SqueezeNet的Caffe实现

1.SqueezeNet-train_val.prototxt

layer {

  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    crop_size: 227
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "../SqueezeNet-Residual/hand_train_lmdb"
    batch_size: 128
    backend: LMDB
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    crop_size: 227
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "../SqueezeNet-Residual/hand_val_lmdb"
    batch_size: 64 #not *iter_size
    backend: LMDB
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "relu_conv1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "fire2/squeeze1x1"
  type: "Convolution"
  bottom: "pool1"
  top: "fire2/squeeze1x1"
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire2/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire2/squeeze1x1"
  top: "fire2/squeeze1x1"
}
layer {
  name: "fire2/expand1x1"
  type: "Convolution"
  bottom: "fire2/squeeze1x1"
  top: "fire2/expand1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire2/relu_expand1x1"
  type: "ReLU"
  bottom: "fire2/expand1x1"
  top: "fire2/expand1x1"
}
layer {
  name: "fire2/expand3x3"
  type: "Convolution"
  bottom: "fire2/squeeze1x1"
  top: "fire2/expand3x3"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire2/relu_expand3x3"
  type: "ReLU"
  bottom: "fire2/expand3x3"
  top: "fire2/expand3x3"
}
layer {
  name: "fire2/concat"
  type: "Concat"
  bottom: "fire2/expand1x1"
  bottom: "fire2/expand3x3"
  top: "fire2/concat"
}
layer {
  name: "fire3/squeeze1x1"
  type: "Convolution"
  bottom: "fire2/concat"
  top: "fire3/squeeze1x1"
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire3/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire3/squeeze1x1"
  top: "fire3/squeeze1x1"
}
layer {
  name: "fire3/expand1x1"
  type: "Convolution"
  bottom: "fire3/squeeze1x1"
  top: "fire3/expand1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire3/relu_expand1x1"
  type: "ReLU"
  bottom: "fire3/expand1x1"
  top: "fire3/expand1x1"
}
layer {
  name: "fire3/expand3x3"
  type: "Convolution"
  bottom: "fire3/squeeze1x1"
  top: "fire3/expand3x3"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire3/relu_expand3x3"
  type: "ReLU"
  bottom: "fire3/expand3x3"
  top: "fire3/expand3x3"
}
layer {
  name: "fire3/concat"
  type: "Concat"
  bottom: "fire3/expand1x1"
  bottom: "fire3/expand3x3"
  top: "fire3/concat"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "fire3/concat"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "fire4/squeeze1x1"
  type: "Convolution"
  bottom: "pool3"
  top: "fire4/squeeze1x1"
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire4/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire4/squeeze1x1"
  top: "fire4/squeeze1x1"
}
layer {
  name: "fire4/expand1x1"
  type: "Convolution"
  bottom: "fire4/squeeze1x1"
  top: "fire4/expand1x1"
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire4/relu_expand1x1"
  type: "ReLU"
  bottom: "fire4/expand1x1"
  top: "fire4/expand1x1"
}
layer {
  name: "fire4/expand3x3"
  type: "Convolution"
  bottom: "fire4/squeeze1x1"
  top: "fire4/expand3x3"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire4/relu_expand3x3"
  type: "ReLU"
  bottom: "fire4/expand3x3"
  top: "fire4/expand3x3"
}
layer {
  name: "fire4/concat"
  type: "Concat"
  bottom: "fire4/expand1x1"
  bottom: "fire4/expand3x3"
  top: "fire4/concat"
}
layer {
  name: "fire5/squeeze1x1"
  type: "Convolution"
  bottom: "fire4/concat"
  top: "fire5/squeeze1x1"
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire5/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire5/squeeze1x1"
  top: "fire5/squeeze1x1"
}
layer {
  name: "fire5/expand1x1"
  type: "Convolution"
  bottom: "fire5/squeeze1x1"
  top: "fire5/expand1x1"
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire5/relu_expand1x1"
  type: "ReLU"
  bottom: "fire5/expand1x1"
  top: "fire5/expand1x1"
}
layer {
  name: "fire5/expand3x3"
  type: "Convolution"
  bottom: "fire5/squeeze1x1"
  top: "fire5/expand3x3"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire5/relu_expand3x3"
  type: "ReLU"
  bottom: "fire5/expand3x3"
  top: "fire5/expand3x3"
}
layer {
  name: "fire5/concat"
  type: "Concat"
  bottom: "fire5/expand1x1"
  bottom: "fire5/expand3x3"
  top: "fire5/concat"
}
layer {
  name: "pool5"
  type: "Pooling"
  bottom: "fire5/concat"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "fire6/squeeze1x1"
  type: "Convolution"
  bottom: "pool5"
  top: "fire6/squeeze1x1"
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire6/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire6/squeeze1x1"
