Triplet_googlenet_train_test.prototxt

name: "sketch_triplet_train_test"
layer {
  name: "pair_data1"
  type: "ImageData"
  top: "pair_data1"
  top: "label1"
  transform_param {
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  image_data_param {
    source: "data/sketch/triplet_sketch_train_finegrain_r2.txt"
    batch_size: 16
    new_height: 256
    new_width: 256
  }
  include: { phase: TRAIN }
}
layer {
  name: "pair_data2"
  type: "ImageData"
  top: "pair_data2"
  top: "label2"
  transform_param {
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123   
  }
  image_data_param {
    source: "data/sketch/triplet_image_pos_train_finegrain_r2.txt"
    batch_size: 16
    new_height: 256
    new_width: 256
  }

  include: { phase: TRAIN }
}

layer {
  name: "pair_data3"
  type: "ImageData"
  top: "pair_data3"
  top: "label3"
  transform_param {
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123   
  }
  image_data_param {
    source: "data/sketch/triplet_image_neg_train_finegrain_r2.txt"
    batch_size: 16
    new_height: 256
    new_width: 256
  }

  include: { phase: TRAIN }
}

layer {
  name: "pair_data1"
  type: "ImageData"
  top: "pair_data1"
  top: "label1"
  image_data_param {
    source: "data/sketch_ori/sketch_test_list_ours.txt"
    batch_size: 1
    new_height: 256
    new_width: 256
  }
  transform_param {
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123  
  }
  include: { phase: TEST }
}
layer {
  name: "pair_data2"
  type: "ImageData"
  top: "pair_data2"
  top: "label2"
  image_data_param {
    source: "data/sketch/imagecat_test_list.txt"
    batch_size: 1
    new_height: 256
    new_width: 256
  }
  transform_param {
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123  
  }
  include: { phase: TEST }
}
layer {
  name: "pair_data3"
  type: "ImageData"
  top: "pair_data3"
  top: "label3"
  image_data_param {
    source: "data/sketch/triplet_image_neg_test.txt"
    batch_size: 1
    new_height: 256
    new_width: 256
  }
  transform_param {
    crop_size: 224
    mean_value: 104
    mean_value: 117
    mean_value: 123  
  }
  include: { phase: TEST }
}
#############################################################################


layer {
  name: "conv1/7x7_s2_s"
  type: "Convolution"
  bottom: "pair_data1"
  top: "conv1/7x7_s2_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/relu_7x7_s"
  type: "ReLU"
  bottom: "conv1/7x7_s2_s"
  top: "conv1/7x7_s2_s"
}
layer {
  name: "pool1/3x3_s2_s"
  type: "Pooling"
  bottom: "conv1/7x7_s2_s"
  top: "pool1/3x3_s2_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "pool1/norm1_s"
  type: "LRN"
  bottom: "pool1/3x3_s2_s"
  top: "pool1/norm1_s"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv2/3x3_reduce_s"
  type: "Convolution"
  bottom: "pool1/norm1_s"
  top: "conv2/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "conv2/3x3_reduce_s"
  top: "conv2/3x3_reduce_s"
}
layer {
  name: "conv2/3x3_s"
  type: "Convolution"
  bottom: "conv2/3x3_reduce_s"
  top: "conv2/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_s"
  type: "ReLU"
  bottom: "conv2/3x3_s"
  top: "conv2/3x3_s"
}
layer {
  name: "conv2/norm2_s"
  type: "LRN"
  bottom: "conv2/3x3_s"
  top: "conv2/norm2_s"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "pool2/3x3_s2_s"
  type: "Pooling"
  bottom: "conv2/norm2_s"
  top: "pool2/3x3_s2_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_3a/1x1_s"
  type: "Convolution"
  bottom: "pool2/3x3_s2_s"
  top: "inception_3a/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_3a/1x1_s"
  top: "inception_3a/1x1_s"
}
layer {
  name: "inception_3a/3x3_reduce_s"
  type: "Convolution"
  bottom: "pool2/3x3_s2_s"
  top: "inception_3a/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_3a/3x3_reduce_s"
  top: "inception_3a/3x3_reduce_s"
}
layer {
  name: "inception_3a/3x3_s"
  type: "Convolution"
  bottom: "inception_3a/3x3_reduce_s"
  top: "inception_3a/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_3a/3x3_s"
  top: "inception_3a/3x3_s"
}
layer {
  name: "inception_3a/5x5_reduce_s"
  type: "Convolution"
  bottom: "pool2/3x3_s2_s"
  top: "inception_3a/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_3a/5x5_reduce_s"
  top: "inception_3a/5x5_reduce_s"
}
layer {
  name: "inception_3a/5x5_s"
  type: "Convolution"
  bottom: "inception_3a/5x5_reduce_s"
  top: "inception_3a/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_3a/5x5_s"
  top: "inception_3a/5x5_s"
}
layer {
  name: "inception_3a/pool_s"
  type: "Pooling"
  bottom: "pool2/3x3_s2_s"
  top: "inception_3a/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3a/pool_proj_s"
  type: "Convolution"
  bottom: "inception_3a/pool_s"
  top: "inception_3a/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_3a/pool_proj_s"
  top: "inception_3a/pool_proj_s"
}
layer {
  name: "inception_3a/output_s"
  type: "Concat"
  bottom: "inception_3a/1x1_s"
  bottom: "inception_3a/3x3_s"
  bottom: "inception_3a/5x5_s"
  bottom: "inception_3a/pool_proj_s"
  top: "inception_3a/output_s"
}
layer {
  name: "inception_3b/1x1_s"
  type: "Convolution"
  bottom: "inception_3a/output_s"
  top: "inception_3b/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_3b/1x1_s"
  top: "inception_3b/1x1_s"
}
layer {
  name: "inception_3b/3x3_reduce_s"
  type: "Convolution"
  bottom: "inception_3a/output_s"
  top: "inception_3b/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_3b/3x3_reduce_s"
  top: "inception_3b/3x3_reduce_s"
}
layer {
  name: "inception_3b/3x3_s"
  type: "Convolution"
  bottom: "inception_3b/3x3_reduce_s"
  top: "inception_3b/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_3b/3x3_s"
  top: "inception_3b/3x3_s"
}
layer {
  name: "inception_3b/5x5_reduce_s"
  type: "Convolution"
  bottom: "inception_3a/output_s"
  top: "inception_3b/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_3b/5x5_reduce_s"
  top: "inception_3b/5x5_reduce_s"
}
layer {
  name: "inception_3b/5x5_s"
  type: "Convolution"
  bottom: "inception_3b/5x5_reduce_s"
  top: "inception_3b/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_3b/5x5_s"
  top: "inception_3b/5x5_s"
}
layer {
  name: "inception_3b/pool_s"
  type: "Pooling"
  bottom: "inception_3a/output_s"
  top: "inception_3b/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3b/pool_proj_s"
  type: "Convolution"
  bottom: "inception_3b/pool_s"
  top: "inception_3b/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_3b/pool_proj_s"
  top: "inception_3b/pool_proj_s"
}
layer {
  name: "inception_3b/output_s"
  type: "Concat"
  bottom: "inception_3b/1x1_s"
  bottom: "inception_3b/3x3_s"
  bottom: "inception_3b/5x5_s"
  bottom: "inception_3b/pool_proj_s"
  top: "inception_3b/output_s"
}
layer {
  name: "pool3/3x3_s2_s"
  type: "Pooling"
  bottom: "inception_3b/output_s"
  top: "pool3/3x3_s2_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_4a/1x1_s"
  type: "Convolution"
  bottom: "pool3/3x3_s2_s"
  top: "inception_4a/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_4a/1x1_s"
  top: "inception_4a/1x1_s"
}
layer {
  name: "inception_4a/3x3_reduce_s"
  type: "Convolution"
  bottom: "pool3/3x3_s2_s"
  top: "inception_4a/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_4a/3x3_reduce_s"
  top: "inception_4a/3x3_reduce_s"
}
layer {
  name: "inception_4a/3x3_s"
  type: "Convolution"
  bottom: "inception_4a/3x3_reduce_s"
  top: "inception_4a/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 208
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_4a/3x3_s"
  top: "inception_4a/3x3_s"
}
layer {
  name: "inception_4a/5x5_reduce_s"
  type: "Convolution"
  bottom: "pool3/3x3_s2_s"
  top: "inception_4a/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_4a/5x5_reduce_s"
  top: "inception_4a/5x5_reduce_s"
}
layer {
  name: "inception_4a/5x5_s"
  type: "Convolution"
  bottom: "inception_4a/5x5_reduce_s"
  top: "inception_4a/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_4a/5x5_s"
  top: "inception_4a/5x5_s"
}
layer {
  name: "inception_4a/pool_s"
  type: "Pooling"
  bottom: "pool3/3x3_s2_s"
  top: "inception_4a/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4a/pool_proj_s"
  type: "Convolution"
  bottom: "inception_4a/pool_s"
  top: "inception_4a/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_4a/pool_proj_s"
  top: "inception_4a/pool_proj_s"
}
layer {
  name: "inception_4a/output_s"
  type: "Concat"
  bottom: "inception_4a/1x1_s"
  bottom: "inception_4a/3x3_s"
  bottom: "inception_4a/5x5_s"
  bottom: "inception_4a/pool_proj_s"
  top: "inception_4a/output_s"
}
layer {
  name: "loss1/ave_pool_s"
  type: "Pooling"
  bottom: "inception_4a/output_s"
  top: "loss1/ave_pool_s"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss1/conv_s"
  type: "Convolution"
  bottom: "loss1/ave_pool_s"
  top: "loss1/conv_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.08
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_conv_s"
  type: "ReLU"
  bottom: "loss1/conv_s"
  top: "loss1/conv_s"
}
layer {
  name: "loss1/fc_s"
  type: "InnerProduct"
  bottom: "loss1/conv_s"
  top: "loss1/fc_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
      std: 0.02
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_fc_s"
  type: "ReLU"
  bottom: "loss1/fc_s"
  top: "loss1/fc_s"
}
layer {
  name: "loss1/drop_fc_s"
  type: "Dropout"
  bottom: "loss1/fc_s"
  top: "loss1/fc_s"
  dropout_param {
    dropout_ratio: 0.7
  }
}
layer {
  name: "inception_4b/1x1_s"
  type: "Convolution"
  bottom: "inception_4a/output_s"
  top: "inception_4b/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_4b/1x1_s"
  top: "inception_4b/1x1_s"
}
layer {
  name: "inception_4b/3x3_reduce_s"
  type: "Convolution"
  bottom: "inception_4a/output_s"
  top: "inception_4b/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_4b/3x3_reduce_s"
  top: "inception_4b/3x3_reduce_s"
}
layer {
  name: "inception_4b/3x3_s"
  type: "Convolution"
  bottom: "inception_4b/3x3_reduce_s"
  top: "inception_4b/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0

