Created
November 10, 2016 05:36
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resnet20 for cifar10
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| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 32 | |
| mean_file: "mean" | |
| } | |
| data_param { | |
| source: "./train" | |
| batch_size: 128 | |
| backend: LEVELDB | |
| } | |
| image_data_param { | |
| shuffle: true | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mirror: false | |
| crop_size: 32 | |
| mean_file: "mean" | |
| } | |
| data_param { | |
| source: "./test" | |
| batch_size: 100 | |
| backend: LEVELDB | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_conv1" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "bn_conv1" | |
| 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: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "scale_conv1" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_conv1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "map16_1_conv_a" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "map16_1_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map16_1_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map16_1_conv_a" | |
| top: "map16_1_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map16_1_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map16_1_conv_a" | |
| top: "map16_1_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map16_1_scale_a" | |
| type: "Scale" | |
| bottom: "map16_1_conv_a" | |
| top: "map16_1_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map16_1_relu_a" | |
| type: "ReLU" | |
| bottom: "map16_1_conv_a" | |
| top: "map16_1_conv_a" | |
| } | |
| layer { | |
| name: "map16_1_conv_b" | |
| type: "Convolution" | |
| bottom: "map16_1_conv_a" | |
| top: "map16_1_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map16_1_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map16_1_conv_b" | |
| top: "map16_1_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map16_1_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map16_1_conv_b" | |
| top: "map16_1_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map16_1_scale_b" | |
| type: "Scale" | |
| bottom: "map16_1_conv_b" | |
| top: "map16_1_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map16_1_eltsum" | |
| type: "Eltwise" | |
| bottom: "conv1" | |
| bottom: "map16_1_conv_b" | |
| top: "map16_1_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map16_1_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map16_1_eltsum" | |
| top: "map16_1_eltsum" | |
| } | |
| layer { | |
| name: "map16_2_conv_a" | |
| type: "Convolution" | |
| bottom: "map16_1_eltsum" | |
| top: "map16_2_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map16_2_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map16_2_conv_a" | |
| top: "map16_2_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map16_2_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map16_2_conv_a" | |
| top: "map16_2_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map16_2_scale_a" | |
| type: "Scale" | |
| bottom: "map16_2_conv_a" | |
| top: "map16_2_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map16_2_relu_a" | |
| type: "ReLU" | |
| bottom: "map16_2_conv_a" | |
| top: "map16_2_conv_a" | |
| } | |
| layer { | |
| name: "map16_2_conv_b" | |
| type: "Convolution" | |
| bottom: "map16_2_conv_a" | |
| top: "map16_2_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map16_2_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map16_2_conv_b" | |
| top: "map16_2_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map16_2_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map16_2_conv_b" | |
| top: "map16_2_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map16_2_scale_b" | |
| type: "Scale" | |
| bottom: "map16_2_conv_b" | |
| top: "map16_2_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map16_2_eltsum" | |
| type: "Eltwise" | |
| bottom: "map16_1_eltsum" | |
| bottom: "map16_2_conv_b" | |
| top: "map16_2_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map16_2_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map16_2_eltsum" | |
| top: "map16_2_eltsum" | |
| } | |
| layer { | |
| name: "map16_3_conv_a" | |
| type: "Convolution" | |
| bottom: "map16_2_eltsum" | |
| top: "map16_3_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map16_3_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map16_3_conv_a" | |
| top: "map16_3_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map16_3_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map16_3_conv_a" | |
| top: "map16_3_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map16_3_scale_a" | |
| type: "Scale" | |
| bottom: "map16_3_conv_a" | |
| top: "map16_3_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map16_3_relu_a" | |
| type: "ReLU" | |
| bottom: "map16_3_conv_a" | |
| top: "map16_3_conv_a" | |
| } | |
| layer { | |
| name: "map16_3_conv_b" | |
| type: "Convolution" | |
| bottom: "map16_3_conv_a" | |
| top: "map16_3_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map16_3_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map16_3_conv_b" | |
| top: "map16_3_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map16_3_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map16_3_conv_b" | |
| top: "map16_3_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map16_3_scale_b" | |
| type: "Scale" | |
| bottom: "map16_3_conv_b" | |
| top: "map16_3_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map16_3_eltsum" | |
| type: "Eltwise" | |
| bottom: "map16_2_eltsum" | |
| bottom: "map16_3_conv_b" | |
| top: "map16_3_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map16_3_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map16_3_eltsum" | |
