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October 21, 2015 07:22
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Batchnorm example
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| name: "CIFAR10_full" | |
| layer { | |
| name: "cifar" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mean_file: "examples/cifar10/mean.binaryproto" | |
| } | |
| data_param { | |
| source: "examples/cifar10/cifar10_train_lmdb" | |
| batch_size: 100 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "cifar" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mean_file: "examples/cifar10/mean.binaryproto" | |
| } | |
| data_param { | |
| source: "examples/cifar10/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: "bn1" | |
| type: "BatchNorm" | |
| bottom: "pool1" | |
| top: "bn1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| } | |
| layer { | |
| name: "bn1" | |
| type: "BatchNorm" | |
| bottom: "pool1" | |
| top: "bn1" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "Sigmoid1" | |
| type: "Sigmoid" | |
| bottom: "bn1" | |
| 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: "bn2" | |
| type: "BatchNorm" | |
| bottom: "conv2" | |
| top: "bn2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| } | |
| layer { | |
| name: "bn2" | |
| type: "BatchNorm" | |
| bottom: "conv2" | |
| top: "bn2" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "Sigmoid2" | |
| type: "Sigmoid" | |
| bottom: "bn2" | |
| 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: "bn3" | |
| type: "BatchNorm" | |
| bottom: "conv3" | |
| top: "bn3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| } | |
| layer { | |
| name: "bn3" | |
| type: "BatchNorm" | |
| bottom: "conv3" | |
| top: "bn3" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "Sigmoid3" | |
| type: "Sigmoid" | |
| bottom: "bn3" | |
| 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: 250 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 10 | |
| 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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