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April 24, 2017 08:04
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wideresidual network in caffe_wrn_128_v8
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| name: "wrn_128_v8" | |
| layer { | |
| name: "Data1" | |
| type: "Data" | |
| top: "Data1" | |
| top: "Data2" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 119 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| } | |
| data_param { | |
| source: "/PATH/TO/train_imagenet_128_lmdb" | |
| batch_size: 128 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "Data1" | |
| type: "Data" | |
| top: "Data1" | |
| top: "Data2" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 119 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| } | |
| data_param { | |
| source: "/PATH/TO/val_imagenet_128_lmdb" | |
| batch_size: 16 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "Convolution1" | |
| type: "Convolution" | |
| bottom: "Data1" | |
| top: "Convolution1" | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm1" | |
| type: "BatchNorm" | |
| bottom: "Convolution1" | |
| top: "Convolution1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale1" | |
| type: "Scale" | |
| bottom: "Convolution1" | |
| top: "Convolution1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU1" | |
| type: "ReLU" | |
| bottom: "Convolution1" | |
| top: "Convolution1" | |
| } | |
| layer { | |
| name: "Convolution2" | |
| type: "Convolution" | |
| bottom: "Convolution1" | |
| top: "Convolution2" | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm2" | |
| type: "BatchNorm" | |
| bottom: "Convolution2" | |
| top: "Convolution2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale2" | |
| type: "Scale" | |
| bottom: "Convolution2" | |
| top: "Convolution2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU2" | |
| type: "ReLU" | |
| bottom: "Convolution2" | |
| top: "Convolution2" | |
| } | |
| layer { | |
| name: "Convolution3" | |
| type: "Convolution" | |
| bottom: "Convolution2" | |
| top: "Convolution3" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm3" | |
| type: "BatchNorm" | |
| bottom: "Convolution3" | |
| top: "Convolution3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale3" | |
| type: "Scale" | |
| bottom: "Convolution3" | |
| top: "Convolution3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU3" | |
| type: "ReLU" | |
| bottom: "Convolution3" | |
| top: "Convolution3" | |
| } | |
| layer { | |
| name: "Pooling1" | |
| type: "Pooling" | |
| bottom: "Convolution3" | |
| top: "Pooling1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "Convolution4" | |
| type: "Convolution" | |
| bottom: "Pooling1" | |
| top: "Convolution4" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm4" | |
| type: "BatchNorm" | |
| bottom: "Convolution4" | |
| top: "Convolution4" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale4" | |
| type: "Scale" | |
| bottom: "Convolution4" | |
| top: "Convolution4" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU4" | |
| type: "ReLU" | |
| bottom: "Convolution4" | |
| top: "Convolution4" | |
| } | |
| layer { | |
| name: "Convolution5" | |
| type: "Convolution" | |
| bottom: "Convolution4" | |
| top: "Convolution5" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm5" | |
| type: "BatchNorm" | |
| bottom: "Convolution5" | |
| top: "Convolution5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale5" | |
| type: "Scale" | |
| bottom: "Convolution5" | |
| top: "Convolution5" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU5" | |
| type: "ReLU" | |
| bottom: "Convolution5" | |
| top: "Convolution5" | |
| } | |
| layer { | |
| name: "Convolution6" | |
| type: "Convolution" | |
| bottom: "Convolution5" | |
| top: "Convolution6" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm6" | |
| type: "BatchNorm" | |
| bottom: "Convolution6" | |
| top: "Convolution6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale6" | |
| type: "Scale" | |
| bottom: "Convolution6" | |
| top: "Convolution6" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU6" | |
| type: "ReLU" | |
| bottom: "Convolution6" | |
| top: "Convolution6" | |
| } | |
| layer { | |
| name: "Convolution7" | |
| type: "Convolution" | |
| bottom: "Convolution6" | |
| top: "Convolution7" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Convolution8" | |
| type: "Convolution" | |
| bottom: "Convolution5" | |
| top: "Convolution8" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise1" | |
| type: "Eltwise" | |
| bottom: "Convolution7" | |
| bottom: "Convolution8" | |
