train_agnostic_ohem.prototxt

name: "ResNet-101"
layer {
  name: 'input-data'
  type: 'Python'
  top: 'data'
  top: 'im_info'
  top: 'gt_boxes'
  python_param {
    module: 'roi_data_layer.layer'
    layer: 'RoIDataLayer'
    param_str: "'num_classes': 21"
  }
}

# ------------------------ conv1 -----------------------------
layer {
    bottom: "data"
    top: "conv1"
    name: "conv1"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 7
        pad: 3
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "conv1"
    top: "conv1"
    name: "bn_conv1"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "conv1"
    top: "conv1"
    name: "scale_conv1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "conv1"
    bottom: "conv1"
    name: "conv1_relu"
    type: "ReLU"
}

layer {
    bottom: "conv1"
    top: "pool1"
    name: "pool1"
    type: "Pooling"
    pooling_param {
        kernel_size: 3
        stride: 2
        pool: MAX
    }
}

layer {
    bottom: "pool1"
    top: "res2a_branch1"
    name: "res2a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "bn2a_branch1"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "scale2a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "pool1"
    top: "res2a_branch2a"
    name: "res2a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "bn2a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "scale2a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res2a_branch2a"
    bottom: "res2a_branch2a"
    name: "res2a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2b"
    name: "res2a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "bn2a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "scale2a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res2a_branch2b"
    bottom: "res2a_branch2b"
    name: "res2a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2c"
    name: "res2a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2c"
    top: "res2a_branch2c"
    name: "bn2a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2c"
    top: "res2a_branch2c"
    name: "scale2a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch1"
    bottom: "res2a_branch2c"
    top: "res2a"
    name: "res2a"
    type: "Eltwise"
}

layer {
    bottom: "res2a"
    top: "res2a"
    name: "res2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2a"
    top: "res2b_branch2a"
    name: "res2b_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "bn2b_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "scale2b_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res2b_branch2a"
    bottom: "res2b_branch2a"
    name: "res2b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2b"
    name: "res2b_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "bn2b_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "scale2b_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res2b_branch2b"
    bottom: "res2b_branch2b"
    name: "res2b_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2c"
    name: "res2b_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2c"
    top: "res2b_branch2c"
    name: "bn2b_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2c"
    top: "res2b_branch2c"
    name: "scale2b_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a"
    bottom: "res2b_branch2c"
    top: "res2b"
    name: "res2b"
    type: "Eltwise"
}

layer {
    bottom: "res2b"
    top: "res2b"
    name: "res2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b"
    top: "res2c_branch2a"
    name: "res2c_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "bn2c_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "scale2c_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res2c_branch2a"
    bottom: "res2c_branch2a"
    name: "res2c_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2b"
    name: "res2c_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "bn2c_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "scale2c_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res2c_branch2b"
    bottom: "res2c_branch2b"
    name: "res2c_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2c"
    name: "res2c_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2c"
    top: "res2c_branch2c"
    name: "bn2c_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2c"
    top: "res2c_branch2c"
    name: "scale2c_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b"
    bottom: "res2c_branch2c"
    top: "res2c"
    name: "res2c"
    type: "Eltwise"
}

layer {
    bottom: "res2c"
    top: "res2c"
    name: "res2c_relu"
    type: "ReLU"
}

layer {
    bottom: "res2c"
    top: "res3a_branch1"
    name: "res3a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "bn3a_branch1"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "scale3a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c"
    top: "res3a_branch2a"
    name: "res3a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "bn3a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "scale3a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3a_branch2a"
    bottom: "res3a_branch2a"
    name: "res3a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2b"
    name: "res3a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "bn3a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "scale3a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3a_branch2b"
    bottom: "res3a_branch2b"
    name: "res3a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2c"
    name: "res3a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch2c"
    top: "res3a_branch2c"
    name: "bn3a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch2c"
    top: "res3a_branch2c"
    name: "scale3a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch1"
    bottom: "res3a_branch2c"
    top: "res3a"
    name: "res3a"
    type: "Eltwise"
}

layer {
    bottom: "res3a"
    top: "res3a"
    name: "res3a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a"
    top: "res3b1_branch2a"
    name: "res3b1_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b1_branch2a"
    top: "res3b1_branch2a"
    name: "bn3b1_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b1_branch2a"
    top: "res3b1_branch2a"
    name: "scale3b1_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3b1_branch2a"
    bottom: "res3b1_branch2a"
    name: "res3b1_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b1_branch2a"
    top: "res3b1_branch2b"
    name: "res3b1_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b1_branch2b"
    top: "res3b1_branch2b"
    name: "bn3b1_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b1_branch2b"
    top: "res3b1_branch2b"
    name: "scale3b1_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3b1_branch2b"
    bottom: "res3b1_branch2b"
    name: "res3b1_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b1_branch2b"
    top: "res3b1_branch2c"
    name: "res3b1_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b1_branch2c"
    top: "res3b1_branch2c"
    name: "bn3b1_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b1_branch2c"
    top: "res3b1_branch2c"
    name: "scale3b1_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a"
    bottom: "res3b1_branch2c"
    top: "res3b1"
    name: "res3b1"
    type: "Eltwise"
}

layer {
    bottom: "res3b1"
    top: "res3b1"
    name: "res3b1_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b1"
    top: "res3b2_branch2a"
    name: "res3b2_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b2_branch2a"
    top: "res3b2_branch2a"
    name: "bn3b2_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b2_branch2a"
    top: "res3b2_branch2a"
    name: "scale3b2_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3b2_branch2a"
    bottom: "res3b2_branch2a"
    name: "res3b2_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b2_branch2a"
    top: "res3b2_branch2b"
    name: "res3b2_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b2_branch2b"
    top: "res3b2_branch2b"
    name: "bn3b2_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b2_branch2b"
    top: "res3b2_branch2b"
    name: "scale3b2_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3b2_branch2b"
    bottom: "res3b2_branch2b"
    name: "res3b2_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b2_branch2b"
    top: "res3b2_branch2c"
    name: "res3b2_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b2_branch2c"
    top: "res3b2_branch2c"
    name: "bn3b2_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b2_branch2c"
    top: "res3b2_branch2c"
    name: "scale3b2_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b1"
    bottom: "res3b2_branch2c"
    top: "res3b2"
    name: "res3b2"
    type: "Eltwise"
}