| top: "map16_3_eltsum" | |
| } | |
| layer { | |
| name: "map32_1_conv_proj" | |
| type: "Convolution" | |
| bottom: "map16_3_eltsum" | |
| top: "map32_1_conv_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_1_bn_proj" | |
| type: "BatchNorm" | |
| bottom: "map32_1_conv_proj" | |
| top: "map32_1_conv_proj" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_1_bn_proj" | |
| type: "BatchNorm" | |
| bottom: "map32_1_conv_proj" | |
| top: "map32_1_conv_proj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_1_scale_proj" | |
| type: "Scale" | |
| bottom: "map32_1_conv_proj" | |
| top: "map32_1_conv_proj" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_1_conv_a" | |
| type: "Convolution" | |
| bottom: "map16_3_eltsum" | |
| top: "map32_1_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_1_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map32_1_conv_a" | |
| top: "map32_1_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_1_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map32_1_conv_a" | |
| top: "map32_1_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_1_scale_a" | |
| type: "Scale" | |
| bottom: "map32_1_conv_a" | |
| top: "map32_1_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_1_relu_a" | |
| type: "ReLU" | |
| bottom: "map32_1_conv_a" | |
| top: "map32_1_conv_a" | |
| } | |
| layer { | |
| name: "map32_1_conv_b" | |
| type: "Convolution" | |
| bottom: "map32_1_conv_a" | |
| top: "map32_1_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_1_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map32_1_conv_b" | |
| top: "map32_1_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_1_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map32_1_conv_b" | |
| top: "map32_1_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_1_scale_b" | |
| type: "Scale" | |
| bottom: "map32_1_conv_b" | |
| top: "map32_1_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_1_eltsum" | |
| type: "Eltwise" | |
| bottom: "map32_1_conv_proj" | |
| bottom: "map32_1_conv_b" | |
| top: "map32_1_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map32_1_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map32_1_eltsum" | |
| top: "map32_1_eltsum" | |
| } | |
| layer { | |
| name: "map32_2_conv_a" | |
| type: "Convolution" | |
| bottom: "map32_1_eltsum" | |
| top: "map32_2_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_2_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map32_2_conv_a" | |
| top: "map32_2_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_2_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map32_2_conv_a" | |
| top: "map32_2_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_2_scale_a" | |
| type: "Scale" | |
| bottom: "map32_2_conv_a" | |
| top: "map32_2_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_2_relu_a" | |
| type: "ReLU" | |
| bottom: "map32_2_conv_a" | |
| top: "map32_2_conv_a" | |
| } | |
| layer { | |
| name: "map32_2_conv_b" | |
| type: "Convolution" | |
| bottom: "map32_2_conv_a" | |
| top: "map32_2_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_2_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map32_2_conv_b" | |
| top: "map32_2_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_2_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map32_2_conv_b" | |
| top: "map32_2_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_2_scale_b" | |
| type: "Scale" | |
| bottom: "map32_2_conv_b" | |
| top: "map32_2_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_2_eltsum" | |
| type: "Eltwise" | |
| bottom: "map32_1_eltsum" | |
| bottom: "map32_2_conv_b" | |
| top: "map32_2_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map32_2_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map32_2_eltsum" | |
| top: "map32_2_eltsum" | |
| } | |
| layer { | |
| name: "map32_3_conv_a" | |
| type: "Convolution" | |
| bottom: "map32_2_eltsum" | |
| top: "map32_3_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_3_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map32_3_conv_a" | |
| top: "map32_3_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_3_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map32_3_conv_a" | |
| top: "map32_3_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_3_scale_a" | |
| type: "Scale" | |
| bottom: "map32_3_conv_a" | |
| top: "map32_3_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_3_relu_a" | |
| type: "ReLU" | |
| bottom: "map32_3_conv_a" | |
| top: "map32_3_conv_a" | |
| } | |
| layer { | |
| name: "map32_3_conv_b" | |
| type: "Convolution" | |
| bottom: "map32_3_conv_a" | |
| top: "map32_3_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map32_3_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map32_3_conv_b" | |
| top: "map32_3_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map32_3_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map32_3_conv_b" | |
| top: "map32_3_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map32_3_scale_b" | |
| type: "Scale" | |
| bottom: "map32_3_conv_b" | |
| top: "map32_3_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map32_3_eltsum" | |
| type: "Eltwise" | |
| bottom: "map32_2_eltsum" | |
| bottom: "map32_3_conv_b" | |
| top: "map32_3_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map32_3_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map32_3_eltsum" | |
| top: "map32_3_eltsum" | |
| } | |
| layer { | |
| name: "map64_1_conv_proj" | |
| type: "Convolution" | |
| bottom: "map32_3_eltsum" | |
| top: "map64_1_conv_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_1_bn_proj" | |
| type: "BatchNorm" | |
| bottom: "map64_1_conv_proj" | |
| top: "map64_1_conv_proj" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_1_bn_proj" | |
| type: "BatchNorm" | |
