net_train_resnet.prototxt

name: "resnet50_ssd"
layer {
  name: "data"
  type: "AnnotatedData"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    mean_value: 104.0
    mean_value: 117.0
    mean_value: 123.0
    resize_param {
      prob: 1.0
      resize_mode: WARP
      height: 512
      width: 512
      interp_mode: LINEAR
      interp_mode: AREA
      interp_mode: NEAREST
      interp_mode: CUBIC
      interp_mode: LANCZOS4
    }
    emit_constraint {
      emit_type: CENTER
    }
    distort_param {
      brightness_prob: 0.5
      brightness_delta: 32.0
      contrast_prob: 0.5
      contrast_lower: 0.5
      contrast_upper: 1.5
      hue_prob: 0.5
      hue_delta: 18.0
      saturation_prob: 0.5
      saturation_lower: 0.5
      saturation_upper: 1.5
      random_order_prob: 0.0
    }
  }
  data_param {
    source: "../database/car_logo_lmdb"
    batch_size: 24
    backend: LMDB
  }
  annotated_data_param {
    batch_sampler {
      max_sample: 1
      max_trials: 1
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.1
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.3
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.5
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.7
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.9
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        max_jaccard_overlap: 1.0
      }
      max_sample: 1
      max_trials: 50
    }
    label_map_file: "../database/labelmap_car_logo.prototxt"
  }
}
layer {
  name: "conv_1"
  type: "Convolution"
  bottom: "data"
  top: "conv_1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_1"
  type: "BatchNorm"
  bottom: "conv_1"
  top: "conv_1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_1"
  type: "Scale"
  bottom: "conv_1"
  top: "conv_1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_1"
  type: "ReLU"
  bottom: "conv_1"
  top: "conv_1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv_1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "conv_stage0_block0_proj_shortcut"
  type: "Convolution"
  bottom: "pool1"
  top: "conv_stage0_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block0_proj_shortcut"
  type: "BatchNorm"
  bottom: "conv_stage0_block0_proj_shortcut"
  top: "conv_stage0_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block0_proj_shortcut"
  type: "Scale"
  bottom: "conv_stage0_block0_proj_shortcut"
  top: "conv_stage0_block0_proj_shortcut"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_stage0_block0_branch2a"
  type: "Convolution"
  bottom: "pool1"
  top: "conv_stage0_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block0_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage0_block0_branch2a"
  top: "conv_stage0_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block0_branch2a"
  type: "Scale"
  bottom: "conv_stage0_block0_branch2a"
  top: "conv_stage0_block0_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage0_block0_branch2a"
  type: "ReLU"
  bottom: "conv_stage0_block0_branch2a"
  top: "conv_stage0_block0_branch2a"
}
layer {
  name: "conv_stage0_block0_branch2b"
  type: "Convolution"
  bottom: "conv_stage0_block0_branch2a"
  top: "conv_stage0_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block0_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage0_block0_branch2b"
  top: "conv_stage0_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block0_branch2b"
  type: "Scale"
  bottom: "conv_stage0_block0_branch2b"
  top: "conv_stage0_block0_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage0_block0_branch2b"
  type: "ReLU"
  bottom: "conv_stage0_block0_branch2b"
  top: "conv_stage0_block0_branch2b"
}
layer {
  name: "conv_stage0_block0_branch2c"
  type: "Convolution"
  bottom: "conv_stage0_block0_branch2b"
  top: "conv_stage0_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block0_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage0_block0_branch2c"
  top: "conv_stage0_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block0_branch2c"
  type: "Scale"
  bottom: "conv_stage0_block0_branch2c"
  top: "conv_stage0_block0_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage0_block0"
  type: "Eltwise"
  bottom: "conv_stage0_block0_proj_shortcut"
  bottom: "conv_stage0_block0_branch2c"
  top: "eltwise_stage0_block0"
}
layer {
  name: "relu_stage0_block0"
  type: "ReLU"
  bottom: "eltwise_stage0_block0"
  top: "eltwise_stage0_block0"
}
layer {
  name: "conv_stage0_block1_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage0_block0"
  top: "conv_stage0_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block1_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage0_block1_branch2a"
  top: "conv_stage0_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block1_branch2a"
  type: "Scale"
  bottom: "conv_stage0_block1_branch2a"
  top: "conv_stage0_block1_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage0_block1_branch2a"
  type: "ReLU"
  bottom: "conv_stage0_block1_branch2a"
  top: "conv_stage0_block1_branch2a"
}
layer {
  name: "conv_stage0_block1_branch2b"
  type: "Convolution"
  bottom: "conv_stage0_block1_branch2a"
  top: "conv_stage0_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block1_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage0_block1_branch2b"
  top: "conv_stage0_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block1_branch2b"
  type: "Scale"
  bottom: "conv_stage0_block1_branch2b"
  top: "conv_stage0_block1_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage0_block1_branch2b"
  type: "ReLU"
  bottom: "conv_stage0_block1_branch2b"
  top: "conv_stage0_block1_branch2b"
}
layer {
  name: "conv_stage0_block1_branch2c"
  type: "Convolution"
  bottom: "conv_stage0_block1_branch2b"
  top: "conv_stage0_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block1_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage0_block1_branch2c"
  top: "conv_stage0_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block1_branch2c"
  type: "Scale"
  bottom: "conv_stage0_block1_branch2c"
  top: "conv_stage0_block1_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage0_block1"
  type: "Eltwise"
  bottom: "eltwise_stage0_block0"
  bottom: "conv_stage0_block1_branch2c"
  top: "eltwise_stage0_block1"
}
layer {
  name: "relu_stage0_block1"
  type: "ReLU"
  bottom: "eltwise_stage0_block1"
  top: "eltwise_stage0_block1"
}
layer {
  name: "conv_stage0_block2_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage0_block1"
  top: "conv_stage0_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block2_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage0_block2_branch2a"
  top: "conv_stage0_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block2_branch2a"
  type: "Scale"
  bottom: "conv_stage0_block2_branch2a"
  top: "conv_stage0_block2_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage0_block2_branch2a"
  type: "ReLU"
  bottom: "conv_stage0_block2_branch2a"
  top: "conv_stage0_block2_branch2a"
}
layer {
  name: "conv_stage0_block2_branch2b"
  type: "Convolution"
  bottom: "conv_stage0_block2_branch2a"
  top: "conv_stage0_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block2_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage0_block2_branch2b"
  top: "conv_stage0_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block2_branch2b"
  type: "Scale"
  bottom: "conv_stage0_block2_branch2b"
  top: "conv_stage0_block2_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage0_block2_branch2b"
  type: "ReLU"
