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  • caffe prototxt分析

    测试用prototxt

    name: "CIFAR10_quick"
    layer {
    name: "data"
    type: "MemoryData"
    top: "data"
    top: "label"
    memory_data_param {
    batch_size: 1     #样本个数
    channels: 3
    height: 32
    32
    }
    }
    layer {
    name: "conv1"
    type: "Convolution"    #卷积层
    bottom: "data"
    top: "conv1"
    param {
    lr_mult: 1
    }
    param {
    lr_mult: 2
    }
    convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
    type: "gaussian"
    std: 0.0001
    }
    bias_filler {
    type: "constant"
    }
    }
    }
    layer {
    name: "pool1"
    type: "Pooling"    #池化层
    bottom: "conv1"
    top: "pool1"
    pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    }
    }
    layer {
    name: "relu1"
    type: "ReLU"
    bottom: "pool1"
    top: "pool1"
    }
    layer {
    name: "conv2"
    type: "Convolution"
    bottom: "pool1"
    top: "conv2"
    param {
    lr_mult: 1
    }
    param {
    lr_mult: 2
    }
    convolution_param {
    num_output: 32
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
    type: "gaussian"
    std: 0.01
    }
    bias_filler {
    type: "constant"
    }
    }
    }
    layer {
    name: "relu2"
    type: "ReLU"      #非线性ReLU层
    bottom: "conv2"
    top: "conv2"
    }
    layer {
    name: "pool2"
    type: "Pooling"
    bottom: "conv2"
    top: "pool2"
    pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
    }
    }
    layer {
    name: "conv3"
    type: "Convolution"
    bottom: "pool2"
    top: "conv3"
    param {
    lr_mult: 1
    }
    param {
    lr_mult: 2
    }
    convolution_param {
    num_output: 64
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
    type: "gaussian"
    std: 0.01
    }
    bias_filler {
    type: "constant"
    }
    }
    }
    layer {
    name: "relu3"
    type: "ReLU"
    bottom: "conv3"
    top: "conv3"
    }
    layer {
    name: "pool3"
    type: "Pooling"
    bottom: "conv3"
    top: "pool3"
    pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
    }
    }
    layer {
    name: "ip1"
    type: "InnerProduct"
    bottom: "pool3"
    top: "ip1"
    param {
    lr_mult: 1
    }
    param {
    lr_mult: 2
    }
    inner_product_param {
    num_output: 64
    weight_filler {
    type: "gaussian"
    std: 0.1
    }
    bias_filler {
    type: "constant"
    }
    }
    }
    layer {
    name: "ip2"
    type: "InnerProduct"
    bottom: "ip1"
    top: "ip2"
    param {
    lr_mult: 1
    }
    param {
    lr_mult: 2
    }
    inner_product_param {
    num_output: 10
    weight_filler {
    type: "gaussian"
    std: 0.1
    }
    bias_filler {
    type: "constant"
    }
    }
    }
    layer {
    name: "prob"
    type: "Softmax"
    bottom: "ip2"
    top: "prob"
    }

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  • 原文地址:https://www.cnblogs.com/luoyinjie/p/9258627.html
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