resnetbn_56_bn_after.prototxt

test_iter: 2000
test_interval: 5000
test_initialization: false
base_lr: 0.02
clip_gradients: 100
lr_policy: "step"
gamma: 0.1
stepsize: 100000
display: 20
max_iter: 320000
momentum: 0.9
weight_decay: 0.0001
snapshot: 10000
iter_size: 2
solver_mode: GPU
type: "Nesterov"
snapshot_prefix: "snapshots1/ResNet56_lrwd_lsuv_BN_after"

net_param {
name: "ResNet56"
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
 transform_param {
    force_color: true
    scale: 0.04
    mirror: true
    crop_size: 128
    mean_value: 104
    mean_value: 117
    mean_value: 124
    resize_param {
      prob: 1.0
      resize_mode: FIT_SMALL_SIZE
      height: 144
      width: 144
      pad_mode: MIRRORED
      pad_value: 104
      pad_value: 117
      pad_value: 124
      interp_mode: LINEAR
      center_object: false
      max_angle: 0
    }
  }
  data_param {
    source: "/home/old-ufo/datasets/imagenet/ilsvrc12_train_shuffle_lmdb"
    backend: LMDB
    batch_size: 128
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    force_color: true
    scale: 0.04
    mirror: false
    crop_size: 128
    mean_value: 104
    mean_value: 117
    mean_value: 123
    resize_param {
      prob: 1.0
      resize_mode: FIT_SMALL_SIZE
      height: 144
      width: 144
      pad_mode: MIRRORED
      pad_value: 104
      pad_value: 117
      pad_value: 124
      interp_mode: LINEAR
      center_object: false
      max_angle: 0
    }
  }
  data_param {
    source: "/home/old-ufo/datasets/imagenet/ilsvrc12_val_lmdb"
    backend: LMDB
    batch_size: 25
  }
}
layer {
  name: "block1_conv1"
  type: "Convolution"
  bottom: "data"
  top: "block1_conv1"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 7
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block1_relu1"
  type: "ReLU"
  bottom: "block1_conv1"
  top: "block1_conv1"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block1_conv1_BN"
  type: "BatchNorm"
  bottom: "block1_conv1"
  top: "block1_conv1"
  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
    moving_average_fraction: 0.98
  }
}
layer {
  name: "block1_conv1_max"
  type: "Pooling"
  bottom: "block1_conv1"
  top: "block1_conv1_max"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "block1_conv3"
  type: "Convolution"
  bottom: "block1_conv1_max"
  top: "block1_conv3"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_conv4"
  type: "Convolution"
  bottom: "block1_conv3"
  top: "block2_conv4"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_relu4"
  type: "ReLU"
  bottom: "block2_conv4"
  top: "block2_conv4"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_conv4_BN"
  type: "BatchNorm"
  bottom: "block2_conv4"
  top: "block2_conv4"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv5"
  type: "Convolution"
  bottom: "block2_conv4"
  top: "block2_conv5"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_relu5"
  type: "ReLU"
  bottom: "block2_conv5"
  top: "block2_conv5"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_conv5_BN"
  type: "BatchNorm"
  bottom: "block2_conv5"
  top: "block2_conv5"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv6"
  type: "Convolution"
  bottom: "block2_conv5"
  top: "block2_conv6"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_conv6_eltwise"
  type: "Eltwise"
  bottom: "block2_conv6"
  bottom: "block1_conv3"
  top: "block2_conv6_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block2_relu7"
  type: "ReLU"
  bottom: "block2_conv6_eltwise"
  top: "block2_relu7"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_relu7_BN"
  type: "BatchNorm"
  bottom: "block2_relu7"
  top: "block2_relu7"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv9"
  type: "Convolution"
  bottom: "block2_relu7"
  top: "block2_conv9"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_relu9"
  type: "ReLU"
  bottom: "block2_conv9"
  top: "block2_conv9"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_conv9_BN"
  type: "BatchNorm"
  bottom: "block2_conv9"
  top: "block2_conv9"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv10"
  type: "Convolution"
  bottom: "block2_conv9"
  top: "block2_conv10"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_relu10"
  type: "ReLU"
  bottom: "block2_conv10"
  top: "block2_conv10"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_conv10_BN"
  type: "BatchNorm"
  bottom: "block2_conv10"
  top: "block2_conv10"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv11"
  type: "Convolution"
  bottom: "block2_conv10"
  top: "block2_conv11"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_conv11_eltwise"
  type: "Eltwise"
  bottom: "block2_conv11"
  bottom: "block2_relu7"
  top: "block2_conv11_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block2_relu12"
  type: "ReLU"
  bottom: "block2_conv11_eltwise"
  top: "block2_relu12"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_relu12_BN"
  type: "BatchNorm"
  bottom: "block2_relu12"
