv_13a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_13a"
    type: "ReLU"
    bottom: "conv_13a"
    top: "conv_13a"
}
################### 13b #####################
layer {
    name: "conv_13b"
    type: "Convolution"
    bottom: "conv_13a"
    top: "conv_13b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_13b"
    type: "ReLU"
    bottom: "conv_13b"
    top: "conv_13b"
}
################### 13c ####################
layer {
    name: "conv_13c"
    type: "Convolution"
    bottom: "conv_13b"
    top: "conv_13c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise13"
    type: "Eltwise"
    bottom: "eltwise12"
    bottom: "conv_13c"
    top: "eltwise13"
    eltwise_param {
        operation: SUM
    }
}
################### 14a #####################
layer {
    name: "conv_14a"
    type: "Convolution"
    bottom: "eltwise13"
    top: "conv_14a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_14a"
    type: "ReLU"
    bottom: "conv_14a"
    top: "conv_14a"
}
################### 14b #####################
layer {
    name: "conv_14b"
    type: "Convolution"
    bottom: "conv_14a"
    top: "conv_14b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_14b"
    type: "ReLU"
    bottom: "conv_14b"
    top: "conv_14b"
}
################### 14c ####################
layer {
    name: "conv_14c"
    type: "Convolution"
    bottom: "conv_14b"
    top: "conv_14c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise14"
    type: "Eltwise"
    bottom: "eltwise13"
    bottom: "conv_14c"
    top: "eltwise14"
    eltwise_param {
        operation: SUM
    }
}
################### 15a #####################
layer {
    name: "conv_15a"
    type: "Convolution"
    bottom: "eltwise14"
    top: "conv_15a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_15a"
    type: "ReLU"
    bottom: "conv_15a"
    top: "conv_15a"
}
################### 15b #####################
layer {
    name: "conv_15b"
    type: "Convolution"
    bottom: "conv_15a"
    top: "conv_15b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_15b"
    type: "ReLU"
    bottom: "conv_15b"
    top: "conv_15b"
}
################### 15c ####################
layer {
    name: "conv_15c"
    type: "Convolution"
    bottom: "conv_15b"
    top: "conv_15c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise15"
    type: "Eltwise"
    bottom: "eltwise14"
    bottom: "conv_15c"
    top: "eltwise15"
    eltwise_param {
        operation: SUM
    }
}
################### 16a #####################
layer {
    name: "conv_16a"
    type: "Convolution"
    bottom: "eltwise15"
    top: "conv_16a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_16a"
    type: "ReLU"
    bottom: "conv_16a"
    top: "conv_16a"
}
################### 16b #####################
layer {
    name: "conv_16b"
    type: "Convolution"
    bottom: "conv_16a"
    top: "conv_16b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_16b"
    type: "ReLU"
    bottom: "conv_16b"
    top: "conv_16b"
}
################### 16c #####################
layer {
    name: "conv_16c"
    type: "Convolution"
    bottom: "conv_16b"
    top: "conv_16c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise16"
    type: "Eltwise"
    bottom: "eltwise15"
    bottom: "conv_16c"
    top: "eltwise16"
    eltwise_param {
        operation: SUM
    }
}
################### 17a #####################
layer {
    name: "conv_17a"
    type: "Convolution"
    bottom: "eltwise16"
    top: "conv_17a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_17a"
    type: "ReLU"
    bottom: "conv_17a"
    top: "conv_17a"
}
################### 17b #####################
layer {
    name: "conv_17b"
    type: "Convolution"
    bottom: "conv_17a"
    top: "conv_17b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_17b"
    type: "ReLU"
    bottom: "conv_17b"
    top: "conv_17b"
}
################### 17c #####################
layer {
    name: "conv_17c"
    type: "Convolution"
    bottom: "conv_17b"
    top: "conv_17c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise17"
    type: "Eltwise"
    bottom: "eltwise16"
    bottom: "conv_17c"
    top: "eltwise17"
    eltwise_param {
        operation: SUM
    }
}
################### 18a #####################
layer {
    name: "conv_18a"
    type: "Convolution"
    bottom: "eltwise17"
    top: "conv_18a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_18a"
    type: "ReLU"
    bottom: "conv_18a"
    top: "conv_18a"
}
################### 18b #####################
layer {
    name: "conv_18b"
    type: "Convolution"
    bottom: "conv_18a"
    top: "conv_18b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_18b"
    type: "ReLU"
    bottom: "conv_18b"
    top: "conv_18b"
}
################### 18c #####################
layer {
    name: "conv_18c"
    type: "Convolution"
    bottom: "conv_18b"
    top: "conv_18c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise18"
    type: "Eltwise"
    bottom: "eltwise17"
    bottom: "conv_18c"
    top: "eltwise18"
    eltwise_param {
        operation: SUM
    }
}
################### 19a #####################
layer {
    name: "conv_19a"
    type: "Convolution"
    bottom: "eltwise18"
    top: "conv_19a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_19a"
    type: "ReLU"
    bottom: "conv_19a"
    top: "conv_19a"
}
################### 19b #####################
layer {
    name: "conv_19b"
    type: "Convolution"
    bottom: "conv_19a"
    top: "conv_19b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_19b"
    type: "ReLU"
    bottom: "conv_19b"
    top: "conv_19b"
}
################### 19c #####################
layer {
    name: "conv_19c"
    type: "Convolution"
    bottom: "conv_19b"
    top: "conv_19c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise19"
    type: "Eltwise"
    bottom: "eltwise18"
    bottom: "conv_19c"
    top: "eltwise19"
    eltwise_param {
        operation: SUM
    }
}################### 20a #####################
layer {
    name: "conv_20a"
    type: "Convolution"
    bottom: "eltwise19"
    top: "conv_20a"
    param {
        name: "RB2_wa"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_ba"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_20a"
    type: "ReLU"
    bottom: "conv_20a"
    top: "conv_20a"
}
################### 20b #####################
layer {
    name: "conv_20b"
    type: "Convolution"
    bottom: "conv_20a"
    top: "conv_20b"
    param {
        name: "RB2_wb"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bb"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_20b"
    type: "ReLU"
    bottom: "conv_20b"
    top: "conv_20b"
}
################### 20c #####################
layer {
    name: "conv_20c"
    type: "Convolution"
    bottom: "conv_20b"
    top: "conv_20c"
    param {
        name: "RB2_wc"
        lr_mult: 1.000000
    }
    param {
        name: "RB2_bc"
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 64
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}


