name: "PR_Lightweight11LayerNet"

input: 'data'
input_shape {
    dim: 1
    dim: 1
    dim: 32
    dim: 512
}

#-----------------------------Conv1-----------------------------
layer {
  name: "conv1_1_1"   type: "Convolution"
  bottom: "data"    top: "conv1_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 32   kernel_size: 7   pad: 3	stride: 2
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu1"    type: "ReLU"
  bottom: "conv1_1"  top: "conv1_1"
}
# current shape: 16*256

#-----------------------------ResBlock_1--------------------------
# 1*1
layer {
  name: "ResBlock_1_1"   type: "Convolution"
  bottom: "conv1_1"    top: "ResBlock_1_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 32   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu2"    type: "ReLU"
  bottom: "ResBlock_1_1"  top: "ResBlock_1_1"
}


# 3*3
layer {
  name: "ResBlock_1_2"   type: "Convolution"
  bottom: "ResBlock_1_1"    top: "ResBlock_1_2"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 32   kernel_size: 3   pad: 1    group: 32
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu3"    type: "ReLU"
  bottom: "ResBlock_1_2"  top: "ResBlock_1_2"
}

# 1*1
layer {
  name: "ResBlock_1_3"   type: "Convolution"
  bottom: "ResBlock_1_2"    top: "ResBlock_1_3"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu4"    type: "ReLU"
  bottom: "ResBlock_1_3"  top: "ResBlock_1_3"
}


# 1*1	for the change of channel number change!
layer {
  name: "ResBlock_1_4"   type: "Convolution"
  bottom: "conv1_1"    top: "ResBlock_1_4"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu5"    type: "ReLU"
  bottom: "ResBlock_1_4"  top: "ResBlock_1_4"
}


# SUM
layer {
    bottom: "ResBlock_1_4"
    bottom: "ResBlock_1_3"
    top: "Block1"
    name: "Block1"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

#-----------------------------Pooling1-------------------------------
layer {
  name: "pool1"      type: "Pooling"
  bottom: "Block1"  top: "pool1"
  pooling_param {  pool: MAX   kernel_size: 2   stride: 2 }
}
# current shape: 8*128

#-----------------------------ResBlock_3--------------------------
# 1*1
layer {
  name: "ResBlock_3_1"   type: "Convolution"
  bottom: "pool1"    top: "ResBlock_3_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu8"    type: "ReLU"
  bottom: "ResBlock_3_1"  top: "ResBlock_3_1"
}


# 3*3
layer {
  name: "ResBlock_3_2"   type: "Convolution"
  bottom: "ResBlock_3_1"    top: "ResBlock_3_2"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 3   pad: 1    group: 64
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu9"    type: "ReLU"
  bottom: "ResBlock_3_2"  top: "ResBlock_3_2"
}

# 1*1
layer {
  name: "ResBlock_3_3"   type: "Convolution"
  bottom: "ResBlock_3_2"    top: "ResBlock_3_3"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 128   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu10"    type: "ReLU"
  bottom: "ResBlock_3_3"  top: "ResBlock_3_3"
}



# 1*1	for the change of channel number change!
layer {
  name: "ResBlock_3_4"   type: "Convolution"
  bottom: "pool1"    top: "ResBlock_3_4"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 128   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu5"    type: "ReLU"
  bottom: "ResBlock_3_4"  top: "ResBlock_3_4"
}


# SUM
layer {
    bottom: "ResBlock_3_4"
    bottom: "ResBlock_3_3"
    top: "Block3"
    name: "Block3"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

#-----------------------------Pooling2-------------------------------
layer {
  name: "pool2"      type: "Pooling"
  bottom: "Block3"  top: "pool2"
  pooling_param {  pool: MAX   kernel_size: 2   stride: 2 }
}
# current shape: 4*64


#-----------------------------ResBlock_4--------------------------
# 1*1
layer {
  name: "ResBlock_4_1"   type: "Convolution"
  bottom: "pool2"    top: "ResBlock_4_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu11"    type: "ReLU"
  bottom: "ResBlock_4_1"  top: "ResBlock_4_1"
}


# 3*3
layer {
  name: "ResBlock_4_2"   type: "Convolution"
  bottom: "ResBlock_4_1"    top: "ResBlock_4_2"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 3   pad: 1    group: 64
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu12"    type: "ReLU"
  bottom: "ResBlock_4_2"  top: "ResBlock_4_2"
}

