name: "CaffeNet" layers { layer { name: "data" type: "data" source: "/home/jiayq/caffe-train-leveldb" meanfile: "/home/jiayq/ilsvrc2012_mean.binaryproto" batchsize: 64 cropsize: 227 mirror: true } top: "data" top: "label" } layers { layer { name: "conv1" type: "conv" num_output: 96 kernelsize: 11 stride: 4 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "data" top: "conv1" } layers { layer { name: "relu1" type: "relu" } bottom: "conv1" top: "conv1" } layers { layer { name: "pool1" type: "pool" pool: MAX kernelsize: 3 stride: 2 } bottom: "conv1" top: "pool1" } layers { layer { name: "norm1" type: "lrn" local_size: 5 alpha: 0.0001 beta: 0.75 } bottom: "pool1" top: "norm1" } layers { layer { name: "pad2" type: "padding" pad: 2 } bottom: "norm1" top: "pad2" } layers { layer { name: "conv2" type: "conv" num_output: 256 group: 2 kernelsize: 5 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "pad2" top: "conv2" } layers { layer { name: "relu2" type: "relu" } bottom: "conv2" top: "conv2" } layers { layer { name: "pool2" type: "pool" pool: MAX kernelsize: 3 stride: 2 } bottom: "conv2" top: "pool2" } layers { layer { name: "norm2" type: "lrn" local_size: 5 alpha: 0.0001 beta: 0.75 } bottom: "pool2" top: "norm2" } layers { layer { name: "pad3" type: "padding" pad: 1 } bottom: "norm2" top: "pad3" } layers { layer { name: "conv3" type: "conv" num_output: 384 kernelsize: 3 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "pad3" top: "conv3" } layers { layer { name: "relu3" type: "relu" } bottom: "conv3" top: "conv3" } layers { layer { name: "pad4" type: "padding" pad: 1 } bottom: "conv3" top: "pad4" } layers { layer { name: "conv4" type: "conv" num_output: 384 group: 2 kernelsize: 3 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "pad4" top: "conv4" } layers { layer { name: "relu4" type: "relu" } bottom: "conv4" top: "conv4" } layers { layer { name: "pad5" type: "padding" pad: 1 } bottom: "conv4" top: "pad5" } layers { layer { name: "conv5" type: "conv" num_output: 256 group: 2 kernelsize: 3 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "pad5" top: "conv5" } layers { layer { name: "relu5" type: "relu" } bottom: "conv5" top: "conv5" } layers { layer { name: "pool5" type: "pool" kernelsize: 3 pool: MAX stride: 2 } bottom: "conv5" top: "pool5" } layers { layer { name: "fc6" type: "innerproduct" num_output: 4096 weight_filler { type: "gaussian" std: 0.005 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "pool5" top: "fc6" } layers { layer { name: "relu6" type: "relu" } bottom: "fc6" top: "fc6" } layers { layer { name: "drop6" type: "dropout" dropout_ratio: 0.5 } bottom: "fc6" top: "fc6" } layers { layer { name: "fc7" type: "innerproduct" num_output: 4096 weight_filler { type: "gaussian" std: 0.005 } bias_filler { type: "constant" value: 0.1 } blobs_lr: 1. blobs_lr: 2. } bottom: "fc6" top: "fc7" } layers { layer { name: "relu7" type: "relu" } bottom: "fc7" top: "fc7" } layers { layer { name: "drop7" type: "dropout" dropout_ratio: 0.5 } bottom: "fc7" top: "fc7" } layers { layer { name: "fc8" type: "innerproduct" num_output: 1000 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0 } blobs_lr: 1. blobs_lr: 2. } bottom: "fc7" top: "fc8" } layers { layer { name: "loss" type: "softmax_loss" } bottom: "fc8" bottom: "label" }