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February 5, 2019 11:53
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SimpNet/SimpNetV2/Architectures/CIFAR10/8.9Mil/train.prototxt
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| name: "CIFAR10_SimpleNet_GP_13L_drpall_8Mil_66_DRP_After_Pooling" | |
| state { | |
| phase: TRAIN | |
| level: 0 | |
| stage: "" | |
| } | |
| layer { | |
| name: "cifar" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 32 | |
| } | |
| data_param { | |
| source: "examples/cifar10/cifar10_train_leveldb_padding" | |
| batch_size: 100 | |
| backend: LEVELDB | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale1" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "drop1" | |
| type: "Dropout" | |
| bottom: "conv1" | |
| top: "conv1" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv1_0" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "conv1_0" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1_0" | |
| type: "BatchNorm" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale1_0" | |
| type: "Scale" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu1_0" | |
| type: "ReLU" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| } | |
| layer { | |
| name: "drop2" | |
| type: "Dropout" | |
| bottom: "conv1_0" | |
| top: "conv1_0" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv1_0" | |
| top: "conv2" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2" | |
| type: "BatchNorm" | |
| bottom: "conv2" | |
| top: "conv2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale2" | |
| type: "Scale" | |
| bottom: "conv2" | |
| top: "conv2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| } | |
| layer { | |
| name: "drop3" | |
| type: "Dropout" | |
| bottom: "conv2" | |
| top: "conv2" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1" | |
| type: "Convolution" | |
| bottom: "conv2" | |
| top: "conv2_1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_1" | |
| type: "BatchNorm" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale2_1" | |
| type: "Scale" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_1" | |
| type: "ReLU" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| } | |
| layer { | |
| name: "drop4" | |
| type: "Dropout" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2" | |
| type: "Convolution" | |
| bottom: "conv2_1" | |
| top: "conv2_2" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2_2" | |
| type: "BatchNorm" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale2_2" | |
| type: "Scale" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_2" | |
| type: "ReLU" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| } | |
| layer { | |
| name: "pool2_1" | |
| type: "Pooling" | |
| bottom: "conv2_2" | |
| top: "pool2_1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "drop5" | |
| type: "Dropout" | |
| bottom: "pool2_1" | |
| top: "pool2_1" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "pool2_1" | |
| top: "conv3" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3" | |
| type: "BatchNorm" | |
| bottom: "conv3" | |
| top: "conv3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale3" | |
| type: "Scale" | |
| bottom: "conv3" | |
| top: "conv3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| } | |
| layer { | |
| name: "drop6" | |
| type: "Dropout" | |
| bottom: "conv3" | |
| top: "conv3" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3_1" | |
| type: "BatchNorm" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale3_1" | |
| type: "Scale" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_1" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| } | |
| layer { | |
| name: "drop6_1" | |
| type: "Dropout" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv4" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn4" | |
| type: "BatchNorm" | |
| bottom: "conv4" | |
| top: "conv4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale4" | |
| type: "Scale" | |
| bottom: "conv4" | |
| top: "conv4" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| } | |
| layer { | |
| name: "drop7" | |
| type: "Dropout" | |
| bottom: "conv4" | |
| top: "conv4" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 182 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn4_1" | |
| type: "BatchNorm" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale4_1" | |
| type: "Scale" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_1" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| } | |
| layer { | |
| name: "drop8" | |
| type: "Dropout" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 430 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn4_2" | |
| type: "BatchNorm" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale4_2" | |
| type: "Scale" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_2" | |
| type: "ReLU" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| } | |
| layer { | |
| name: "pool4_2" | |
| type: "Pooling" | |
| bottom: "conv4_2" | |
| top: "pool4_2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "drop9" | |
| type: "Dropout" | |
| bottom: "pool4_2" | |
| top: "pool4_2" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_0" | |
| type: "Convolution" | |
| bottom: "pool4_2" | |
| top: "conv4_0" | |
| param { | |
| lr_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 430 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn4_0" | |
| type: "BatchNorm" | |
| bottom: "conv4_0" | |
| top: "conv4_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale4_0" | |
| type: "Scale" | |
| bottom: "conv4_0" | |
| top: "conv4_0" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_0" | |
| type: "ReLU" | |
| bottom: "conv4_0" | |
| top: "conv4_0" | |
| } | |
| layer { | |
| name: "drop10" | |
| type: "Dropout" | |
| bottom: "conv4_0" | |
| top: "conv4_0" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv11" | |
| type: "Convolution" | |
| bottom: "conv4_0" | |
| top: "conv11" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 455 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_conv11" | |
| type: "BatchNorm" | |
| bottom: "conv11" | |
| top: "conv11" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale_conv11" | |
| type: "Scale" | |
| bottom: "conv11" | |
| top: "conv11" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_conv11" | |
| type: "ReLU" | |
| bottom: "conv11" | |
| top: "conv11" | |
| } | |
| layer { | |
| name: "drop11" | |
| type: "Dropout" | |
| bottom: "conv11" | |
| top: "conv11" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "conv12" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| top: "conv12" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 600 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_conv12" | |
| type: "BatchNorm" | |
| bottom: "conv12" | |
| top: "conv12" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| moving_average_fraction: 0.95 | |
| } | |
| } | |
| layer { | |
| name: "scale_conv12" | |
| type: "Scale" | |
| bottom: "conv12" | |
| top: "conv12" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_conv12" | |
| type: "ReLU" | |
| bottom: "conv12" | |
| top: "conv12" | |
| } | |
| layer { | |
| name: "poolcp6" | |
| type: "Pooling" | |
| bottom: "conv12" | |
| top: "poolcp6" | |
| pooling_param { | |
| pool: MAX | |
| global_pooling: true | |
| } | |
| } | |
| layer { | |
| name: "drop12" | |
| type: "Dropout" | |
| bottom: "poolcp6" | |
| top: "poolcp6" | |
| dropout_param { | |
| dropout_ratio: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "ip1" | |
| type: "InnerProduct" | |
| bottom: "poolcp6" | |
| top: "ip1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 10 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "accuracy_training" | |
| type: "Accuracy" | |
| bottom: "ip1" | |
| bottom: "label" | |
| top: "accuracy_training" | |
| include { | |
| phase: TRAIN | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "ip1" | |
| bottom: "label" | |
| top: "loss" | |
| } |
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