  bottom: "conv_stage0_block2_branch2b"
  top: "conv_stage0_block2_branch2b"
}
layer {
  name: "conv_stage0_block2_branch2c"
  type: "Convolution"
  bottom: "conv_stage0_block2_branch2b"
  top: "conv_stage0_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage0_block2_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage0_block2_branch2c"
  top: "conv_stage0_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale_stage0_block2_branch2c"
  type: "Scale"
  bottom: "conv_stage0_block2_branch2c"
  top: "conv_stage0_block2_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage0_block2"
  type: "Eltwise"
  bottom: "eltwise_stage0_block1"
  bottom: "conv_stage0_block2_branch2c"
  top: "eltwise_stage0_block2"
}
layer {
  name: "relu_stage0_block2"
  type: "ReLU"
  bottom: "eltwise_stage0_block2"
  top: "eltwise_stage0_block2"
}
layer {
  name: "conv_stage1_block0_proj_shortcut"
  type: "Convolution"
  bottom: "eltwise_stage0_block2"
  top: "conv_stage1_block0_proj_shortcut"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block0_proj_shortcut"
  type: "BatchNorm"
  bottom: "conv_stage1_block0_proj_shortcut"
  top: "conv_stage1_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block0_proj_shortcut"
  type: "Scale"
  bottom: "conv_stage1_block0_proj_shortcut"
  top: "conv_stage1_block0_proj_shortcut"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_stage1_block0_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage0_block2"
  top: "conv_stage1_block0_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block0_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage1_block0_branch2a"
  top: "conv_stage1_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block0_branch2a"
  type: "Scale"
  bottom: "conv_stage1_block0_branch2a"
  top: "conv_stage1_block0_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block0_branch2a"
  type: "ReLU"
  bottom: "conv_stage1_block0_branch2a"
  top: "conv_stage1_block0_branch2a"
}
layer {
  name: "conv_stage1_block0_branch2b"
  type: "Convolution"
  bottom: "conv_stage1_block0_branch2a"
  top: "conv_stage1_block0_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block0_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage1_block0_branch2b"
  top: "conv_stage1_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block0_branch2b"
  type: "Scale"
  bottom: "conv_stage1_block0_branch2b"
  top: "conv_stage1_block0_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block0_branch2b"
  type: "ReLU"
  bottom: "conv_stage1_block0_branch2b"
  top: "conv_stage1_block0_branch2b"
}
layer {
  name: "conv_stage1_block0_branch2c"
  type: "Convolution"
  bottom: "conv_stage1_block0_branch2b"
  top: "conv_stage1_block0_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block0_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage1_block0_branch2c"
  top: "conv_stage1_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block0_branch2c"
  type: "Scale"
  bottom: "conv_stage1_block0_branch2c"
  top: "conv_stage1_block0_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage1_block0"
  type: "Eltwise"
  bottom: "conv_stage1_block0_proj_shortcut"
  bottom: "conv_stage1_block0_branch2c"
  top: "eltwise_stage1_block0"
}
layer {
  name: "relu_stage1_block0"
  type: "ReLU"
  bottom: "eltwise_stage1_block0"
  top: "eltwise_stage1_block0"
}
layer {
  name: "conv_stage1_block1_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage1_block0"
  top: "conv_stage1_block1_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block1_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage1_block1_branch2a"
  top: "conv_stage1_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block1_branch2a"
  type: "Scale"
  bottom: "conv_stage1_block1_branch2a"
  top: "conv_stage1_block1_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block1_branch2a"
  type: "ReLU"
  bottom: "conv_stage1_block1_branch2a"
  top: "conv_stage1_block1_branch2a"
}
layer {
  name: "conv_stage1_block1_branch2b"
  type: "Convolution"
  bottom: "conv_stage1_block1_branch2a"
  top: "conv_stage1_block1_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block1_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage1_block1_branch2b"
  top: "conv_stage1_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block1_branch2b"
  type: "Scale"
  bottom: "conv_stage1_block1_branch2b"
  top: "conv_stage1_block1_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block1_branch2b"
  type: "ReLU"
  bottom: "conv_stage1_block1_branch2b"
  top: "conv_stage1_block1_branch2b"
}
layer {
  name: "conv_stage1_block1_branch2c"
  type: "Convolution"
  bottom: "conv_stage1_block1_branch2b"
  top: "conv_stage1_block1_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block1_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage1_block1_branch2c"
  top: "conv_stage1_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block1_branch2c"
  type: "Scale"
  bottom: "conv_stage1_block1_branch2c"
  top: "conv_stage1_block1_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage1_block1"
  type: "Eltwise"
  bottom: "eltwise_stage1_block0"
  bottom: "conv_stage1_block1_branch2c"
  top: "eltwise_stage1_block1"
}
layer {
  name: "relu_stage1_block1"
  type: "ReLU"
  bottom: "eltwise_stage1_block1"
  top: "eltwise_stage1_block1"
}
layer {
  name: "conv_stage1_block2_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage1_block1"
  top: "conv_stage1_block2_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block2_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage1_block2_branch2a"
  top: "conv_stage1_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block2_branch2a"
  type: "Scale"
  bottom: "conv_stage1_block2_branch2a"
  top: "conv_stage1_block2_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block2_branch2a"
  type: "ReLU"
  bottom: "conv_stage1_block2_branch2a"
  top: "conv_stage1_block2_branch2a"
}
layer {
  name: "conv_stage1_block2_branch2b"
  type: "Convolution"
  bottom: "conv_stage1_block2_branch2a"
  top: "conv_stage1_block2_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block2_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage1_block2_branch2b"
  top: "conv_stage1_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block2_branch2b"
  type: "Scale"
  bottom: "conv_stage1_block2_branch2b"
  top: "conv_stage1_block2_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block2_branch2b"
  type: "ReLU"
  bottom: "conv_stage1_block2_branch2b"
  top: "conv_stage1_block2_branch2b"
}
layer {
  name: "conv_stage1_block2_branch2c"
  type: "Convolution"
  bottom: "conv_stage1_block2_branch2b"
  top: "conv_stage1_block2_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block2_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage1_block2_branch2c"
  top: "conv_stage1_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block2_branch2c"
  type: "Scale"
  bottom: "conv_stage1_block2_branch2c"
  top: "conv_stage1_block2_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage1_block2"
  type: "Eltwise"
  bottom: "eltwise_stage1_block1"
  bottom: "conv_stage1_block2_branch2c"
  top: "eltwise_stage1_block2"
}
layer {
  name: "relu_stage1_block2"
  type: "ReLU"
  bottom: "eltwise_stage1_block2"
  top: "eltwise_stage1_block2"
}
layer {
  name: "conv_stage1_block3_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage1_block2"
  top: "conv_stage1_block3_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block3_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage1_block3_branch2a"