layer {
    bottom: "res3b2"
    top: "res3b2"
    name: "res3b2_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b2"
    top: "res3b3_branch2a"
    name: "res3b3_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b3_branch2a"
    top: "res3b3_branch2a"
    name: "bn3b3_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b3_branch2a"
    top: "res3b3_branch2a"
    name: "scale3b3_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3b3_branch2a"
    bottom: "res3b3_branch2a"
    name: "res3b3_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b3_branch2a"
    top: "res3b3_branch2b"
    name: "res3b3_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b3_branch2b"
    top: "res3b3_branch2b"
    name: "bn3b3_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b3_branch2b"
    top: "res3b3_branch2b"
    name: "scale3b3_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res3b3_branch2b"
    bottom: "res3b3_branch2b"
    name: "res3b3_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b3_branch2b"
    top: "res3b3_branch2c"
    name: "res3b3_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b3_branch2c"
    top: "res3b3_branch2c"
    name: "bn3b3_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b3_branch2c"
    top: "res3b3_branch2c"
    name: "scale3b3_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b2"
    bottom: "res3b3_branch2c"
    top: "res3b3"
    name: "res3b3"
    type: "Eltwise"
}

layer {
    bottom: "res3b3"
    top: "res3b3"
    name: "res3b3_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b3"
    top: "res4a_branch1"
    name: "res4a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch1"
    top: "res4a_branch1"
    name: "bn4a_branch1"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch1"
    top: "res4a_branch1"
    name: "scale4a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b3"
    top: "res4a_branch2a"
    name: "res4a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "bn4a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "scale4a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4a_branch2a"
    bottom: "res4a_branch2a"
    name: "res4a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2b"
    name: "res4a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "bn4a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "scale4a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4a_branch2b"
    bottom: "res4a_branch2b"
    name: "res4a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2c"
    name: "res4a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch2c"
    top: "res4a_branch2c"
    name: "bn4a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch2c"
    top: "res4a_branch2c"
    name: "scale4a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch1"
    bottom: "res4a_branch2c"
    top: "res4a"
    name: "res4a"
    type: "Eltwise"
}

layer {
    bottom: "res4a"
    top: "res4a"
    name: "res4a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4a"
    top: "res4b1_branch2a"
    name: "res4b1_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b1_branch2a"
    top: "res4b1_branch2a"
    name: "bn4b1_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b1_branch2a"
    top: "res4b1_branch2a"
    name: "scale4b1_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b1_branch2a"
    bottom: "res4b1_branch2a"
    name: "res4b1_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b1_branch2a"
    top: "res4b1_branch2b"
    name: "res4b1_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b1_branch2b"
    top: "res4b1_branch2b"
    name: "bn4b1_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b1_branch2b"
    top: "res4b1_branch2b"
    name: "scale4b1_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b1_branch2b"
    bottom: "res4b1_branch2b"
    name: "res4b1_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b1_branch2b"
    top: "res4b1_branch2c"
    name: "res4b1_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b1_branch2c"
    top: "res4b1_branch2c"
    name: "bn4b1_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b1_branch2c"
    top: "res4b1_branch2c"
    name: "scale4b1_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a"
    bottom: "res4b1_branch2c"
    top: "res4b1"
    name: "res4b1"
    type: "Eltwise"
}

layer {
    bottom: "res4b1"
    top: "res4b1"
    name: "res4b1_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b1"
    top: "res4b2_branch2a"
    name: "res4b2_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b2_branch2a"
    top: "res4b2_branch2a"
    name: "bn4b2_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b2_branch2a"
    top: "res4b2_branch2a"
    name: "scale4b2_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b2_branch2a"
    bottom: "res4b2_branch2a"
    name: "res4b2_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b2_branch2a"
    top: "res4b2_branch2b"
    name: "res4b2_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b2_branch2b"
    top: "res4b2_branch2b"
    name: "bn4b2_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b2_branch2b"
    top: "res4b2_branch2b"
    name: "scale4b2_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b2_branch2b"
    bottom: "res4b2_branch2b"
    name: "res4b2_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b2_branch2b"
    top: "res4b2_branch2c"
    name: "res4b2_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b2_branch2c"
    top: "res4b2_branch2c"
    name: "bn4b2_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b2_branch2c"
    top: "res4b2_branch2c"
    name: "scale4b2_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b1"
    bottom: "res4b2_branch2c"
    top: "res4b2"
    name: "res4b2"
    type: "Eltwise"
}

layer {
    bottom: "res4b2"
    top: "res4b2"
    name: "res4b2_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b2"
    top: "res4b3_branch2a"
    name: "res4b3_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b3_branch2a"
    top: "res4b3_branch2a"
    name: "bn4b3_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b3_branch2a"
    top: "res4b3_branch2a"
    name: "scale4b3_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b3_branch2a"
    bottom: "res4b3_branch2a"
    name: "res4b3_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b3_branch2a"
    top: "res4b3_branch2b"
    name: "res4b3_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b3_branch2b"
    top: "res4b3_branch2b"
    name: "bn4b3_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b3_branch2b"
    top: "res4b3_branch2b"
    name: "scale4b3_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b3_branch2b"
    bottom: "res4b3_branch2b"
    name: "res4b3_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b3_branch2b"
    top: "res4b3_branch2c"
    name: "res4b3_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b3_branch2c"
    top: "res4b3_branch2c"
    name: "bn4b3_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b3_branch2c"
    top: "res4b3_branch2c"
    name: "scale4b3_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b2"
    bottom: "res4b3_branch2c"
    top: "res4b3"
    name: "res4b3"
    type: "Eltwise"
}

