Last active
June 13, 2017 12:46
-
-
Save dudu159632/fb747800273880d273b4873da56c68b6 to your computer and use it in GitHub Desktop.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: "Inception_Resnet2_v2" | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| transform_param { | |
| mirror: false | |
| crop_size: 34 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| } | |
| data_param { | |
| source: "imagenet_train_lmdb" | |
| batch_size: 64 | |
| backend: LMDB | |
| } | |
| } | |
| 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: 64 | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "conv1_scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "resx6_conv1" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "resx6_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx6_conv1" | |
| top: "resx6_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv1_scale" | |
| bottom: "resx6_conv1" | |
| top: "resx6_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx6_conv1" | |
| top: "resx6_conv1" | |
| } | |
| layer { | |
| name: "resx6_conv2" | |
| type: "Convolution" | |
| bottom: "resx6_conv1" | |
| top: "resx6_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx6_conv2" | |
| top: "resx6_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv2_scale" | |
| bottom: "resx6_conv2" | |
| top: "resx6_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx6_conv2" | |
| top: "resx6_conv2" | |
| } | |
| layer { | |
| name: "resx6_conv3" | |
| type: "Convolution" | |
| bottom: "resx6_conv2" | |
| top: "resx6_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx6_conv3" | |
| top: "resx6_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx6_conv3_scale" | |
| bottom: "resx6_conv3" | |
| top: "resx6_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx1_match_conv" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "resx1_match_conv" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx1_match_conv_bn" | |
| type: "BatchNorm" | |
| bottom: "resx1_match_conv" | |
| top: "resx1_match_conv" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx1_match_conv_scale" | |
| bottom: "resx1_match_conv" | |
| top: "resx1_match_conv" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx6_elewise" | |
| type: "Eltwise" | |
| bottom: "resx1_match_conv" | |
| bottom: "resx6_conv3" | |
| top: "resx6_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx6_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx6_elewise" | |
| top: "resx6_elewise" | |
| } | |
| layer { | |
| name: "resx8_conv1" | |
| type: "Convolution" | |
| bottom: "resx6_elewise" | |
| top: "resx8_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx8_conv1" | |
| top: "resx8_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv1_scale" | |
| bottom: "resx8_conv1" | |
| top: "resx8_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx8_conv1" | |
| top: "resx8_conv1" | |
| } | |
| layer { | |
| name: "resx8_conv2" | |
| type: "Convolution" | |
| bottom: "resx8_conv1" | |
| top: "resx8_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx8_conv2" | |
| top: "resx8_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv2_scale" | |
| bottom: "resx8_conv2" | |
| top: "resx8_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx8_conv2" | |
| top: "resx8_conv2" | |
| } | |
| layer { | |
| name: "resx8_conv3" | |
| type: "Convolution" | |
| bottom: "resx8_conv2" | |
| top: "resx8_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx8_conv3" | |
| top: "resx8_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx8_conv3_scale" | |
| bottom: "resx8_conv3" | |
| top: "resx8_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx8_match_conv" | |
| type: "Convolution" | |
| bottom: "resx6_elewise" | |
| top: "resx8_match_conv" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 2 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx8_match_conv_bn" | |
| type: "BatchNorm" | |
| bottom: "resx8_match_conv" | |
| top: "resx8_match_conv" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx8_match_conv_scale" | |
| bottom: "resx8_match_conv" | |
| top: "resx8_match_conv" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx8_elewise" | |
| type: "Eltwise" | |
| bottom: "resx8_conv3" | |
| bottom: "resx8_match_conv" | |
| top: "resx8_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx8_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx8_elewise" | |
| top: "resx8_elewise" | |
| } | |
| layer { | |
| name: "resx9_conv1" | |
| type: "Convolution" | |
| bottom: "resx8_elewise" | |
| top: "resx9_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx9_conv1" | |
| top: "resx9_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv1_scale" | |
| bottom: "resx9_conv1" | |
| top: "resx9_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx9_conv1" | |
| top: "resx9_conv1" | |
| } | |
| layer { | |
| name: "resx9_conv2" | |
| type: "Convolution" | |
| bottom: "resx9_conv1" | |
| top: "resx9_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx9_conv2" | |
| top: "resx9_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv2_scale" | |
| bottom: "resx9_conv2" | |
| top: "resx9_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx9_conv2" | |
