Hello World For Hexo

Published: February 01, 2016

Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.

Quick Start

Create a new post

$ hexo new "My New Post"

More info: Writing

Run server

$ hexo server

More info: Server

Generate static files

$ hexo generate

More info: Generating

Deploy to remote sites

$ hexo deploy

More info: Deployment

eg.prototxt

name: "CaffeNet"
layers {
  name: "data"
  type: DATA
  top: "data_age"
  top: "label_age"
  data_param {
    source: "age_train_leveldb"
    mean_file: "mean.binaryproto"
    batch_size: 50
    crop_size: 227
    mirror: true
  }
  include: { phase: TRAIN }
}
layers {
  name: "data"
  type: DATA
  top: "data_age"
  top: "label_age"
  data_param {
    source: "age_val_leveldb"
    mean_file: "mean.binaryproto"
    batch_size: 50
    crop_size: 227
    mirror: false
  }
  include: { phase: TEST }
}
layers {
  name: "data"
  type: DATA
  top: "data_gender"
  top: "label_gender"
  data_param {
    source: "gender_train_leveldb"
    mean_file: "mean.binaryproto"
    batch_size: 50
    crop_size: 227
    mirror: true
  }
  include: { phase: TRAIN }
}
layers {
  name: "data"
  type: DATA
  top: "data_gender"
  top: "label_gender"
  data_param {
    source: "gender_val_leveldb"
    mean_file: "mean.binaryproto"
    batch_size: 50
    crop_size: 227
    mirror: false
  }
  include: { phase: TEST }
}
layers {
  name: "conv1"
  type: CONVOLUTION
  bottom: "data_age"
  bottom: "data_gender"
  top: "conv1_age"
  top: "conv1_gender"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 96
    kernel_size: 11
    stride: 4
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu1_age"
  type: RELU
  bottom: "conv1_age"
  top: "conv1_age"
}
layers {
  name: "relu1_gender"
  type: RELU
  bottom: "conv1_gender"
  top: "conv1_gender"
}
layers {
  name: "pool1_age"
  type: POOLING
  bottom: "conv1_age"
  top: "pool1_age"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "pool1_gender"
  type: POOLING
  bottom: "conv1_gender"
  top: "pool1_gender"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "norm1_age"
  type: LRN
  bottom: "pool1_age"
  top: "norm1_age"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layers {
  name: "norm1_gender"
  type: LRN
  bottom: "pool1_gender"
  top: "norm1_gender"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layers {
  name: "conv2"
  type: CONVOLUTION
  bottom: "norm1_age"
  bottom: "norm1_gender"
  top: "conv2_age"
  top: "conv2_gender"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 256
    pad: 2
    kernel_size: 5
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "relu2_age"
  type: RELU
  bottom: "conv2_age"
  top: "conv2_age"
}
layers {
  name: "relu2_gender"
  type: RELU
  bottom: "conv2_gender"
  top: "conv2_gender"
}
layers {
  name: "pool2_age"
  type: POOLING
  bottom: "conv2_age"
  top: "pool2_age"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "pool2_gender"
  type: POOLING
  bottom: "conv2_gender"
  top: "pool2_gender"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "norm2_age"
  type: LRN
  bottom: "pool2_age"
  top: "norm2_age"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layers {
  name: "norm2_gender"
  type: LRN
  bottom: "pool2_gender"
  top: "norm2_gender"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layers {
  name: "conv3"
  type: CONVOLUTION
  bottom: "norm2_age"
  bottom: "norm2_gender"
  top: "conv3_age"
  top: "conv3_gender"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "relu3_age"
  type: RELU
  bottom: "conv3_age"
  top: "conv3_age"
}
layers {
  name: "relu3_gender"
  type: RELU
  bottom: "conv3_gender"
  top: "conv3_gender"
}
layers {
  name: "conv4"
  type: CONVOLUTION
  bottom: "conv3_age"
  bottom: "conv3_gender"
  top: "conv4_age"