  }
  convolution_param {
    num_output: 224
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_4b/3x3_s"
  top: "inception_4b/3x3_s"
}
layer {
  name: "inception_4b/5x5_reduce_s"
  type: "Convolution"
  bottom: "inception_4a/output_s"
  top: "inception_4b/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_4b/5x5_reduce_s"
  top: "inception_4b/5x5_reduce_s"
}
layer {
  name: "inception_4b/5x5_s"
  type: "Convolution"
  bottom: "inception_4b/5x5_reduce_s"
  top: "inception_4b/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_4b/5x5_s"
  top: "inception_4b/5x5_s"
}
layer {
  name: "inception_4b/pool_s"
  type: "Pooling"
  bottom: "inception_4a/output_s"
  top: "inception_4b/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4b/pool_proj_s"
  type: "Convolution"
  bottom: "inception_4b/pool_s"
  top: "inception_4b/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_4b/pool_proj_s"
  top: "inception_4b/pool_proj_s"
}
layer {
  name: "inception_4b/output_s"
  type: "Concat"
  bottom: "inception_4b/1x1_s"
  bottom: "inception_4b/3x3_s"
  bottom: "inception_4b/5x5_s"
  bottom: "inception_4b/pool_proj_s"
  top: "inception_4b/output_s"
}
layer {
  name: "inception_4c/1x1_s"
  type: "Convolution"
  bottom: "inception_4b/output_s"
  top: "inception_4c/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_4c/1x1_s"
  top: "inception_4c/1x1_s"
}
layer {
  name: "inception_4c/3x3_reduce_s"
  type: "Convolution"
  bottom: "inception_4b/output_s"
  top: "inception_4c/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_4c/3x3_reduce_s"
  top: "inception_4c/3x3_reduce_s"
}
layer {
  name: "inception_4c/3x3_s"
  type: "Convolution"
  bottom: "inception_4c/3x3_reduce_s"
  top: "inception_4c/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_4c/3x3_s"
  top: "inception_4c/3x3_s"
}
layer {
  name: "inception_4c/5x5_reduce_s"
  type: "Convolution"
  bottom: "inception_4b/output_s"
  top: "inception_4c/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_4c/5x5_reduce_s"
  top: "inception_4c/5x5_reduce_s"
}
layer {
  name: "inception_4c/5x5_s"
  type: "Convolution"
  bottom: "inception_4c/5x5_reduce_s"
  top: "inception_4c/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_4c/5x5_s"
  top: "inception_4c/5x5_s"
}
layer {
  name: "inception_4c/pool_s"
  type: "Pooling"
  bottom: "inception_4b/output_s"
  top: "inception_4c/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4c/pool_proj_s"
  type: "Convolution"
  bottom: "inception_4c/pool_s"
  top: "inception_4c/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_4c/pool_proj_s"
  top: "inception_4c/pool_proj_s"
}
layer {
  name: "inception_4c/output_s"
  type: "Concat"
  bottom: "inception_4c/1x1_s"
  bottom: "inception_4c/3x3_s"
  bottom: "inception_4c/5x5_s"
  bottom: "inception_4c/pool_proj_s"
  top: "inception_4c/output_s"
}
layer {
  name: "inception_4d/1x1_s"
  type: "Convolution"
  bottom: "inception_4c/output_s"
  top: "inception_4d/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_4d/1x1_s"
  top: "inception_4d/1x1_s"
}
layer {
  name: "inception_4d/3x3_reduce_s"
  type: "Convolution"
  bottom: "inception_4c/output_s"
  top: "inception_4d/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 144
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_4d/3x3_reduce_s"
  top: "inception_4d/3x3_reduce_s"
}
layer {
  name: "inception_4d/3x3_s"
  type: "Convolution"
  bottom: "inception_4d/3x3_reduce_s"
  top: "inception_4d/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 288
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_4d/3x3_s"
  top: "inception_4d/3x3_s"
}
layer {
  name: "inception_4d/5x5_reduce_s"
  type: "Convolution"
  bottom: "inception_4c/output_s"
  top: "inception_4d/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_4d/5x5_reduce_s"
  top: "inception_4d/5x5_reduce_s"
}
layer {
  name: "inception_4d/5x5_s"
  type: "Convolution"
  bottom: "inception_4d/5x5_reduce_s"
  top: "inception_4d/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_4d/5x5_s"
  top: "inception_4d/5x5_s"
}
layer {
  name: "inception_4d/pool_s"
  type: "Pooling"
  bottom: "inception_4c/output_s"
  top: "inception_4d/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4d/pool_proj_s"
  type: "Convolution"
  bottom: "inception_4d/pool_s"
  top: "inception_4d/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_4d/pool_proj_s"
  top: "inception_4d/pool_proj_s"
}
layer {
  name: "inception_4d/output_s"
  type: "Concat"
  bottom: "inception_4d/1x1_s"
  bottom: "inception_4d/3x3_s"
  bottom: "inception_4d/5x5_s"
  bottom: "inception_4d/pool_proj_s"
  top: "inception_4d/output_s"
}
layer {
  name: "loss2/ave_pool_s"
  type: "Pooling"
  bottom: "inception_4d/output_s"
  top: "loss2/ave_pool_s"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss2/conv_s"
  type: "Convolution"
  bottom: "loss2/ave_pool_s"
  top: "loss2/conv_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.08
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_conv_s"
  type: "ReLU"
  bottom: "loss2/conv_s"
  top: "loss2/conv_s"
}
layer {
  name: "loss2/fc_s"
  type: "InnerProduct"
  bottom: "loss2/conv_s"
  top: "loss2/fc_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
      std: 0.02
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_fc_s"
  type: "ReLU"
  bottom: "loss2/fc_s"
  top: "loss2/fc_s"
}
layer {
  name: "loss2/drop_fc_s"
  type: "Dropout"
  bottom: "loss2/fc_s"
  top: "loss2/fc_s"
  dropout_param {
    dropout_ratio: 0.7
  }
}
layer {
  name: "inception_4e/1x1_s"
  type: "Convolution"
  bottom: "inception_4d/output_s"
  top: "inception_4e/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_4e/1x1_s"
  top: "inception_4e/1x1_s"
}
layer {
  name: "inception_4e/3x3_reduce_s"
  type: "Convolution"
  bottom: "inception_4d/output_s"
  top: "inception_4e/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_4e/3x3_reduce_s"
  top: "inception_4e/3x3_reduce_s"
}
layer {
  name: "inception_4e/3x3_s"
  type: "Convolution"
  bottom: "inception_4e/3x3_reduce_s"
  top: "inception_4e/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 320
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_4e/3x3_s"
  top: "inception_4e/3x3_s"
}
layer {
  name: "inception_4e/5x5_reduce_s"
  type: "Convolution"
  bottom: "inception_4d/output_s"
  top: "inception_4e/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_4e/5x5_reduce_s"
  top: "inception_4e/5x5_reduce_s"
}
layer {
  name: "inception_4e/5x5_s"
  type: "Convolution"
  bottom: "inception_4e/5x5_reduce_s"
  top: "inception_4e/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_4e/5x5_s"
  top: "inception_4e/5x5_s"
}
layer {
  name: "inception_4e/pool_s"
  type: "Pooling"
  bottom: "inception_4d/output_s"
  top: "inception_4e/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4e/pool_proj_s"
  type: "Convolution"
  bottom: "inception_4e/pool_s"
  top: "inception_4e/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_4e/pool_proj_s"
  top: "inception_4e/pool_proj_s"
}
layer {
  name: "inception_4e/output_s"
  type: "Concat"
  bottom: "inception_4e/1x1_s"
  bottom: "inception_4e/3x3_s"
  bottom: "inception_4e/5x5_s"
  bottom: "inception_4e/pool_proj_s"
  top: "inception_4e/output_s"
}
layer {
  name: "pool4/3x3_s2_s"
  type: "Pooling"
  bottom: "inception_4e/output_s"
  top: "pool4/3x3_s2_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_5a/1x1_s"
  type: "Convolution"
  bottom: "pool4/3x3_s2_s"
  top: "inception_5a/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_5a/1x1_s"
  top: "inception_5a/1x1_s"
}
layer {
  name: "inception_5a/3x3_reduce_s"
  type: "Convolution"
  bottom: "pool4/3x3_s2_s"
  top: "inception_5a/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_5a/3x3_reduce_s"
  top: "inception_5a/3x3_reduce_s"
}
layer {
  name: "inception_5a/3x3_s"
  type: "Convolution"
  bottom: "inception_5a/3x3_reduce_s"
  top: "inception_5a/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 320
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_5a/3x3_s"
  top: "inception_5a/3x3_s"
}
layer {
  name: "inception_5a/5x5_reduce_s"
  type: "Convolution"
  bottom: "pool4/3x3_s2_s"
  top: "inception_5a/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_5a/5x5_reduce_s"
  top: "inception_5a/5x5_reduce_s"
}
layer {
  name: "inception_5a/5x5_s"
  type: "Convolution"
  bottom: "inception_5a/5x5_reduce_s"
  top: "inception_5a/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_5a/5x5_s"
  top: "inception_5a/5x5_s"
}
layer {
  name: "inception_5a/pool_s"
  type: "Pooling"
  bottom: "pool4/3x3_s2_s"
  top: "inception_5a/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_5a/pool_proj_s"
  type: "Convolution"
  bottom: "inception_5a/pool_s"
  top: "inception_5a/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_5a/pool_proj_s"
  top: "inception_5a/pool_proj_s"
}
layer {
  name: "inception_5a/output_s"
  type: "Concat"
  bottom: "inception_5a/1x1_s"
  bottom: "inception_5a/3x3_s"
  bottom: "inception_5a/5x5_s"
  bottom: "inception_5a/pool_proj_s"
  top: "inception_5a/output_s"
}
layer {
  name: "inception_5b/1x1_s"
  type: "Convolution"
  bottom: "inception_5a/output_s"
  top: "inception_5b/1x1_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_1x1_s"
  type: "ReLU"
  bottom: "inception_5b/1x1_s"
  top: "inception_5b/1x1_s"
}
layer {
  name: "inception_5b/3x3_reduce_s"
  type: "Convolution"
  bottom: "inception_5a/output_s"
  top: "inception_5b/3x3_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_3x3_reduce_s"
  type: "ReLU"
  bottom: "inception_5b/3x3_reduce_s"
  top: "inception_5b/3x3_reduce_s"
}
layer {
  name: "inception_5b/3x3_s"
  type: "Convolution"
  bottom: "inception_5b/3x3_reduce_s"
  top: "inception_5b/3x3_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_3x3_s"
  type: "ReLU"
  bottom: "inception_5b/3x3_s"
  top: "inception_5b/3x3_s"
}
layer {
  name: "inception_5b/5x5_reduce_s"
  type: "Convolution"
  bottom: "inception_5a/output_s"
  top: "inception_5b/5x5_reduce_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_5x5_reduce_s"
  type: "ReLU"
  bottom: "inception_5b/5x5_reduce_s"
  top: "inception_5b/5x5_reduce_s"
}
layer {
  name: "inception_5b/5x5_s"
  type: "Convolution"
  bottom: "inception_5b/5x5_reduce_s"
  top: "inception_5b/5x5_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_5x5_s"
  type: "ReLU"
  bottom: "inception_5b/5x5_s"
  top: "inception_5b/5x5_s"
}
layer {
  name: "inception_5b/pool_s"
  type: "Pooling"
  bottom: "inception_5a/output_s"
  top: "inception_5b/pool_s"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_5b/pool_proj_s"
  type: "Convolution"
  bottom: "inception_5b/pool_s"
  top: "inception_5b/pool_proj_s"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_pool_proj_s"
  type: "ReLU"
  bottom: "inception_5b/pool_proj_s"
  top: "inception_5b/pool_proj_s"
}
layer {
  name: "inception_5b/output_s"
  type: "Concat"
  bottom: "inception_5b/1x1_s"
  bottom: "inception_5b/3x3_s"
  bottom: "inception_5b/5x5_s"
  bottom: "inception_5b/pool_proj_s"
  top: "inception_5b/output_s"
}
layer {
  name: "pool5/7x7_s1_s"
  type: "Pooling"
  bottom: "inception_5b/output_s"
  top: "pool5/7x7_s1_s"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 1
  }
}