| top: "Eltwise1" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm7" | |
| type: "BatchNorm" | |
| bottom: "Eltwise1" | |
| top: "Eltwise1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale7" | |
| type: "Scale" | |
| bottom: "Eltwise1" | |
| top: "Eltwise1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU7" | |
| type: "ReLU" | |
| bottom: "Eltwise1" | |
| top: "Eltwise1" | |
| } | |
| layer { | |
| name: "Convolution9" | |
| type: "Convolution" | |
| bottom: "Eltwise1" | |
| top: "Convolution9" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm8" | |
| type: "BatchNorm" | |
| bottom: "Convolution9" | |
| top: "Convolution9" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale8" | |
| type: "Scale" | |
| bottom: "Convolution9" | |
| top: "Convolution9" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU8" | |
| type: "ReLU" | |
| bottom: "Convolution9" | |
| top: "Convolution9" | |
| } | |
| layer { | |
| name: "Convolution10" | |
| type: "Convolution" | |
| bottom: "Convolution9" | |
| top: "Convolution10" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise2" | |
| type: "Eltwise" | |
| bottom: "Convolution10" | |
| bottom: "Eltwise1" | |
| top: "Eltwise2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm9" | |
| type: "BatchNorm" | |
| bottom: "Eltwise2" | |
| top: "Eltwise2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale9" | |
| type: "Scale" | |
| bottom: "Eltwise2" | |
| top: "Eltwise2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU9" | |
| type: "ReLU" | |
| bottom: "Eltwise2" | |
| top: "Eltwise2" | |
| } | |
| layer { | |
| name: "Convolution11" | |
| type: "Convolution" | |
| bottom: "Eltwise2" | |
| top: "Convolution11" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm10" | |
| type: "BatchNorm" | |
| bottom: "Convolution11" | |
| top: "Convolution11" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale10" | |
| type: "Scale" | |
| bottom: "Convolution11" | |
| top: "Convolution11" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU10" | |
| type: "ReLU" | |
| bottom: "Convolution11" | |
| top: "Convolution11" | |
| } | |
| layer { | |
| name: "Convolution12" | |
| type: "Convolution" | |
| bottom: "Convolution11" | |
| top: "Convolution12" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise3" | |
| type: "Eltwise" | |
| bottom: "Convolution12" | |
| bottom: "Eltwise2" | |
| top: "Eltwise3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm11" | |
| type: "BatchNorm" | |
| bottom: "Eltwise3" | |
| top: "Eltwise3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale11" | |
| type: "Scale" | |
| bottom: "Eltwise3" | |
| top: "Eltwise3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU11" | |
| type: "ReLU" | |
| bottom: "Eltwise3" | |
| top: "Eltwise3" | |
| } | |
| layer { | |
| name: "Convolution13" | |
| type: "Convolution" | |
| bottom: "Eltwise3" | |
| top: "Convolution13" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm12" | |
| type: "BatchNorm" | |
| bottom: "Convolution13" | |
| top: "Convolution13" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale12" | |
| type: "Scale" | |
| bottom: "Convolution13" | |
| top: "Convolution13" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU12" | |
| type: "ReLU" | |
| bottom: "Convolution13" | |
| top: "Convolution13" | |
| } | |
| layer { | |
| name: "Convolution14" | |
| type: "Convolution" | |
| bottom: "Convolution13" | |
| top: "Convolution14" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise4" | |
| type: "Eltwise" | |
| bottom: "Convolution14" | |
| bottom: "Eltwise3" | |
| top: "Eltwise4" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "Convolution15" | |
| type: "Convolution" | |
| bottom: "Eltwise4" | |
| top: "Convolution15" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm13" | |
| type: "BatchNorm" | |
| bottom: "Convolution15" | |
| top: "Convolution15" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale13" | |
| type: "Scale" | |
| bottom: "Convolution15" | |
| top: "Convolution15" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU13" | |
| type: "ReLU" | |
| bottom: "Convolution15" | |
| top: "Convolution15" | |
| } | |
| layer { | |
| name: "Convolution16" | |
| type: "Convolution" | |
| bottom: "Convolution15" | |
| top: "Convolution16" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Convolution17" | |
| type: "Convolution" | |
| bottom: "Eltwise4" | |
| top: "Convolution17" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise5" | |
| type: "Eltwise" | |
| bottom: "Convolution16" | |
| bottom: "Convolution17" | |
| top: "Eltwise5" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm14" | |