  top: "conv_stage1_block3_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block3_branch2a"
  type: "Scale"
  bottom: "conv_stage1_block3_branch2a"
  top: "conv_stage1_block3_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block3_branch2a"
  type: "ReLU"
  bottom: "conv_stage1_block3_branch2a"
  top: "conv_stage1_block3_branch2a"
}
layer {
  name: "conv_stage1_block3_branch2b"
  type: "Convolution"
  bottom: "conv_stage1_block3_branch2a"
  top: "conv_stage1_block3_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block3_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage1_block3_branch2b"
  top: "conv_stage1_block3_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block3_branch2b"
  type: "Scale"
  bottom: "conv_stage1_block3_branch2b"
  top: "conv_stage1_block3_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage1_block3_branch2b"
  type: "ReLU"
  bottom: "conv_stage1_block3_branch2b"
  top: "conv_stage1_block3_branch2b"
}
layer {
  name: "conv_stage1_block3_branch2c"
  type: "Convolution"
  bottom: "conv_stage1_block3_branch2b"
  top: "conv_stage1_block3_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage1_block3_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage1_block3_branch2c"
  top: "conv_stage1_block3_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage1_block3_branch2c"
  type: "Scale"
  bottom: "conv_stage1_block3_branch2c"
  top: "conv_stage1_block3_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage1_block3"
  type: "Eltwise"
  bottom: "eltwise_stage1_block2"
  bottom: "conv_stage1_block3_branch2c"
  top: "eltwise_stage1_block3"
}
layer {
  name: "relu_stage1_block3"
  type: "ReLU"
  bottom: "eltwise_stage1_block3"
  top: "eltwise_stage1_block3"
}
layer {
  name: "conv_stage2_block0_proj_shortcut"
  type: "Convolution"
  bottom: "eltwise_stage1_block3"
  top: "conv_stage2_block0_proj_shortcut"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block0_proj_shortcut"
  type: "BatchNorm"
  bottom: "conv_stage2_block0_proj_shortcut"
  top: "conv_stage2_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block0_proj_shortcut"
  type: "Scale"
  bottom: "conv_stage2_block0_proj_shortcut"
  top: "conv_stage2_block0_proj_shortcut"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_stage2_block0_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage1_block3"
  top: "conv_stage2_block0_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block0_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage2_block0_branch2a"
  top: "conv_stage2_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block0_branch2a"
  type: "Scale"
  bottom: "conv_stage2_block0_branch2a"
  top: "conv_stage2_block0_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block0_branch2a"
  type: "ReLU"
  bottom: "conv_stage2_block0_branch2a"
  top: "conv_stage2_block0_branch2a"
}
layer {
  name: "conv_stage2_block0_branch2b"
  type: "Convolution"
  bottom: "conv_stage2_block0_branch2a"
  top: "conv_stage2_block0_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block0_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage2_block0_branch2b"
  top: "conv_stage2_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block0_branch2b"
  type: "Scale"
  bottom: "conv_stage2_block0_branch2b"
  top: "conv_stage2_block0_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block0_branch2b"
  type: "ReLU"
  bottom: "conv_stage2_block0_branch2b"
  top: "conv_stage2_block0_branch2b"
}
layer {
  name: "conv_stage2_block0_branch2c"
  type: "Convolution"
  bottom: "conv_stage2_block0_branch2b"
  top: "conv_stage2_block0_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block0_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage2_block0_branch2c"
  top: "conv_stage2_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block0_branch2c"
  type: "Scale"
  bottom: "conv_stage2_block0_branch2c"
  top: "conv_stage2_block0_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage2_block0"
  type: "Eltwise"
  bottom: "conv_stage2_block0_proj_shortcut"
  bottom: "conv_stage2_block0_branch2c"
  top: "eltwise_stage2_block0"
}
layer {
  name: "relu_stage2_block0"
  type: "ReLU"
  bottom: "eltwise_stage2_block0"
  top: "eltwise_stage2_block0"
}
layer {
  name: "conv_stage2_block1_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage2_block0"
  top: "conv_stage2_block1_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block1_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage2_block1_branch2a"
  top: "conv_stage2_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block1_branch2a"
  type: "Scale"
  bottom: "conv_stage2_block1_branch2a"
  top: "conv_stage2_block1_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block1_branch2a"
  type: "ReLU"
  bottom: "conv_stage2_block1_branch2a"
  top: "conv_stage2_block1_branch2a"
}
layer {
  name: "conv_stage2_block1_branch2b"
  type: "Convolution"
  bottom: "conv_stage2_block1_branch2a"
  top: "conv_stage2_block1_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block1_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage2_block1_branch2b"
  top: "conv_stage2_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block1_branch2b"
  type: "Scale"
  bottom: "conv_stage2_block1_branch2b"
  top: "conv_stage2_block1_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block1_branch2b"
  type: "ReLU"
  bottom: "conv_stage2_block1_branch2b"
  top: "conv_stage2_block1_branch2b"
}
layer {
  name: "conv_stage2_block1_branch2c"
  type: "Convolution"
  bottom: "conv_stage2_block1_branch2b"
  top: "conv_stage2_block1_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block1_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage2_block1_branch2c"
  top: "conv_stage2_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block1_branch2c"
  type: "Scale"
  bottom: "conv_stage2_block1_branch2c"
  top: "conv_stage2_block1_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage2_block1"
  type: "Eltwise"
  bottom: "eltwise_stage2_block0"
  bottom: "conv_stage2_block1_branch2c"
  top: "eltwise_stage2_block1"
}
layer {
  name: "relu_stage2_block1"
  type: "ReLU"
  bottom: "eltwise_stage2_block1"
  top: "eltwise_stage2_block1"
}
layer {
  name: "conv_stage2_block2_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage2_block1"
  top: "conv_stage2_block2_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block2_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage2_block2_branch2a"
  top: "conv_stage2_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block2_branch2a"
  type: "Scale"
  bottom: "conv_stage2_block2_branch2a"
  top: "conv_stage2_block2_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block2_branch2a"
  type: "ReLU"
  bottom: "conv_stage2_block2_branch2a"
  top: "conv_stage2_block2_branch2a"
}
layer {
  name: "conv_stage2_block2_branch2b"
  type: "Convolution"
  bottom: "conv_stage2_block2_branch2a"
  top: "conv_stage2_block2_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block2_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage2_block2_branch2b"
  top: "conv_stage2_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block2_branch2b"
  type: "Scale"
  bottom: "conv_stage2_block2_branch2b"
  top: "conv_stage2_block2_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block2_branch2b"
  type: "ReLU"
  bottom: "conv_stage2_block2_branch2b"
  top: "conv_stage2_block2_branch2b"
}
layer {
  name: "conv_stage2_block2_branch2c"
  type: "Convolution"