  top: "conv4_gender"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "relu4_age"
  type: RELU
  bottom: "conv4_age"
  top: "conv4_age"
}
layers {
  name: "relu4_gender"
  type: RELU
  bottom: "conv4_gender"
  top: "conv4_gender"
}
layers {
  name: "conv5"
  type: CONVOLUTION
  bottom: "conv4_age"
  bottom: "conv4_gender"
  top: "conv5_age"
  top: "conv5_gender"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "relu5_age"
  type: RELU
  bottom: "conv5_age"
  top: "conv5_age"
}
layers {
  name: "relu5_gender"
  type: RELU
  bottom: "conv5_gender"
  top: "conv5_gender"
}
layers {
  name: "pool5_age"
  type: POOLING
  bottom: "conv5_age"
  top: "pool5_age"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "pool5_gender"
  type: POOLING
  bottom: "conv5_gender"
  top: "pool5_gender"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "fc6_age"
  type: INNER_PRODUCT
  bottom: "pool5_age"
  top: "fc6_age"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "fc6_gender"
  type: INNER_PRODUCT
  bottom: "pool5_gender"
  top: "fc6_gender"
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "relu6_age"
  type: RELU
  bottom: "fc6_age"
  top: "fc6_age"
}
layers {
  name: "relu6_gender"
  type: RELU
  bottom: "fc6_age"
  top: "fc6_age"
}
layers {
  name: "drop6_age"
  type: DROPOUT
  bottom: "fc6_age"
  top: "fc6_age"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "drop6_gender"
  type: DROPOUT
  bottom: "fc6_age"
  top: "fc6_age"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "fc7_age"
  type: INNER_PRODUCT
  bottom: "fc6_age"
  top: "fc7_age"
  # Note that blobs_lr can be set to 0 to disable any fine-tuning of this, and any other, layer
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "fc7_gender"
  type: INNER_PRODUCT
  bottom: "fc6_gender"
  top: "fc7_gender"
  # Note that blobs_lr can be set to 0 to disable any fine-tuning of this, and any other, layer
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  name: "relu7_age"
  type: RELU
  bottom: "fc7_age"
  top: "fc7_age"
}
layers {
  name: "relu7_gender"
  type: RELU
  bottom: "fc7_gender"
  top: "fc7_gender"
}
layers {
  name: "drop7_age"
  type: DROPOUT
  bottom: "fc7_age"
  top: "fc7_age"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "drop7_gender"
  type: DROPOUT
  bottom: "fc7_gender"
  top: "fc7_gender"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layers {
  name: "fc8_age"
  type: INNER_PRODUCT
  bottom: "fc7_age"
  top: "fc8_age"
  # blobs_lr is set to higher than for other layers, because this layer is starting from random while the others are already trained
  blobs_lr: 10
  blobs_lr: 20
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 8
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "fc8_gender"
  type: INNER_PRODUCT
  bottom: "fc7_gender"
  top: "fc8_gender"
  # blobs_lr is set to higher than for other layers, because this layer is starting from random while the others are already trained
  blobs_lr: 10
  blobs_lr: 20
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  name: "loss_age"
  type: SOFTMAX_LOSS
  bottom: "fc8_age"
  bottom: "label_age"
}
layers {
  name: "loss_gender"
  type: SOFTMAX_LOSS
  bottom: "fc8_gender"
  bottom: "label_gender"
}
layers {
  name: "accuracy_age"
  type: ACCURACY
  bottom: "fc8_age"
  bottom: "label_age"
  top: "accuracy_age"
  include: { phase: TEST }
}
layers {
  name: "accuracy_gender"
  type: ACCURACY
  bottom: "fc8_gender"
  bottom: "label_gender"
  top: "accuracy_gender"
  include: { phase: TEST }
}

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Hello World For Hexo

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Run server

Generate static files

Deploy to remote sites

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