xchen ResNet-18

xchen ResNet-18

name: "ResNet-18"
layer {
  name: "data"
  type: "Data" 
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    scale: 0.00390625
    mean_file: "/u02/xchen/char/ImageData/char/gray/gray135mean.binaryproto"
#    crop_size: 128
  }
  data_param {
    source: "/u02/xchen/char/ImageData/char/gray/lmdb135train-2/"
    batch_size: 256
    backend: LMDB
  }
}
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    scale: 0.00390625
    mean_file: "/u02/xchen/char/ImageData/char/gray/gray135mean.binaryproto"
#    crop_size: 128
  }
  data_param {
    source: "/u02/xchen/char/ImageData/char/gray/lmdb135val/"
    batch_size: 1
    backend: LMDB
  }
}


layer {
  bottom: "data"
    top: "conv1"
    name: "conv1"
    type: "Convolution"
    convolution_param {
    num_output: 24 
      kernel_size: 5 
      pad: 2
      stride: 2
    weight_filler { 
      type: "gaussian"
      std: 0.01
      }
    bias_filler { 
      type: "constant"
     }
    } 
}

layer {
  bottom: "conv1"
    top: "conv1"
    name: "conv1_relu"
    type: "ReLU"
    }

layer {
  bottom: "conv1"
    top: "pool1"
    name: "pool1"
    type: "Pooling"
    pooling_param {
    kernel_size: 3
      stride: 3 
      pool: MAX
      }
}
##########################
######first shortcut######
##########################
layer {
  bottom: "pool1"
    top: "res2a_branch1"
    name: "res2a_branch1"
    type: "Convolution"
    convolution_param {
    num_output: 48 
      kernel_size: 1
      pad: 0
      stride: 1
      bias_term: false
    weight_filler { 
      type: "gaussian"
      std: 0.01
      }
    bias_filler { 
      type: "constant"
     }
    } 
}

layer {
  bottom: "pool1"
    top: "res2a_branch2a"
    name: "res2a_branch2a"
    type: "ReLU"
    }

layer {
  bottom: "res2a_branch2a"
    top: "res2a_branch2b"
    name: "res2a_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 48
      kernel_size: 3
      pad: 1
      stride: 1
      bias_term: false
    weight_filler { 
      type: "gaussian"
      std: 0.01
      }
    bias_filler { 
      type: "constant"
     }
    } 
}

layer {
    bottom: "res2a_branch1"
    bottom: "res2a_branch2b"
    top: "res2a"
    name: "res2a"
    type: "Eltwise"
    eltwise_param {
	operation: MAX
    }
}

##########################
######second shortcut#####
##########################


layer {
  bottom: "res2a"
    top: "res3a_branch1"
    name: "res3a_branch1"
    type: "Convolution"
    convolution_param {
    num_output: 64 
      kernel_size: 1
      pad: 0
      stride: 2
      bias_term: false
    weight_filler { 
      type: "gaussian"
      std: 0.01
      }
    bias_filler { 
      type: "constant"
     }
    } 
}

layer {
  bottom: "res2a"
    top: "res3a_branch2a"
    name: "res3a_branch2a"
    type: "ReLU"
    }

layer {
  bottom: "res3a_branch2a"
    top: "res3a_branch2b"
    name: "res3a_branch2b"
    type: "Convolution"
    convolution_param {
    num_output: 64 
      kernel_size: 3
      pad: 1
      stride: 2
      bias_term: false
    weight_filler { 
      type: "gaussian"
      std: 0.01
      }
    bias_filler { 
      type: "constant"
     }
    } 
}

layer {
  bottom: "res3a_branch1"
    bottom: "res3a_branch2b"
    top: "res3a"
    name: "res3a"
    type: "Eltwise"
    eltwise_param {
	operation: MAX
    }
    }


layer {
  bottom: "res3a"
    top: "pool5"
    name: "pool5"
    type: "Pooling"
    pooling_param {
    kernel_size: 3 
      stride: 3 
      pool: MAX
      }
}
layer {
  bottom: "pool5"
    top: "fc1"
    name: "fc1"
    type: "InnerProduct"
    inner_product_param {
    num_output: 512 
weight_filler {
      type: "gaussian"
      std: 0.01
      }
    bias_filler {
      type: "constant"
     }
    }
}

layer{
  name: "slice6"
  type: "Slice"
  slice_param {
        slice_dim: 1
  }
  bottom: "fc1"
  top: "slice1_1"
  top: "slice1_2"
}
layer{
  name: "eltwise1"
  type: "Eltwise"
  bottom: "slice1_1"
  bottom: "slice1_2"
  top: "eltwise1"
  eltwise_param {
        operation: MAX
  }
}

layer{
        name: "dropout1"
        type: "Dropout"
        bottom: "eltwise1"
        top: "dropout1"
        dropout_param {
                dropout_ratio: 0.7
  }
}
layer {
  bottom: "dropout1"
    top: "fc7"
    name: "fc7"
    type: "InnerProduct"
    inner_product_param {
    num_output: 7906
      }
}

#layer {
#  bottom: "fc7"
#    top: "prob"
#    name: "prob"
#    type: "Softmax"
#    }

  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
      }
}