  top: "block2_relu12"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv14"
  type: "Convolution"
  bottom: "block2_relu12"
  top: "block2_conv14"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_relu14"
  type: "ReLU"
  bottom: "block2_conv14"
  top: "block2_conv14"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_conv14_BN"
  type: "BatchNorm"
  bottom: "block2_conv14"
  top: "block2_conv14"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv15"
  type: "Convolution"
  bottom: "block2_conv14"
  top: "block2_conv15"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_relu15"
  type: "ReLU"
  bottom: "block2_conv15"
  top: "block2_conv15"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_conv15_BN"
  type: "BatchNorm"
  bottom: "block2_conv15"
  top: "block2_conv15"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv16"
  type: "Convolution"
  bottom: "block2_conv15"
  top: "block2_conv16"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block2_conv16_eltwise"
  type: "Eltwise"
  bottom: "block2_conv16"
  bottom: "block2_relu12"
  top: "block2_conv16_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block2_relu17"
  type: "ReLU"
  bottom: "block2_conv16_eltwise"
  top: "block2_relu17"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block2_relu17_BN"
  type: "BatchNorm"
  bottom: "block2_relu17"
  top: "block2_relu17"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block2_conv19"
  type: "Convolution"
  bottom: "block2_relu17"
  top: "block2_conv19"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_conv20"
  type: "Convolution"
  bottom: "block2_conv19"
  top: "block3_conv20"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu20"
  type: "ReLU"
  bottom: "block3_conv20"
  top: "block3_conv20"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv20_BN"
  type: "BatchNorm"
  bottom: "block3_conv20"
  top: "block3_conv20"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv21"
  type: "Convolution"
  bottom: "block3_conv20"
  top: "block3_conv21"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu21"
  type: "ReLU"
  bottom: "block3_conv21"
  top: "block3_conv21"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv21_BN"
  type: "BatchNorm"
  bottom: "block3_conv21"
  top: "block3_conv21"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv22"
  type: "Convolution"
  bottom: "block3_conv21"
  top: "block3_conv22"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_conv22_eltwise"
  type: "Eltwise"
  bottom: "block3_conv22"
  bottom: "block2_conv19"
  top: "block3_conv22_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block3_relu23"
  type: "ReLU"
  bottom: "block3_conv22_eltwise"
  top: "block3_relu23"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_relu23_BN"
  type: "BatchNorm"
  bottom: "block3_relu23"
  top: "block3_relu23"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv25"
  type: "Convolution"
  bottom: "block3_relu23"
  top: "block3_conv25"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu25"
  type: "ReLU"
  bottom: "block3_conv25"
  top: "block3_conv25"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv25_BN"
  type: "BatchNorm"
  bottom: "block3_conv25"
  top: "block3_conv25"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv26"
  type: "Convolution"
  bottom: "block3_conv25"
  top: "block3_conv26"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu26"
  type: "ReLU"
  bottom: "block3_conv26"
  top: "block3_conv26"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv26_BN"
  type: "BatchNorm"
  bottom: "block3_conv26"
  top: "block3_conv26"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv27"
  type: "Convolution"
  bottom: "block3_conv26"
  top: "block3_conv27"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_conv27_eltwise"
  type: "Eltwise"
  bottom: "block3_conv27"
  bottom: "block3_relu23"
  top: "block3_conv27_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block3_relu28"
  type: "ReLU"
  bottom: "block3_conv27_eltwise"
  top: "block3_relu28"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_relu28_BN"
  type: "BatchNorm"
  bottom: "block3_relu28"
  top: "block3_relu28"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv30"
  type: "Convolution"
  bottom: "block3_relu28"
  top: "block3_conv30"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu30"
  type: "ReLU"
  bottom: "block3_conv30"
  top: "block3_conv30"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv30_BN"
  type: "BatchNorm"
  bottom: "block3_conv30"
  top: "block3_conv30"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv31"
  type: "Convolution"
  bottom: "block3_conv30"
  top: "block3_conv31"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu31"
  type: "ReLU"
  bottom: "block3_conv31"
  top: "block3_conv31"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv31_BN"
  type: "BatchNorm"
  bottom: "block3_conv31"
  top: "block3_conv31"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv32"
