name:"Gender Net"

layer {
	name: 'data'
	type: 'Input'
	top: 'data'
	input_param { shape {dim: 1 dim: 3 dim: 112 dim: 112}}
}

layer {
  name: "conv_pre"
  type: "Convolution"
  bottom: "data"
  top: "conv_pre"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      # std: 0.07142857142857142
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm1"
  type: "BatchNorm"
  bottom: "conv_pre"
  top: "BatchNorm1"
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale1"
  type: "Scale"
  bottom: "BatchNorm1"
  top: "Scale1"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu_pre"
  type: "ReLU"
  bottom: "Scale1"
  top: "relu_pre"
}

layer {
  name: "conv1_1"
  type: "Convolution"
  bottom: "relu_pre"
  top: "conv1_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm2"
  type: "BatchNorm"
  bottom: "conv1_1"
  top: "BatchNorm2"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale2"
  type: "Scale"
  bottom: "BatchNorm2"
  top: "Scale2"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu1_1"
  type: "ReLU"
  bottom: "Scale2"
  top: "relu1_1"
}

layer {
  name: "conv1_2"
  type: "Convolution"
  bottom: "relu1_1"
  top: "conv1_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm3"
  type: "BatchNorm"
  bottom: "conv1_2"
  top: "BatchNorm3"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale3"
  type: "Scale"
  bottom: "BatchNorm3"
  top: "Scale3"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu1_2"
  type: "ReLU"
  bottom: "Scale3"
  top: "relu1_2"
}

layer {
  name: "conv1_p"
  type: "Convolution"
  bottom: "relu_pre"
  top: "conv1_p"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm1_p"
  type: "BatchNorm"
  bottom: "conv1_p"
  top: "BatchNorm1_p"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale1_p"
  type: "Scale"
  bottom: "BatchNorm1_p"
  top: "Scale1_p"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu1_p"
  type: "ReLU"
  bottom: "Scale1_p"
  top: "relu1_p"
}


layer 
{
  name: "res_1"
  type: "Eltwise"
  bottom: "relu1_2"
  bottom: "relu1_p"
  top: "res_1"
  eltwise_param {
    operation: SUM
    coeff: 1
    coeff: 1
  }
}

layer {
  name: "convf_1"
  type: "Convolution"
  bottom: "res_1"
  top: "convf_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNormf2"
  type: "BatchNorm"
  bottom: "convf_1"
  top: "BatchNormf2"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scalef2"
  type: "Scale"
  bottom: "BatchNormf2"
  top: "Scalef2"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "reluf_1"
  type: "ReLU"
  bottom: "Scalef2"
  top: "reluf_1"
}

layer {
  name: "convf_2"
  type: "Convolution"
  bottom: "reluf_1"
  top: "convf_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNormf3"
  type: "BatchNorm"
  bottom: "convf_2"
  top: "BatchNormf3"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scalef3"
  type: "Scale"
  bottom: "BatchNormf3"
  top: "Scalef3"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "reluf_2"
  type: "ReLU"
  bottom: "Scalef3"
  top: "reluf_2"
}

layer 
{
  name: "resf_1"
  type: "Eltwise"
  bottom: "reluf_2"
  bottom: "res_1"
  top: "resf_1"
  eltwise_param {
    operation: SUM
    coeff: 1
    coeff: 1
  }
}

layer {
  name: "conv2_1"
  type: "Convolution"
  bottom: "resf_1"
  top: "conv2_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm4"
  type: "BatchNorm"
  bottom: "conv2_1"
  top: "BatchNorm4"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale4"
  type: "Scale"
  bottom: "BatchNorm4"
  top: "Scale4"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu2_1"
  type: "ReLU"
  bottom: "Scale4"
  top: "relu2_1"
}

layer {
  name: "conv2_2"
  type: "Convolution"
  bottom: "relu2_1"
  top: "conv2_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm5"
  type: "BatchNorm"
  bottom: "conv2_2"
  top: "BatchNorm5"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale5"
  type: "Scale"
  bottom: "BatchNorm5"
  top: "Scale5"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu2_2"
  type: "ReLU"
  bottom: "Scale5"
  top: "relu2_2"
}

layer {
  name: "conv2_p"
  type: "Convolution"
  bottom: "resf_1"
  top: "conv2_p"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 24
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm2_p"
  type: "BatchNorm"
  bottom: "conv2_p"
  top: "BatchNorm2_p"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale2_p"
  type: "Scale"
  bottom: "BatchNorm2_p"
  top: "Scale2_p"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu2_p"
  type: "ReLU"
  bottom: "Scale2_p"
  top: "relu2_p"
}

layer 
{
  name: "res_2"
  type: "Eltwise"
  bottom: "relu2_p"
  bottom: "relu2_2"
  top: "res_2"
  eltwise_param {
    operation: SUM
    coeff: 1
    coeff: 1
  }
}

layer {
  name: "convf_3"
  type: "Convolution"
  bottom: "res_2"
  top: "convf_3"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNormf4"
  type: "BatchNorm"
  bottom: "convf_3"
  top: "BatchNormf4"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scalef4"
  type: "Scale"
  bottom: "BatchNormf4"
  top: "Scalef4"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "reluf_3"
  type: "ReLU"
  bottom: "Scalef4"
  top: "reluf_3"
}