layer {
    bottom: "res4b3"
    top: "res4b3"
    name: "res4b3_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b3"
    top: "res4b4_branch2a"
    name: "res4b4_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b4_branch2a"
    top: "res4b4_branch2a"
    name: "bn4b4_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b4_branch2a"
    top: "res4b4_branch2a"
    name: "scale4b4_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b4_branch2a"
    bottom: "res4b4_branch2a"
    name: "res4b4_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b4_branch2a"
    top: "res4b4_branch2b"
    name: "res4b4_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b4_branch2b"
    top: "res4b4_branch2b"
    name: "bn4b4_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b4_branch2b"
    top: "res4b4_branch2b"
    name: "scale4b4_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b4_branch2b"
    bottom: "res4b4_branch2b"
    name: "res4b4_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b4_branch2b"
    top: "res4b4_branch2c"
    name: "res4b4_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b4_branch2c"
    top: "res4b4_branch2c"
    name: "bn4b4_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b4_branch2c"
    top: "res4b4_branch2c"
    name: "scale4b4_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b3"
    bottom: "res4b4_branch2c"
    top: "res4b4"
    name: "res4b4"
    type: "Eltwise"
}

layer {
    bottom: "res4b4"
    top: "res4b4"
    name: "res4b4_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b4"
    top: "res4b5_branch2a"
    name: "res4b5_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b5_branch2a"
    top: "res4b5_branch2a"
    name: "bn4b5_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b5_branch2a"
    top: "res4b5_branch2a"
    name: "scale4b5_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b5_branch2a"
    bottom: "res4b5_branch2a"
    name: "res4b5_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b5_branch2a"
    top: "res4b5_branch2b"
    name: "res4b5_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b5_branch2b"
    top: "res4b5_branch2b"
    name: "bn4b5_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b5_branch2b"
    top: "res4b5_branch2b"
    name: "scale4b5_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b5_branch2b"
    bottom: "res4b5_branch2b"
    name: "res4b5_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b5_branch2b"
    top: "res4b5_branch2c"
    name: "res4b5_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b5_branch2c"
    top: "res4b5_branch2c"
    name: "bn4b5_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b5_branch2c"
    top: "res4b5_branch2c"
    name: "scale4b5_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b4"
    bottom: "res4b5_branch2c"
    top: "res4b5"
    name: "res4b5"
    type: "Eltwise"
}

layer {
    bottom: "res4b5"
    top: "res4b5"
    name: "res4b5_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b5"
    top: "res4b6_branch2a"
    name: "res4b6_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b6_branch2a"
    top: "res4b6_branch2a"
    name: "bn4b6_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b6_branch2a"
    top: "res4b6_branch2a"
    name: "scale4b6_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b6_branch2a"
    bottom: "res4b6_branch2a"
    name: "res4b6_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b6_branch2a"
    top: "res4b6_branch2b"
    name: "res4b6_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b6_branch2b"
    top: "res4b6_branch2b"
    name: "bn4b6_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b6_branch2b"
    top: "res4b6_branch2b"
    name: "scale4b6_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b6_branch2b"
    bottom: "res4b6_branch2b"
    name: "res4b6_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b6_branch2b"
    top: "res4b6_branch2c"
    name: "res4b6_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b6_branch2c"
    top: "res4b6_branch2c"
    name: "bn4b6_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b6_branch2c"
    top: "res4b6_branch2c"
    name: "scale4b6_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b5"
    bottom: "res4b6_branch2c"
    top: "res4b6"
    name: "res4b6"
    type: "Eltwise"
}

layer {
    bottom: "res4b6"
    top: "res4b6"
    name: "res4b6_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b6"
    top: "res4b7_branch2a"
    name: "res4b7_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b7_branch2a"
    top: "res4b7_branch2a"
    name: "bn4b7_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b7_branch2a"
    top: "res4b7_branch2a"
    name: "scale4b7_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b7_branch2a"
    bottom: "res4b7_branch2a"
    name: "res4b7_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b7_branch2a"
    top: "res4b7_branch2b"
    name: "res4b7_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b7_branch2b"
    top: "res4b7_branch2b"
    name: "bn4b7_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b7_branch2b"
    top: "res4b7_branch2b"
    name: "scale4b7_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b7_branch2b"
    bottom: "res4b7_branch2b"
    name: "res4b7_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b7_branch2b"
    top: "res4b7_branch2c"
    name: "res4b7_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b7_branch2c"
    top: "res4b7_branch2c"
    name: "bn4b7_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b7_branch2c"
    top: "res4b7_branch2c"
    name: "scale4b7_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b6"
    bottom: "res4b7_branch2c"
    top: "res4b7"
    name: "res4b7"
    type: "Eltwise"
}

layer {
    bottom: "res4b7"
    top: "res4b7"
    name: "res4b7_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b7"
    top: "res4b8_branch2a"
    name: "res4b8_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b8_branch2a"
    top: "res4b8_branch2a"
    name: "bn4b8_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b8_branch2a"
    top: "res4b8_branch2a"
    name: "scale4b8_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b8_branch2a"
    bottom: "res4b8_branch2a"
    name: "res4b8_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b8_branch2a"
    top: "res4b8_branch2b"
    name: "res4b8_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b8_branch2b"
    top: "res4b8_branch2b"
    name: "bn4b8_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b8_branch2b"
    top: "res4b8_branch2b"
    name: "scale4b8_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b8_branch2b"
    bottom: "res4b8_branch2b"
    name: "res4b8_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b8_branch2b"
    top: "res4b8_branch2c"
    name: "res4b8_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b8_branch2c"
    top: "res4b8_branch2c"
    name: "bn4b8_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b8_branch2c"
    top: "res4b8_branch2c"
    name: "scale4b8_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b7"
    bottom: "res4b8_branch2c"
    top: "res4b8"
    name: "res4b8"
    type: "Eltwise"
}