| top: "resx9_conv2" | |
| } | |
| layer { | |
| name: "resx9_conv3" | |
| type: "Convolution" | |
| bottom: "resx9_conv2" | |
| top: "resx9_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx9_conv3" | |
| top: "resx9_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx9_conv3_scale" | |
| bottom: "resx9_conv3" | |
| top: "resx9_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx9_elewise" | |
| type: "Eltwise" | |
| bottom: "resx8_elewise" | |
| bottom: "resx9_conv3" | |
| top: "resx9_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx9_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx9_elewise" | |
| top: "resx9_elewise" | |
| } | |
| layer { | |
| name: "resx10_conv1" | |
| type: "Convolution" | |
| bottom: "resx9_elewise" | |
| top: "resx10_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx10_conv1" | |
| top: "resx10_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv1_scale" | |
| bottom: "resx10_conv1" | |
| top: "resx10_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx10_conv1" | |
| top: "resx10_conv1" | |
| } | |
| layer { | |
| name: "resx10_conv2" | |
| type: "Convolution" | |
| bottom: "resx10_conv1" | |
| top: "resx10_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx10_conv2" | |
| top: "resx10_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv2_scale" | |
| bottom: "resx10_conv2" | |
| top: "resx10_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx10_conv2" | |
| top: "resx10_conv2" | |
| } | |
| layer { | |
| name: "resx10_conv3" | |
| type: "Convolution" | |
| bottom: "resx10_conv2" | |
| top: "resx10_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx10_conv3" | |
| top: "resx10_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx10_conv3_scale" | |
| bottom: "resx10_conv3" | |
| top: "resx10_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx10_elewise" | |
| type: "Eltwise" | |
| bottom: "resx9_elewise" | |
| bottom: "resx10_conv3" | |
| top: "resx10_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx10_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx10_elewise" | |
| top: "resx10_elewise" | |
| } | |
| layer { | |
| name: "resx11_conv1" | |
| type: "Convolution" | |
| bottom: "resx10_elewise" | |
| top: "resx11_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx11_conv1" | |
| top: "resx11_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv1_scale" | |
| bottom: "resx11_conv1" | |
| top: "resx11_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx11_conv1" | |
| top: "resx11_conv1" | |
| } | |
| layer { | |
| name: "resx11_conv2" | |
| type: "Convolution" | |
| bottom: "resx11_conv1" | |
| top: "resx11_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx11_conv2" | |
| top: "resx11_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv2_scale" | |
| bottom: "resx11_conv2" | |
| top: "resx11_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx11_conv2" | |
| top: "resx11_conv2" | |
| } | |
| layer { | |
| name: "resx11_conv3" | |
| type: "Convolution" | |
| bottom: "resx11_conv2" | |
| top: "resx11_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx11_conv3" | |
| top: "resx11_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx11_conv3_scale" | |
| bottom: "resx11_conv3" | |
| top: "resx11_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx11_elewise" | |
| type: "Eltwise" | |
| bottom: "resx10_elewise" | |
| bottom: "resx11_conv3" | |
| top: "resx11_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx11_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx11_elewise" | |
| top: "resx11_elewise" | |
| } | |
| layer { | |
| name: "resx12_conv1" | |
| type: "Convolution" | |
| bottom: "resx11_elewise" | |
| top: "resx12_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx12_conv1" | |
| top: "resx12_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv1_scale" | |
| bottom: "resx12_conv1" | |
| top: "resx12_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx12_conv1" | |
| top: "resx12_conv1" | |
| } | |
| layer { | |
| name: "resx12_conv2" | |
| type: "Convolution" | |
| bottom: "resx12_conv1" | |
| top: "resx12_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx12_conv2" | |
| top: "resx12_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv2_scale" | |
| bottom: "resx12_conv2" | |
| top: "resx12_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx12_conv2" | |
| top: "resx12_conv2" | |
| } | |
| layer { | |
| name: "resx12_conv3" | |
| type: "Convolution" | |
| bottom: "resx12_conv2" | |
| top: "resx12_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx12_conv3" | |
| top: "resx12_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx12_conv3_scale" | |
| bottom: "resx12_conv3" | |
| top: "resx12_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx12_elewise" | |
| type: "Eltwise" | |
| bottom: "resx11_elewise" | |
| bottom: "resx12_conv3" | |
| top: "resx12_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx12_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx12_elewise" | |
| top: "resx12_elewise" | |
| } | |
| layer { | |
| name: "resx13_conv1" | |
| type: "Convolution" | |
| bottom: "resx12_elewise" | |