#######################################################################################


layer {
  name: "conv1/7x7_s2_p"
  type: "Convolution"
  bottom: "pair_data2"
  top: "conv1/7x7_s2_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "conv1/7x7_s2_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "conv1/7x7_s2_b"
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/relu_7x7_p"
  type: "ReLU"
  bottom: "conv1/7x7_s2_p"
  top: "conv1/7x7_s2_p"
}
layer {
  name: "pool1/3x3_s2_p"
  type: "Pooling"
  bottom: "conv1/7x7_s2_p"
  top: "pool1/3x3_s2_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "pool1/norm1_p"
  type: "LRN"
  bottom: "pool1/3x3_s2_p"
  top: "pool1/norm1_p"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv2/3x3_reduce_p"
  type: "Convolution"
  bottom: "pool1/norm1_p"
  top: "conv2/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "conv2/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "conv2/3x3_reduce_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "conv2/3x3_reduce_p"
  top: "conv2/3x3_reduce_p"
}
layer {
  name: "conv2/3x3_p"
  type: "Convolution"
  bottom: "conv2/3x3_reduce_p"
  top: "conv2/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "conv2/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "conv2/3x3_b"
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_p"
  type: "ReLU"
  bottom: "conv2/3x3_p"
  top: "conv2/3x3_p"
}
layer {
  name: "conv2/norm2_p"
  type: "LRN"
  bottom: "conv2/3x3_p"
  top: "conv2/norm2_p"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "pool2/3x3_s2_p"
  type: "Pooling"
  bottom: "conv2/norm2_p"
  top: "pool2/3x3_s2_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_3a/1x1_p"
  type: "Convolution"
  bottom: "pool2/3x3_s2_p"
  top: "inception_3a/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/1x1_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_3a/1x1_p"
  top: "inception_3a/1x1_p"
}
layer {
  name: "inception_3a/3x3_reduce_p"
  type: "Convolution"
  bottom: "pool2/3x3_s2_p"
  top: "inception_3a/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/3x3_reduce_b"
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_3a/3x3_reduce_p"
  top: "inception_3a/3x3_reduce_p"
}
layer {
  name: "inception_3a/3x3_p"
  type: "Convolution"
  bottom: "inception_3a/3x3_reduce_p"
  top: "inception_3a/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/3x3_b"
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_3a/3x3_p"
  top: "inception_3a/3x3_p"
}
layer {
  name: "inception_3a/5x5_reduce_p"
  type: "Convolution"
  bottom: "pool2/3x3_s2_p"
  top: "inception_3a/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/5x5_reduce_b"
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_3a/5x5_reduce_p"
  top: "inception_3a/5x5_reduce_p"
}
layer {
  name: "inception_3a/5x5_p"
  type: "Convolution"
  bottom: "inception_3a/5x5_reduce_p"
  top: "inception_3a/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/5x5_b"
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_3a/5x5_p"
  top: "inception_3a/5x5_p"
}
layer {
  name: "inception_3a/pool_p"
  type: "Pooling"
  bottom: "pool2/3x3_s2_p"
  top: "inception_3a/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3a/pool_proj_p"
  type: "Convolution"
  bottom: "inception_3a/pool_p"
  top: "inception_3a/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/pool_proj_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_3a/pool_proj_p"
  top: "inception_3a/pool_proj_p"
}
layer {
  name: "inception_3a/output_p"
  type: "Concat"
  bottom: "inception_3a/1x1_p"
  bottom: "inception_3a/3x3_p"
  bottom: "inception_3a/5x5_p"
  bottom: "inception_3a/pool_proj_p"
  top: "inception_3a/output_p"
}
layer {
  name: "inception_3b/1x1_p"
  type: "Convolution"
  bottom: "inception_3a/output_p"
  top: "inception_3b/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/1x1_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_3b/1x1_p"
  top: "inception_3b/1x1_p"
}
layer {
  name: "inception_3b/3x3_reduce_p"
  type: "Convolution"
  bottom: "inception_3a/output_p"
  top: "inception_3b/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/3x3_reduce_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_3b/3x3_reduce_p"
  top: "inception_3b/3x3_reduce_p"
}
layer {
  name: "inception_3b/3x3_p"
  type: "Convolution"
  bottom: "inception_3b/3x3_reduce_p"
  top: "inception_3b/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/3x3_b"
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_3b/3x3_p"
  top: "inception_3b/3x3_p"
}
layer {
  name: "inception_3b/5x5_reduce_p"
  type: "Convolution"
  bottom: "inception_3a/output_p"
  top: "inception_3b/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_3b/5x5_reduce_p"
  top: "inception_3b/5x5_reduce_p"
}
layer {
  name: "inception_3b/5x5_p"
  type: "Convolution"
  bottom: "inception_3b/5x5_reduce_p"
  top: "inception_3b/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/5x5_b"
  }
  convolution_param {
    num_output: 96
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_3b/5x5_p"
  top: "inception_3b/5x5_p"
}
layer {
  name: "inception_3b/pool_p"
  type: "Pooling"
  bottom: "inception_3a/output_p"
  top: "inception_3b/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3b/pool_proj_p"
  type: "Convolution"
  bottom: "inception_3b/pool_p"
  top: "inception_3b/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_3b/pool_proj_p"
  top: "inception_3b/pool_proj_p"
}
layer {
  name: "inception_3b/output_p"
  type: "Concat"
  bottom: "inception_3b/1x1_p"
  bottom: "inception_3b/3x3_p"
  bottom: "inception_3b/5x5_p"
  bottom: "inception_3b/pool_proj_p"
  top: "inception_3b/output_p"
}
layer {
  name: "pool3/3x3_s2_p"
  type: "Pooling"
  bottom: "inception_3b/output_p"
  top: "pool3/3x3_s2_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_4a/1x1_p"
  type: "Convolution"
  bottom: "pool3/3x3_s2_p"
  top: "inception_4a/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/1x1_b"
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_4a/1x1_p"
  top: "inception_4a/1x1_p"
}
layer {
  name: "inception_4a/3x3_reduce_p"
  type: "Convolution"
  bottom: "pool3/3x3_s2_p"
  top: "inception_4a/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/3x3_reduce_b"
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_4a/3x3_reduce_p"
  top: "inception_4a/3x3_reduce_p"
}
layer {
  name: "inception_4a/3x3_p"
  type: "Convolution"
  bottom: "inception_4a/3x3_reduce_p"
  top: "inception_4a/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/3x3_b"
  }
  convolution_param {
    num_output: 208
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_4a/3x3_p"
  top: "inception_4a/3x3_p"
}
layer {
  name: "inception_4a/5x5_reduce_p"
  type: "Convolution"
  bottom: "pool3/3x3_s2_p"
  top: "inception_4a/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/5x5_reduce_b"
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_4a/5x5_reduce_p"
  top: "inception_4a/5x5_reduce_p"
}
layer {
  name: "inception_4a/5x5_p"
  type: "Convolution"
  bottom: "inception_4a/5x5_reduce_p"
  top: "inception_4a/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/5x5_b"
  }
  convolution_param {
    num_output: 48
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_4a/5x5_p"
  top: "inception_4a/5x5_p"
}
layer {
  name: "inception_4a/pool_p"
  type: "Pooling"
  bottom: "pool3/3x3_s2_p"
  top: "inception_4a/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4a/pool_proj_p"
  type: "Convolution"
  bottom: "inception_4a/pool_p"
  top: "inception_4a/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_4a/pool_proj_p"
  top: "inception_4a/pool_proj_p"
}
layer {
  name: "inception_4a/output_p"
  type: "Concat"
  bottom: "inception_4a/1x1_p"
  bottom: "inception_4a/3x3_p"
  bottom: "inception_4a/5x5_p"
  bottom: "inception_4a/pool_proj_p"
  top: "inception_4a/output_p"
}
layer {
  name: "loss1/ave_pool_p"
  type: "Pooling"
  bottom: "inception_4a/output_p"
  top: "loss1/ave_pool_p"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss1/conv_p"
  type: "Convolution"
  bottom: "loss1/ave_pool_p"
  top: "loss1/conv_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss1/conv_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss1/conv_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.08
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_conv_p"
  type: "ReLU"
  bottom: "loss1/conv_p"
  top: "loss1/conv_p"
}
layer {
  name: "loss1/fc_p"
  type: "InnerProduct"
  bottom: "loss1/conv_p"
  top: "loss1/fc_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss1/fc_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss1/fc_b"
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
      std: 0.02
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_fc_p"
  type: "ReLU"
  bottom: "loss1/fc_p"
  top: "loss1/fc_p"
}
layer {
  name: "loss1/drop_fc_p"
  type: "Dropout"
  bottom: "loss1/fc_p"
  top: "loss1/fc_p"
  dropout_param {
    dropout_ratio: 0.7
  }
}