  bottom: "conv_stage2_block2_branch2b"
  top: "conv_stage2_block2_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block2_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage2_block2_branch2c"
  top: "conv_stage2_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block2_branch2c"
  type: "Scale"
  bottom: "conv_stage2_block2_branch2c"
  top: "conv_stage2_block2_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage2_block2"
  type: "Eltwise"
  bottom: "eltwise_stage2_block1"
  bottom: "conv_stage2_block2_branch2c"
  top: "eltwise_stage2_block2"
}
layer {
  name: "relu_stage2_block2"
  type: "ReLU"
  bottom: "eltwise_stage2_block2"
  top: "eltwise_stage2_block2"
}
layer {
  name: "conv_stage2_block3_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage2_block2"
  top: "conv_stage2_block3_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block3_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage2_block3_branch2a"
  top: "conv_stage2_block3_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block3_branch2a"
  type: "Scale"
  bottom: "conv_stage2_block3_branch2a"
  top: "conv_stage2_block3_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block3_branch2a"
  type: "ReLU"
  bottom: "conv_stage2_block3_branch2a"
  top: "conv_stage2_block3_branch2a"
}
layer {
  name: "conv_stage2_block3_branch2b"
  type: "Convolution"
  bottom: "conv_stage2_block3_branch2a"
  top: "conv_stage2_block3_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block3_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage2_block3_branch2b"
  top: "conv_stage2_block3_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block3_branch2b"
  type: "Scale"
  bottom: "conv_stage2_block3_branch2b"
  top: "conv_stage2_block3_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block3_branch2b"
  type: "ReLU"
  bottom: "conv_stage2_block3_branch2b"
  top: "conv_stage2_block3_branch2b"
}
layer {
  name: "conv_stage2_block3_branch2c"
  type: "Convolution"
  bottom: "conv_stage2_block3_branch2b"
  top: "conv_stage2_block3_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block3_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage2_block3_branch2c"
  top: "conv_stage2_block3_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block3_branch2c"
  type: "Scale"
  bottom: "conv_stage2_block3_branch2c"
  top: "conv_stage2_block3_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage2_block3"
  type: "Eltwise"
  bottom: "eltwise_stage2_block2"
  bottom: "conv_stage2_block3_branch2c"
  top: "eltwise_stage2_block3"
}
layer {
  name: "relu_stage2_block3"
  type: "ReLU"
  bottom: "eltwise_stage2_block3"
  top: "eltwise_stage2_block3"
}
layer {
  name: "conv_stage2_block4_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage2_block3"
  top: "conv_stage2_block4_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block4_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage2_block4_branch2a"
  top: "conv_stage2_block4_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block4_branch2a"
  type: "Scale"
  bottom: "conv_stage2_block4_branch2a"
  top: "conv_stage2_block4_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block4_branch2a"
  type: "ReLU"
  bottom: "conv_stage2_block4_branch2a"
  top: "conv_stage2_block4_branch2a"
}
layer {
  name: "conv_stage2_block4_branch2b"
  type: "Convolution"
  bottom: "conv_stage2_block4_branch2a"
  top: "conv_stage2_block4_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block4_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage2_block4_branch2b"
  top: "conv_stage2_block4_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block4_branch2b"
  type: "Scale"
  bottom: "conv_stage2_block4_branch2b"
  top: "conv_stage2_block4_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block4_branch2b"
  type: "ReLU"
  bottom: "conv_stage2_block4_branch2b"
  top: "conv_stage2_block4_branch2b"
}
layer {
  name: "conv_stage2_block4_branch2c"
  type: "Convolution"
  bottom: "conv_stage2_block4_branch2b"
  top: "conv_stage2_block4_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block4_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage2_block4_branch2c"
  top: "conv_stage2_block4_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block4_branch2c"
  type: "Scale"
  bottom: "conv_stage2_block4_branch2c"
  top: "conv_stage2_block4_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage2_block4"
  type: "Eltwise"
  bottom: "eltwise_stage2_block3"
  bottom: "conv_stage2_block4_branch2c"
  top: "eltwise_stage2_block4"
}
layer {
  name: "relu_stage2_block4"
  type: "ReLU"
  bottom: "eltwise_stage2_block4"
  top: "eltwise_stage2_block4"
}
layer {
  name: "conv_stage2_block5_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage2_block4"
  top: "conv_stage2_block5_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block5_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage2_block5_branch2a"
  top: "conv_stage2_block5_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block5_branch2a"
  type: "Scale"
  bottom: "conv_stage2_block5_branch2a"
  top: "conv_stage2_block5_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block5_branch2a"
  type: "ReLU"
  bottom: "conv_stage2_block5_branch2a"
  top: "conv_stage2_block5_branch2a"
}
layer {
  name: "conv_stage2_block5_branch2b"
  type: "Convolution"
  bottom: "conv_stage2_block5_branch2a"
  top: "conv_stage2_block5_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block5_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage2_block5_branch2b"
  top: "conv_stage2_block5_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block5_branch2b"
  type: "Scale"
  bottom: "conv_stage2_block5_branch2b"
  top: "conv_stage2_block5_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage2_block5_branch2b"
  type: "ReLU"
  bottom: "conv_stage2_block5_branch2b"
  top: "conv_stage2_block5_branch2b"
}
layer {
  name: "conv_stage2_block5_branch2c"
  type: "Convolution"
  bottom: "conv_stage2_block5_branch2b"
  top: "conv_stage2_block5_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage2_block5_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage2_block5_branch2c"
  top: "conv_stage2_block5_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage2_block5_branch2c"
  type: "Scale"
  bottom: "conv_stage2_block5_branch2c"
  top: "conv_stage2_block5_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage2_block5"
  type: "Eltwise"
  bottom: "eltwise_stage2_block4"
  bottom: "conv_stage2_block5_branch2c"
  top: "eltwise_stage2_block5"
}
layer {
  name: "relu_stage2_block5"
  type: "ReLU"
  bottom: "eltwise_stage2_block5"
  top: "eltwise_stage2_block5"
}
layer {
  name: "conv_stage3_block0_proj_shortcut"
  type: "Convolution"
  bottom: "eltwise_stage2_block5"
  top: "conv_stage3_block0_proj_shortcut"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block0_proj_shortcut"
  type: "BatchNorm"
  bottom: "conv_stage3_block0_proj_shortcut"
  top: "conv_stage3_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block0_proj_shortcut"
  type: "Scale"
  bottom: "conv_stage3_block0_proj_shortcut"
  top: "conv_stage3_block0_proj_shortcut"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_stage3_block0_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage2_block5"
  top: "conv_stage3_block0_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block0_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage3_block0_branch2a"
  top: "conv_stage3_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block0_branch2a"
