name: "AlexNet" layers { name: "data" type: DATA data_param { source: "ilsvrc12_val_leveldb" mean_file: "../../data/ilsvrc12/imagenet_mean.binaryproto" batch_size: 50 crop_size: 227 mirror: false } top: "data" top: "label" } layers { name: "conv1" type: CONVOLUTION convolution_param { num_output: 96 kernel_size: 11 stride: 4 } bottom: "data" top: "conv1" } layers { name: "relu1" type: RELU bottom: "conv1" top: "conv1" } layers { name: "norm1" type: LRN lrn_param { local_size: 5 alpha: 0.0001 beta: 0.75 } bottom: "conv1" top: "norm1" } layers { name: "pool1" type: POOLING pooling_param { pool: MAX kernel_size: 3 stride: 2 } bottom: "norm1" top: "pool1" } layers { name: "conv2" type: CONVOLUTION convolution_param { num_output: 256 pad: 2 kernel_size: 5 group: 2 } bottom: "pool1" top: "conv2" } layers { name: "relu2" type: RELU bottom: "conv2" top: "conv2" } layers { name: "norm2" type: LRN lrn_param { local_size: 5 alpha: 0.0001 beta: 0.75 } bottom: "conv2" top: "norm2" } layers { name: "pool2" type: POOLING pooling_param { pool: MAX kernel_size: 3 stride: 2 } bottom: "norm2" top: "pool2" } layers { name: "conv3" type: CONVOLUTION convolution_param { num_output: 384 pad: 1 kernel_size: 3 } bottom: "pool2" top: "conv3" } layers { name: "relu3" type: RELU bottom: "conv3" top: "conv3" } layers { name: "conv4" type: CONVOLUTION convolution_param { num_output: 384 pad: 1 kernel_size: 3 group: 2 } bottom: "conv3" top: "conv4" } layers { name: "relu4" type: RELU bottom: "conv4" top: "conv4" } layers { name: "conv5" type: CONVOLUTION convolution_param { num_output: 256 pad: 1 kernel_size: 3 group: 2 } bottom: "conv4" top: "conv5" } layers { name: "relu5" type: RELU bottom: "conv5" top: "conv5" } layers { name: "pool5" type: POOLING pooling_param { pool: MAX kernel_size: 3 stride: 2 } bottom: "conv5" top: "pool5" } layers { name: "fc6" type: INNER_PRODUCT inner_product_param { num_output: 4096 } bottom: "pool5" top: "fc6" } layers { name: "relu6" type: RELU bottom: "fc6" top: "fc6" } layers { name: "drop6" type: DROPOUT dropout_param { dropout_ratio: 0.5 } bottom: "fc6" top: "fc6" } layers { name: "fc7" type: INNER_PRODUCT inner_product_param { num_output: 4096 } bottom: "fc6" top: "fc7" } layers { name: "relu7" type: RELU bottom: "fc7" top: "fc7" } layers { name: "drop7" type: DROPOUT dropout_param { dropout_ratio: 0.5 } bottom: "fc7" top: "fc7" } layers { name: "fc8" type: INNER_PRODUCT inner_product_param { num_output: 1000 } bottom: "fc7" top: "fc8" } layers { name: "prob" type: SOFTMAX bottom: "fc8" top: "prob" } layers { top: "accuracy" name: "accuracy" type: ACCURACY bottom: "prob" bottom: "label" }