layer {
  name: "inception_4b/1x1_p"
  type: "Convolution"
  bottom: "inception_4a/output_p"
  top: "inception_4b/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/1x1_b"
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_4b/1x1_p"
  top: "inception_4b/1x1_p"
}
layer {
  name: "inception_4b/3x3_reduce_p"
  type: "Convolution"
  bottom: "inception_4a/output_p"
  top: "inception_4b/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/3x3_reduce_b"
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_4b/3x3_reduce_p"
  top: "inception_4b/3x3_reduce_p"
}
layer {
  name: "inception_4b/3x3_p"
  type: "Convolution"
  bottom: "inception_4b/3x3_reduce_p"
  top: "inception_4b/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/3x3_b"

  }
  convolution_param {
    num_output: 224
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_4b/3x3_p"
  top: "inception_4b/3x3_p"
}
layer {
  name: "inception_4b/5x5_reduce_p"
  type: "Convolution"
  bottom: "inception_4a/output_p"
  top: "inception_4b/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/5x5_reduce_b"
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_4b/5x5_reduce_p"
  top: "inception_4b/5x5_reduce_p"
}
layer {
  name: "inception_4b/5x5_p"
  type: "Convolution"
  bottom: "inception_4b/5x5_reduce_p"
  top: "inception_4b/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/5x5_b"
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_4b/5x5_p"
  top: "inception_4b/5x5_p"
}
layer {
  name: "inception_4b/pool_p"
  type: "Pooling"
  bottom: "inception_4a/output_p"
  top: "inception_4b/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4b/pool_proj_p"
  type: "Convolution"
  bottom: "inception_4b/pool_p"
  top: "inception_4b/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_4b/pool_proj_p"
  top: "inception_4b/pool_proj_p"
}
layer {
  name: "inception_4b/output_p"
  type: "Concat"
  bottom: "inception_4b/1x1_p"
  bottom: "inception_4b/3x3_p"
  bottom: "inception_4b/5x5_p"
  bottom: "inception_4b/pool_proj_p"
  top: "inception_4b/output_p"
}
layer {
  name: "inception_4c/1x1_p"
  type: "Convolution"
  bottom: "inception_4b/output_p"
  top: "inception_4c/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "inception_4c/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "inception_4c/1x1_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_4c/1x1_p"
  top: "inception_4c/1x1_p"
}
layer {
  name: "inception_4c/3x3_reduce_p"
  type: "Convolution"
  bottom: "inception_4b/output_p"
  top: "inception_4c/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/3x3_reduce_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_4c/3x3_reduce_p"
  top: "inception_4c/3x3_reduce_p"
}
layer {
  name: "inception_4c/3x3_p"
  type: "Convolution"
  bottom: "inception_4c/3x3_reduce_p"
  top: "inception_4c/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/3x3_b"
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_4c/3x3_p"
  top: "inception_4c/3x3_p"
}
layer {
  name: "inception_4c/5x5_reduce_p"
  type: "Convolution"
  bottom: "inception_4b/output_p"
  top: "inception_4c/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/5x5_reduce_b"
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_4c/5x5_reduce_p"
  top: "inception_4c/5x5_reduce_p"
}
layer {
  name: "inception_4c/5x5_p"
  type: "Convolution"
  bottom: "inception_4c/5x5_reduce_p"
  top: "inception_4c/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/5x5_b"
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_4c/5x5_p"
  top: "inception_4c/5x5_p"
}
layer {
  name: "inception_4c/pool_p"
  type: "Pooling"
  bottom: "inception_4b/output_p"
  top: "inception_4c/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4c/pool_proj_p"
  type: "Convolution"
  bottom: "inception_4c/pool_p"
  top: "inception_4c/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_4c/pool_proj_p"
  top: "inception_4c/pool_proj_p"
}
layer {
  name: "inception_4c/output_p"
  type: "Concat"
  bottom: "inception_4c/1x1_p"
  bottom: "inception_4c/3x3_p"
  bottom: "inception_4c/5x5_p"
  bottom: "inception_4c/pool_proj_p"
  top: "inception_4c/output_p"
}
layer {
  name: "inception_4d/1x1_p"
  type: "Convolution"
  bottom: "inception_4c/output_p"
  top: "inception_4d/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/1x1_b"
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_4d/1x1_p"
  top: "inception_4d/1x1_p"
}
layer {
  name: "inception_4d/3x3_reduce_p"
  type: "Convolution"
  bottom: "inception_4c/output_p"
  top: "inception_4d/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/3x3_reduce_b"
  }
  convolution_param {
    num_output: 144
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_4d/3x3_reduce_p"
  top: "inception_4d/3x3_reduce_p"
}
layer {
  name: "inception_4d/3x3_p"
  type: "Convolution"
  bottom: "inception_4d/3x3_reduce_p"
  top: "inception_4d/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/3x3_b"
  }
  convolution_param {
    num_output: 288
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_4d/3x3_p"
  top: "inception_4d/3x3_p"
}
layer {
  name: "inception_4d/5x5_reduce_p"
  type: "Convolution"
  bottom: "inception_4c/output_p"
  top: "inception_4d/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_4d/5x5_reduce_p"
  top: "inception_4d/5x5_reduce_p"
}
layer {
  name: "inception_4d/5x5_p"
  type: "Convolution"
  bottom: "inception_4d/5x5_reduce_p"
  top: "inception_4d/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/5x5_b"
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_4d/5x5_p"
  top: "inception_4d/5x5_p"
}
layer {
  name: "inception_4d/pool_p"
  type: "Pooling"
  bottom: "inception_4c/output_p"
  top: "inception_4d/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4d/pool_proj_p"
  type: "Convolution"
  bottom: "inception_4d/pool_p"
  top: "inception_4d/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_4d/pool_proj_p"
  top: "inception_4d/pool_proj_p"
}
layer {
  name: "inception_4d/output_p"
  type: "Concat"
  bottom: "inception_4d/1x1_p"
  bottom: "inception_4d/3x3_p"
  bottom: "inception_4d/5x5_p"
  bottom: "inception_4d/pool_proj_p"
  top: "inception_4d/output_p"
}
layer {
  name: "loss2/ave_pool_p"
  type: "Pooling"
  bottom: "inception_4d/output_p"
  top: "loss2/ave_pool_p"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss2/conv_p"
  type: "Convolution"
  bottom: "loss2/ave_pool_p"
  top: "loss2/conv_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss2/conv_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss2/conv_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.08
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_conv_p"
  type: "ReLU"
  bottom: "loss2/conv_p"
  top: "loss2/conv_p"
}
layer {
  name: "loss2/fc_p"
  type: "InnerProduct"
  bottom: "loss2/conv_p"
  top: "loss2/fc_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss2/fc_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss2/fc_b"
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
      std: 0.02
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_fc_p"
  type: "ReLU"
  bottom: "loss2/fc_p"
  top: "loss2/fc_p"
}
layer {
  name: "loss2/drop_fc_p"
  type: "Dropout"
  bottom: "loss2/fc_p"
  top: "loss2/fc_p"
  dropout_param {
    dropout_ratio: 0.7
  }
}