  type: "Scale"
  bottom: "conv_stage3_block0_branch2a"
  top: "conv_stage3_block0_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage3_block0_branch2a"
  type: "ReLU"
  bottom: "conv_stage3_block0_branch2a"
  top: "conv_stage3_block0_branch2a"
}
layer {
  name: "conv_stage3_block0_branch2b"
  type: "Convolution"
  bottom: "conv_stage3_block0_branch2a"
  top: "conv_stage3_block0_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block0_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage3_block0_branch2b"
  top: "conv_stage3_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block0_branch2b"
  type: "Scale"
  bottom: "conv_stage3_block0_branch2b"
  top: "conv_stage3_block0_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage3_block0_branch2b"
  type: "ReLU"
  bottom: "conv_stage3_block0_branch2b"
  top: "conv_stage3_block0_branch2b"
}
layer {
  name: "conv_stage3_block0_branch2c"
  type: "Convolution"
  bottom: "conv_stage3_block0_branch2b"
  top: "conv_stage3_block0_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block0_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage3_block0_branch2c"
  top: "conv_stage3_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block0_branch2c"
  type: "Scale"
  bottom: "conv_stage3_block0_branch2c"
  top: "conv_stage3_block0_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage3_block0"
  type: "Eltwise"
  bottom: "conv_stage3_block0_proj_shortcut"
  bottom: "conv_stage3_block0_branch2c"
  top: "eltwise_stage3_block0"
}
layer {
  name: "relu_stage3_block0"
  type: "ReLU"
  bottom: "eltwise_stage3_block0"
  top: "eltwise_stage3_block0"
}
layer {
  name: "conv_stage3_block1_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage3_block0"
  top: "conv_stage3_block1_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block1_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage3_block1_branch2a"
  top: "conv_stage3_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block1_branch2a"
  type: "Scale"
  bottom: "conv_stage3_block1_branch2a"
  top: "conv_stage3_block1_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage3_block1_branch2a"
  type: "ReLU"
  bottom: "conv_stage3_block1_branch2a"
  top: "conv_stage3_block1_branch2a"
}
layer {
  name: "conv_stage3_block1_branch2b"
  type: "Convolution"
  bottom: "conv_stage3_block1_branch2a"
  top: "conv_stage3_block1_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block1_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage3_block1_branch2b"
  top: "conv_stage3_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block1_branch2b"
  type: "Scale"
  bottom: "conv_stage3_block1_branch2b"
  top: "conv_stage3_block1_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage3_block1_branch2b"
  type: "ReLU"
  bottom: "conv_stage3_block1_branch2b"
  top: "conv_stage3_block1_branch2b"
}
layer {
  name: "conv_stage3_block1_branch2c"
  type: "Convolution"
  bottom: "conv_stage3_block1_branch2b"
  top: "conv_stage3_block1_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block1_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage3_block1_branch2c"
  top: "conv_stage3_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block1_branch2c"
  type: "Scale"
  bottom: "conv_stage3_block1_branch2c"
  top: "conv_stage3_block1_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage3_block1"
  type: "Eltwise"
  bottom: "eltwise_stage3_block0"
  bottom: "conv_stage3_block1_branch2c"
  top: "eltwise_stage3_block1"
}
layer {
  name: "relu_stage3_block1"
  type: "ReLU"
  bottom: "eltwise_stage3_block1"
  top: "eltwise_stage3_block1"
}
layer {
  name: "conv_stage3_block2_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage3_block1"
  top: "conv_stage3_block2_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block2_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage3_block2_branch2a"
  top: "conv_stage3_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block2_branch2a"
  type: "Scale"
  bottom: "conv_stage3_block2_branch2a"
  top: "conv_stage3_block2_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage3_block2_branch2a"
  type: "ReLU"
  bottom: "conv_stage3_block2_branch2a"
  top: "conv_stage3_block2_branch2a"
}
layer {
  name: "conv_stage3_block2_branch2b"
  type: "Convolution"
  bottom: "conv_stage3_block2_branch2a"
  top: "conv_stage3_block2_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block2_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage3_block2_branch2b"
  top: "conv_stage3_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block2_branch2b"
  type: "Scale"
  bottom: "conv_stage3_block2_branch2b"
  top: "conv_stage3_block2_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage3_block2_branch2b"
  type: "ReLU"
  bottom: "conv_stage3_block2_branch2b"
  top: "conv_stage3_block2_branch2b"
}
layer {
  name: "conv_stage3_block2_branch2c"
  type: "Convolution"
  bottom: "conv_stage3_block2_branch2b"
  top: "conv_stage3_block2_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage3_block2_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage3_block2_branch2c"
  top: "conv_stage3_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage3_block2_branch2c"
  type: "Scale"
  bottom: "conv_stage3_block2_branch2c"
  top: "conv_stage3_block2_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage3_block2"
  type: "Eltwise"
  bottom: "eltwise_stage3_block1"
  bottom: "conv_stage3_block2_branch2c"
  top: "eltwise_stage3_block2"
}
layer {
  name: "relu_stage3_block2"
  type: "ReLU"
  bottom: "eltwise_stage3_block2"
  top: "eltwise_stage3_block2"
}
layer {
  name: "pool"
  type: "Pooling"
  bottom: "eltwise_stage3_block2"
  top: "pool"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 1
    pad: 3
  }
}
layer {
  name: "conv_stage4_block0_proj_shortcut"
  type: "Convolution"
  bottom: "pool"
  top: "conv_stage4_block0_proj_shortcut"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block0_proj_shortcut"
  type: "BatchNorm"
  bottom: "conv_stage4_block0_proj_shortcut"
  top: "conv_stage4_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block0_proj_shortcut"
  type: "Scale"
  bottom: "conv_stage4_block0_proj_shortcut"
  top: "conv_stage4_block0_proj_shortcut"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_stage4_block0_branch2a"
  type: "Convolution"
  bottom: "pool"
  top: "conv_stage4_block0_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block0_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage4_block0_branch2a"
  top: "conv_stage4_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block0_branch2a"
  type: "Scale"
  bottom: "conv_stage4_block0_branch2a"
  top: "conv_stage4_block0_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage4_block0_branch2a"
  type: "ReLU"
  bottom: "conv_stage4_block0_branch2a"
  top: "conv_stage4_block0_branch2a"
}
layer {
  name: "conv_stage4_block0_branch2b"
  type: "Convolution"
  bottom: "conv_stage4_block0_branch2a"
  top: "conv_stage4_block0_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block0_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage4_block0_branch2b"
  top: "conv_stage4_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block0_branch2b"
  type: "Scale"
  bottom: "conv_stage4_block0_branch2b"
  top: "conv_stage4_block0_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage4_block0_branch2b"
  type: "ReLU"
  bottom: "conv_stage4_block0_branch2b"
  top: "conv_stage4_block0_branch2b"
}
layer {
  name: "conv_stage4_block0_branch2c"