layer {
    bottom: "res4b8"
    top: "res4b8"
    name: "res4b8_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b8"
    top: "res4b9_branch2a"
    name: "res4b9_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b9_branch2a"
    top: "res4b9_branch2a"
    name: "bn4b9_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b9_branch2a"
    top: "res4b9_branch2a"
    name: "scale4b9_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b9_branch2a"
    bottom: "res4b9_branch2a"
    name: "res4b9_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b9_branch2a"
    top: "res4b9_branch2b"
    name: "res4b9_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b9_branch2b"
    top: "res4b9_branch2b"
    name: "bn4b9_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b9_branch2b"
    top: "res4b9_branch2b"
    name: "scale4b9_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b9_branch2b"
    bottom: "res4b9_branch2b"
    name: "res4b9_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b9_branch2b"
    top: "res4b9_branch2c"
    name: "res4b9_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b9_branch2c"
    top: "res4b9_branch2c"
    name: "bn4b9_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b9_branch2c"
    top: "res4b9_branch2c"
    name: "scale4b9_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b8"
    bottom: "res4b9_branch2c"
    top: "res4b9"
    name: "res4b9"
    type: "Eltwise"
}

layer {
    bottom: "res4b9"
    top: "res4b9"
    name: "res4b9_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b9"
    top: "res4b10_branch2a"
    name: "res4b10_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b10_branch2a"
    top: "res4b10_branch2a"
    name: "bn4b10_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b10_branch2a"
    top: "res4b10_branch2a"
    name: "scale4b10_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b10_branch2a"
    bottom: "res4b10_branch2a"
    name: "res4b10_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b10_branch2a"
    top: "res4b10_branch2b"
    name: "res4b10_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b10_branch2b"
    top: "res4b10_branch2b"
    name: "bn4b10_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b10_branch2b"
    top: "res4b10_branch2b"
    name: "scale4b10_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b10_branch2b"
    bottom: "res4b10_branch2b"
    name: "res4b10_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b10_branch2b"
    top: "res4b10_branch2c"
    name: "res4b10_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b10_branch2c"
    top: "res4b10_branch2c"
    name: "bn4b10_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b10_branch2c"
    top: "res4b10_branch2c"
    name: "scale4b10_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b9"
    bottom: "res4b10_branch2c"
    top: "res4b10"
    name: "res4b10"
    type: "Eltwise"
}

layer {
    bottom: "res4b10"
    top: "res4b10"
    name: "res4b10_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b10"
    top: "res4b11_branch2a"
    name: "res4b11_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b11_branch2a"
    top: "res4b11_branch2a"
    name: "bn4b11_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b11_branch2a"
    top: "res4b11_branch2a"
    name: "scale4b11_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b11_branch2a"
    bottom: "res4b11_branch2a"
    name: "res4b11_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b11_branch2a"
    top: "res4b11_branch2b"
    name: "res4b11_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b11_branch2b"
    top: "res4b11_branch2b"
    name: "bn4b11_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b11_branch2b"
    top: "res4b11_branch2b"
    name: "scale4b11_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b11_branch2b"
    bottom: "res4b11_branch2b"
    name: "res4b11_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b11_branch2b"
    top: "res4b11_branch2c"
    name: "res4b11_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b11_branch2c"
    top: "res4b11_branch2c"
    name: "bn4b11_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b11_branch2c"
    top: "res4b11_branch2c"
    name: "scale4b11_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b10"
    bottom: "res4b11_branch2c"
    top: "res4b11"
    name: "res4b11"
    type: "Eltwise"
}

layer {
    bottom: "res4b11"
    top: "res4b11"
    name: "res4b11_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b11"
    top: "res4b12_branch2a"
    name: "res4b12_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b12_branch2a"
    top: "res4b12_branch2a"
    name: "bn4b12_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b12_branch2a"
    top: "res4b12_branch2a"
    name: "scale4b12_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b12_branch2a"
    bottom: "res4b12_branch2a"
    name: "res4b12_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b12_branch2a"
    top: "res4b12_branch2b"
    name: "res4b12_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b12_branch2b"
    top: "res4b12_branch2b"
    name: "bn4b12_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b12_branch2b"
    top: "res4b12_branch2b"
    name: "scale4b12_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b12_branch2b"
    bottom: "res4b12_branch2b"
    name: "res4b12_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b12_branch2b"
    top: "res4b12_branch2c"
    name: "res4b12_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b12_branch2c"
    top: "res4b12_branch2c"
    name: "bn4b12_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b12_branch2c"
    top: "res4b12_branch2c"
    name: "scale4b12_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b11"
    bottom: "res4b12_branch2c"
    top: "res4b12"
    name: "res4b12"
    type: "Eltwise"
}

layer {
    bottom: "res4b12"
    top: "res4b12"
    name: "res4b12_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b12"
    top: "res4b13_branch2a"
    name: "res4b13_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b13_branch2a"
    top: "res4b13_branch2a"
    name: "bn4b13_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b13_branch2a"
    top: "res4b13_branch2a"
    name: "scale4b13_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b13_branch2a"
    bottom: "res4b13_branch2a"
    name: "res4b13_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b13_branch2a"
    top: "res4b13_branch2b"
    name: "res4b13_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b13_branch2b"
    top: "res4b13_branch2b"
    name: "bn4b13_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b13_branch2b"
    top: "res4b13_branch2b"
    name: "scale4b13_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b13_branch2b"
    bottom: "res4b13_branch2b"
    name: "res4b13_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b13_branch2b"
    top: "res4b13_branch2c"
    name: "res4b13_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b13_branch2c"
    top: "res4b13_branch2c"
    name: "bn4b13_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b13_branch2c"
    top: "res4b13_branch2c"
    name: "scale4b13_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b12"
    bottom: "res4b13_branch2c"
    top: "res4b13"
    name: "res4b13"
    type: "Eltwise"
}