  top: "fire6/squeeze1x1"
}
layer {
  name: "fire6/expand1x1"
  type: "Convolution"
  bottom: "fire6/squeeze1x1"
  top: "fire6/expand1x1"
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire6/relu_expand1x1"
  type: "ReLU"
  bottom: "fire6/expand1x1"
  top: "fire6/expand1x1"
}
layer {
  name: "fire6/expand3x3"
  type: "Convolution"
  bottom: "fire6/squeeze1x1"
  top: "fire6/expand3x3"
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire6/relu_expand3x3"
  type: "ReLU"
  bottom: "fire6/expand3x3"
  top: "fire6/expand3x3"
}
layer {
  name: "fire6/concat"
  type: "Concat"
  bottom: "fire6/expand1x1"
  bottom: "fire6/expand3x3"
  top: "fire6/concat"
}
layer {
  name: "fire7/squeeze1x1"
  type: "Convolution"
  bottom: "fire6/concat"
  top: "fire7/squeeze1x1"
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire7/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire7/squeeze1x1"
  top: "fire7/squeeze1x1"
}
layer {
  name: "fire7/expand1x1"
  type: "Convolution"
  bottom: "fire7/squeeze1x1"
  top: "fire7/expand1x1"
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire7/relu_expand1x1"
  type: "ReLU"
  bottom: "fire7/expand1x1"
  top: "fire7/expand1x1"
}
layer {
  name: "fire7/expand3x3"
  type: "Convolution"
  bottom: "fire7/squeeze1x1"
  top: "fire7/expand3x3"
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire7/relu_expand3x3"
  type: "ReLU"
  bottom: "fire7/expand3x3"
  top: "fire7/expand3x3"
}
layer {
  name: "fire7/concat"
  type: "Concat"
  bottom: "fire7/expand1x1"
  bottom: "fire7/expand3x3"
  top: "fire7/concat"
}
layer {
  name: "fire8/squeeze1x1"
  type: "Convolution"
  bottom: "fire7/concat"
  top: "fire8/squeeze1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire8/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire8/squeeze1x1"
  top: "fire8/squeeze1x1"
}
layer {
  name: "fire8/expand1x1"
  type: "Convolution"
  bottom: "fire8/squeeze1x1"
  top: "fire8/expand1x1"
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire8/relu_expand1x1"
  type: "ReLU"
  bottom: "fire8/expand1x1"
  top: "fire8/expand1x1"
}
layer {
  name: "fire8/expand3x3"
  type: "Convolution"
  bottom: "fire8/squeeze1x1"
  top: "fire8/expand3x3"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire8/relu_expand3x3"
  type: "ReLU"
  bottom: "fire8/expand3x3"
  top: "fire8/expand3x3"
}
layer {
  name: "fire8/concat"
  type: "Concat"
  bottom: "fire8/expand1x1"
  bottom: "fire8/expand3x3"
  top: "fire8/concat"
}
layer {
  name: "fire9/squeeze1x1"
  type: "Convolution"
  bottom: "fire8/concat"
  top: "fire9/squeeze1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire9/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire9/squeeze1x1"
  top: "fire9/squeeze1x1"
}
layer {
  name: "fire9/expand1x1_z"
  type: "Convolution"
  bottom: "fire9/squeeze1x1"
  top: "fire9/expand1x1_z"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire9/relu_expand1x1"
  type: "ReLU"
  bottom: "fire9/expand1x1_z"
  top: "fire9/expand1x1_z"
}
layer {
  name: "fire9/expand3x3_z"
  type: "Convolution"
  bottom: "fire9/squeeze1x1"
  top: "fire9/expand3x3_z"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire9/relu_expand3x3"
  type: "ReLU"
  bottom: "fire9/expand3x3_z"
  top: "fire9/expand3x3_z"
}
layer {
  name: "fire9/concat"
  type: "Concat"
  bottom: "fire9/expand1x1_z"
  bottom: "fire9/expand3x3_z"
  top: "fire9/concat"
}
layer {
  name: "drop9"
  type: "Dropout"
  bottom: "fire9/concat"
  top: "fire9/concat"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "conv10_add"
  type: "Convolution"
  bottom: "fire9/concat"
  top: "conv10_add"
  convolution_param {
    num_output: 6809
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      mean: 0.0
      std: 0.01
    }
  }
}
layer {
  name: "relu_conv10"
  type: "ReLU"
  bottom: "conv10_add"
  top: "conv10_add"
}
layer {
  name: "pool10"
  type: "Pooling"
  bottom: "conv10_add"
  top: "pool10"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "pool10"
  bottom: "label"
  top: "loss"
  #include {
  #  phase: TRAIN
  #}
}
layer {
  name: "accuracy"
  type: "Accuracy"
  bottom: "pool10"
  bottom: "label"
  top: "accuracy"
  #include {
  #  phase: TEST
  #}
}
layer {
  name: "accuracy_top5"
  type: "Accuracy"
  bottom: "pool10"
  bottom: "label"
  top: "accuracy_top5"
  #include {
  #  phase: TEST
  #}
  accuracy_param {
    top_k: 5
  }
}
layer {
  name: "accuracy_top10"
  type: "Accuracy"
  bottom: "pool10"
  bottom: "label"
  top: "accuracy_top10"
  #include {
  #  phase: TEST
  #}
  accuracy_param {
    top_k: 10
  }

