name: "PR_Lightweight11LayerNet"

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

#-----------------------------Conv1_1---------------------------------
layer {
  name: "conv1_1"   type: "Convolution"
  bottom: "data"    top: "conv1_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 50   kernel_size: 3   pad: 1
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu1_1"    type: "ReLU"
  bottom: "conv1_1"  top: "conv1_1"
}

#-----------------------------Conv1_2---------------------------------

layer {
  name: "conv1b_3x3"    type: "Convolution"
  bottom: "conv1_1"     top: "conv1b_3x3"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 48    kernel_size: 3    pad: 1
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}
layer {
  name: "relu1b_3x3"    type: "ReLU"
  bottom: "conv1b_3x3"  top: "conv1b_3x3"
}
layer {
  name: "conv1b_1x1"     type: "Convolution"
  bottom: "conv1_1"      top: "conv1b_1x1"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 }   
  convolution_param {
    num_output: 48    kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_conv1b_1x1"    type: "ReLU"
  bottom: "conv1b_1x1"       top: "conv1b_1x1"
}
layer {
  name: "conv1b_concat"      type: "Concat"
  bottom: "conv1b_3x3"       bottom: "conv1b_1x1"
  top: "conv1_2"
}

#-----------------------------drop1_2---------------------------------
# layer {
  # name: "drop1_2"     type: "Dropout"  
  # bottom: "conv1_2"   top: "conv1_2"
  # dropout_param { dropout_ratio: 0.1 }
# }

#-----------------------------Pooling1-------------------------------
layer {
  name: "pool1"      type: "Pooling"
  bottom: "conv1_2"  top: "pool1"
  pooling_param {  pool: MAX   kernel_size: 2   stride: 2  }
}

#-----------------------------Conv2_1---------------------------------
layer {
  name: "conv2a_3x3"   type: "Convolution"
  bottom: "pool1"      top: "conv2a_3x3"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 80   kernel_size: 3   pad: 1
    weight_filler {  type: "xavier" }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu2a_3x3"      type: "ReLU"
  bottom: "conv2a_3x3"    top: "conv2a_3x3"
}
layer {
  name: "conv2a_1x1"     type: "Convolution"
  bottom: "pool1"        top: "conv2a_1x1"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 }   
  convolution_param {
    num_output: 80    kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_conv2a_1x1"    type: "ReLU"
  bottom: "conv2a_1x1"       top: "conv2a_1x1"
}
layer {
  name: "conv2a_concat"      type: "Concat"
  bottom: "conv2a_3x3"       bottom: "conv2a_1x1"
  top: "conv2_1"
}

#-----------------------------drop1_1---------------------------------
# layer {
  # name: "drop2_1"     type: "Dropout"  
  # bottom: "conv2_1"   top: "conv2_1"
  # dropout_param { dropout_ratio: 0.1 }
# }

#-----------------------------Conv2_2---------------------------------
layer {
  name: "compress2b"      type: "Convolution" 
  bottom: "conv2_1"       top: "compress2b"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 }
  convolution_param {
    num_output: 100   kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_compress2b"    type: "ReLU"
  bottom: "compress2b"       top: "compress2b"
}
layer {
  name: "conv2b_3x3"         type: "Convolution"
  bottom: "compress2b"       top: "conv2b_3x3"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 96    kernel_size: 3   pad: 1
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}
layer {
  name: "relu_conv2b_3x3"    type: "ReLU"
  bottom: "conv2b_3x3"       top: "conv2b_3x3"
}
layer {
  name: "conv2b_1x1"       type: "Convolution"
  bottom: "compress2b"     top: "conv2b_1x1"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 }   
  convolution_param {
    num_output: 96    kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_conv2b_1x1"    type: "ReLU"
  bottom: "conv2b_1x1"       top: "conv2b_1x1"
}
layer {
  name: "conv2b_concat"      type: "Concat"
  bottom: "conv2b_3x3"       bottom: "conv2b_1x1"
  top: "conv2_2"
}

#-----------------------------drop2_2---------------------------------
# layer {
  # name: "drop2_2"     type: "Dropout"  
  # bottom: "conv2_2"   top: "conv2_2"
  # dropout_param { dropout_ratio: 0.2 }
# }

#-----------------------------Pooling2-------------------------------
layer {
  name: "pool2"      type: "Pooling"
  bottom: "conv2_2"  top: "pool2"
  pooling_param {  pool: MAX   kernel_size: 2   stride: 2 }
}

#-----------------------------Conv3_1----------------------------------
layer {
  name: "compress3a"      type: "Convolution" 
  bottom: "pool2"         top: "compress3a"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 } 
  convolution_param {
    num_output: 100   kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_compress3a"    type: "ReLU"
  bottom: "compress3a"       top: "compress3a"
}
layer {
  name: "conv3_1"         type: "Convolution"
  bottom: "compress3a"    top: "conv3_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 250   kernel_size: 3   pad: 1
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu3_1"    type: "ReLU"
  bottom: "conv3_1"  top: "conv3_1"
}

#-----------------------------drop3_1---------------------------------
# layer {
  # name: "drop3_1"     type: "Dropout"  
  # bottom: "conv3_1"   top: "conv3_1"
  # dropout_param { dropout_ratio: 0.2 }
# }