layer {
    bottom: "res4b13"
    top: "res4b13"
    name: "res4b13_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b13"
    top: "res4b14_branch2a"
    name: "res4b14_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b14_branch2a"
    top: "res4b14_branch2a"
    name: "bn4b14_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b14_branch2a"
    top: "res4b14_branch2a"
    name: "scale4b14_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b14_branch2a"
    bottom: "res4b14_branch2a"
    name: "res4b14_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b14_branch2a"
    top: "res4b14_branch2b"
    name: "res4b14_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b14_branch2b"
    top: "res4b14_branch2b"
    name: "bn4b14_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b14_branch2b"
    top: "res4b14_branch2b"
    name: "scale4b14_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b14_branch2b"
    bottom: "res4b14_branch2b"
    name: "res4b14_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b14_branch2b"
    top: "res4b14_branch2c"
    name: "res4b14_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b14_branch2c"
    top: "res4b14_branch2c"
    name: "bn4b14_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b14_branch2c"
    top: "res4b14_branch2c"
    name: "scale4b14_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b13"
    bottom: "res4b14_branch2c"
    top: "res4b14"
    name: "res4b14"
    type: "Eltwise"
}

layer {
    bottom: "res4b14"
    top: "res4b14"
    name: "res4b14_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b14"
    top: "res4b15_branch2a"
    name: "res4b15_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b15_branch2a"
    top: "res4b15_branch2a"
    name: "bn4b15_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b15_branch2a"
    top: "res4b15_branch2a"
    name: "scale4b15_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b15_branch2a"
    bottom: "res4b15_branch2a"
    name: "res4b15_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b15_branch2a"
    top: "res4b15_branch2b"
    name: "res4b15_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b15_branch2b"
    top: "res4b15_branch2b"
    name: "bn4b15_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b15_branch2b"
    top: "res4b15_branch2b"
    name: "scale4b15_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b15_branch2b"
    bottom: "res4b15_branch2b"
    name: "res4b15_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b15_branch2b"
    top: "res4b15_branch2c"
    name: "res4b15_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b15_branch2c"
    top: "res4b15_branch2c"
    name: "bn4b15_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b15_branch2c"
    top: "res4b15_branch2c"
    name: "scale4b15_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b14"
    bottom: "res4b15_branch2c"
    top: "res4b15"
    name: "res4b15"
    type: "Eltwise"
}

layer {
    bottom: "res4b15"
    top: "res4b15"
    name: "res4b15_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b15"
    top: "res4b16_branch2a"
    name: "res4b16_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b16_branch2a"
    top: "res4b16_branch2a"
    name: "bn4b16_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b16_branch2a"
    top: "res4b16_branch2a"
    name: "scale4b16_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b16_branch2a"
    bottom: "res4b16_branch2a"
    name: "res4b16_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b16_branch2a"
    top: "res4b16_branch2b"
    name: "res4b16_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b16_branch2b"
    top: "res4b16_branch2b"
    name: "bn4b16_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b16_branch2b"
    top: "res4b16_branch2b"
    name: "scale4b16_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b16_branch2b"
    bottom: "res4b16_branch2b"
    name: "res4b16_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b16_branch2b"
    top: "res4b16_branch2c"
    name: "res4b16_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b16_branch2c"
    top: "res4b16_branch2c"
    name: "bn4b16_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b16_branch2c"
    top: "res4b16_branch2c"
    name: "scale4b16_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b15"
    bottom: "res4b16_branch2c"
    top: "res4b16"
    name: "res4b16"
    type: "Eltwise"
}

layer {
    bottom: "res4b16"
    top: "res4b16"
    name: "res4b16_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b16"
    top: "res4b17_branch2a"
    name: "res4b17_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b17_branch2a"
    top: "res4b17_branch2a"
    name: "bn4b17_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b17_branch2a"
    top: "res4b17_branch2a"
    name: "scale4b17_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b17_branch2a"
    bottom: "res4b17_branch2a"
    name: "res4b17_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b17_branch2a"
    top: "res4b17_branch2b"
    name: "res4b17_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b17_branch2b"
    top: "res4b17_branch2b"
    name: "bn4b17_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b17_branch2b"
    top: "res4b17_branch2b"
    name: "scale4b17_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b17_branch2b"
    bottom: "res4b17_branch2b"
    name: "res4b17_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b17_branch2b"
    top: "res4b17_branch2c"
    name: "res4b17_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b17_branch2c"
    top: "res4b17_branch2c"
    name: "bn4b17_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b17_branch2c"
    top: "res4b17_branch2c"
    name: "scale4b17_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b16"
    bottom: "res4b17_branch2c"
    top: "res4b17"
    name: "res4b17"
    type: "Eltwise"
}

layer {
    bottom: "res4b17"
    top: "res4b17"
    name: "res4b17_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b17"
    top: "res4b18_branch2a"
    name: "res4b18_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b18_branch2a"
    top: "res4b18_branch2a"
    name: "bn4b18_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b18_branch2a"
    top: "res4b18_branch2a"
    name: "scale4b18_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b18_branch2a"
    bottom: "res4b18_branch2a"
    name: "res4b18_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b18_branch2a"
    top: "res4b18_branch2b"
    name: "res4b18_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b18_branch2b"
    top: "res4b18_branch2b"
    name: "bn4b18_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b18_branch2b"
    top: "res4b18_branch2b"
    name: "scale4b18_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b18_branch2b"
    bottom: "res4b18_branch2b"
    name: "res4b18_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b18_branch2b"
    top: "res4b18_branch2c"
    name: "res4b18_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b18_branch2c"
    top: "res4b18_branch2c"
    name: "bn4b18_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b18_branch2c"
    top: "res4b18_branch2c"
    name: "scale4b18_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b17"
    bottom: "res4b18_branch2c"
    top: "res4b18"
    name: "res4b18"
    type: "Eltwise"
}