layer {
  name: "inception_4e/1x1_p"
  type: "Convolution"
  bottom: "inception_4d/output_p"
  top: "inception_4e/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/1x1_b"
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_4e/1x1_p"
  top: "inception_4e/1x1_p"
}
layer {
  name: "inception_4e/3x3_reduce_p"
  type: "Convolution"
  bottom: "inception_4d/output_p"
  top: "inception_4e/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/3x3_reduce_b"
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_4e/3x3_reduce_p"
  top: "inception_4e/3x3_reduce_p"
}
layer {
  name: "inception_4e/3x3_p"
  type: "Convolution"
  bottom: "inception_4e/3x3_reduce_p"
  top: "inception_4e/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/3x3_b"
  }
  convolution_param {
    num_output: 320
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_4e/3x3_p"
  top: "inception_4e/3x3_p"
}
layer {
  name: "inception_4e/5x5_reduce_p"
  type: "Convolution"
  bottom: "inception_4d/output_p"
  top: "inception_4e/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_4e/5x5_reduce_p"
  top: "inception_4e/5x5_reduce_p"
}
layer {
  name: "inception_4e/5x5_p"
  type: "Convolution"
  bottom: "inception_4e/5x5_reduce_p"
  top: "inception_4e/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/5x5_b"
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_4e/5x5_p"
  top: "inception_4e/5x5_p"
}
layer {
  name: "inception_4e/pool_p"
  type: "Pooling"
  bottom: "inception_4d/output_p"
  top: "inception_4e/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4e/pool_proj_p"
  type: "Convolution"
  bottom: "inception_4e/pool_p"
  top: "inception_4e/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/pool_proj_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_4e/pool_proj_p"
  top: "inception_4e/pool_proj_p"
}
layer {
  name: "inception_4e/output_p"
  type: "Concat"
  bottom: "inception_4e/1x1_p"
  bottom: "inception_4e/3x3_p"
  bottom: "inception_4e/5x5_p"
  bottom: "inception_4e/pool_proj_p"
  top: "inception_4e/output_p"
}
layer {
  name: "pool4/3x3_s2_p"
  type: "Pooling"
  bottom: "inception_4e/output_p"
  top: "pool4/3x3_s2_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_5a/1x1_p"
  type: "Convolution"
  bottom: "pool4/3x3_s2_p"
  top: "inception_5a/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/1x1_b"
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_5a/1x1_p"
  top: "inception_5a/1x1_p"
}
layer {
  name: "inception_5a/3x3_reduce_p"
  type: "Convolution"
  bottom: "pool4/3x3_s2_p"
  top: "inception_5a/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/3x3_reduce_b"
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_5a/3x3_reduce_p"
  top: "inception_5a/3x3_reduce_p"
}
layer {
  name: "inception_5a/3x3_p"
  type: "Convolution"
  bottom: "inception_5a/3x3_reduce_p"
  top: "inception_5a/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/3x3_b"
  }
  convolution_param {
    num_output: 320
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_5a/3x3_p"
  top: "inception_5a/3x3_p"
}
layer {
  name: "inception_5a/5x5_reduce_p"
  type: "Convolution"
  bottom: "pool4/3x3_s2_p"
  top: "inception_5a/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_5a/5x5_reduce_p"
  top: "inception_5a/5x5_reduce_p"
}
layer {
  name: "inception_5a/5x5_p"
  type: "Convolution"
  bottom: "inception_5a/5x5_reduce_p"
  top: "inception_5a/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/5x5_b"
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_5a/5x5_p"
  top: "inception_5a/5x5_p"
}
layer {
  name: "inception_5a/pool_p"
  type: "Pooling"
  bottom: "pool4/3x3_s2_p"
  top: "inception_5a/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_5a/pool_proj_p"
  type: "Convolution"
  bottom: "inception_5a/pool_p"
  top: "inception_5a/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/pool_proj_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_5a/pool_proj_p"
  top: "inception_5a/pool_proj_p"
}
layer {
  name: "inception_5a/output_p"
  type: "Concat"
  bottom: "inception_5a/1x1_p"
  bottom: "inception_5a/3x3_p"
  bottom: "inception_5a/5x5_p"
  bottom: "inception_5a/pool_proj_p"
  top: "inception_5a/output_p"
}
layer {
  name: "inception_5b/1x1_p"
  type: "Convolution"
  bottom: "inception_5a/output_p"
  top: "inception_5b/1x1_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/1x1_b"
  }
  convolution_param {
    num_output: 384
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_1x1_p"
  type: "ReLU"
  bottom: "inception_5b/1x1_p"
  top: "inception_5b/1x1_p"
}
layer {
  name: "inception_5b/3x3_reduce_p"
  type: "Convolution"
  bottom: "inception_5a/output_p"
  top: "inception_5b/3x3_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/3x3_reduce_b"
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_3x3_reduce_p"
  type: "ReLU"
  bottom: "inception_5b/3x3_reduce_p"
  top: "inception_5b/3x3_reduce_p"
}
layer {
  name: "inception_5b/3x3_p"
  type: "Convolution"
  bottom: "inception_5b/3x3_reduce_p"
  top: "inception_5b/3x3_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/3x3_b"
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_3x3_p"
  type: "ReLU"
  bottom: "inception_5b/3x3_p"
  top: "inception_5b/3x3_p"
}
layer {
  name: "inception_5b/5x5_reduce_p"
  type: "Convolution"
  bottom: "inception_5a/output_p"
  top: "inception_5b/5x5_reduce_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/5x5_reduce_b"
  }
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_5x5_reduce_p"
  type: "ReLU"
  bottom: "inception_5b/5x5_reduce_p"
  top: "inception_5b/5x5_reduce_p"
}
layer {
  name: "inception_5b/5x5_p"
  type: "Convolution"
  bottom: "inception_5b/5x5_reduce_p"
  top: "inception_5b/5x5_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/5x5_b"
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_5x5_p"
  type: "ReLU"
  bottom: "inception_5b/5x5_p"
  top: "inception_5b/5x5_p"
}
layer {
  name: "inception_5b/pool_p"
  type: "Pooling"
  bottom: "inception_5a/output_p"
  top: "inception_5b/pool_p"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_5b/pool_proj_p"
  type: "Convolution"
  bottom: "inception_5b/pool_p"
  top: "inception_5b/pool_proj_p"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/pool_proj_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_pool_proj_p"
  type: "ReLU"
  bottom: "inception_5b/pool_proj_p"
  top: "inception_5b/pool_proj_p"
}
layer {
  name: "inception_5b/output_p"
  type: "Concat"
  bottom: "inception_5b/1x1_p"
  bottom: "inception_5b/3x3_p"
  bottom: "inception_5b/5x5_p"
  bottom: "inception_5b/pool_proj_p"
  top: "inception_5b/output_p"
}
layer {
  name: "pool5/7x7_s1_p"
  type: "Pooling"
  bottom: "inception_5b/output_p"
  top: "pool5/7x7_s1_p"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 1
  }
}