  type: "Convolution"
  bottom: "conv_stage4_block0_branch2b"
  top: "conv_stage4_block0_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block0_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage4_block0_branch2c"
  top: "conv_stage4_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block0_branch2c"
  type: "Scale"
  bottom: "conv_stage4_block0_branch2c"
  top: "conv_stage4_block0_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage4_block0"
  type: "Eltwise"
  bottom: "conv_stage4_block0_proj_shortcut"
  bottom: "conv_stage4_block0_branch2c"
  top: "eltwise_stage4_block0"
}
layer {
  name: "relu_stage4_block0"
  type: "ReLU"
  bottom: "eltwise_stage4_block0"
  top: "eltwise_stage4_block0"
}
layer {
  name: "conv_stage4_block1_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage4_block0"
  top: "conv_stage4_block1_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block1_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage4_block1_branch2a"
  top: "conv_stage4_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block1_branch2a"
  type: "Scale"
  bottom: "conv_stage4_block1_branch2a"
  top: "conv_stage4_block1_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage4_block1_branch2a"
  type: "ReLU"
  bottom: "conv_stage4_block1_branch2a"
  top: "conv_stage4_block1_branch2a"
}
layer {
  name: "conv_stage4_block1_branch2b"
  type: "Convolution"
  bottom: "conv_stage4_block1_branch2a"
  top: "conv_stage4_block1_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block1_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage4_block1_branch2b"
  top: "conv_stage4_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block1_branch2b"
  type: "Scale"
  bottom: "conv_stage4_block1_branch2b"
  top: "conv_stage4_block1_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage4_block1_branch2b"
  type: "ReLU"
  bottom: "conv_stage4_block1_branch2b"
  top: "conv_stage4_block1_branch2b"
}
layer {
  name: "conv_stage4_block1_branch2c"
  type: "Convolution"
  bottom: "conv_stage4_block1_branch2b"
  top: "conv_stage4_block1_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block1_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage4_block1_branch2c"
  top: "conv_stage4_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block1_branch2c"
  type: "Scale"
  bottom: "conv_stage4_block1_branch2c"
  top: "conv_stage4_block1_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage4_block1"
  type: "Eltwise"
  bottom: "eltwise_stage4_block0"
  bottom: "conv_stage4_block1_branch2c"
  top: "eltwise_stage4_block1"
}
layer {
  name: "relu_stage4_block1"
  type: "ReLU"
  bottom: "eltwise_stage4_block1"
  top: "eltwise_stage4_block1"
}
layer {
  name: "conv_stage4_block2_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage4_block1"
  top: "conv_stage4_block2_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block2_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage4_block2_branch2a"
  top: "conv_stage4_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block2_branch2a"
  type: "Scale"
  bottom: "conv_stage4_block2_branch2a"
  top: "conv_stage4_block2_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage4_block2_branch2a"
  type: "ReLU"
  bottom: "conv_stage4_block2_branch2a"
  top: "conv_stage4_block2_branch2a"
}
layer {
  name: "conv_stage4_block2_branch2b"
  type: "Convolution"
  bottom: "conv_stage4_block2_branch2a"
  top: "conv_stage4_block2_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block2_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage4_block2_branch2b"
  top: "conv_stage4_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block2_branch2b"
  type: "Scale"
  bottom: "conv_stage4_block2_branch2b"
  top: "conv_stage4_block2_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage4_block2_branch2b"
  type: "ReLU"
  bottom: "conv_stage4_block2_branch2b"
  top: "conv_stage4_block2_branch2b"
}
layer {
  name: "conv_stage4_block2_branch2c"
  type: "Convolution"
  bottom: "conv_stage4_block2_branch2b"
  top: "conv_stage4_block2_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage4_block2_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage4_block2_branch2c"
  top: "conv_stage4_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage4_block2_branch2c"
  type: "Scale"
  bottom: "conv_stage4_block2_branch2c"
  top: "conv_stage4_block2_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage4_block2"
  type: "Eltwise"
  bottom: "eltwise_stage4_block1"
  bottom: "conv_stage4_block2_branch2c"
  top: "eltwise_stage4_block2"
}
layer {
  name: "relu_stage4_block2"
  type: "ReLU"
  bottom: "eltwise_stage4_block2"
  top: "eltwise_stage4_block2"
}
layer {
  name: "conv_stage5_block0_proj_shortcut"
  type: "Convolution"
  bottom: "eltwise_stage4_block2"
  top: "conv_stage5_block0_proj_shortcut"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block0_proj_shortcut"
  type: "BatchNorm"
  bottom: "conv_stage5_block0_proj_shortcut"
  top: "conv_stage5_block0_proj_shortcut"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block0_proj_shortcut"
  type: "Scale"
  bottom: "conv_stage5_block0_proj_shortcut"
  top: "conv_stage5_block0_proj_shortcut"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv_stage5_block0_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage4_block2"
  top: "conv_stage5_block0_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 2
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block0_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage5_block0_branch2a"
  top: "conv_stage5_block0_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block0_branch2a"
  type: "Scale"
  bottom: "conv_stage5_block0_branch2a"
  top: "conv_stage5_block0_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage5_block0_branch2a"
  type: "ReLU"
  bottom: "conv_stage5_block0_branch2a"
  top: "conv_stage5_block0_branch2a"
}
layer {
  name: "conv_stage5_block0_branch2b"
  type: "Convolution"
  bottom: "conv_stage5_block0_branch2a"
  top: "conv_stage5_block0_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block0_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage5_block0_branch2b"
  top: "conv_stage5_block0_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block0_branch2b"
  type: "Scale"
  bottom: "conv_stage5_block0_branch2b"
  top: "conv_stage5_block0_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage5_block0_branch2b"
  type: "ReLU"
  bottom: "conv_stage5_block0_branch2b"
  top: "conv_stage5_block0_branch2b"
}
layer {
  name: "conv_stage5_block0_branch2c"
  type: "Convolution"
  bottom: "conv_stage5_block0_branch2b"
  top: "conv_stage5_block0_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block0_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage5_block0_branch2c"
  top: "conv_stage5_block0_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block0_branch2c"
  type: "Scale"
  bottom: "conv_stage5_block0_branch2c"
  top: "conv_stage5_block0_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage5_block0"
  type: "Eltwise"
  bottom: "conv_stage5_block0_proj_shortcut"
  bottom: "conv_stage5_block0_branch2c"
  top: "eltwise_stage5_block0"
}
layer {
  name: "relu_stage5_block0"
  type: "ReLU"
  bottom: "eltwise_stage5_block0"
  top: "eltwise_stage5_block0"
}
layer {
  name: "conv_stage5_block1_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage5_block0"
  top: "conv_stage5_block1_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block1_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage5_block1_branch2a"