layer {
    bottom: "res4b18"
    top: "res4b18"
    name: "res4b18_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b18"
    top: "res4b19_branch2a"
    name: "res4b19_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b19_branch2a"
    top: "res4b19_branch2a"
    name: "bn4b19_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b19_branch2a"
    top: "res4b19_branch2a"
    name: "scale4b19_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b19_branch2a"
    bottom: "res4b19_branch2a"
    name: "res4b19_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b19_branch2a"
    top: "res4b19_branch2b"
    name: "res4b19_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b19_branch2b"
    top: "res4b19_branch2b"
    name: "bn4b19_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b19_branch2b"
    top: "res4b19_branch2b"
    name: "scale4b19_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b19_branch2b"
    bottom: "res4b19_branch2b"
    name: "res4b19_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b19_branch2b"
    top: "res4b19_branch2c"
    name: "res4b19_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b19_branch2c"
    top: "res4b19_branch2c"
    name: "bn4b19_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b19_branch2c"
    top: "res4b19_branch2c"
    name: "scale4b19_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b18"
    bottom: "res4b19_branch2c"
    top: "res4b19"
    name: "res4b19"
    type: "Eltwise"
}

layer {
    bottom: "res4b19"
    top: "res4b19"
    name: "res4b19_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b19"
    top: "res4b20_branch2a"
    name: "res4b20_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b20_branch2a"
    top: "res4b20_branch2a"
    name: "bn4b20_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b20_branch2a"
    top: "res4b20_branch2a"
    name: "scale4b20_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b20_branch2a"
    bottom: "res4b20_branch2a"
    name: "res4b20_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b20_branch2a"
    top: "res4b20_branch2b"
    name: "res4b20_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b20_branch2b"
    top: "res4b20_branch2b"
    name: "bn4b20_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b20_branch2b"
    top: "res4b20_branch2b"
    name: "scale4b20_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b20_branch2b"
    bottom: "res4b20_branch2b"
    name: "res4b20_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b20_branch2b"
    top: "res4b20_branch2c"
    name: "res4b20_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b20_branch2c"
    top: "res4b20_branch2c"
    name: "bn4b20_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b20_branch2c"
    top: "res4b20_branch2c"
    name: "scale4b20_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b19"
    bottom: "res4b20_branch2c"
    top: "res4b20"
    name: "res4b20"
    type: "Eltwise"
}

layer {
    bottom: "res4b20"
    top: "res4b20"
    name: "res4b20_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b20"
    top: "res4b21_branch2a"
    name: "res4b21_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b21_branch2a"
    top: "res4b21_branch2a"
    name: "bn4b21_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b21_branch2a"
    top: "res4b21_branch2a"
    name: "scale4b21_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b21_branch2a"
    bottom: "res4b21_branch2a"
    name: "res4b21_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b21_branch2a"
    top: "res4b21_branch2b"
    name: "res4b21_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b21_branch2b"
    top: "res4b21_branch2b"
    name: "bn4b21_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b21_branch2b"
    top: "res4b21_branch2b"
    name: "scale4b21_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b21_branch2b"
    bottom: "res4b21_branch2b"
    name: "res4b21_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b21_branch2b"
    top: "res4b21_branch2c"
    name: "res4b21_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b21_branch2c"
    top: "res4b21_branch2c"
    name: "bn4b21_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b21_branch2c"
    top: "res4b21_branch2c"
    name: "scale4b21_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b20"
    bottom: "res4b21_branch2c"
    top: "res4b21"
    name: "res4b21"
    type: "Eltwise"
}

layer {
    bottom: "res4b21"
    top: "res4b21"
    name: "res4b21_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b21"
    top: "res4b22_branch2a"
    name: "res4b22_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b22_branch2a"
    top: "res4b22_branch2a"
    name: "bn4b22_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b22_branch2a"
    top: "res4b22_branch2a"
    name: "scale4b22_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b22_branch2a"
    bottom: "res4b22_branch2a"
    name: "res4b22_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b22_branch2a"
    top: "res4b22_branch2b"
    name: "res4b22_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b22_branch2b"
    top: "res4b22_branch2b"
    name: "bn4b22_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b22_branch2b"
    top: "res4b22_branch2b"
    name: "scale4b22_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res4b22_branch2b"
    bottom: "res4b22_branch2b"
    name: "res4b22_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b22_branch2b"
    top: "res4b22_branch2c"
    name: "res4b22_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b22_branch2c"
    top: "res4b22_branch2c"
    name: "bn4b22_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b22_branch2c"
    top: "res4b22_branch2c"
    name: "scale4b22_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b21"
    bottom: "res4b22_branch2c"
    top: "res4b22"
    name: "res4b22"
    type: "Eltwise"
}

layer {
    bottom: "res4b22"
    top: "res4b22"
    name: "res4b22_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b22"
    top: "res5a_branch1"
    name: "res5a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch1"
    top: "res5a_branch1"
    name: "bn5a_branch1"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a_branch1"
    top: "res5a_branch1"
    name: "scale5a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b22"
    top: "res5a_branch2a"
    name: "res5a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2a"
    name: "bn5a_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2a"
    name: "scale5a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5a_branch2a"
    bottom: "res5a_branch2a"
    name: "res5a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2b"
    name: "res5a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        dilation: 2
        pad: 2
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2b"
    name: "bn5a_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2b"
    name: "scale5a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5a_branch2b"
    bottom: "res5a_branch2b"
    name: "res5a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2c"
    name: "res5a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch2c"
    top: "res5a_branch2c"
    name: "bn5a_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a_branch2c"
    top: "res5a_branch2c"
    name: "scale5a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a_branch1"
    bottom: "res5a_branch2c"
    top: "res5a"
    name: "res5a"
    type: "Eltwise"
}

layer {
    bottom: "res5a"
    top: "res5a"
    name: "res5a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5a"
    top: "res5b_branch2a"
    name: "res5b_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2a"
    name: "bn5b_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2a"
    name: "scale5b_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5b_branch2a"
    bottom: "res5b_branch2a"
    name: "res5b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2b"
    name: "res5b_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        dilation: 2
        pad: 2
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2b"
    name: "bn5b_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2b"
    name: "scale5b_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5b_branch2b"
    bottom: "res5b_branch2b"
    name: "res5b_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2c"
    name: "res5b_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5b_branch2c"
    top: "res5b_branch2c"
    name: "bn5b_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5b_branch2c"
    top: "res5b_branch2c"
    name: "scale5b_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a"
    bottom: "res5b_branch2c"
    top: "res5b"
    name: "res5b"
    type: "Eltwise"
}