  type: "Convolution"
  bottom: "block3_conv31"
  top: "block3_conv32"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_conv32_eltwise"
  type: "Eltwise"
  bottom: "block3_conv32"
  bottom: "block3_relu28"
  top: "block3_conv32_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block3_relu33"
  type: "ReLU"
  bottom: "block3_conv32_eltwise"
  top: "block3_relu33"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_relu33_BN"
  type: "BatchNorm"
  bottom: "block3_relu33"
  top: "block3_relu33"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv35"
  type: "Convolution"
  bottom: "block3_relu33"
  top: "block3_conv35"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu35"
  type: "ReLU"
  bottom: "block3_conv35"
  top: "block3_conv35"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv35_BN"
  type: "BatchNorm"
  bottom: "block3_conv35"
  top: "block3_conv35"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv36"
  type: "Convolution"
  bottom: "block3_conv35"
  top: "block3_conv36"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_relu36"
  type: "ReLU"
  bottom: "block3_conv36"
  top: "block3_conv36"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_conv36_BN"
  type: "BatchNorm"
  bottom: "block3_conv36"
  top: "block3_conv36"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv37"
  type: "Convolution"
  bottom: "block3_conv36"
  top: "block3_conv37"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block3_conv37_eltwise"
  type: "Eltwise"
  bottom: "block3_conv37"
  bottom: "block3_relu33"
  top: "block3_conv37_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block3_relu38"
  type: "ReLU"
  bottom: "block3_conv37_eltwise"
  top: "block3_relu38"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block3_relu38_BN"
  type: "BatchNorm"
  bottom: "block3_relu38"
  top: "block3_relu38"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block3_conv40"
  type: "Convolution"
  bottom: "block3_relu38"
  top: "block3_conv40"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv41"
  type: "Convolution"
  bottom: "block3_conv40"
  top: "block4_conv41"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu41"
  type: "ReLU"
  bottom: "block4_conv41"
  top: "block4_conv41"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv41_BN"
  type: "BatchNorm"
  bottom: "block4_conv41"
  top: "block4_conv41"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv42"
  type: "Convolution"
  bottom: "block4_conv41"
  top: "block4_conv42"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu42"
  type: "ReLU"
  bottom: "block4_conv42"
  top: "block4_conv42"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv42_BN"
  type: "BatchNorm"
  bottom: "block4_conv42"
  top: "block4_conv42"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv43"
  type: "Convolution"
  bottom: "block4_conv42"
  top: "block4_conv43"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv43_eltwise"
  type: "Eltwise"
  bottom: "block4_conv43"
  bottom: "block3_conv40"
  top: "block4_conv43_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block4_relu44"
  type: "ReLU"
  bottom: "block4_conv43_eltwise"
  top: "block4_relu44"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_relu44_BN"
  type: "BatchNorm"
  bottom: "block4_relu44"
  top: "block4_relu44"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv46"
  type: "Convolution"
  bottom: "block4_relu44"
  top: "block4_conv46"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu46"
  type: "ReLU"
  bottom: "block4_conv46"
  top: "block4_conv46"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv46_BN"
  type: "BatchNorm"
  bottom: "block4_conv46"
  top: "block4_conv46"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv47"
  type: "Convolution"
  bottom: "block4_conv46"
  top: "block4_conv47"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu47"
  type: "ReLU"
  bottom: "block4_conv47"
  top: "block4_conv47"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv47_BN"
  type: "BatchNorm"
  bottom: "block4_conv47"
  top: "block4_conv47"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv48"
  type: "Convolution"
  bottom: "block4_conv47"
  top: "block4_conv48"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv48_eltwise"
  type: "Eltwise"
  bottom: "block4_conv48"
  bottom: "block4_relu44"
  top: "block4_conv48_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block4_relu49"
  type: "ReLU"
  bottom: "block4_conv48_eltwise"
  top: "block4_relu49"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_relu49_BN"
  type: "BatchNorm"
  bottom: "block4_relu49"
  top: "block4_relu49"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv51"
  type: "Convolution"
  bottom: "block4_relu49"
  top: "block4_conv51"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu51"
  type: "ReLU"
  bottom: "block4_conv51"
  top: "block4_conv51"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv51_BN"
  type: "BatchNorm"
  bottom: "block4_conv51"