#################################################################

layer {
  name: "conv1/7x7_s2_n"
  type: "Convolution"
  bottom: "pair_data3"
  top: "conv1/7x7_s2_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "conv1/7x7_s2_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "conv1/7x7_s2_b"
  }
  convolution_param {
    num_output: 64
    pad: 3
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv1/relu_7x7_n"
  type: "ReLU"
  bottom: "conv1/7x7_s2_n"
  top: "conv1/7x7_s2_n"
}
layer {
  name: "pool1/3x3_s2_n"
  type: "Pooling"
  bottom: "conv1/7x7_s2_n"
  top: "pool1/3x3_s2_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "pool1/norm1_n"
  type: "LRN"
  bottom: "pool1/3x3_s2_n"
  top: "pool1/norm1_n"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv2/3x3_reduce_n"
  type: "Convolution"
  bottom: "pool1/norm1_n"
  top: "conv2/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "conv2/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "conv2/3x3_reduce_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "conv2/3x3_reduce_n"
  top: "conv2/3x3_reduce_n"
}
layer {
  name: "conv2/3x3_n"
  type: "Convolution"
  bottom: "conv2/3x3_reduce_n"
  top: "conv2/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "conv2/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "conv2/3x3_b"
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "conv2/relu_3x3_n"
  type: "ReLU"
  bottom: "conv2/3x3_n"
  top: "conv2/3x3_n"
}
layer {
  name: "conv2/norm2_n"
  type: "LRN"
  bottom: "conv2/3x3_n"
  top: "conv2/norm2_n"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "pool2/3x3_s2_n"
  type: "Pooling"
  bottom: "conv2/norm2_n"
  top: "pool2/3x3_s2_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_3a/1x1_n"
  type: "Convolution"
  bottom: "pool2/3x3_s2_n"
  top: "inception_3a/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/1x1_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_3a/1x1_n"
  top: "inception_3a/1x1_n"
}
layer {
  name: "inception_3a/3x3_reduce_n"
  type: "Convolution"
  bottom: "pool2/3x3_s2_n"
  top: "inception_3a/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/3x3_reduce_b"
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_3a/3x3_reduce_n"
  top: "inception_3a/3x3_reduce_n"
}
layer {
  name: "inception_3a/3x3_n"
  type: "Convolution"
  bottom: "inception_3a/3x3_reduce_n"
  top: "inception_3a/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/3x3_b"
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_3a/3x3_n"
  top: "inception_3a/3x3_n"
}
layer {
  name: "inception_3a/5x5_reduce_n"
  type: "Convolution"
  bottom: "pool2/3x3_s2_n"
  top: "inception_3a/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/5x5_reduce_b"
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_3a/5x5_reduce_n"
  top: "inception_3a/5x5_reduce_n"
}
layer {
  name: "inception_3a/5x5_n"
  type: "Convolution"
  bottom: "inception_3a/5x5_reduce_n"
  top: "inception_3a/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/5x5_b"
  }
  convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_3a/5x5_n"
  top: "inception_3a/5x5_n"
}
layer {
  name: "inception_3a/pool_n"
  type: "Pooling"
  bottom: "pool2/3x3_s2_n"
  top: "inception_3a/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3a/pool_proj_n"
  type: "Convolution"
  bottom: "inception_3a/pool_n"
  top: "inception_3a/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3a/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3a/pool_proj_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3a/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_3a/pool_proj_n"
  top: "inception_3a/pool_proj_n"
}
layer {
  name: "inception_3a/output_n"
  type: "Concat"
  bottom: "inception_3a/1x1_n"
  bottom: "inception_3a/3x3_n"
  bottom: "inception_3a/5x5_n"
  bottom: "inception_3a/pool_proj_n"
  top: "inception_3a/output_n"
}
layer {
  name: "inception_3b/1x1_n"
  type: "Convolution"
  bottom: "inception_3a/output_n"
  top: "inception_3b/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/1x1_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_3b/1x1_n"
  top: "inception_3b/1x1_n"
}
layer {
  name: "inception_3b/3x3_reduce_n"
  type: "Convolution"
  bottom: "inception_3a/output_n"
  top: "inception_3b/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/3x3_reduce_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_3b/3x3_reduce_n"
  top: "inception_3b/3x3_reduce_n"
}
layer {
  name: "inception_3b/3x3_n"
  type: "Convolution"
  bottom: "inception_3b/3x3_reduce_n"
  top: "inception_3b/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/3x3_b"
  }
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_3b/3x3_n"
  top: "inception_3b/3x3_n"
}
layer {
  name: "inception_3b/5x5_reduce_n"
  type: "Convolution"
  bottom: "inception_3a/output_n"
  top: "inception_3b/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_3b/5x5_reduce_n"
  top: "inception_3b/5x5_reduce_n"
}
layer {
  name: "inception_3b/5x5_n"
  type: "Convolution"
  bottom: "inception_3b/5x5_reduce_n"
  top: "inception_3b/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/5x5_b"
  }
  convolution_param {
    num_output: 96
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_3b/5x5_n"
  top: "inception_3b/5x5_n"
}
layer {
  name: "inception_3b/pool_n"
  type: "Pooling"
  bottom: "inception_3a/output_n"
  top: "inception_3b/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_3b/pool_proj_n"
  type: "Convolution"
  bottom: "inception_3b/pool_n"
  top: "inception_3b/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_3b/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_3b/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_3b/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_3b/pool_proj_n"
  top: "inception_3b/pool_proj_n"
}
layer {
  name: "inception_3b/output_n"
  type: "Concat"
  bottom: "inception_3b/1x1_n"
  bottom: "inception_3b/3x3_n"
  bottom: "inception_3b/5x5_n"
  bottom: "inception_3b/pool_proj_n"
  top: "inception_3b/output_n"
}
layer {
  name: "pool3/3x3_s2_n"
  type: "Pooling"
  bottom: "inception_3b/output_n"
  top: "pool3/3x3_s2_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_4a/1x1_n"
  type: "Convolution"
  bottom: "pool3/3x3_s2_n"
  top: "inception_4a/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/1x1_b"
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_4a/1x1_n"
  top: "inception_4a/1x1_n"
}
layer {
  name: "inception_4a/3x3_reduce_n"
  type: "Convolution"
  bottom: "pool3/3x3_s2_n"
  top: "inception_4a/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/3x3_reduce_b"
  }
  convolution_param {
    num_output: 96
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_4a/3x3_reduce_n"
  top: "inception_4a/3x3_reduce_n"
}
layer {
  name: "inception_4a/3x3_n"
  type: "Convolution"
  bottom: "inception_4a/3x3_reduce_n"
  top: "inception_4a/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/3x3_b"
  }
  convolution_param {
    num_output: 208
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_4a/3x3_n"
  top: "inception_4a/3x3_n"
}
layer {
  name: "inception_4a/5x5_reduce_n"
  type: "Convolution"
  bottom: "pool3/3x3_s2_n"
  top: "inception_4a/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/5x5_reduce_b"
  }
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_4a/5x5_reduce_n"
  top: "inception_4a/5x5_reduce_n"
}
layer {
  name: "inception_4a/5x5_n"
  type: "Convolution"
  bottom: "inception_4a/5x5_reduce_n"
  top: "inception_4a/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/5x5_b"
  }
  convolution_param {
    num_output: 48
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_4a/5x5_n"
  top: "inception_4a/5x5_n"
}
layer {
  name: "inception_4a/pool_n"
  type: "Pooling"
  bottom: "pool3/3x3_s2_n"
  top: "inception_4a/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4a/pool_proj_n"
  type: "Convolution"
  bottom: "inception_4a/pool_n"
  top: "inception_4a/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4a/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4a/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4a/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_4a/pool_proj_n"
  top: "inception_4a/pool_proj_n"
}
layer {
  name: "inception_4a/output_n"
  type: "Concat"
  bottom: "inception_4a/1x1_n"
  bottom: "inception_4a/3x3_n"
  bottom: "inception_4a/5x5_n"
  bottom: "inception_4a/pool_proj_n"
  top: "inception_4a/output_n"
}
layer {
  name: "loss1/ave_pool_n"
  type: "Pooling"
  bottom: "inception_4a/output_n"
  top: "loss1/ave_pool_n"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss1/conv_n"
  type: "Convolution"
  bottom: "loss1/ave_pool_n"
  top: "loss1/conv_n"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss1/conv_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss1/conv_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.08
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_conv_n"
  type: "ReLU"
  bottom: "loss1/conv_n"
  top: "loss1/conv_n"
}
layer {
  name: "loss1/fc_n"
  type: "InnerProduct"
  bottom: "loss1/conv_n"
  top: "loss1/fc_n"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss1/fc_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss1/fc_b"
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
      std: 0.02
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss1/relu_fc_n"
  type: "ReLU"
  bottom: "loss1/fc_n"
  top: "loss1/fc_n"
}
layer {
  name: "loss1/drop_fc_n"
  type: "Dropout"
  bottom: "loss1/fc_n"
  top: "loss1/fc_n"
  dropout_param {
    dropout_ratio: 0.7
  }
}

layer {
  name: "inception_4b/1x1_n"
  type: "Convolution"
  bottom: "inception_4a/output_n"
  top: "inception_4b/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/1x1_b"
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_4b/1x1_n"
  top: "inception_4b/1x1_n"
}
layer {
  name: "inception_4b/3x3_reduce_n"
  type: "Convolution"
  bottom: "inception_4a/output_n"
  top: "inception_4b/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/3x3_reduce_b"
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_4b/3x3_reduce_n"
  top: "inception_4b/3x3_reduce_n"
}
layer {
  name: "inception_4b/3x3_n"
  type: "Convolution"
  bottom: "inception_4b/3x3_reduce_n"
  top: "inception_4b/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/3x3_b"

  }
  convolution_param {
    num_output: 224
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_4b/3x3_n"
  top: "inception_4b/3x3_n"
}
layer {
  name: "inception_4b/5x5_reduce_n"
  type: "Convolution"
  bottom: "inception_4a/output_n"
  top: "inception_4b/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/5x5_reduce_b"
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_4b/5x5_reduce_n"
  top: "inception_4b/5x5_reduce_n"
}
layer {
  name: "inception_4b/5x5_n"
  type: "Convolution"
  bottom: "inception_4b/5x5_reduce_n"
  top: "inception_4b/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/5x5_b"
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_4b/5x5_n"
  top: "inception_4b/5x5_n"
}
layer {
  name: "inception_4b/pool_n"
  type: "Pooling"
  bottom: "inception_4a/output_n"
  top: "inception_4b/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4b/pool_proj_n"
  type: "Convolution"
  bottom: "inception_4b/pool_n"
  top: "inception_4b/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4b/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4b/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4b/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_4b/pool_proj_n"
  top: "inception_4b/pool_proj_n"
}
layer {
  name: "inception_4b/output_n"
  type: "Concat"
  bottom: "inception_4b/1x1_n"
  bottom: "inception_4b/3x3_n"
  bottom: "inception_4b/5x5_n"
  bottom: "inception_4b/pool_proj_n"
  top: "inception_4b/output_n"
}
layer {
  name: "inception_4c/1x1_n"
  type: "Convolution"
  bottom: "inception_4b/output_n"
  top: "inception_4c/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "inception_4c/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "inception_4c/1x1_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_4c/1x1_n"
  top: "inception_4c/1x1_n"
}
layer {
  name: "inception_4c/3x3_reduce_n"
  type: "Convolution"
  bottom: "inception_4b/output_n"
  top: "inception_4c/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/3x3_reduce_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_4c/3x3_reduce_n"
  top: "inception_4c/3x3_reduce_n"
}
layer {
  name: "inception_4c/3x3_n"
  type: "Convolution"
  bottom: "inception_4c/3x3_reduce_n"
  top: "inception_4c/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/3x3_b"
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_4c/3x3_n"
  top: "inception_4c/3x3_n"
}
layer {
  name: "inception_4c/5x5_reduce_n"
  type: "Convolution"
  bottom: "inception_4b/output_n"
  top: "inception_4c/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/5x5_reduce_b"
  }
  convolution_param {
    num_output: 24
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_4c/5x5_reduce_n"
  top: "inception_4c/5x5_reduce_n"
}
layer {
  name: "inception_4c/5x5_n"
  type: "Convolution"
  bottom: "inception_4c/5x5_reduce_n"
  top: "inception_4c/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/5x5_b"
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_4c/5x5_n"
  top: "inception_4c/5x5_n"
}
layer {
  name: "inception_4c/pool_n"
  type: "Pooling"
  bottom: "inception_4b/output_n"
  top: "inception_4c/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4c/pool_proj_n"
  type: "Convolution"
  bottom: "inception_4c/pool_n"
  top: "inception_4c/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4c/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4c/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4c/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_4c/pool_proj_n"
  top: "inception_4c/pool_proj_n"
}
layer {
  name: "inception_4c/output_n"
  type: "Concat"
  bottom: "inception_4c/1x1_n"
  bottom: "inception_4c/3x3_n"
  bottom: "inception_4c/5x5_n"
  bottom: "inception_4c/pool_proj_n"
  top: "inception_4c/output_n"
}
layer {
  name: "inception_4d/1x1_n"
  type: "Convolution"
  bottom: "inception_4c/output_n"
  top: "inception_4d/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/1x1_b"
  }
  convolution_param {
    num_output: 112
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_4d/1x1_n"
  top: "inception_4d/1x1_n"
}
layer {
  name: "inception_4d/3x3_reduce_n"
  type: "Convolution"
  bottom: "inception_4c/output_n"
  top: "inception_4d/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/3x3_reduce_b"
  }
  convolution_param {
    num_output: 144
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_4d/3x3_reduce_n"
  top: "inception_4d/3x3_reduce_n"
}
layer {
  name: "inception_4d/3x3_n"
  type: "Convolution"
  bottom: "inception_4d/3x3_reduce_n"
  top: "inception_4d/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/3x3_b"
  }
  convolution_param {
    num_output: 288
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_4d/3x3_n"
  top: "inception_4d/3x3_n"
}
layer {
  name: "inception_4d/5x5_reduce_n"
  type: "Convolution"
  bottom: "inception_4c/output_n"
  top: "inception_4d/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_4d/5x5_reduce_n"
  top: "inception_4d/5x5_reduce_n"
}
layer {
  name: "inception_4d/5x5_n"
  type: "Convolution"
  bottom: "inception_4d/5x5_reduce_n"
  top: "inception_4d/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/5x5_b"
  }
  convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_4d/5x5_n"
  top: "inception_4d/5x5_n"
}
layer {
  name: "inception_4d/pool_n"
  type: "Pooling"
  bottom: "inception_4c/output_n"
  top: "inception_4d/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4d/pool_proj_n"
  type: "Convolution"
  bottom: "inception_4d/pool_n"
  top: "inception_4d/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4d/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4d/pool_proj_b"
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4d/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_4d/pool_proj_n"
  top: "inception_4d/pool_proj_n"
}
layer {
  name: "inception_4d/output_n"
  type: "Concat"
  bottom: "inception_4d/1x1_n"
  bottom: "inception_4d/3x3_n"
  bottom: "inception_4d/5x5_n"
  bottom: "inception_4d/pool_proj_n"
  top: "inception_4d/output_n"
}
layer {
  name: "loss2/ave_pool_n"
  type: "Pooling"
  bottom: "inception_4d/output_n"
  top: "loss2/ave_pool_n"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 3
  }
}
layer {
  name: "loss2/conv_n"
  type: "Convolution"
  bottom: "loss2/ave_pool_n"
  top: "loss2/conv_n"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss2/conv_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss2/conv_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.08
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_conv_n"
  type: "ReLU"
  bottom: "loss2/conv_n"
  top: "loss2/conv_n"
}
layer {
  name: "loss2/fc_n"
  type: "InnerProduct"
  bottom: "loss2/conv_n"
  top: "loss2/fc_n"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss2/fc_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss2/fc_b"
  }
  inner_product_param {
    num_output: 1024
    weight_filler {
      type: "xavier"
      std: 0.02
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "loss2/relu_fc_n"
  type: "ReLU"
  bottom: "loss2/fc_n"
  top: "loss2/fc_n"
}
layer {
  name: "loss2/drop_fc_n"
  type: "Dropout"
  bottom: "loss2/fc_n"
  top: "loss2/fc_n"
  dropout_param {
    dropout_ratio: 0.7
  }
}