layer {
    name: "eltwise20"
    type: "Eltwise"
    bottom: "eltwise19"
    bottom: "conv_20c"
    top: "eltwise20"
    eltwise_param {
        operation: SUM
    }
}
################# conv 3  ###########################################################
layer {
    name: "conv3"
    type: "Convolution"
    bottom: "eltwise20"
    top: "conv3"
    param {
        lr_mult: 1.000000
    }
    param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 48  
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
}
layer {
    name: "relu_conv3"
    type: "ReLU"
    bottom: "conv3"
    top: "conv3"
}
################  Reconstruction  ####################################################################
layer {
  name:"merge"
  bottom:"conv1"
  bottom:"conv2"
  bottom:"conv3"
  top:"merge"
  type:"Concat"
  concat_param {
    concat_dim: 1 # 0 is n    1 is layers
  }
}



layer {
    name: "hr"
    type: "Convolution"
    bottom: "merge"
    top: "hr"
    param {
        lr_mult: 0.100000
    }
    param {
        lr_mult: 0.100000
    }
    convolution_param {
        num_output: 1  #input 11   output 44
        kernel_size: 3
        stride: 1
        pad: 1
        weight_filler {
            type: "msra"
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
} 


layer {
    name: "loss"
    type: "EuclideanLoss"
    bottom: "hr"
    bottom: "label"
    top: "loss"
}