# 1*1
layer {
  name: "ResBlock_4_3"   type: "Convolution"
  bottom: "ResBlock_4_2"    top: "ResBlock_4_3"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 128   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu13"    type: "ReLU"
  bottom: "ResBlock_4_3"  top: "ResBlock_4_3"
}


# 1*1	for the change of channel number change!
layer {
  name: "ResBlock_4_4"   type: "Convolution"
  bottom: "pool2"    top: "ResBlock_4_4"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 128   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu14"    type: "ReLU"
  bottom: "ResBlock_4_4"  top: "ResBlock_4_4"
}


# SUM
layer {
    bottom: "ResBlock_4_4"
    bottom: "ResBlock_4_3"
    top: "Block4"
    name: "Block4"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

#-----------------------------ResBlock_5--------------------------
# 1*1
layer {
  name: "ResBlock_5_1"   type: "Convolution"
  bottom: "Block4"    top: "ResBlock_5_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu15"    type: "ReLU"
  bottom: "ResBlock_5_1"  top: "ResBlock_5_1"
}


# 3*3
layer {
  name: "ResBlock_5_2"   type: "Convolution"
  bottom: "ResBlock_5_1"    top: "ResBlock_5_2"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 64   kernel_size: 3   pad: 1    group: 64
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu16"    type: "ReLU"
  bottom: "ResBlock_5_2"  top: "ResBlock_5_2"
}

# 1*1
layer {
  name: "ResBlock_5_3"   type: "Convolution"
  bottom: "ResBlock_5_2"    top: "ResBlock_5_3"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 128   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu17"    type: "ReLU"
  bottom: "ResBlock_5_3"  top: "ResBlock_5_3"
}

# SUM
layer {
    bottom: "Block4"
    bottom: "ResBlock_5_3"
    top: "Block5"
    name: "Block5"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}

#-----------------------------ResBlock_9--------------------------
# 1*1
layer {
  name: "ResBlock_9_1"   type: "Convolution"
  bottom: "Block5"    top: "ResBlock_9_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 256   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu27"    type: "ReLU"
  bottom: "ResBlock_9_1"  top: "ResBlock_9_1"
}


# 4*4
layer {
  name: "ResBlock_9_2"   type: "Convolution"
  bottom: "ResBlock_9_1"    top: "ResBlock_9_2"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 256   kernel_size: 4   pad_w: 2    group: 256
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu28"    type: "ReLU"
  bottom: "ResBlock_9_2"  top: "ResBlock_9_2"
}


# 1*1
layer {
  name: "ResBlock_added1"   type: "Convolution"
  bottom: "ResBlock_9_2"    top: "ResBlock_added1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 256   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu29"    type: "ReLU"
  bottom: "ResBlock_added1"  top: "ResBlock_added1"
}



# 1*1
layer {
  name: "ResBlock_9_3"   type: "Convolution"
  bottom: "ResBlock_added1"    top: "ResBlock_9_3"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 512   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu29"    type: "ReLU"
  bottom: "ResBlock_9_3"  top: "ResBlock_9_3"
}

#-----------------------------ResBlock_10--------------------------
# 1*1
layer {
  name: "ResBlock_10_1"   type: "Convolution"
  bottom: "ResBlock_9_3"    top: "ResBlock_10_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 256   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu30"    type: "ReLU"
  bottom: "ResBlock_10_1"  top: "ResBlock_10_1"
}



# SUM
layer {
    bottom: "ResBlock_10_1"
    bottom: "ResBlock_added1"
    top: "Block_End"
    name: "Block_End"
    type: "Eltwise"
    eltwise_param {
        operation: SUM
    }
}


# 1*1
layer {
  name: "conv_end_yao"   type: "Convolution"
  bottom: "Block_End"    top: "conv_end_yao"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 2  decay_mult: 0 }
  convolution_param {
    num_output: 7402   kernel_size: 1   pad: 0
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}


#------------------------------------------------------------------------
#
#layer {
#    name: "transpose"
#	type: "Permute"
#	bottom: "conv_end_yao"
#	top: "transpose"
#	permute_param{ order: 3	order: 2 order: 0 order:1}
#}
#
#layer {
#  name: "reshape"
#  type: "Reshape"
#  bottom: "transpose"
#  top: "cnn_end"
#  reshape_param {
#    shape { dim: -1 }
#    axis: 1
#    num_axes: 2
#  }
#}