layer {
  name: "convf_4"
  type: "Convolution"
  bottom: "reluf_3"
  top: "convf_4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.11785113019775792
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNormf5"
  type: "BatchNorm"
  bottom: "convf_4"
  top: "BatchNormf5"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scalef5"
  type: "Scale"
  bottom: "BatchNormf5"
  top: "Scalef5"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "reluf_4"
  type: "ReLU"
  bottom: "Scalef5"
  top: "reluf_4"
}

layer 
{
  name: "resf_2"
  type: "Eltwise"
  bottom: "reluf_4"
  bottom: "res_2"
  top: "resf_2"
  eltwise_param {
    operation: SUM
    coeff: 1
    coeff: 1
  }
}

layer {
  name: "conv3_1"
  type: "Convolution"
  bottom: "resf_2"
  top: "conv3_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.08333333333333333
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm6"
  type: "BatchNorm"
  bottom: "conv3_1"
  top: "BatchNorm6"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale6"
  type: "Scale"
  bottom: "BatchNorm6"
  top: "Scale6"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu3_1"
  type: "ReLU"
  bottom: "Scale6"
  top: "relu3_1"
}
layer {
  name: "conv3_2"
  type: "Convolution"
  bottom: "relu3_1"
  top: "conv3_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 40
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.08333333333333333
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm7"
  type: "BatchNorm"
  bottom: "conv3_2"
  top: "BatchNorm7"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale7"
  type: "Scale"
  bottom: "BatchNorm7"
  top: "Scale7"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu3_2"
  type: "ReLU"
  bottom: "Scale7"
  top: "relu3_2"
}

layer {
  name: "conv3_p"
  type: "Convolution"
  bottom: "resf_2"
  top: "conv3_p"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 40
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm3_p"
  type: "BatchNorm"
  bottom: "conv3_p"
  top: "BatchNorm3_p"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale3_p"
  type: "Scale"
  bottom: "BatchNorm3_p"
  top: "Scale3_p"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu3_p"
  type: "ReLU"
  bottom: "Scale3_p"
  top: "relu3_p"
}

layer 
{
  name: "res_3"
  type: "Eltwise"
  bottom: "relu3_p"
  bottom: "relu3_2"
  top: "res_3"
  eltwise_param {
    operation: SUM
    coeff: 1
    coeff: 1
  }
}

layer {
  name: "conv4_1"
  type: "Convolution"
  bottom: "res_3"
  top: "conv4_1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 80
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.08333333333333333
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm8"
  type: "BatchNorm"
  bottom: "conv4_1"
  top: "BatchNorm8"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale8"
  type: "Scale"
  bottom: "BatchNorm8"
  top: "Scale8"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu4_1"
  type: "ReLU"
  bottom: "Scale8"
  top: "relu4_1"
}
layer {
  name: "conv4_2"
  type: "Convolution"
  bottom: "relu4_1"
  top: "conv4_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
      #std: 0.08333333333333333
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm9"
  type: "BatchNorm"
  bottom: "conv4_2"
  top: "BatchNorm9"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale9"
  type: "Scale"
  bottom: "BatchNorm9"
  top: "Scale9"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu4_2"
  type: "ReLU"
  bottom: "Scale9"
  top: "relu4_2"
}


layer {
  name: "conv4_p"
  type: "Convolution"
  bottom: "res_3"
  top: "conv4_p"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.09622504486493763
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm4_p"
  type: "BatchNorm"
  bottom: "conv4_p"
  top: "BatchNorm4_p"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}

layer {
  name: "Scale4_p"
  type: "Scale"
  bottom: "BatchNorm4_p"
  top: "Scale4_p"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu4_p"
  type: "ReLU"
  bottom: "Scale4_p"
  top: "relu4_p"
}

layer 
{
  name: "res_4"
  type: "Eltwise"
  bottom: "relu4_p"
  bottom: "relu4_2"
  top: "res_4"
  eltwise_param {
    operation: SUM
    coeff: 1
    coeff: 1
  }
}

layer {
  name: "ip1"
  type: "InnerProduct"
  bottom: "res_4"
  top: "ip1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 64
    weight_filler {
      type: "xavier"
      #std: 0.001
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm10"
  type: "BatchNorm"
  bottom: "ip1"
  top: "ip1"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale10"
  type: "Scale"
  bottom: "ip1"
  top: "ip1"
  scale_param {
    bias_term: true
  }
}

layer {
  name: "relu_ip1"
  type: "ReLU"
  bottom: "ip1"
  top: "ip1"
}

layer {
  name: "ip2"
  type: "InnerProduct"
  bottom: "ip1"
  top: "ip2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 64
    weight_filler {
      type: "xavier"
      #std: 0.001
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "BatchNorm11"
  type: "BatchNorm"
  bottom: "ip2"
  top: "ip2"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  batch_norm_param {
		use_global_stats: true
	}
  include: { phase: TEST}
}
layer {
  name: "Scale11"
  type: "Scale"
  bottom: "ip2"
  top: "ip2"
  scale_param {
    bias_term: true
  }
}


layer {
  name: "relu_ip2"
  type: "ReLU"
  bottom: "ip2"
  top: "ip2"
}

layer {
  name: "fc3_8W_PosAug"
  type: "InnerProduct"
  bottom: "ip2"
  top: "fc3_8W_PosAug"
  param {
        lr_mult: 1
        decay_mult: 1
  }
  param {
        lr_mult: 2
        decay_mult: 1
  }
  inner_product_param {
    num_output: 2
  }
}