NIN.prototxt

name: "NIN"
layers {
  name: "data"
  type: HDF5_DATA
  top: "data"
  top: "label"
  hdf5_data_param {
    source: "/home/ecater/Desktop/caffe/examples/science_bowl/aug/data/aug_train.txt"
    batch_size: 64
  }
  transform_param {
    crop_size: 60
    mirror: 1
  }
  include: { phase: TRAIN }
}
layers {
  name: "data"
  type: HDF5_DATA
  top: "data"
  top: "label"
  hdf5_data_param {
    source: "/home/ecater/Desktop/caffe/examples/science_bowl/aug/data/aug_test.txt"
    batch_size: 64
  }
  include: { phase: TEST }
}
layers {
  name: "conv1"
  type: CONVOLUTION
  bottom: "data"
  top: "conv1"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1.
  weight_decay: 0.
  convolution_param {
    num_output: 192
    
    kernel_size: 9
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu1"
  type: RELU
  bottom: "conv1"
  top: "conv1"
}
layers {
  name: "cccp1"
  type: CONVOLUTION
  bottom: "conv1"
  top: "cccp1"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 160
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp1"
  type: RELU
  bottom: "cccp1"
  top: "cccp1"
}
layers {
  name: "cccp2"
  type: CONVOLUTION
  bottom: "cccp1"
  top: "cccp2"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 96
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp2"
  type: RELU
  bottom: "cccp2"
  top: "cccp2"
}
layers {
  name: "pool1"
  type: POOLING
  bottom: "cccp2"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "drop3"
  type: DROPOUT
  bottom: "pool1"
  top: "pool1"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "conv2"
  type: CONVOLUTION
  bottom: "pool1"
  top: "conv2"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1.
  weight_decay: 0.
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 7
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu2"
  type: RELU
  bottom: "conv2"
  top: "conv2"
}
layers {
  name: "cccp3"
  type: CONVOLUTION
  bottom: "conv2"
  top: "cccp3"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 192
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp3"
  type: RELU
  bottom: "cccp3"
  top: "cccp3"
}
layers {
  name: "cccp4"
  type: CONVOLUTION
  bottom: "cccp3"
  top: "cccp4"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 192
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp4"
  type: RELU
  bottom: "cccp4"
  top: "cccp4"
}
layers {
  name: "pool2"
  type: POOLING
  bottom: "cccp4"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "drop6"
  type: DROPOUT
  bottom: "pool2"
  top: "pool2"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "conv3"
  type: CONVOLUTION
  bottom: "pool2"
  top: "conv3"
  blobs_lr: 1.
  blobs_lr: 2.
  weight_decay: 1.
  weight_decay: 0.
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 5
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu3"
  type: RELU
  bottom: "conv3"
  top: "conv3"
}
layers {
  name: "cccp5"
  type: CONVOLUTION
  bottom: "conv3"
  top: "cccp5"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 192
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp5"
  type: RELU
  bottom: "cccp5"
  top: "cccp5"
}
layers {
  name: "cccp6"
  type: CONVOLUTION
  bottom: "cccp5"
  top: "cccp6"
  blobs_lr: 0.1
  blobs_lr: 0.1
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 192
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp6"
  type: RELU
  bottom: "cccp6"
  top: "cccp6"
}


layers {
  name: "pool4"
  type: POOLING
  bottom: "cccp6"
  top: "pool4"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}


layers {
  name: "conv4"
  type: CONVOLUTION
  bottom: "pool4"
  top: "conv4"
  blobs_lr: 1.
  blobs_lr: 2.
  weight_decay: 1.
  weight_decay: 0.
  convolution_param {
    num_output: 192
    pad: 1
    kernel_size: 5
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu4"
  type: RELU
  bottom: "conv4"
  top: "conv4"
}
layers {
  name: "cccp7"
  type: CONVOLUTION
  bottom: "conv4"
  top: "cccp7"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 192
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp7"
  type: RELU
  bottom: "cccp7"
  top: "cccp7"
}
layers {
  name: "cccp8"
  type: CONVOLUTION
  bottom: "cccp7"
  top: "cccp8"
  blobs_lr: 0.1
  blobs_lr: 0.1
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 192
    group: 1
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.05
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu_cccp8"
  type: RELU
  bottom: "cccp8"
  top: "cccp8"
}


layers {
  name: "pool5"
  type: POOLING
  bottom: "cccp8"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}

layers {
  name: "ip1"
  type: INNER_PRODUCT
  bottom: "pool5"
  top: "ip1"
  blobs_lr: 1
  blobs_lr: 2
  inner_product_param {
    num_output: 2048
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu_ip1"
  type: RELU
  bottom: "ip1"
  top: "ip1"
}
layers {
  name: "drop7"
  type: DROPOUT
  bottom: "ip1"
  top: "ip1"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "ip2"
  type: INNER_PRODUCT
  bottom: "ip1"
  top: "ip2"
  blobs_lr: 1
  blobs_lr: 2
  inner_product_param {
    num_output: 2048
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "relu_ip2"
  type: RELU
  bottom: "ip2"
  top: "ip2"
}
layers {
  name: "drop8"
  type: DROPOUT
  bottom: "ip2"
  top: "ip2"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "ip3"
  type: INNER_PRODUCT
  bottom: "ip2"
  top: "ip3"
  blobs_lr: 1
  blobs_lr: 2
  inner_product_param {
    num_output: 121
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layers {
  name: "accuracy"
  type: ACCURACY
  bottom: "ip3"
  bottom: "label"
  
  top: "accuracy"
  include: { phase: TEST }
}
layers {
  name: "loss"
  type: SOFTMAX_LOSS
  bottom: "ip3"
  bottom: "label"
  
  top: "loss"
}