  top: "conv_stage5_block1_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block1_branch2a"
  type: "Scale"
  bottom: "conv_stage5_block1_branch2a"
  top: "conv_stage5_block1_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage5_block1_branch2a"
  type: "ReLU"
  bottom: "conv_stage5_block1_branch2a"
  top: "conv_stage5_block1_branch2a"
}
layer {
  name: "conv_stage5_block1_branch2b"
  type: "Convolution"
  bottom: "conv_stage5_block1_branch2a"
  top: "conv_stage5_block1_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block1_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage5_block1_branch2b"
  top: "conv_stage5_block1_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block1_branch2b"
  type: "Scale"
  bottom: "conv_stage5_block1_branch2b"
  top: "conv_stage5_block1_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage5_block1_branch2b"
  type: "ReLU"
  bottom: "conv_stage5_block1_branch2b"
  top: "conv_stage5_block1_branch2b"
}
layer {
  name: "conv_stage5_block1_branch2c"
  type: "Convolution"
  bottom: "conv_stage5_block1_branch2b"
  top: "conv_stage5_block1_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block1_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage5_block1_branch2c"
  top: "conv_stage5_block1_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block1_branch2c"
  type: "Scale"
  bottom: "conv_stage5_block1_branch2c"
  top: "conv_stage5_block1_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage5_block1"
  type: "Eltwise"
  bottom: "eltwise_stage5_block0"
  bottom: "conv_stage5_block1_branch2c"
  top: "eltwise_stage5_block1"
}
layer {
  name: "relu_stage5_block1"
  type: "ReLU"
  bottom: "eltwise_stage5_block1"
  top: "eltwise_stage5_block1"
}
layer {
  name: "conv_stage5_block2_branch2a"
  type: "Convolution"
  bottom: "eltwise_stage5_block1"
  top: "conv_stage5_block2_branch2a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block2_branch2a"
  type: "BatchNorm"
  bottom: "conv_stage5_block2_branch2a"
  top: "conv_stage5_block2_branch2a"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block2_branch2a"
  type: "Scale"
  bottom: "conv_stage5_block2_branch2a"
  top: "conv_stage5_block2_branch2a"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage5_block2_branch2a"
  type: "ReLU"
  bottom: "conv_stage5_block2_branch2a"
  top: "conv_stage5_block2_branch2a"
}
layer {
  name: "conv_stage5_block2_branch2b"
  type: "Convolution"
  bottom: "conv_stage5_block2_branch2a"
  top: "conv_stage5_block2_branch2b"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block2_branch2b"
  type: "BatchNorm"
  bottom: "conv_stage5_block2_branch2b"
  top: "conv_stage5_block2_branch2b"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block2_branch2b"
  type: "Scale"
  bottom: "conv_stage5_block2_branch2b"
  top: "conv_stage5_block2_branch2b"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu_stage5_block2_branch2b"
  type: "ReLU"
  bottom: "conv_stage5_block2_branch2b"
  top: "conv_stage5_block2_branch2b"
}
layer {
  name: "conv_stage5_block2_branch2c"
  type: "Convolution"
  bottom: "conv_stage5_block2_branch2b"
  top: "conv_stage5_block2_branch2c"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "bn_stage5_block2_branch2c"
  type: "BatchNorm"
  bottom: "conv_stage5_block2_branch2c"
  top: "conv_stage5_block2_branch2c"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}
layer {
  name: "scale_stage5_block2_branch2c"
  type: "Scale"
  bottom: "conv_stage5_block2_branch2c"
  top: "conv_stage5_block2_branch2c"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "eltwise_stage5_block2"
  type: "Eltwise"
  bottom: "eltwise_stage5_block1"
  bottom: "conv_stage5_block2_branch2c"
  top: "eltwise_stage5_block2"
}
layer {
  name: "relu_stage5_block2"
  type: "ReLU"
  bottom: "eltwise_stage5_block2"
  top: "eltwise_stage5_block2"
}
layer {
  name: "pool_last"
  type: "Pooling"
  bottom: "eltwise_stage5_block2"
  top: "pool_last"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "relu_stage1_block3_norm"
  type: "Normalize"
  bottom: "eltwise_stage1_block3"
  top: "relu_stage1_block3_norm"
  norm_param {
    across_spatial: false
    scale_filler {
      type: "constant"
      value: 20
    }
    channel_shared: false
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_conf"
  type: "Convolution"
  bottom: "relu_stage1_block3_norm"
  top: "relu_stage1_block3_norm_mbox_conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 63
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_conf_perm"
  type: "Permute"
  bottom: "relu_stage1_block3_norm_mbox_conf"
  top: "relu_stage1_block3_norm_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_conf_flat"
  type: "Flatten"
  bottom: "relu_stage1_block3_norm_mbox_conf_perm"
  top: "relu_stage1_block3_norm_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_loc"
  type: "Convolution"
  bottom: "relu_stage1_block3_norm"
  top: "relu_stage1_block3_norm_mbox_loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 12
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_loc_perm"
  type: "Permute"
  bottom: "relu_stage1_block3_norm_mbox_loc"
  top: "relu_stage1_block3_norm_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_loc_flat"
  type: "Flatten"
  bottom: "relu_stage1_block3_norm_mbox_loc_perm"
  top: "relu_stage1_block3_norm_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage1_block3_norm_mbox_priorbox"
  type: "PriorBox"
  bottom: "relu_stage1_block3_norm"
  bottom: "data"
  top: "relu_stage1_block3_norm_mbox_priorbox"
  prior_box_param {
    min_size: 30.0
    aspect_ratio: 2
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}
layer {
  name: "relu_stage2_block5_norm"
  type: "Normalize"
  bottom: "eltwise_stage2_block5"
  top: "relu_stage2_block5_norm"
  norm_param {
    across_spatial: false
    scale_filler {
      type: "constant"
      value: 20
    }
    channel_shared: false
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_loc"
  type: "Convolution"
  bottom: "relu_stage2_block5_norm"
  top: "relu_stage2_block5_norm_mbox_loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_loc_perm"
  type: "Permute"
  bottom: "relu_stage2_block5_norm_mbox_loc"
  top: "relu_stage2_block5_norm_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_loc_flat"
  type: "Flatten"
  bottom: "relu_stage2_block5_norm_mbox_loc_perm"
  top: "relu_stage2_block5_norm_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage3_block2_norm"
  type: "Normalize"
  bottom: "eltwise_stage3_block2"
  top: "relu_stage3_block2_norm"
  norm_param {
    across_spatial: false
    scale_filler {
      type: "constant"
      value: 20
    }
    channel_shared: false
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_loc"
  type: "Convolution"
  bottom: "relu_stage3_block2_norm"
  top: "relu_stage3_block2_norm_mbox_loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_loc_perm"
  type: "Permute"
  bottom: "relu_stage3_block2_norm_mbox_loc"
  top: "relu_stage3_block2_norm_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_loc_flat"
  type: "Flatten"
  bottom: "relu_stage3_block2_norm_mbox_loc_perm"
  top: "relu_stage3_block2_norm_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage4_block2_mbox_loc"
  type: "Convolution"
  bottom: "eltwise_stage4_block2"
  top: "relu_stage4_block2_mbox_loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage4_block2_mbox_loc_perm"
  type: "Permute"
  bottom: "relu_stage4_block2_mbox_loc"
