Steganalysis/PhaseAwareNet_SRC/Caffe/phase_aware_net_train.prototxt

layer {
  name: "data"
  type: "Python"
  top: "data"
  top: "label"
  python_param {
    module: "AugStegoDataLayer"
    layer: "AugmentDataLayerSync"
    param_str: "{\'im_shape\': [512, 512], \'root\': \'/home/mchen/tmp/caffe/data/JStego/JUNI_0.4/\', \'split\': \'train\', \'batch_size\': 40}"
  }
}
layer {
  name: "conv0"
  type: "Convolution"
  bottom: "data"
  top: "conv0"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 4
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "constant"
      value: 0.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "conv0"
  top: "conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 8
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.00999999977648
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "abs1"
  type: "AbsVal"
  bottom: "conv1"
  top: "abs1"
}
layer {
  name: "bn1"
  type: "BatchNorm"
  bottom: "abs1"
  top: "bn1"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  batch_norm_param {
    moving_average_fraction: 0.980000019073
    eps: 9.99999974738e-05
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "tanh1"
  type: "TanH"
  bottom: "bn1"
  top: "bn1"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "bn1"
  top: "conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.00999999977648
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn2"
  type: "BatchNorm"
  bottom: "conv2"
  top: "bn2"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  batch_norm_param {
    moving_average_fraction: 0.980000019073
    eps: 9.99999974738e-05
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "tanh2"
  type: "TanH"
  bottom: "bn2"
  top: "bn2"
}
layer {
  name: "sbp"
  type: "SplitByPhase"
  bottom: "bn2"
  top: "sbp"
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "sbp"
  top: "conv3"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.00999999977648
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn3"
  type: "BatchNorm"
  bottom: "conv3"
  top: "bn3"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  batch_norm_param {
    moving_average_fraction: 0.980000019073
    eps: 9.99999974738e-05
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "bn3"
  top: "bn3"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "bn3"
  top: "pool3"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 2
    pad: 1
  }
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "pool3"
  top: "conv4"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 256
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.00999999977648
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn4"
  type: "BatchNorm"
  bottom: "conv4"
  top: "bn4"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  batch_norm_param {
    moving_average_fraction: 0.980000019073
    eps: 9.99999974738e-05
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "bn4"
  top: "bn4"
}
layer {
  name: "pool4"
  type: "Pooling"
  bottom: "bn4"
  top: "pool4"
  pooling_param {
    pool: AVE
    kernel_size: 5
    stride: 2
    pad: 1
  }
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "pool4"
  top: "conv5"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 512
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.00999999977648
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "bn5"
  type: "BatchNorm"
  bottom: "conv5"
  top: "bn5"
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  batch_norm_param {
    moving_average_fraction: 0.980000019073
    eps: 9.99999974738e-05
    scale_filler {
      type: "constant"
      value: 1.0
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "bn5"
  top: "bn5"
}
layer {
  name: "pool5"
  type: "Pooling"
  bottom: "bn5"
  top: "pool5"
  pooling_param {
    pool: AVE
    global_pooling: true
  }
}
layer {
  name: "fc6"
  type: "InnerProduct"
  bottom: "pool5"
  top: "fc6"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.00999999977648
    }
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "fc6"
  bottom: "label"
  top: "loss"
}
layer {
  name: "acc"
  type: "Accuracy"
  bottom: "fc6"
  bottom: "label"
  top: "acc"
}