}

2.SqueezeNet-Residual-train_val.prototxt

layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    crop_size: 227
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "hand_train_lmdb"
    batch_size: 80
    backend: LMDB
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    mirror: false
    crop_size: 227
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  data_param {
    source: "hand_val_lmdb"
    batch_size: 64
    backend: LMDB
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 96
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "relu_conv1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "fire2/squeeze1x1"
  type: "Convolution"
  bottom: "pool1"
  top: "fire2/squeeze1x1"
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire2/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire2/squeeze1x1"
  top: "fire2/squeeze1x1"
}
layer {
  name: "fire2/expand1x1"
  type: "Convolution"
  bottom: "fire2/squeeze1x1"
  top: "fire2/expand1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire2/relu_expand1x1"
  type: "ReLU"
  bottom: "fire2/expand1x1"
  top: "fire2/expand1x1"
}
layer {
  name: "fire2/expand3x3"
  type: "Convolution"
  bottom: "fire2/squeeze1x1"
  top: "fire2/expand3x3"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire2/relu_expand3x3"
  type: "ReLU"
  bottom: "fire2/expand3x3"
  top: "fire2/expand3x3"
}
layer {
  name: "fire2/concat"
  type: "Concat"
  bottom: "fire2/expand1x1"
  bottom: "fire2/expand3x3"
  top: "fire2/concat"
}


#fire2 ends: 128 channels
layer {
  name: "fire3/squeeze1x1"
  type: "Convolution"
  bottom: "fire2/concat"
  top: "fire3/squeeze1x1"
  convolution_param {
    num_output: 16
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire3/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire3/squeeze1x1"
  top: "fire3/squeeze1x1"
}
layer {
  name: "fire3/expand1x1"
  type: "Convolution"
  bottom: "fire3/squeeze1x1"
  top: "fire3/expand1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire3/relu_expand1x1"
  type: "ReLU"
  bottom: "fire3/expand1x1"
  top: "fire3/expand1x1"
}
layer {
  name: "fire3/expand3x3"
  type: "Convolution"
  bottom: "fire3/squeeze1x1"
  top: "fire3/expand3x3"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire3/relu_expand3x3"
  type: "ReLU"
  bottom: "fire3/expand3x3"
  top: "fire3/expand3x3"
}
layer {
  name: "fire3/concat"
  type: "Concat"
  bottom: "fire3/expand1x1"
  bottom: "fire3/expand3x3"
  top: "fire3/concat"
}