| bottom: "map64_1_conv_proj" | |
| top: "map64_1_conv_proj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_1_scale_proj" | |
| type: "Scale" | |
| bottom: "map64_1_conv_proj" | |
| top: "map64_1_conv_proj" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_1_conv_a" | |
| type: "Convolution" | |
| bottom: "map32_3_eltsum" | |
| top: "map64_1_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_1_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map64_1_conv_a" | |
| top: "map64_1_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_1_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map64_1_conv_a" | |
| top: "map64_1_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_1_scale_a" | |
| type: "Scale" | |
| bottom: "map64_1_conv_a" | |
| top: "map64_1_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_1_relu_a" | |
| type: "ReLU" | |
| bottom: "map64_1_conv_a" | |
| top: "map64_1_conv_a" | |
| } | |
| layer { | |
| name: "map64_1_conv_b" | |
| type: "Convolution" | |
| bottom: "map64_1_conv_a" | |
| top: "map64_1_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_1_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map64_1_conv_b" | |
| top: "map64_1_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_1_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map64_1_conv_b" | |
| top: "map64_1_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_1_scale_b" | |
| type: "Scale" | |
| bottom: "map64_1_conv_b" | |
| top: "map64_1_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_1_eltsum" | |
| type: "Eltwise" | |
| bottom: "map64_1_conv_proj" | |
| bottom: "map64_1_conv_b" | |
| top: "map64_1_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map64_1_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map64_1_eltsum" | |
| top: "map64_1_eltsum" | |
| } | |
| layer { | |
| name: "map64_2_conv_a" | |
| type: "Convolution" | |
| bottom: "map64_1_eltsum" | |
| top: "map64_2_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_2_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map64_2_conv_a" | |
| top: "map64_2_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_2_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map64_2_conv_a" | |
| top: "map64_2_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_2_scale_a" | |
| type: "Scale" | |
| bottom: "map64_2_conv_a" | |
| top: "map64_2_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_2_relu_a" | |
| type: "ReLU" | |
| bottom: "map64_2_conv_a" | |
| top: "map64_2_conv_a" | |
| } | |
| layer { | |
| name: "map64_2_conv_b" | |
| type: "Convolution" | |
| bottom: "map64_2_conv_a" | |
| top: "map64_2_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_2_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map64_2_conv_b" | |
| top: "map64_2_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_2_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map64_2_conv_b" | |
| top: "map64_2_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_2_scale_b" | |
| type: "Scale" | |
| bottom: "map64_2_conv_b" | |
| top: "map64_2_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_2_eltsum" | |
| type: "Eltwise" | |
| bottom: "map64_1_eltsum" | |
| bottom: "map64_2_conv_b" | |
| top: "map64_2_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map64_2_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map64_2_eltsum" | |
| top: "map64_2_eltsum" | |
| } | |
| layer { | |
| name: "map64_3_conv_a" | |
| type: "Convolution" | |
| bottom: "map64_2_eltsum" | |
| top: "map64_3_conv_a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_3_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map64_3_conv_a" | |
| top: "map64_3_conv_a" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_3_bn_a" | |
| type: "BatchNorm" | |
| bottom: "map64_3_conv_a" | |
| top: "map64_3_conv_a" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_3_scale_a" | |
| type: "Scale" | |
| bottom: "map64_3_conv_a" | |
| top: "map64_3_conv_a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_3_relu_a" | |
| type: "ReLU" | |
| bottom: "map64_3_conv_a" | |
| top: "map64_3_conv_a" | |
| } | |
| layer { | |
| name: "map64_3_conv_b" | |
| type: "Convolution" | |
| bottom: "map64_3_conv_a" | |
| top: "map64_3_conv_b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "map64_3_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map64_3_conv_b" | |
| top: "map64_3_conv_b" | |
| 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 | |
| } | |
| } | |
| layer { | |
| name: "map64_3_bn_b" | |
| type: "BatchNorm" | |
| bottom: "map64_3_conv_b" | |
| top: "map64_3_conv_b" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "map64_3_scale_b" | |
| type: "Scale" | |
| bottom: "map64_3_conv_b" | |
| top: "map64_3_conv_b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "map64_3_eltsum" | |
| type: "Eltwise" | |
| bottom: "map64_2_eltsum" | |
| bottom: "map64_3_conv_b" | |
| top: "map64_3_eltsum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "map64_3_relu_after_sum" | |
| type: "ReLU" | |
| bottom: "map64_3_eltsum" | |
| top: "map64_3_eltsum" | |
| } | |
| layer { | |
| name: "pool_global" | |
| type: "Pooling" | |
| bottom: "map64_3_eltsum" | |
| top: "pool_global" | |
| pooling_param { | |
| pool: AVE | |
| global_pooling: true | |
| } | |
| } | |
| layer { | |
| name: "score" | |
| type: "InnerProduct" | |
| bottom: "pool_global" | |
| top: "score" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 10 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "score" | |
| bottom: "label" | |
| top: "loss" | |
| } | |
| layer { | |
| name: "acc" | |
| type: "Accuracy" | |
| bottom: "score" | |
| bottom: "label" | |
| top: "acc" | |
| } |
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