#-----------------------------Conv3_2----------------------------------
layer {
  name: "compress3b"       type: "Convolution" 
  bottom: "conv3_1"        top: "compress3b"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 } 
  convolution_param {
    num_output: 100   kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_compress3b"    type: "ReLU"
  bottom: "compress3b"       top: "compress3b"
}
layer {
  name: "conv3_2"        type: "Convolution"
  bottom: "compress3b"   top: "conv3_2"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 300    kernel_size: 3   pad: 1
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}
layer {
  name: "relu3_2"    type: "ReLU"
  bottom: "conv3_2"  top: "conv3_2"
}

#-----------------------------drop3_2---------------------------------
# layer {
  # name: "drop3_2"     type: "Dropout"  
  # bottom: "conv3_2"   top: "conv3_2"
  # dropout_param { dropout_ratio: 0.3 }
# }

#-----------------------------Pooling3-------------------------------
layer {
  name: "pool3"      type: "Pooling"
  bottom: "conv3_2"  top: "pool3"
  pooling_param {  pool: MAX   kernel_size: 2   stride: 2 }
}

#-----------------------------Conv4_1----------------------------------
layer {
  name: "compress4a"       type: "Convolution" 
  bottom: "pool3"          top: "compress4a"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 } 
  convolution_param {
    num_output: 150   kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_compress4a"    type: "ReLU"
  bottom: "compress4a"       top: "compress4a"
}
layer {
  name: "conv4_1"         type: "Convolution"
  bottom: "compress4a"    top: "conv4_1"
  param { lr_mult: 1  decay_mult: 1 }
  param { lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 350   kernel_size: 3   pad: 1
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant" }
  }
}
layer {
  name: "relu4_1"    type: "ReLU"
  bottom: "conv4_1"  top: "conv4_1"
}

#-----------------------------drop4_1---------------------------------
# layer {
  # name: "drop4_1"     type: "Dropout"  
  # bottom: "conv4_1"   top: "conv4_1"
  # dropout_param { dropout_ratio: 0.3 }
# }

#-----------------------------Conv4_2----------------------------------
layer {
  name: "compress4b"       type: "Convolution" 
  bottom: "conv4_1"        top: "compress4b"
  param { lr_mult: 1     decay_mult: 1 }
  param { lr_mult: 1     decay_mult: 0 } 
  convolution_param {
    num_output: 150   kernel_size: 1
    weight_filler {  type: "xavier" }
	bias_filler { type: "constant"  }
  }
}
layer {
  name: "relu_compress4b"    type: "ReLU"
  bottom: "compress4b"       top: "compress4b"
}
layer {
  name: "conv4_2"        type: "Convolution"
  bottom: "compress4b"   top: "conv4_2"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 400    kernel_size: 3   pad: 1
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}
layer {
  name: "relu4_2"    type: "ReLU"
  bottom: "conv4_2"  top: "conv4_2"
}

#-----------------------------drop4_2---------------------------------
# layer {
  # name: "drop4_2"     type: "Dropout"  
  # bottom: "conv4_2"   top: "conv4_2"
  # dropout_param { dropout_ratio: 0.4 }
# }

#-----------------------------yao-------------------------------
#-----------------------------yao-------------------------------
#-----------------------------conv 4-------------------------------
layer {
  name: "conv0_Yao"        type: "Convolution"
  bottom: "conv4_2"   top: "conv0_Yao"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 196    kernel_size: 4   pad_w : 2
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}

#layer {
#  name: "dropYao_0"     type: "Dropout"  
#  bottom: "conv0_Yao"   top: "conv0_Yao"
#  dropout_param { dropout_ratio: 0.1 }
#}
layer {
  name: "relu_Yao_0"   type: "ReLU"
  bottom: "conv0_Yao"      top: "conv0_Yao"
}
#-----------------------------yao-------------------------------
#-----------------------------yao-------------------------------
#-----------------------------conv 1-------------------------------
layer {
  name: "conv_1_Yao"        type: "Convolution"
  bottom: "conv0_Yao"   top: "conv_1_Yao"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 128    kernel_size: 1   pad: 0
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}

#layer {
#  name: "dropYao_1"     type: "Dropout"  
#  bottom: "conv_1_Yao"   top: "conv_1_Yao"
#  dropout_param { dropout_ratio: 0.1 }
#}
layer {
  name: "relu_Yao_1"   type: "ReLU"
  bottom: "conv_1_Yao"      top: "conv_1_Yao"
}

#-----------------------------yao-------------------------------
#-----------------------------yao-------------------------------
#-----------------------------conv 1-------------------------------
layer {
  name: "conv_end_yao_jk_1"        type: "Convolution"
  bottom: "conv_1_Yao"   top: "conv_end_yao_jk_1"
  param {  lr_mult: 1  decay_mult: 1 }
  param {  lr_mult: 1  decay_mult: 0 }
  convolution_param {
    num_output: 2571    kernel_size: 1   pad: 0
    weight_filler {  type: "xavier"  }
    bias_filler {  type: "constant"  }
  }
}