#fire3 ends: 128 channels


layer {
  name: "bypass_23"
  type: "Eltwise"
  bottom: "fire2/concat"
  bottom: "fire3/concat"
  top: "fire3_EltAdd"
}




layer {
  name: "fire4/squeeze1x1"
  type: "Convolution"
  bottom: "fire3_EltAdd"
  top: "fire4/squeeze1x1"
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire4/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire4/squeeze1x1"
  top: "fire4/squeeze1x1"
}
layer {
  name: "fire4/expand1x1"
  type: "Convolution"
  bottom: "fire4/squeeze1x1"
  top: "fire4/expand1x1"
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire4/relu_expand1x1"
  type: "ReLU"
  bottom: "fire4/expand1x1"
  top: "fire4/expand1x1"
}
layer {
  name: "fire4/expand3x3"
  type: "Convolution"
  bottom: "fire4/squeeze1x1"
  top: "fire4/expand3x3"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire4/relu_expand3x3"
  type: "ReLU"
  bottom: "fire4/expand3x3"
  top: "fire4/expand3x3"
}
layer {
  name: "fire4/concat"
  type: "Concat"
  bottom: "fire4/expand1x1"
  bottom: "fire4/expand3x3"
  top: "fire4/concat"
}
#fire4 ends: 256 channels


layer {
  name: "pool4"
  type: "Pooling"
  bottom: "fire4/concat"
  top: "pool4"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
#fire4 ends: 256 channels / pooled
layer {
  name: "fire5/squeeze1x1"
  type: "Convolution"
  bottom: "pool4"
  top: "fire5/squeeze1x1"
  convolution_param {
    num_output: 32
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire5/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire5/squeeze1x1"
  top: "fire5/squeeze1x1"
}
layer {
  name: "fire5/expand1x1"
  type: "Convolution"
  bottom: "fire5/squeeze1x1"
  top: "fire5/expand1x1"
  convolution_param {
    num_output: 128
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire5/relu_expand1x1"
  type: "ReLU"
  bottom: "fire5/expand1x1"
  top: "fire5/expand1x1"
}
layer {
  name: "fire5/expand3x3"
  type: "Convolution"
  bottom: "fire5/squeeze1x1"
  top: "fire5/expand3x3"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire5/relu_expand3x3"
  type: "ReLU"
  bottom: "fire5/expand3x3"
  top: "fire5/expand3x3"
}
layer {
  name: "fire5/concat"
  type: "Concat"
  bottom: "fire5/expand1x1"
  bottom: "fire5/expand3x3"
  top: "fire5/concat"
}


#fire5 ends: 256 channels
layer {
  name: "bypass_45"
  type: "Eltwise"
  bottom: "pool4"
  bottom: "fire5/concat"
  top: "fire5_EltAdd"
}




layer {
  name: "fire6/squeeze1x1"
  type: "Convolution"
  bottom: "fire5_EltAdd"
  top: "fire6/squeeze1x1"
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire6/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire6/squeeze1x1"
  top: "fire6/squeeze1x1"
}
layer {
  name: "fire6/expand1x1"
  type: "Convolution"
  bottom: "fire6/squeeze1x1"
  top: "fire6/expand1x1"
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire6/relu_expand1x1"
  type: "ReLU"
  bottom: "fire6/expand1x1"
  top: "fire6/expand1x1"
}
layer {
  name: "fire6/expand3x3"
  type: "Convolution"
  bottom: "fire6/squeeze1x1"
  top: "fire6/expand3x3"
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire6/relu_expand3x3"
  type: "ReLU"
  bottom: "fire6/expand3x3"
  top: "fire6/expand3x3"
}
layer {
  name: "fire6/concat"
  type: "Concat"
  bottom: "fire6/expand1x1"
  bottom: "fire6/expand3x3"
  top: "fire6/concat"
}
#fire6 ends: 384 channels


layer {
  name: "fire7/squeeze1x1"
  type: "Convolution"
  bottom: "fire6/concat"
  top: "fire7/squeeze1x1"
  convolution_param {
    num_output: 48
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire7/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire7/squeeze1x1"
  top: "fire7/squeeze1x1"
}
layer {
  name: "fire7/expand1x1"
  type: "Convolution"
  bottom: "fire7/squeeze1x1"
  top: "fire7/expand1x1"
  convolution_param {
    num_output: 192
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire7/relu_expand1x1"
  type: "ReLU"
  bottom: "fire7/expand1x1"
  top: "fire7/expand1x1"
}
layer {
  name: "fire7/expand3x3"
  type: "Convolution"
  bottom: "fire7/squeeze1x1"
  top: "fire7/expand3x3"
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire7/relu_expand3x3"
  type: "ReLU"
  bottom: "fire7/expand3x3"
  top: "fire7/expand3x3"
}
layer {
  name: "fire7/concat"
  type: "Concat"
  bottom: "fire7/expand1x1"
  bottom: "fire7/expand3x3"
  top: "fire7/concat"
}
#fire7 ends: 384 channels
layer {
  name: "bypass_67"
  type: "Eltwise"
  bottom: "fire6/concat"
  bottom: "fire7/concat"
  top: "fire7_EltAdd"
}