| type: "BatchNorm" | |
| bottom: "Eltwise5" | |
| top: "Eltwise5" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale14" | |
| type: "Scale" | |
| bottom: "Eltwise5" | |
| top: "Eltwise5" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU14" | |
| type: "ReLU" | |
| bottom: "Eltwise5" | |
| top: "Eltwise5" | |
| } | |
| layer { | |
| name: "Convolution18" | |
| type: "Convolution" | |
| bottom: "Eltwise5" | |
| top: "Convolution18" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm15" | |
| type: "BatchNorm" | |
| bottom: "Convolution18" | |
| top: "Convolution18" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale15" | |
| type: "Scale" | |
| bottom: "Convolution18" | |
| top: "Convolution18" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU15" | |
| type: "ReLU" | |
| bottom: "Convolution18" | |
| top: "Convolution18" | |
| } | |
| layer { | |
| name: "Convolution19" | |
| type: "Convolution" | |
| bottom: "Convolution18" | |
| top: "Convolution19" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise6" | |
| type: "Eltwise" | |
| bottom: "Convolution19" | |
| bottom: "Eltwise5" | |
| top: "Eltwise6" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm16" | |
| type: "BatchNorm" | |
| bottom: "Eltwise6" | |
| top: "Eltwise6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale16" | |
| type: "Scale" | |
| bottom: "Eltwise6" | |
| top: "Eltwise6" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU16" | |
| type: "ReLU" | |
| bottom: "Eltwise6" | |
| top: "Eltwise6" | |
| } | |
| layer { | |
| name: "Convolution20" | |
| type: "Convolution" | |
| bottom: "Eltwise6" | |
| top: "Convolution20" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm17" | |
| type: "BatchNorm" | |
| bottom: "Convolution20" | |
| top: "Convolution20" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale17" | |
| type: "Scale" | |
| bottom: "Convolution20" | |
| top: "Convolution20" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU17" | |
| type: "ReLU" | |
| bottom: "Convolution20" | |
| top: "Convolution20" | |
| } | |
| layer { | |
| name: "Convolution21" | |
| type: "Convolution" | |
| bottom: "Convolution20" | |
| top: "Convolution21" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise7" | |
| type: "Eltwise" | |
| bottom: "Convolution21" | |
| bottom: "Eltwise6" | |
| top: "Eltwise7" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm18" | |
| type: "BatchNorm" | |
| bottom: "Eltwise7" | |
| top: "Eltwise7" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale18" | |
| type: "Scale" | |
| bottom: "Eltwise7" | |
| top: "Eltwise7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU18" | |
| type: "ReLU" | |
| bottom: "Eltwise7" | |
| top: "Eltwise7" | |
| } | |
| layer { | |
| name: "Convolution22" | |
| type: "Convolution" | |
| bottom: "Eltwise7" | |
| top: "Convolution22" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm19" | |
| type: "BatchNorm" | |
| bottom: "Convolution22" | |
| top: "Convolution22" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale19" | |
| type: "Scale" | |
| bottom: "Convolution22" | |
| top: "Convolution22" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU19" | |
| type: "ReLU" | |
| bottom: "Convolution22" | |
| top: "Convolution22" | |
| } | |
| layer { | |
| name: "Convolution23" | |
| type: "Convolution" | |
| bottom: "Convolution22" | |
| top: "Convolution23" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise8" | |
| type: "Eltwise" | |
| bottom: "Convolution23" | |
| bottom: "Eltwise7" | |
| top: "Eltwise8" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "Convolution24" | |
| type: "Convolution" | |
| bottom: "Eltwise8" | |
| top: "Convolution24" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm20" | |
| type: "BatchNorm" | |
| bottom: "Convolution24" | |
| top: "Convolution24" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale20" | |
| type: "Scale" | |
| bottom: "Convolution24" | |
| top: "Convolution24" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU20" | |
| type: "ReLU" | |
| bottom: "Convolution24" | |
| top: "Convolution24" | |
| } | |
| layer { | |
| name: "Convolution25" | |
| type: "Convolution" | |
| bottom: "Convolution24" | |
| top: "Convolution25" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Convolution26" | |
| type: "Convolution" | |
| bottom: "Eltwise8" | |
| top: "Convolution26" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise9" | |
| type: "Eltwise" | |
| bottom: "Convolution25" | |
| bottom: "Convolution26" | |
| top: "Eltwise9" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm21" | |
