name: "CIFAR10_full_deploy" # N.B. input image must be in CIFAR-10 format # as described at http://www.cs.toronto.edu/~kriz/cifar.html layer { name: "data" type: "Input" top: "data" input_param { shape: { dim: 1 dim: 3 dim: 32 dim: 32 } } } layer { name: "conv1" type: "Convolution" bottom: "data" top: "conv1" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 32 pad: 2 kernel_size: 5 stride: 1 } } layer { name: "pool1" type: "Pooling" bottom: "conv1" top: "pool1" pooling_param { pool: MAX kernel_size: 3 stride: 2 } } layer { name: "relu1" type: "ReLU" bottom: "pool1" top: "pool1" } layer { name: "norm1" type: "LRN" bottom: "pool1" top: "norm1" lrn_param { local_size: 3 alpha: 5e-05 beta: 0.75 norm_region: WITHIN_CHANNEL } } layer { name: "conv2" type: "Convolution" bottom: "norm1" top: "conv2" param { lr_mult: 1 } param { lr_mult: 2 } convolution_param { num_output: 32 pad: 2 kernel_size: 5 stride: 1 } } layer { name: "relu2" type: "ReLU" bottom: "conv2" top: "conv2" } layer { name: "pool2" type: "Pooling" bottom: "conv2" top: "pool2" pooling_param { pool: AVE kernel_size: 3 stride: 2 } } layer { name: "norm2" type: "LRN" bottom: "pool2" top: "norm2" lrn_param { local_size: 3 alpha: 5e-05 beta: 0.75 norm_region: WITHIN_CHANNEL } } layer { name: "conv3" type: "Convolution" bottom: "norm2" top: "conv3" convolution_param { num_output: 64 pad: 2 kernel_size: 5 stride: 1 } } 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 decay_mult: 250 } param { lr_mult: 2 decay_mult: 0 } inner_product_param { num_output: 10 } } layer { name: "prob" type: "Softmax" bottom: "ip1" top: "prob" }