Skip to content

Instantly share code, notes, and snippets.

@mrgloom

mrgloom/VGG-16

Created September 16, 2016 11:10
Download ZIP

Revisions

  1. mrgloom created this gist Sep 16, 2016.
    546 changes: 546 additions & 0 deletions VGG-16
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,546 @@
    name: "VGG_ILSVRC_16_layers"

    layer {
    name: "train-data"
    type: "Data"
    top: "data"
    top: "label"
    include {
    stage: "train"
    }
    transform_param {
    mirror: true
    crop_size: 224
    }
    data_param {
    batch_size: 16
    }
    }

    layer {
    name: "val-data"
    type: "Data"
    top: "data"
    top: "label"
    include {
    stage: "val"
    }
    transform_param {
    crop_size: 224
    }
    data_param {
    batch_size: 16
    }
    }

    layer {
    name: "conv1_1"
    type: "Convolution"
    bottom: "data"
    top: "conv1_1"
    convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu1_1"
    type: "ReLU"
    bottom: "conv1_1"
    top: "conv1_1"
    }

    layer {
    name: "conv1_2"
    type: "Convolution"
    bottom: "conv1_1"
    top: "conv1_2"
    convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu1_2"
    type: "ReLU"
    bottom: "conv1_2"
    top: "conv1_2"
    }

    layer {
    name: "pool1"
    type: "Pooling"
    bottom: "conv1_2"
    top: "pool1"
    pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    }
    }

    layer {
    name: "conv2_1"
    type: "Convolution"
    bottom: "pool1"
    top: "conv2_1"
    convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu2_1"
    type: "ReLU"
    bottom: "conv2_1"
    top: "conv2_1"
    }

    layer {
    name: "conv2_2"
    type: "Convolution"
    bottom: "conv2_1"
    top: "conv2_2"
    convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu2_2"
    type: "ReLU"
    bottom: "conv2_2"
    top: "conv2_2"
    }

    layer {
    name: "pool2"
    type: "Pooling"
    bottom: "conv2_2"
    top: "pool2"
    pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    }
    }

    layer {
    name: "conv3_1"
    type: "Convolution"
    bottom: "pool2"
    top: "conv3_1"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu3_1"
    type: "ReLU"
    bottom: "conv3_1"
    top: "conv3_1"
    }

    layer {
    name: "conv3_2"
    type: "Convolution"
    bottom: "conv3_1"
    top: "conv3_2"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu3_2"
    type: "ReLU"
    bottom: "conv3_2"
    top: "conv3_2"
    }

    layer {
    name: "conv3_3"
    type: "Convolution"
    bottom: "conv3_2"
    top: "conv3_3"
    convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu3_3"
    type: "ReLU"
    bottom: "conv3_3"
    top: "conv3_3"
    }

    layer {
    name: "pool3"
    type: "Pooling"
    bottom: "conv3_3"
    top: "pool3"
    pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    }
    }

    layer {
    name: "conv4_1"
    type: "Convolution"
    bottom: "pool3"
    top: "conv4_1"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu4_1"
    type: "ReLU"
    bottom: "conv4_1"
    top: "conv4_1"
    }

    layer {
    name: "conv4_2"
    type: "Convolution"
    bottom: "conv4_1"
    top: "conv4_2"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu4_2"
    type: "ReLU"
    bottom: "conv4_2"
    top: "conv4_2"
    }

    layer {
    name: "conv4_3"
    type: "Convolution"
    bottom: "conv4_2"
    top: "conv4_3"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu4_3"
    type: "ReLU"
    bottom: "conv4_3"
    top: "conv4_3"
    }

    layer {
    name: "pool4"
    type: "Pooling"
    bottom: "conv4_3"
    top: "pool4"
    pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    }
    }

    layer {
    name: "conv5_1"
    type: "Convolution"
    bottom: "pool4"
    top: "conv5_1"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu5_1"
    type: "ReLU"
    bottom: "conv5_1"
    top: "conv5_1"
    }

    layer {
    name: "conv5_2"
    type: "Convolution"
    bottom: "conv5_1"
    top: "conv5_2"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu5_2"
    type: "ReLU"
    bottom: "conv5_2"
    top: "conv5_2"
    }

    layer {
    name: "conv5_3"
    type: "Convolution"
    bottom: "conv5_2"
    top: "conv5_3"
    convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.0
    }
    }
    }

    layer {
    name: "relu5_3"
    type: "ReLU"
    bottom: "conv5_3"
    top: "conv5_3"
    }

    layer {
    name: "pool5"
    type: "Pooling"
    bottom: "conv5_3"
    top: "pool5"
    pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
    }
    }

    layer {
    name: "fc6"
    type: "InnerProduct"
    bottom: "pool5"
    top: "fc6"
    inner_product_param {
    num_output: 4096
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.1
    }
    }

    layer {
    name: "relu6"
    type: "ReLU"
    bottom: "fc6"
    top: "fc6"
    }

    layer {
    name: "drop6"
    type: "Dropout"
    bottom: "fc6"
    top: "fc6"
    dropout_param {
    dropout_ratio: 0.5
    }
    }

    layer {
    name: "fc7"
    type: "InnerProduct"
    bottom: "fc6"
    top: "fc7"
    inner_product_param {
    num_output: 4096
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.1
    }
    }

    layer {
    name: "relu7"
    type: "ReLU"
    bottom: "fc7"
    top: "fc7"
    }

    layer {
    name: "drop7"
    type: "Dropout"
    bottom: "fc7"
    top: "fc7"
    dropout_param {
    dropout_ratio: 0.5
    }
    }

    layer {
    name: "fc8"
    type: "InnerProduct"
    bottom: "fc7"
    top: "fc8"
    inner_product_param {
    num_output: 2
    weight_filler {
    type: "xavier"
    }
    bias_filler {
    type: "constant"
    value: 0.1
    }
    }

    layer {
    name: "accuracy"
    type: "Accuracy"
    bottom: "fc8"
    bottom: "label"
    top: "accuracy"
    include {
    stage: "val"
    }
    }

    layer {
    name: "loss"
    type: "SoftmaxWithLoss"
    bottom: "fc8"
    bottom: "label"
    top: "loss"
    exclude {
    stage: "deploy"
    }
    }

    layer {
    name: "softmax"
    type: "Softmax"
    bottom: "fc8"
    top: "softmax"
    include {
    stage: "deploy"
    }
    }