  top: "block4_conv51"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv52"
  type: "Convolution"
  bottom: "block4_conv51"
  top: "block4_conv52"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu52"
  type: "ReLU"
  bottom: "block4_conv52"
  top: "block4_conv52"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv52_BN"
  type: "BatchNorm"
  bottom: "block4_conv52"
  top: "block4_conv52"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv53"
  type: "Convolution"
  bottom: "block4_conv52"
  top: "block4_conv53"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv53_eltwise"
  type: "Eltwise"
  bottom: "block4_conv53"
  bottom: "block4_relu49"
  top: "block4_conv53_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block4_relu54"
  type: "ReLU"
  bottom: "block4_conv53_eltwise"
  top: "block4_relu54"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_relu54_BN"
  type: "BatchNorm"
  bottom: "block4_relu54"
  top: "block4_relu54"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv56"
  type: "Convolution"
  bottom: "block4_relu54"
  top: "block4_conv56"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu56"
  type: "ReLU"
  bottom: "block4_conv56"
  top: "block4_conv56"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv56_BN"
  type: "BatchNorm"
  bottom: "block4_conv56"
  top: "block4_conv56"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv57"
  type: "Convolution"
  bottom: "block4_conv56"
  top: "block4_conv57"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu57"
  type: "ReLU"
  bottom: "block4_conv57"
  top: "block4_conv57"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv57_BN"
  type: "BatchNorm"
  bottom: "block4_conv57"
  top: "block4_conv57"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv58"
  type: "Convolution"
  bottom: "block4_conv57"
  top: "block4_conv58"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv58_eltwise"
  type: "Eltwise"
  bottom: "block4_conv58"
  bottom: "block4_relu54"
  top: "block4_conv58_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block4_relu59"
  type: "ReLU"
  bottom: "block4_conv58_eltwise"
  top: "block4_relu59"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_relu59_BN"
  type: "BatchNorm"
  bottom: "block4_relu59"
  top: "block4_relu59"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv61"
  type: "Convolution"
  bottom: "block4_relu59"
  top: "block4_conv61"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu61"
  type: "ReLU"
  bottom: "block4_conv61"
  top: "block4_conv61"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv61_BN"
  type: "BatchNorm"
  bottom: "block4_conv61"
  top: "block4_conv61"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv62"
  type: "Convolution"
  bottom: "block4_conv61"
  top: "block4_conv62"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu62"
  type: "ReLU"
  bottom: "block4_conv62"
  top: "block4_conv62"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv62_BN"
  type: "BatchNorm"
  bottom: "block4_conv62"
  top: "block4_conv62"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv63"
  type: "Convolution"
  bottom: "block4_conv62"
  top: "block4_conv63"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv63_eltwise"
  type: "Eltwise"
  bottom: "block4_conv63"
  bottom: "block4_relu59"
  top: "block4_conv63_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block4_relu64"
  type: "ReLU"
  bottom: "block4_conv63_eltwise"
  top: "block4_relu64"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_relu64_BN"
  type: "BatchNorm"
  bottom: "block4_relu64"
  top: "block4_relu64"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv66"
  type: "Convolution"
  bottom: "block4_relu64"
  top: "block4_conv66"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu66"
  type: "ReLU"
  bottom: "block4_conv66"
  top: "block4_conv66"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv66_BN"
  type: "BatchNorm"
  bottom: "block4_conv66"
  top: "block4_conv66"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv67"
  type: "Convolution"
  bottom: "block4_conv66"
  top: "block4_conv67"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_relu67"
  type: "ReLU"
  bottom: "block4_conv67"
  top: "block4_conv67"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_conv67_BN"
  type: "BatchNorm"
  bottom: "block4_conv67"
  top: "block4_conv67"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv68"
  type: "Convolution"
  bottom: "block4_conv67"
  top: "block4_conv68"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1024
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block4_conv68_eltwise"
  type: "Eltwise"
  bottom: "block4_conv68"
  bottom: "block4_relu64"
  top: "block4_conv68_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block4_relu69"
  type: "ReLU"
  bottom: "block4_conv68_eltwise"
  top: "block4_relu69"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block4_relu69_BN"
  type: "BatchNorm"
  bottom: "block4_relu69"
