shufflenetSimple2

shufflenetSimple2

name: "shufflenet"
layer {
  name: "data"
  type: "Data" 
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  data_param {
    source: "/u02/xchen/char/ImageData/char/gray/lmdb128train/"
    batch_size: 256
    backend: LMDB
  }
  transform_param {
    scale: 0.00390625
    mean_file: "/u02/xchen/char/ImageData/char/gray/gray128mean.binaryproto"
    crop_size: 128
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  data_param {
    source: "/u02/xchen/char/ImageData/char/gray/lmdb128val/"
    batch_size: 1
    backend: LMDB
  }
  transform_param {
    scale: 0.00390625
    mean_file: "/u02/xchen/char/ImageData/char/gray/gray128mean.binaryproto"
    crop_size: 128
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    stride: 2
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1_relu"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "resx1_match_conv"
  type: "Pooling"
  bottom: "conv1"
  top: "resx1_match_conv"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
	pad: 0
  }
}
layer {
  name: "resx1_conv1"
  type: "Convolution"
  bottom: "conv1"
  top: "resx1_conv1"
  convolution_param {
    num_output: 12
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}

layer {
  name: "resx1_conv1_relu"
  type: "ReLU"
  bottom: "resx1_conv1"
  top: "resx1_conv1"
}
layer {
  name: "resx1_conv2"
  type: "ConvolutionDepthwise"
  bottom: "resx1_conv1"
  top: "resx1_conv2"
  convolution_param {
    num_output: 12
    kernel_size: 3
    stride: 2
    pad: 1
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}

layer {
  name: "resx1_conv3"
  type: "Convolution"
  bottom: "resx1_conv2"
  top: "resx1_conv3"
  convolution_param {
    num_output: 81
    kernel_size: 1
    stride: 1
    pad: 0
    group: 3
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}

layer {
  name: "resx1_concat"
  type: "Concat"
  bottom: "resx1_match_conv"
  bottom: "resx1_conv3"
  top: "resx1_concat"
}
layer {
  name: "resx1_concat_relu"
  type: "ReLU"
  bottom: "resx1_concat"
  top: "resx1_concat"
}

layer {
  name: "resx5_match_conv"
  type: "Pooling"
  bottom: "resx1_concat"
  top: "resx5_match_conv"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "resx5_conv1"
  type: "Convolution"
  bottom: "resx1_concat"
  top: "resx5_conv1"
  convolution_param {
    num_output: 33
    kernel_size: 1
    stride: 1
    pad: 0
    group: 3
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}

layer {
  name: "resx5_conv1_relu"
  type: "ReLU"
  bottom: "resx5_conv1"
  top: "resx5_conv1"
}
layer {
  name: "shuffle5"
  type: "ShuffleChannel"
  bottom: "resx5_conv1"
  top: "shuffle5"
  shuffle_channel_param {
    group: 3
  }
}
layer {
  name: "resx5_conv2"
  type: "ConvolutionDepthwise"
  bottom: "shuffle5"
  top: "resx5_conv2"
  convolution_param {
    num_output: 33
    kernel_size: 3
    stride: 2
    pad: 1
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}

layer {
  name: "resx5_conv3"
  type: "Convolution"
  bottom: "resx5_conv2"
  top: "resx5_conv3"
  convolution_param {
    num_output: 384
    kernel_size: 1
    stride: 1
    pad: 0
    group: 3
    bias_term: false
    weight_filler {
      type: "msra"
    }
  }
}

layer {
  name: "resx5_concat"
  type: "Concat"
  bottom: "resx5_match_conv"
  bottom: "resx5_conv3"
  top: "resx5_concat"
}
layer {
  name: "resx5_concat_relu"
  type: "ReLU"
  bottom: "resx5_concat"
  top: "resx5_concat"
}



layer {
  name: "pool_ave"
  type: "Pooling"
  bottom: "resx5_concat"
  top: "pool_ave"
  pooling_param {
    global_pooling : true
    pool: AVE
  }
}
layer {
  name: "fc7"
  type: "Convolution"
  bottom: "pool_ave"
  top: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 7906
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
	name: "loss"
	  type: "SoftmaxWithLoss"
	  bottom: "fc7"
	  bottom: "label"
	  top: "loss"
	  }

layer {
  name: "accuracy"
    type: "Accuracy"
    bottom: "fc7"
    bottom: "label"
    top: "accuracy"
    include {
    phase: TEST
      }
}