| type: "BatchNorm" | |
| bottom: "Eltwise9" | |
| top: "Eltwise9" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale21" | |
| type: "Scale" | |
| bottom: "Eltwise9" | |
| top: "Eltwise9" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU21" | |
| type: "ReLU" | |
| bottom: "Eltwise9" | |
| top: "Eltwise9" | |
| } | |
| layer { | |
| name: "Convolution27" | |
| type: "Convolution" | |
| bottom: "Eltwise9" | |
| top: "Convolution27" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm22" | |
| type: "BatchNorm" | |
| bottom: "Convolution27" | |
| top: "Convolution27" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale22" | |
| type: "Scale" | |
| bottom: "Convolution27" | |
| top: "Convolution27" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU22" | |
| type: "ReLU" | |
| bottom: "Convolution27" | |
| top: "Convolution27" | |
| } | |
| layer { | |
| name: "Convolution28" | |
| type: "Convolution" | |
| bottom: "Convolution27" | |
| top: "Convolution28" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise10" | |
| type: "Eltwise" | |
| bottom: "Convolution28" | |
| bottom: "Eltwise9" | |
| top: "Eltwise10" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm23" | |
| type: "BatchNorm" | |
| bottom: "Eltwise10" | |
| top: "Eltwise10" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale23" | |
| type: "Scale" | |
| bottom: "Eltwise10" | |
| top: "Eltwise10" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU23" | |
| type: "ReLU" | |
| bottom: "Eltwise10" | |
| top: "Eltwise10" | |
| } | |
| layer { | |
| name: "Convolution29" | |
| type: "Convolution" | |
| bottom: "Eltwise10" | |
| top: "Convolution29" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm24" | |
| type: "BatchNorm" | |
| bottom: "Convolution29" | |
| top: "Convolution29" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale24" | |
| type: "Scale" | |
| bottom: "Convolution29" | |
| top: "Convolution29" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU24" | |
| type: "ReLU" | |
| bottom: "Convolution29" | |
| top: "Convolution29" | |
| } | |
| layer { | |
| name: "Convolution30" | |
| type: "Convolution" | |
| bottom: "Convolution29" | |
| top: "Convolution30" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise11" | |
| type: "Eltwise" | |
| bottom: "Convolution30" | |
| bottom: "Eltwise10" | |
| top: "Eltwise11" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm25" | |
| type: "BatchNorm" | |
| bottom: "Eltwise11" | |
| top: "Eltwise11" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale25" | |
| type: "Scale" | |
| bottom: "Eltwise11" | |
| top: "Eltwise11" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU25" | |
| type: "ReLU" | |
| bottom: "Eltwise11" | |
| top: "Eltwise11" | |
| } | |
| layer { | |
| name: "Convolution31" | |
| type: "Convolution" | |
| bottom: "Eltwise11" | |
| top: "Convolution31" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm26" | |
| type: "BatchNorm" | |
| bottom: "Convolution31" | |
| top: "Convolution31" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "Scale26" | |
| type: "Scale" | |
| bottom: "Convolution31" | |
| top: "Convolution31" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "ReLU26" | |
| type: "ReLU" | |
| bottom: "Convolution31" | |
| top: "Convolution31" | |
| } | |
| layer { | |
| name: "Convolution32" | |
| type: "Convolution" | |
| bottom: "Convolution31" | |
| top: "Convolution32" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "Eltwise12" | |
| type: "Eltwise" | |
| bottom: "Convolution32" | |
| bottom: "Eltwise11" | |
| top: "Eltwise12" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "Pooling2" | |
| type: "Pooling" | |
| bottom: "Eltwise12" | |
| top: "Pooling2" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 4 | |
| stride: 4 | |
| } | |
| } | |
| layer { | |
| name: "InnerProduct1" | |
| type: "InnerProduct" | |
| bottom: "Pooling2" | |
| top: "InnerProduct1" | |
| inner_product_param { | |
| num_output: 1000 | |
| } | |
| } | |
| layer { | |
| name: "SoftmaxWithLoss1" | |
| type: "SoftmaxWithLoss" | |
| bottom: "InnerProduct1" | |
| bottom: "Data2" | |
| top: "SoftmaxWithLoss1" | |
| } | |
| layer { | |
| name: "Accuracy1" | |
| type: "Accuracy" | |
| bottom: "InnerProduct1" | |
| bottom: "Data2" | |
| top: "Accuracy1" | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "Accuracy5" | |
| type: "Accuracy" | |
| bottom: "InnerProduct1" | |
| bottom: "Data2" | |
| top: "Accuracy5" | |
| include { | |
| phase: TEST | |
| } | |
| accuracy_param { | |
| top_k: 5 | |
| } | |
| } |
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