layer {
  name: "fire8/squeeze1x1"
  type: "Convolution"
  bottom: "fire7_EltAdd"
  top: "fire8/squeeze1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire8/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire8/squeeze1x1"
  top: "fire8/squeeze1x1"
}
layer {
  name: "fire8/expand1x1"
  type: "Convolution"
  bottom: "fire8/squeeze1x1"
  top: "fire8/expand1x1"
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire8/relu_expand1x1"
  type: "ReLU"
  bottom: "fire8/expand1x1"
  top: "fire8/expand1x1"
}
layer {
  name: "fire8/expand3x3"
  type: "Convolution"
  bottom: "fire8/squeeze1x1"
  top: "fire8/expand3x3"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire8/relu_expand3x3"
  type: "ReLU"
  bottom: "fire8/expand3x3"
  top: "fire8/expand3x3"
}
layer {
  name: "fire8/concat"
  type: "Concat"
  bottom: "fire8/expand1x1"
  bottom: "fire8/expand3x3"
  top: "fire8/concat"
}
#fire8 ends: 512 channels


layer {
  name: "pool8"
  type: "Pooling"
  bottom: "fire8/concat"
  top: "pool8"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
#fire8 ends: 512 channels
layer {
  name: "fire9/squeeze1x1"
  type: "Convolution"
  bottom: "pool8"
  top: "fire9/squeeze1x1"
  convolution_param {
    num_output: 64
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire9/relu_squeeze1x1"
  type: "ReLU"
  bottom: "fire9/squeeze1x1"
  top: "fire9/squeeze1x1"
}
layer {
  name: "fire9/expand1x1"
  type: "Convolution"
  bottom: "fire9/squeeze1x1"
  top: "fire9/expand1x1"
  convolution_param {
    num_output: 256
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire9/relu_expand1x1"
  type: "ReLU"
  bottom: "fire9/expand1x1"
  top: "fire9/expand1x1"
}
layer {
  name: "fire9/expand3x3"
  type: "Convolution"
  bottom: "fire9/squeeze1x1"
  top: "fire9/expand3x3"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
  }
}
layer {
  name: "fire9/relu_expand3x3"
  type: "ReLU"
  bottom: "fire9/expand3x3"
  top: "fire9/expand3x3"
}
layer {
  name: "fire9/concat"
  type: "Concat"
  bottom: "fire9/expand1x1"
  bottom: "fire9/expand3x3"
  top: "fire9/concat"
}
#fire9 ends: 512 channels
layer {
  name: "bypass_89"
  type: "Eltwise"
  bottom: "pool8"
  bottom: "fire9/concat"
  top: "fire9_EltAdd"
}






layer {
  name: "drop9"
  type: "Dropout"
  bottom: "fire9_EltAdd"
  top: "fire9_EltAdd"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "conv10_add"
  type: "Convolution"
  bottom: "fire9_EltAdd"
  top: "conv10_add"
  convolution_param {
    num_output: 6809
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      mean: 0.0
      std: 0.01
    }
  }
}
layer {
  name: "relu_conv10_add"
  type: "ReLU"
  bottom: "conv10_add"
  top: "conv10_add"
}
layer {
  name: "pool10_add"
  type: "Pooling"
  bottom: "conv10_add"
  top: "pool10_add"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}




# loss, top1, top5
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "pool10_add"
  bottom: "label"
  top: "loss"
  include {
#    phase: TRAIN
  }
}
layer {
  name: "accuracy_top1"
  type: "Accuracy"
  bottom: "pool10_add"
  bottom: "label"
  top: "accuracy_top1"
  include {
    # phase: TEST
  }
  accuracy_param {
    top_k: 1
  }
}
layer {
  name: "accuracy_top5"
  type: "Accuracy"
  bottom: "pool10_add"
  bottom: "label"
  top: "accuracy_top5"
  include {
    # phase: TEST
  }
  accuracy_param {
    top_k: 5
  }
}
layer {
   name: "accuracy_top10"
   type: "Accuracy"
   bottom: "pool10_add"
   bottom: "label"
   top: "accuracy_top10"
   include {
     # phase: TEST
   }
   accuracy_param {
     top_k: 10
   }
}