layer {
  name: "inception_4e/1x1_n"
  type: "Convolution"
  bottom: "inception_4d/output_n"
  top: "inception_4e/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/1x1_b"
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_4e/1x1_n"
  top: "inception_4e/1x1_n"
}
layer {
  name: "inception_4e/3x3_reduce_n"
  type: "Convolution"
  bottom: "inception_4d/output_n"
  top: "inception_4e/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/3x3_reduce_b"
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_4e/3x3_reduce_n"
  top: "inception_4e/3x3_reduce_n"
}
layer {
  name: "inception_4e/3x3_n"
  type: "Convolution"
  bottom: "inception_4e/3x3_reduce_n"
  top: "inception_4e/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/3x3_b"
  }
  convolution_param {
    num_output: 320
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_4e/3x3_n"
  top: "inception_4e/3x3_n"
}
layer {
  name: "inception_4e/5x5_reduce_n"
  type: "Convolution"
  bottom: "inception_4d/output_n"
  top: "inception_4e/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_4e/5x5_reduce_n"
  top: "inception_4e/5x5_reduce_n"
}
layer {
  name: "inception_4e/5x5_n"
  type: "Convolution"
  bottom: "inception_4e/5x5_reduce_n"
  top: "inception_4e/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/5x5_b"
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_4e/5x5_n"
  top: "inception_4e/5x5_n"
}
layer {
  name: "inception_4e/pool_n"
  type: "Pooling"
  bottom: "inception_4d/output_n"
  top: "inception_4e/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_4e/pool_proj_n"
  type: "Convolution"
  bottom: "inception_4e/pool_n"
  top: "inception_4e/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_4e/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_4e/pool_proj_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_4e/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_4e/pool_proj_n"
  top: "inception_4e/pool_proj_n"
}
layer {
  name: "inception_4e/output_n"
  type: "Concat"
  bottom: "inception_4e/1x1_n"
  bottom: "inception_4e/3x3_n"
  bottom: "inception_4e/5x5_n"
  bottom: "inception_4e/pool_proj_n"
  top: "inception_4e/output_n"
}
layer {
  name: "pool4/3x3_s2_n"
  type: "Pooling"
  bottom: "inception_4e/output_n"
  top: "pool4/3x3_s2_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "inception_5a/1x1_n"
  type: "Convolution"
  bottom: "pool4/3x3_s2_n"
  top: "inception_5a/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/1x1_b"
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_5a/1x1_n"
  top: "inception_5a/1x1_n"
}
layer {
  name: "inception_5a/3x3_reduce_n"
  type: "Convolution"
  bottom: "pool4/3x3_s2_n"
  top: "inception_5a/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/3x3_reduce_b"
  }
  convolution_param {
    num_output: 160
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_5a/3x3_reduce_n"
  top: "inception_5a/3x3_reduce_n"
}
layer {
  name: "inception_5a/3x3_n"
  type: "Convolution"
  bottom: "inception_5a/3x3_reduce_n"
  top: "inception_5a/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/3x3_b"
  }
  convolution_param {
    num_output: 320
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_5a/3x3_n"
  top: "inception_5a/3x3_n"
}
layer {
  name: "inception_5a/5x5_reduce_n"
  type: "Convolution"
  bottom: "pool4/3x3_s2_n"
  top: "inception_5a/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/5x5_reduce_b"
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_5a/5x5_reduce_n"
  top: "inception_5a/5x5_reduce_n"
}
layer {
  name: "inception_5a/5x5_n"
  type: "Convolution"
  bottom: "inception_5a/5x5_reduce_n"
  top: "inception_5a/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/5x5_b"
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_5a/5x5_n"
  top: "inception_5a/5x5_n"
}
layer {
  name: "inception_5a/pool_n"
  type: "Pooling"
  bottom: "pool4/3x3_s2_n"
  top: "inception_5a/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_5a/pool_proj_n"
  type: "Convolution"
  bottom: "inception_5a/pool_n"
  top: "inception_5a/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5a/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5a/pool_proj_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5a/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_5a/pool_proj_n"
  top: "inception_5a/pool_proj_n"
}
layer {
  name: "inception_5a/output_n"
  type: "Concat"
  bottom: "inception_5a/1x1_n"
  bottom: "inception_5a/3x3_n"
  bottom: "inception_5a/5x5_n"
  bottom: "inception_5a/pool_proj_n"
  top: "inception_5a/output_n"
}
layer {
  name: "inception_5b/1x1_n"
  type: "Convolution"
  bottom: "inception_5a/output_n"
  top: "inception_5b/1x1_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/1x1_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/1x1_b"
  }
  convolution_param {
    num_output: 384
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_1x1_n"
  type: "ReLU"
  bottom: "inception_5b/1x1_n"
  top: "inception_5b/1x1_n"
}
layer {
  name: "inception_5b/3x3_reduce_n"
  type: "Convolution"
  bottom: "inception_5a/output_n"
  top: "inception_5b/3x3_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/3x3_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/3x3_reduce_b"
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.09
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_3x3_reduce_n"
  type: "ReLU"
  bottom: "inception_5b/3x3_reduce_n"
  top: "inception_5b/3x3_reduce_n"
}
layer {
  name: "inception_5b/3x3_n"
  type: "Convolution"
  bottom: "inception_5b/3x3_reduce_n"
  top: "inception_5b/3x3_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/3x3_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/3x3_b"
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_3x3_n"
  type: "ReLU"
  bottom: "inception_5b/3x3_n"
  top: "inception_5b/3x3_n"
}
layer {
  name: "inception_5b/5x5_reduce_n"
  type: "Convolution"
  bottom: "inception_5a/output_n"
  top: "inception_5b/5x5_reduce_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/5x5_reduce_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/5x5_reduce_b"
  }
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.2
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_5x5_reduce_n"
  type: "ReLU"
  bottom: "inception_5b/5x5_reduce_n"
  top: "inception_5b/5x5_reduce_n"
}
layer {
  name: "inception_5b/5x5_n"
  type: "Convolution"
  bottom: "inception_5b/5x5_reduce_n"
  top: "inception_5b/5x5_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/5x5_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/5x5_b"
  }
  convolution_param {
    num_output: 128
    pad: 2
    kernel_size: 5
    weight_filler {
      type: "xavier"
      std: 0.03
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_5x5_n"
  type: "ReLU"
  bottom: "inception_5b/5x5_n"
  top: "inception_5b/5x5_n"
}
layer {
  name: "inception_5b/pool_n"
  type: "Pooling"
  bottom: "inception_5a/output_n"
  top: "inception_5b/pool_n"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}
layer {
  name: "inception_5b/pool_proj_n"
  type: "Convolution"
  bottom: "inception_5b/pool_n"
  top: "inception_5b/pool_proj_n"
  param {
    lr_mult: 1
    decay_mult: 1
name: "inception_5b/pool_proj_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
name: "inception_5b/pool_proj_b"
  }
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "inception_5b/relu_pool_proj_n"
  type: "ReLU"
  bottom: "inception_5b/pool_proj_n"
  top: "inception_5b/pool_proj_n"
}
layer {
  name: "inception_5b/output_n"
  type: "Concat"
  bottom: "inception_5b/1x1_n"
  bottom: "inception_5b/3x3_n"
  bottom: "inception_5b/5x5_n"
  bottom: "inception_5b/pool_proj_n"
  top: "inception_5b/output_n"
}
layer {
  name: "pool5/7x7_s1_n"
  type: "Pooling"
  bottom: "inception_5b/output_n"
  top: "pool5/7x7_s1_n"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 1
  }
}


