clarifai.prototxt

name: "Clafifai"
# --------------------- Data Layer --------------------------
# input dimension is 36x36x3
layers {
  name: "data"
  type: DATA
  top: "data"
  top: "label"
  data_param {
    source: "cache/lsp/LMDB_train"
    backend: LMDB
    batch_size: 512
  }
  transform_param {
    mean_value: 128
    mean_value: 128
    mean_value: 128
    mirror: false
  }
  include: { phase: TRAIN }
}

layers {
  name: "data"
  type: DATA
  top: "data"
  top: "label"
  data_param {
    source: "cache/lsp/LMDB_train"
    backend: LMDB
    batch_size: 512
  }
  transform_param {
    mean_value: 128
    mean_value: 128
    mean_value: 128
    mirror: false
  }
  include: { phase: TEST }
}

# --------------------- conv 1 --------------------------
layers {
  bottom: "data"
  top: "conv1"
  name: "conv1"
  type: CONVOLUTION
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 96
    kernel_size: 7
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layers {
  bottom: "conv1"
  top: "conv1"
  name: "relu1"
  type: RELU
}
layers {
  bottom: "conv1"
  top: "pool1"
  name: "pool1"
  type: POOLING
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  bottom: "pool1"
  top: "norm1"
  name: "norm1"
  type: LRN
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}

# --------------------- conv 2 --------------------------
layers {
  bottom: "norm1"
  top: "conv2"
  name: "conv2"
  type: CONVOLUTION
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 5
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  bottom: "conv2"
  top: "conv2"
  name: "relu2"
  type: RELU
}
layers {
  bottom: "conv2"
  top: "pool2"
  name: "pool2"
  type: POOLING
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  bottom: "pool2"
  top: "norm2"
  name: "norm2"
  type: LRN
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}

# --------------------- conv 3 --------------------------
layers {
  bottom: "norm2"
  top: "conv3"
  name: "conv3"
  type: CONVOLUTION
  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 {
  bottom: "conv3"
  top: "conv3"
  name: "relu3"
  type: RELU
}

# --------------------- conv 4 --------------------------
layers {
  bottom: "conv3"
  top: "conv4"
  name: "conv4"
  type: CONVOLUTION
  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: 1
    }
  }
}
layers {
  bottom: "conv4"
  top: "conv4"
  name: "relu4"
  type: RELU
}
# --------------------- conv 5 --------------------------
layers {
  bottom: "conv4"
  top: "conv5"
  name: "conv5"
  type: CONVOLUTION
  blobs_lr: 1
  blobs_lr: 2
  weight_decay: 1
  weight_decay: 0
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layers {
  bottom: "conv5"
  top: "conv5"
  name: "relu5"
  type: RELU
}
layers {
  bottom: "conv5"
  top: "pool5"
  name: "pool5"
  type: POOLING
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
# -------------------- fully connected 1 ------------------
layers {
  bottom: "pool5"
  top: "fc6"
  name: "fc6"
  type: INNER_PRODUCT
  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 {
  bottom: "fc6"
  top: "fc6"
  name: "relu6"
  type: RELU
}
layers {
  bottom: "fc6"
  top: "fc6"
  name: "drop6"
  type: DROPOUT
  dropout_param {
    dropout_ratio: 0.5
  }
}
# -------------------- fully connected 2 ------------------
layers {
  bottom: "fc6"
  top: "fc7"
  name: "fc7"
  type: INNER_PRODUCT
  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 {
  bottom: "fc7"
  top: "fc7"
  name: "relu7"
  type: RELU
}
layers {
  bottom: "fc7"
  top: "fc7"
  name: "drop7"
  type: DROPOUT
  dropout_param {
    dropout_ratio: 0.5
  }
}
# -------------------- output layer ------------------
layers {
  bottom: "fc7"
  top: "fc8"
  name: "fc8"
  type: INNER_PRODUCT
  blobs_lr: 10
  blobs_lr: 20
  weight_decay: 1
  weight_decay: 0
  inner_product_param {
    num_output: 9699
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
# -------------------- loss layer ------------------
layers {
  name: "accuracy"
  type: ACCURACY
  bottom: "fc8"
  bottom: "label"
  top: "accuracy"
  include: { phase: TEST }
}

layers {
  name: "loss"
  type: SOFTMAX_LOSS
  bottom: "fc8"
  bottom: "label"
  top: "loss"
}