  top: "relu_stage4_block2_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage4_block2_mbox_loc_flat"
  type: "Flatten"
  bottom: "relu_stage4_block2_mbox_loc_perm"
  top: "relu_stage4_block2_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage5_block2_mbox_loc"
  type: "Convolution"
  bottom: "eltwise_stage5_block2"
  top: "relu_stage5_block2_mbox_loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage5_block2_mbox_loc_perm"
  type: "Permute"
  bottom: "relu_stage5_block2_mbox_loc"
  top: "relu_stage5_block2_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage5_block2_mbox_loc_flat"
  type: "Flatten"
  bottom: "relu_stage5_block2_mbox_loc_perm"
  top: "relu_stage5_block2_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pool_last_mbox_loc"
  type: "Convolution"
  bottom: "pool_last"
  top: "pool_last_mbox_loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool_last_mbox_loc_perm"
  type: "Permute"
  bottom: "pool_last_mbox_loc"
  top: "pool_last_mbox_loc_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "pool_last_mbox_loc_flat"
  type: "Flatten"
  bottom: "pool_last_mbox_loc_perm"
  top: "pool_last_mbox_loc_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "mbox_loc"
  type: "Concat"
  bottom: "relu_stage1_block3_norm_mbox_loc_flat"
  bottom: "relu_stage2_block5_norm_mbox_loc_flat"
  bottom: "relu_stage3_block2_norm_mbox_loc_flat"
  bottom: "relu_stage4_block2_mbox_loc_flat"
  bottom: "relu_stage5_block2_mbox_loc_flat"
  bottom: "pool_last_mbox_loc_flat"
  top: "mbox_loc"
  concat_param {
    axis: 1
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_conf"
  type: "Convolution"
  bottom: "relu_stage2_block5_norm"
  top: "relu_stage2_block5_norm_mbox_conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 126
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_conf_perm"
  type: "Permute"
  bottom: "relu_stage2_block5_norm_mbox_conf"
  top: "relu_stage2_block5_norm_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_conf_flat"
  type: "Flatten"
  bottom: "relu_stage2_block5_norm_mbox_conf_perm"
  top: "relu_stage2_block5_norm_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_conf"
  type: "Convolution"
  bottom: "relu_stage3_block2_norm"
  top: "relu_stage3_block2_norm_mbox_conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 126
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_conf_perm"
  type: "Permute"
  bottom: "relu_stage3_block2_norm_mbox_conf"
  top: "relu_stage3_block2_norm_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_conf_flat"
  type: "Flatten"
  bottom: "relu_stage3_block2_norm_mbox_conf_perm"
  top: "relu_stage3_block2_norm_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage4_block2_mbox_conf"
  type: "Convolution"
  bottom: "eltwise_stage4_block2"
  top: "relu_stage4_block2_mbox_conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 126
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage4_block2_mbox_conf_perm"
  type: "Permute"
  bottom: "relu_stage4_block2_mbox_conf"
  top: "relu_stage4_block2_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage4_block2_mbox_conf_flat"
  type: "Flatten"
  bottom: "relu_stage4_block2_mbox_conf_perm"
  top: "relu_stage4_block2_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "relu_stage5_block2_mbox_conf"
  type: "Convolution"
  bottom: "eltwise_stage5_block2"
  top: "relu_stage5_block2_mbox_conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 126
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu_stage5_block2_mbox_conf_perm"
  type: "Permute"
  bottom: "relu_stage5_block2_mbox_conf"
  top: "relu_stage5_block2_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "relu_stage5_block2_mbox_conf_flat"
  type: "Flatten"
  bottom: "relu_stage5_block2_mbox_conf_perm"
  top: "relu_stage5_block2_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "pool_last_mbox_conf"
  type: "Convolution"
  bottom: "pool_last"
  top: "pool_last_mbox_conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 126
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool_last_mbox_conf_perm"
  type: "Permute"
  bottom: "pool_last_mbox_conf"
  top: "pool_last_mbox_conf_perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}
layer {
  name: "pool_last_mbox_conf_flat"
  type: "Flatten"
  bottom: "pool_last_mbox_conf_perm"
  top: "pool_last_mbox_conf_flat"
  flatten_param {
    axis: 1
  }
}
layer {
  name: "mbox_conf"
  type: "Concat"
  bottom: "relu_stage1_block3_norm_mbox_conf_flat"
  bottom: "relu_stage2_block5_norm_mbox_conf_flat"
  bottom: "relu_stage3_block2_norm_mbox_conf_flat"
  bottom: "relu_stage4_block2_mbox_conf_flat"
  bottom: "relu_stage5_block2_mbox_conf_flat"
  bottom: "pool_last_mbox_conf_flat"
  top: "mbox_conf"
  concat_param {
    axis: 1
  }
}
layer {
  name: "relu_stage2_block5_norm_mbox_priorbox"
  type: "PriorBox"
  bottom: "relu_stage2_block5_norm"
  bottom: "data"
  top: "relu_stage2_block5_norm_mbox_priorbox"
  prior_box_param {
    min_size: 60.0
    max_size: 111.0
    aspect_ratio: 2
    aspect_ratio: 3
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}
layer {
  name: "relu_stage3_block2_norm_mbox_priorbox"
  type: "PriorBox"
  bottom: "relu_stage3_block2_norm"
  bottom: "data"
  top: "relu_stage3_block2_norm_mbox_priorbox"
  prior_box_param {
    min_size: 111.0
    max_size: 162.0
    aspect_ratio: 2
    aspect_ratio: 3
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}
layer {
  name: "relu_stage4_block2_mbox_priorbox"
  type: "PriorBox"
  bottom: "eltwise_stage4_block2"
  bottom: "data"
  top: "relu_stage4_block2_mbox_priorbox"
  prior_box_param {
    min_size: 162.0
    max_size: 213.0
    aspect_ratio: 2
    aspect_ratio: 3
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}
layer {
  name: "relu_stage5_block2_mbox_priorbox"
  type: "PriorBox"
  bottom: "eltwise_stage5_block2"
  bottom: "data"
  top: "relu_stage5_block2_mbox_priorbox"
  prior_box_param {
    min_size: 213.0
    max_size: 264.0
    aspect_ratio: 2
    aspect_ratio: 3
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}
layer {
  name: "pool_last_mbox_priorbox"
  type: "PriorBox"
  bottom: "pool_last"
  bottom: "data"
  top: "pool_last_mbox_priorbox"
  prior_box_param {
    min_size: 264.0
    max_size: 315.0
    aspect_ratio: 2
    aspect_ratio: 3
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}
layer {
  name: "mbox_priorbox"
  type: "Concat"
  bottom: "relu_stage1_block3_norm_mbox_priorbox"
  bottom: "relu_stage2_block5_norm_mbox_priorbox"
  bottom: "relu_stage3_block2_norm_mbox_priorbox"
  bottom: "relu_stage4_block2_mbox_priorbox"
  bottom: "relu_stage5_block2_mbox_priorbox"
  bottom: "pool_last_mbox_priorbox"
  top: "mbox_priorbox"
  concat_param {
    axis: 2
  }
}
layer {
  name: "mbox_loss"
  type: "MultiBoxLoss"
  bottom: "mbox_loc"
  bottom: "mbox_conf"
  bottom: "mbox_priorbox"
  bottom: "label"
  top: "mbox_loss"
  include {
    phase: TRAIN
  }
  propagate_down: true
  propagate_down: true
  propagate_down: false
  propagate_down: false
  loss_param {
    normalization: VALID
  }
  multibox_loss_param {
    loc_loss_type: SMOOTH_L1
    conf_loss_type: SOFTMAX
    loc_weight: 1.0
    num_classes: 31
    share_location: true
    match_type: PER_PREDICTION
    overlap_threshold: 0.5
    use_prior_for_matching: true
    background_label_id: 0
    use_difficult_gt: true
    do_neg_mining: true
    neg_pos_ratio: 3.0
    neg_overlap: 0.5
    ignore_cross_boundary_bbox: false
    code_type: CENTER_SIZE
  }
}