#################################################################
layer {
  name: "loss1/classifier_sketch_s"
  type: "InnerProduct"
  bottom: "loss1/fc_s"
  top: "loss1/classifier_sketch_s"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss1/classifier_w"	
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss1/classifier_b"	
  }
  inner_product_param {
    num_output: 125
    weight_filler {
      type: "xavier"
      std: 0.0009765625
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "loss1/loss_s"
  type: "SoftmaxWithLoss"
  bottom: "loss1/classifier_sketch_s"
  bottom: "label1"
  top: "loss1/loss1_s"
  loss_weight: 0
}
layer {
  name: "loss1/top-1_s"
  type: "Accuracy"
  bottom: "loss1/classifier_sketch_s"
  bottom: "label1"
  top: "loss1/top-1_s"
  include {
    phase: TEST
  }
}
layer {
  name: "loss1/top-5_s"
  type: "Accuracy"
  bottom: "loss1/classifier_sketch_s"
  bottom: "label1"
  top: "loss1/top-5_s"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}
layer {
  name: "loss2/classifier_sketch_s"
  type: "InnerProduct"
  bottom: "loss2/fc_s"
  top: "loss2/classifier_sketch_s"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss2/classifier_w"	
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss2/classifier_b"	
  }
  inner_product_param {
    num_output: 125 
    weight_filler {
      type: "xavier"
      std: 0.0009765625
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "loss2/loss_s"
  type: "SoftmaxWithLoss"
  bottom: "loss2/classifier_sketch_s"
  bottom: "label1"
  top: "loss2/loss1_s"
  loss_weight: 0
}
layer {
  name: "loss2/top-1_s"
  type: "Accuracy"
  bottom: "loss2/classifier_sketch_s"
  bottom: "label1"
  top: "loss2/top-1_s"
  include {
    phase: TEST
  }
}
layer {
  name: "loss2/top-5_s"
  type: "Accuracy"
  bottom: "loss2/classifier_sketch_s"
  bottom: "label1"
  top: "loss2/top-5_s"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}

#################################################################

layer {
  name: "loss1/classifier_photo_p"
  type: "InnerProduct"
  bottom: "loss1/fc_p"
  top: "loss1/classifier_photo_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss1/classifier_w"	
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss1/classifier_b"	
  }
  inner_product_param {
    num_output: 125
    weight_filler {
      type: "xavier"
      std: 0.0009765625
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "loss1/loss_p"
  type: "SoftmaxWithLoss"
  bottom: "loss1/classifier_photo_p"
  bottom: "label2"
  top: "loss1/loss1_p"
  loss_weight: 0
}
layer {
  name: "loss1/top-1_p"
  type: "Accuracy"
  bottom: "loss1/classifier_photo_p"
  bottom: "label2"
  top: "loss1/top-1_p"
  include {
    phase: TEST
  }
}
layer {
  name: "loss1/top-5_p"
  type: "Accuracy"
  bottom: "loss1/classifier_photo_p"
  bottom: "label2"
  top: "loss1/top-5_p"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}
layer {
  name: "loss2/classifier_photo_p"
  type: "InnerProduct"
  bottom: "loss2/fc_p"
  top: "loss2/classifier_photo_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss2/classifier_w"	
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss2/classifier_b"	
  }
  inner_product_param {
    num_output: 125
    weight_filler {
      type: "xavier"
      std: 0.0009765625
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss2/loss_p"
  type: "SoftmaxWithLoss"
  bottom: "loss2/classifier_photo_p"
  bottom: "label2"
  top: "loss2/loss1_p"
  loss_weight: 0
}
layer {
  name: "loss2/top-1_p"
  type: "Accuracy"
  bottom: "loss2/classifier_photo_p"
  bottom: "label2"
  top: "loss2/top-1_p"
  include {
    phase: TEST
  }
}
layer {
  name: "loss2/top-5_p"
  type: "Accuracy"
  bottom: "loss2/classifier_photo_p"
  bottom: "label2"
  top: "loss2/top-5_p"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}

#################################################################

layer {
  name: "loss3/classifier_sketch_s"
  type: "InnerProduct"
  bottom: "pool5/7x7_s1_s"
  top: "loss3/classifier_sketch_s"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss3/classifier_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss3/classifier_b"
  }
  inner_product_param {
    num_output: 125
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "loss3/loss3_s"
  type: "SoftmaxWithLoss"
  bottom: "loss3/classifier_sketch_s"
  bottom: "label1"
  top: "loss3/loss3_s"
  loss_weight: 10
}
layer {
  name: "loss3/top-1_s"
  type: "Accuracy"
  bottom: "loss3/classifier_sketch_s"
  bottom: "label1"
  top: "loss3/top-1_s"
  include {
    phase: TEST
  }
}
layer {
  name: "loss3/top-5_s"
  type: "Accuracy"
  bottom: "loss3/classifier_sketch_s"
  bottom: "label1"
  top: "loss3/top-5_s"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}
############################################################

layer {
  name: "loss3/classifier_photo_n"
  type: "InnerProduct"
  bottom: "pool5/7x7_s1_n"
  top: "loss3/classifier_photo_n"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss3/classifier_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss3/classifier_b"
  }
  inner_product_param {
    num_output: 125
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss3/loss3_n"
  type: "SoftmaxWithLoss"
  bottom: "loss3/classifier_photo_n"
  bottom: "label3"
  top: "loss3/loss3_n"
  loss_weight: 0
}
layer {
  name: "loss3/top-1_n"
  type: "Accuracy"
  bottom: "loss3/classifier_photo_n"
  bottom: "label3"
  top: "loss3/top-1_n"
  include {
    phase: TEST
  }
}
layer {
  name: "loss3/top-5_n"
  type: "Accuracy"
  bottom: "loss3/classifier_photo_n"
  bottom: "label3"
  top: "loss3/top-5_n"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}

############################################################
layer {
  name: "loss3/classifier_photo_p"
  type: "InnerProduct"
  bottom: "pool5/7x7_s1_p"
  top: "loss3/classifier_photo_p"
  param {
    lr_mult: 1
    decay_mult: 1
	name: "loss3/classifier_w"
  }
  param {
    lr_mult: 2
    decay_mult: 0
	name: "loss3/classifier_b"
  }
  inner_product_param {
    num_output: 125
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "loss3/loss3_p"
  type: "SoftmaxWithLoss"
  bottom: "loss3/classifier_photo_p"
  bottom: "label2"
  top: "loss3/loss3_p"
  loss_weight: 10
}
layer {
  name: "loss3/top-1_p"
  type: "Accuracy"
  bottom: "loss3/classifier_photo_p"
  bottom: "label2"
  top: "loss3/top-1_p"
  include {
    phase: TEST
  }
}
layer {
  name: "loss3/top-5_p"
  type: "Accuracy"
  bottom: "loss3/classifier_photo_p"
  bottom: "label2"
  top: "loss3/top-5_p"
  include {
    phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}

#############################################################

layer {
  name: "fc_s"
  type: "InnerProduct"
  bottom: "pool5/7x7_s1_s"
  top: "fc_s"
  # lr_mult is set to higher than for other layers, because this layer is starting from random while the others are already trained
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}


layer {
  name: "fc_p"
  type: "InnerProduct"
  bottom: "pool5/7x7_s1_p"
  top: "fc_p"
  # lr_mult is set to higher than for other layers, because this layer is starting from random while the others are already trained
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}


layer {
  name: "fc_n"
  type: "InnerProduct"
  bottom: "pool5/7x7_s1_n"
  top: "fc_n"
  # lr_mult is set to higher than for other layers, because this layer is starting from random while the others are already trained
  param {
    lr_mult: 10
    decay_mult: 1
  }
  param {
    lr_mult: 20
    decay_mult: 0
  }
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

#############################################################


layer {
  name: "accuracy1"
  type: "Accuracy"
  bottom: "loss3/classifier_sketch_s"
  bottom: "label1"
  top: "accuracy1"
  include {
    phase: TEST
  }
}
layer {
  name: "accuracy2"
  type: "Accuracy"
  bottom: "loss3/classifier_photo_p"
  bottom: "label2"
  top: "accuracy2"
  include {
    phase: TEST
  }
}
layer {
  name: "accuracy3"
  type: "Accuracy"
  bottom: "loss3/classifier_photo_n"
  bottom: "label3"
  top: "accuracy3"
  include {
    phase: TEST
  }
}
layer {
    name: "euloss"
    type: "EuclideanLoss"
	loss_weight: 0
    bottom: "pool5/7x7_s1_s"
    bottom: "pool5/7x7_s1_n"
    top: "euloss"
}
layer {
    name: "simloss1"
    type: "TripletLoss"
	loss_weight: 0.3
    bottom: "loss1/fc_s"
    bottom: "loss1/fc_p"
    bottom: "loss1/fc_n"
    top: "simloss1"
}
layer {
    name: "simloss1_cont"
    type: "ContrastiveLoss"
	loss_weight: 0
    bottom: "loss1/fc_s"
    bottom: "loss1/fc_p"
    bottom: "label1"
	bottom: "label2"
    top: "simloss1_cont"
}
layer {
    name: "simloss2"
    type: "TripletLoss"
	loss_weight: 0.3
    bottom: "loss2/fc_s"
    bottom: "loss2/fc_p"
    bottom: "loss2/fc_n"
    top: "simloss2"
}
layer {
    name: "simloss2_cont"
    type: "ContrastiveLoss"
	loss_weight: 0
    bottom: "loss2/fc_s"
    bottom: "loss2/fc_p"
    bottom: "label1"
	bottom: "label2"
    top: "simloss2_cont"
}
layer {
    name: "simloss3"
    type: "TripletLoss"
	loss_weight: 1
    triplet_loss_param {
        margin: 15
    }
    bottom: "fc_s"
    bottom: "fc_p"
    bottom: "fc_n"
    top: "simloss3"
}
layer {
    name: "simloss3_cont"
    type: "ContrastiveLoss"
	loss_weight: 0

    bottom: "fc_s"
    bottom: "fc_p"
    bottom: "label1"
	bottom: "label2"
    top: "simloss3_cont"
}