  top: "block4_relu69"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block4_conv71"
  type: "Convolution"
  bottom: "block4_relu69"
  top: "block4_conv71"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_conv72"
  type: "Convolution"
  bottom: "block4_conv71"
  top: "block5_conv72"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_relu72"
  type: "ReLU"
  bottom: "block5_conv72"
  top: "block5_conv72"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_conv72_BN"
  type: "BatchNorm"
  bottom: "block5_conv72"
  top: "block5_conv72"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv73"
  type: "Convolution"
  bottom: "block5_conv72"
  top: "block5_conv73"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_relu73"
  type: "ReLU"
  bottom: "block5_conv73"
  top: "block5_conv73"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_conv73_BN"
  type: "BatchNorm"
  bottom: "block5_conv73"
  top: "block5_conv73"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv74"
  type: "Convolution"
  bottom: "block5_conv73"
  top: "block5_conv74"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_conv74_eltwise"
  type: "Eltwise"
  bottom: "block5_conv74"
  bottom: "block4_conv71"
  top: "block5_conv74_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block5_relu75"
  type: "ReLU"
  bottom: "block5_conv74_eltwise"
  top: "block5_relu75"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_relu75_BN"
  type: "BatchNorm"
  bottom: "block5_relu75"
  top: "block5_relu75"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv77"
  type: "Convolution"
  bottom: "block5_relu75"
  top: "block5_conv77"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_relu77"
  type: "ReLU"
  bottom: "block5_conv77"
  top: "block5_conv77"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_conv77_BN"
  type: "BatchNorm"
  bottom: "block5_conv77"
  top: "block5_conv77"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv78"
  type: "Convolution"
  bottom: "block5_conv77"
  top: "block5_conv78"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_relu78"
  type: "ReLU"
  bottom: "block5_conv78"
  top: "block5_conv78"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_conv78_BN"
  type: "BatchNorm"
  bottom: "block5_conv78"
  top: "block5_conv78"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv79"
  type: "Convolution"
  bottom: "block5_conv78"
  top: "block5_conv79"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_conv79_eltwise"
  type: "Eltwise"
  bottom: "block5_conv79"
  bottom: "block5_relu75"
  top: "block5_conv79_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block5_relu80"
  type: "ReLU"
  bottom: "block5_conv79_eltwise"
  top: "block5_relu80"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_relu80_BN"
  type: "BatchNorm"
  bottom: "block5_relu80"
  top: "block5_relu80"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv82"
  type: "Convolution"
  bottom: "block5_relu80"
  top: "block5_conv82"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_relu82"
  type: "ReLU"
  bottom: "block5_conv82"
  top: "block5_conv82"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_conv82_BN"
  type: "BatchNorm"
  bottom: "block5_conv82"
  top: "block5_conv82"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv83"
  type: "Convolution"
  bottom: "block5_conv82"
  top: "block5_conv83"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_relu83"
  type: "ReLU"
  bottom: "block5_conv83"
  top: "block5_conv83"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_conv83_BN"
  type: "BatchNorm"
  bottom: "block5_conv83"
  top: "block5_conv83"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_conv84"
  type: "Convolution"
  bottom: "block5_conv83"
  top: "block5_conv84"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 2048
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "block5_conv84_eltwise"
  type: "Eltwise"
  bottom: "block5_conv84"
  bottom: "block5_relu80"
  top: "block5_conv84_eltwise"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "block5_relu85"
  type: "ReLU"
  bottom: "block5_conv84_eltwise"
  top: "block5_relu85"
  relu_param {
    negative_slope: 0
  }
}
layer {
  name: "block5_relu85_BN"
  type: "BatchNorm"
  bottom: "block5_relu85"
  top: "block5_relu85"
  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
    moving_average_fraction: 0.95
  }
}
layer {
  name: "block5_relu85_global_ave"
  type: "Pooling"
  bottom: "block5_relu85"
  top: "block5_relu85_global_ave"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "final_conv88"
  type: "Convolution"
  bottom: "block5_relu85_global_ave"
  top: "final_conv88"
  param {
    decay_mult: 1
  }
  param {
    decay_mult: 0
  }
  convolution_param {
    num_output: 1000
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "final_conv88"
  bottom: "label"
  top: "loss"
  loss_weight: 1
}
layer {
  name: "acc"
  type: "Accuracy"
  bottom: "final_conv88"
  bottom: "label"
  top: "acc"
}
}