layer {
    bottom: "res5b"
    top: "res5b"
    name: "res5b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5b"
    top: "res5c_branch2a"
    name: "res5c_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2a"
    name: "bn5c_branch2a"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2a"
    name: "scale5c_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5c_branch2a"
    bottom: "res5c_branch2a"
    name: "res5c_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2b"
    name: "res5c_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        dilation: 2
        pad: 2
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2b"
    name: "bn5c_branch2b"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2b"
    name: "scale5c_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5c_branch2b"
    bottom: "res5c_branch2b"
    name: "res5c_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2c"
    name: "res5c_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5c_branch2c"
    top: "res5c_branch2c"
    name: "bn5c_branch2c"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5c_branch2c"
    top: "res5c_branch2c"
    name: "scale5c_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5b"
    bottom: "res5c_branch2c"
    top: "res5c"
    name: "res5c"
    type: "Eltwise"
}

layer {
    bottom: "res5c"
    top: "res5c"
    name: "res5c_relu"
    type: "ReLU"
}



#========= RPN ============

layer {
  name: "rpn_conv/3x3"
  type: "Convolution"
  bottom: "res4b22"
  top: "rpn/output"
  param { lr_mult: 1.0 }
  param { lr_mult: 2.0 }
  convolution_param {
    num_output: 512
    kernel_size: 3 pad: 1 stride: 1
    weight_filler { type: "gaussian" std: 0.01 }
    bias_filler { type: "constant" value: 0 }
  }
}
layer {
  name: "rpn_relu/3x3"
  type: "ReLU"
  bottom: "rpn/output"
  top: "rpn/output"
}

layer {
  name: "rpn_cls_score"
  type: "Convolution"
  bottom: "rpn/output"
  top: "rpn_cls_score"
  param { lr_mult: 1.0 }
  param { lr_mult: 2.0 }
  convolution_param {
    num_output: 18   # 2(bg/fg) * 9(anchors)
    kernel_size: 1 pad: 0 stride: 1
    weight_filler { type: "gaussian" std: 0.01 }
    bias_filler { type: "constant" value: 0 }
  }
}

layer {
  name: "rpn_bbox_pred"
  type: "Convolution"
  bottom: "rpn/output"
  top: "rpn_bbox_pred"
  param { lr_mult: 1.0 }
  param { lr_mult: 2.0 }
  convolution_param {
    num_output: 36   # 4 * 9(anchors)
    kernel_size: 1 pad: 0 stride: 1
    weight_filler { type: "gaussian" std: 0.01 }
    bias_filler { type: "constant" value: 0 }
  }
}

layer {
   bottom: "rpn_cls_score"
   top: "rpn_cls_score_reshape"
   name: "rpn_cls_score_reshape"
   type: "Reshape"
   reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } }
}

layer {
  name: 'rpn-data'
  type: 'Python'
  bottom: 'rpn_cls_score'
  bottom: 'gt_boxes'
  bottom: 'im_info'
  bottom: 'data'
  top: 'rpn_labels'
  top: 'rpn_bbox_targets'
  top: 'rpn_bbox_inside_weights'
  top: 'rpn_bbox_outside_weights'
  python_param {
    module: 'rpn.anchor_target_layer'
    layer: 'AnchorTargetLayer'
    param_str: "'feat_stride': 16"
  }
}

layer {
  name: "rpn_loss_cls"
  type: "SoftmaxWithLoss"
  bottom: "rpn_cls_score_reshape"
  bottom: "rpn_labels"
  propagate_down: 1
  propagate_down: 0
  top: "rpn_cls_loss"
  loss_weight: 1
  loss_param {
    ignore_label: -1
    normalize: true
  }
}

layer {
  name: "rpn_loss_bbox"
  type: "SmoothL1Loss"
  bottom: "rpn_bbox_pred"
  bottom: "rpn_bbox_targets"
  bottom: 'rpn_bbox_inside_weights'
  bottom: 'rpn_bbox_outside_weights'
  top: "rpn_loss_bbox"
  loss_weight: 1
  smooth_l1_loss_param { sigma: 3.0 }
}

#========= RoI Proposal ============

layer {
  name: "rpn_cls_prob"
  type: "Softmax"
  bottom: "rpn_cls_score_reshape"
  top: "rpn_cls_prob"
}

layer {
  name: 'rpn_cls_prob_reshape'
  type: 'Reshape'
  bottom: 'rpn_cls_prob'
  top: 'rpn_cls_prob_reshape'
  reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } }
}

layer {
  name: 'proposal'
  type: 'Python'
  bottom: 'rpn_cls_prob_reshape'
  bottom: 'rpn_bbox_pred'
  bottom: 'im_info'
  top: 'rpn_rois'
#  top: 'rpn_scores'
  python_param {
    module: 'rpn.proposal_layer'
    layer: 'ProposalLayer'
    param_str: "'feat_stride': 16"
  }
}

#layer {
#  name: 'debug-data'
#  type: 'Python'
#  bottom: 'data'
#  bottom: 'rpn_rois'
#  bottom: 'rpn_scores'
#  python_param {
#    module: 'rpn.debug_layer'
#    layer: 'RPNDebugLayer'
#  }
#}

layer {
  name: 'roi-data'
  type: 'Python'
  bottom: 'rpn_rois'
  bottom: 'gt_boxes'
  top: 'rois'
  top: 'labels'
  top: 'bbox_targets'
  top: 'bbox_inside_weights'
  top: 'bbox_outside_weights'
  python_param {
    module: 'rpn.proposal_target_layer'
    layer: 'ProposalTargetLayer'
    param_str: "'num_classes': 2"
  }
}

