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May 7, 2016 07:10
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| 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: 2 | |
| } | |
| } | |
| layer { | |
| name: "prob" | |
| type: "Softmax" | |
| bottom: "ip1" | |
| top: "prob" | |
| } |
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| net: "train_val.prototxt" | |
| test_iter: 1000 | |
| test_interval: 1000 | |
| base_lr: 0.01 | |
| lr_policy: "step" | |
| gamma: 0.1 | |
| stepsize: 100000 | |
| display: 20 | |
| max_iter: 450000 | |
| momentum: 0.9 | |
| weight_decay: 0.0005 | |
| snapshot: 10000 | |
| snapshot_prefix: "caffenet_train/" | |
| solver_mode: CPU |
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| name: "CIFAR10_full" | |
| layer { | |
| name: "cifar" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mean_file: "mean.binaryproto" | |
| } | |
| data_param { | |
| source: "cifar10_train_lmdb" | |
| batch_size: 111 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "cifar" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mean_file: "mean.binaryproto" | |
| } | |
| data_param { | |
| source: "cifar10_test_lmdb" | |
| batch_size: 1000 | |
| backend: LMDB | |
| } | |
| } | |
| 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 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.0001 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "Sigmoid1" | |
| type: "Sigmoid" | |
| bottom: "pool1" | |
| top: "Sigmoid1" | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "Sigmoid1" | |
| 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: "Sigmoid2" | |
| type: "Sigmoid" | |
| bottom: "conv2" | |
| top: "Sigmoid2" | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "Sigmoid2" | |
| top: "pool2" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "conv3" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| } | |
| } | |
| layer { | |
| name: "Sigmoid3" | |
| type: "Sigmoid" | |
| bottom: "conv3" | |
| top: "Sigmoid3" | |
| } | |
| layer { | |
| name: "pool3" | |
| type: "Pooling" | |
| bottom: "Sigmoid3" | |
| 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: 0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "accuracy" | |
| type: "Accuracy" | |
| bottom: "ip1" | |
| bottom: "label" | |
| top: "accuracy" | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "ip1" | |
| bottom: "label" | |
| top: "loss" | |
| } |
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