name: "alexnet"
input: "data"
input_dim: 128
input_dim: 3
input_dim: 224
input_dim: 224
force_backward: true
layers {
  name: "conv1"
  type: CONVOLUTION
  bottom: "data"
  top: "conv1/11x11_s4"
  blobs_lr: 1
  blobs_lr: 2 
  weight_decay: 1
  weight_decay: 0 
  convolution_param {
    num_output: 64
    kernel_size: 11
    stride: 4
    pad: 2
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layers {
  name: "conv1/relu"
  type: RELU
  bottom: "conv1/11x11_s4"
  top: "conv1/11x11_s4"
}
layers {
  name: "pool1/3x3_s2"
  type: POOLING
  bottom: "conv1/11x11_s4"
  top: "pool1/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "conv2/5x5_s1"
  type: CONVOLUTION
  bottom: "pool1/3x3_s2"
  top: "conv2/5x5_s1"
  blobs_lr: 1
  blobs_lr: 2 
  weight_decay: 1
  weight_decay: 0 
  convolution_param {
    num_output: 192
    kernel_size: 5
    stride: 1
    pad: 2
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layers {
  name: "conv2/relu"
  type: RELU
  bottom: "conv2/5x5_s1"
  top: "conv2/5x5_s1"
}
layers {
  name: "pool2/3x3_s2"
  type: POOLING
  bottom: "conv2/5x5_s1"
  top: "pool2/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "conv3/3x3_s1"
  type: CONVOLUTION
  bottom: "pool2/3x3_s2"
  top: "conv3/3x3_s1"
  blobs_lr: 1
  blobs_lr: 2 
  weight_decay: 1
  weight_decay: 0 
  convolution_param {
    num_output: 384
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layers {
  name: "conv3/relu"
  type: RELU
  bottom: "conv3/3x3_s1"
  top: "conv3/3x3_s1"
}
layers {
  name: "conv4/3x3_s1"
  type: CONVOLUTION
  bottom: "conv3/3x3_s1"
  top: "conv4/3x3_s1"
  blobs_lr: 1
  blobs_lr: 2 
  weight_decay: 1
  weight_decay: 0 
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layers {
  name: "conv4/relu"
  type: RELU
  bottom: "conv4/3x3_s1"
  top: "conv4/3x3_s1"
}
layers {
  name: "conv5/3x3_s1"
  type: CONVOLUTION
  bottom: "conv4/3x3_s1"
  top: "conv5/3x3_s1"
  blobs_lr: 1
  blobs_lr: 2 
  weight_decay: 1
  weight_decay: 0 
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layers {
  name: "conv5/relu"
  type: RELU
  bottom: "conv5/3x3_s1"
  top: "conv5/3x3_s1"
}
layers {
  name: "pool5/3x3_s2"
  type: POOLING
  bottom: "conv5/3x3_s1"
  top: "pool5/3x3_s2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layers {
  name: "fc6"
  type: INNER_PRODUCT
  bottom: "pool5/3x3_s2"
  top: "fc6"
  inner_product_param {
    num_output: 4096
  }
}
layers {
  name: "conv1/relu"
  type: RELU
  bottom: "fc6"
  top: "fc6"
}
layers {
  name: "fc7"
  type: INNER_PRODUCT
  bottom: "fc6"
  top: "fc7"
  inner_product_param {
    num_output: 4096
  }
}
layers {
  name: "conv1/relu"
  type: RELU
  bottom: "fc7"
  top: "fc7"
}
layers {
  name: "fc8"
  type: INNER_PRODUCT
  bottom: "fc7"
  top: "fc8"
  inner_product_param {
    num_output: 1000
  }
}