#----------------------new conv layer------------------
layer {
    bottom: "res5c"
    top: "conv_new_1"
    name: "conv_new_1"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}

layer {
    bottom: "conv_new_1"
    top: "conv_new_1"
    name: "conv_new_1_relu"
    type: "ReLU"
}
########################################################
layer {
    bottom: "conv_new_1"
    top: "local_cls"
    name: "local_cls"
    type: "Convolution"
    convolution_param {
        num_output: 1029 #21*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}
layer {
    bottom: "conv_new_1"
    top: "local_bbox"
    name: "local_bbox"
    type: "Convolution"
    convolution_param {
        num_output: 392 #8*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}
########################################################
layer {
  name: "roi_pool5"
  type: "ROIPooling"
  bottom: "conv_new_1"
  bottom: "rois"
  top: "pool5"
  roi_pooling_param {
    pooled_w: 7
    pooled_h: 7
    spatial_scale: 0.0625 # 1/16
  }
}
layer {
    bottom: "pool5"
    top: "conv_pool5"
    name: "conv_pool5"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 7
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}

layer {
    bottom: "conv_pool5"
    top: "conv_pool5"
    name: "conv_pool5_relu"
    type: "ReLU"
}
layer {
    bottom: "conv_pool5"
    top: "conv_pool5_1"
    name: "conv_pool5_1"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}

layer {
    bottom: "conv_pool5_1"
    top: "conv_pool5_1"
    name: "conv_pool5_1_relu"
    type: "ReLU"
}
layer {
    bottom: "conv_pool5_1"
    top: "global_cls_score"
    name: "global_cls_score"
    type: "Convolution"
    convolution_param {
        num_output: 21
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}
layer {
    bottom: "conv_pool5_1"
    top: "global_bbox_pred"
    name: "global_bbox_pred"
    type: "Convolution"
    convolution_param {
        num_output: 8
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}
#--------------position sensitive RoI pooling--------------
layer {
    bottom: "local_cls"
    bottom: "rois"
    top: "psroipooled_cls_rois_local"
    name: "psroipooled_cls_rois_local"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 21
        group_size: 7
    }
}

layer {
    bottom: "psroipooled_cls_rois_local"
    top: "local_cls_score"
    name: "ave_cls_score_rois_local"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

layer {
    bottom: "local_cls_score"
    top: "conv/local_cls_score"
    name: "conv/local_cls_score"
    type: "Convolution"
    convolution_param {
        num_output: 21
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}

layer {
    bottom: "global_cls_score"
    bottom: "conv/local_cls_score"
    top: "cls_score"
    name: "cls_score"
    type: "Eltwise"
}
########################################################

layer {
    bottom: "local_bbox"
    bottom: "rois"
    top: "psroipooled_loc_rois_local"
    name: "psroipooled_loc_rois_local"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 8
        group_size: 7
    }
}

layer {
    bottom: "psroipooled_loc_rois_local"
    top: "local_bbox_pred"
    name: "ave_bbox_pred_rois_local"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}
layer {
    bottom: "global_bbox_pred"
    bottom: "local_bbox_pred"
    top: "bbox_pred"
    name: "bbox_pred"
    type: "Eltwise"
}

#--------------online hard example mining--------------
layer {
   name: "per_roi_loss_cls"
   type: "SoftmaxWithLossOHEM"
   bottom: "cls_score"
   bottom: "labels"
   top: "temp_loss_cls"
   top: "temp_prob_cls"
   top: "per_roi_loss_cls"
   loss_weight: 0
   loss_weight: 0
   loss_weight: 0
   propagate_down: false
   propagate_down: false
}

layer {
   name: "per_roi_loss_bbox"
   type: "SmoothL1LossOHEM"
   bottom: "bbox_pred"
   bottom: "bbox_targets"
   bottom: "bbox_inside_weights"
   top: "temp_loss_bbox"
   top: "per_roi_loss_bbox"
   loss_weight: 0
   loss_weight: 0
   propagate_down: false
   propagate_down: false
   propagate_down: false
}

layer {
   name: "per_roi_loss"
   type: "Eltwise"
   bottom: "per_roi_loss_cls"
   bottom: "per_roi_loss_bbox"
   top: "per_roi_loss"
   propagate_down: false
   propagate_down: false
}

layer {
   bottom: "rois"
   bottom: "per_roi_loss"
   bottom: "labels"
   bottom: "bbox_inside_weights"
   top: "labels_ohem"
   top: "bbox_loss_weights_ohem"
   name: "annotator_detector"
   type: "BoxAnnotatorOHEM"
   box_annotator_ohem_param {
        roi_per_img: 128
        ignore_label: -1
   }
   propagate_down: false
   propagate_down: false
   propagate_down: false
   propagate_down: false
}

layer {
   name: "silence"
   type: "Silence"
   bottom: "bbox_outside_weights"
   bottom: "temp_loss_cls"
   bottom: "temp_prob_cls"
   bottom: "temp_loss_bbox"
}

#-----------------------output------------------------
layer {
   name: "loss"
   type: "SoftmaxWithLoss"
   bottom: "cls_score"
   bottom: "labels_ohem"
   top: "loss_cls"
   loss_weight: 1
   loss_param {
        ignore_label: -1
   }
   propagate_down: true
   propagate_down: false
}

layer {
   name: "accuarcy"
   type: "Accuracy"
   bottom: "cls_score"
   bottom: "labels_ohem"
   top: "accuarcy"
   #include: { phase: TEST }
   accuracy_param {
        ignore_label: -1
   }
   propagate_down: false
   propagate_down: false
}

layer {
   name: "loss_bbox"
   type: "SmoothL1LossOHEM"
   bottom: "bbox_pred"
   bottom: "bbox_targets"
   bottom: "bbox_loss_weights_ohem"
   top: "loss_bbox"
   loss_weight: 1
   loss_param {
        normalization: PRE_FIXED
        pre_fixed_normalizer: 128
   }
   propagate_down: true
   propagate_down: false
   propagate_down: false
}