| top: "resx13_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx13_conv1" | |
| top: "resx13_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv1_scale" | |
| bottom: "resx13_conv1" | |
| top: "resx13_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx13_conv1" | |
| top: "resx13_conv1" | |
| } | |
| layer { | |
| name: "resx13_conv2" | |
| type: "Convolution" | |
| bottom: "resx13_conv1" | |
| top: "resx13_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx13_conv2" | |
| top: "resx13_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv2_scale" | |
| bottom: "resx13_conv2" | |
| top: "resx13_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx13_conv2" | |
| top: "resx13_conv2" | |
| } | |
| layer { | |
| name: "resx13_conv3" | |
| type: "Convolution" | |
| bottom: "resx13_conv2" | |
| top: "resx13_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx13_conv3" | |
| top: "resx13_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx13_conv3_scale" | |
| bottom: "resx13_conv3" | |
| top: "resx13_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx13_elewise" | |
| type: "Eltwise" | |
| bottom: "resx12_elewise" | |
| bottom: "resx13_conv3" | |
| top: "resx13_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx13_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx13_elewise" | |
| top: "resx13_elewise" | |
| } | |
| layer { | |
| name: "resx14_conv1" | |
| type: "Convolution" | |
| bottom: "resx13_elewise" | |
| top: "resx14_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx14_conv1" | |
| top: "resx14_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv1_scale" | |
| bottom: "resx14_conv1" | |
| top: "resx14_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx14_conv1" | |
| top: "resx14_conv1" | |
| } | |
| layer { | |
| name: "resx14_conv2" | |
| type: "Convolution" | |
| bottom: "resx14_conv1" | |
| top: "resx14_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx14_conv2" | |
| top: "resx14_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv2_scale" | |
| bottom: "resx14_conv2" | |
| top: "resx14_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx14_conv2" | |
| top: "resx14_conv2" | |
| } | |
| layer { | |
| name: "resx14_conv3" | |
| type: "Convolution" | |
| bottom: "resx14_conv2" | |
| top: "resx14_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx14_conv3" | |
| top: "resx14_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx14_conv3_scale" | |
| bottom: "resx14_conv3" | |
| top: "resx14_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx14_match_conv" | |
| type: "Convolution" | |
| bottom: "resx13_elewise" | |
| top: "resx14_match_conv" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| stride: 2 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx14_match_conv_bn" | |
| type: "BatchNorm" | |
| bottom: "resx14_match_conv" | |
| top: "resx14_match_conv" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx14_match_conv_scale" | |
| bottom: "resx14_match_conv" | |
| top: "resx14_match_conv" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx14_elewise" | |
| type: "Eltwise" | |
| bottom: "resx14_match_conv" | |
| bottom: "resx14_conv3" | |
| top: "resx14_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx14_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx14_elewise" | |
| top: "resx14_elewise" | |
| } | |
| layer { | |
| name: "resx15_conv1" | |
| type: "Convolution" | |
| bottom: "resx14_elewise" | |
| top: "resx15_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx15_conv1" | |
| top: "resx15_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv1_scale" | |
| bottom: "resx15_conv1" | |
| top: "resx15_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx15_conv1" | |
| top: "resx15_conv1" | |
| } | |
| layer { | |
| name: "resx15_conv2" | |
| type: "Convolution" | |
| bottom: "resx15_conv1" | |
| top: "resx15_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx15_conv2" | |
| top: "resx15_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv2_scale" | |
| bottom: "resx15_conv2" | |
| top: "resx15_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx15_conv2" | |
| top: "resx15_conv2" | |
| } | |
| layer { | |
| name: "resx15_conv3" | |
| type: "Convolution" | |
| bottom: "resx15_conv2" | |
| top: "resx15_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx15_conv3" | |
| top: "resx15_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx15_conv3_scale" | |
| bottom: "resx15_conv3" | |
| top: "resx15_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx15_elewise" | |
| type: "Eltwise" | |
| bottom: "resx14_elewise" | |
| bottom: "resx15_conv3" | |
| top: "resx15_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx15_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx15_elewise" | |
| top: "resx15_elewise" | |
| } | |
| layer { | |
| name: "resx16_conv1" | |
| type: "Convolution" | |
| bottom: "resx15_elewise" | |
| top: "resx16_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "resx16_conv1" | |
| top: "resx16_conv1" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv1_scale" | |
| bottom: "resx16_conv1" | |
| top: "resx16_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv1_relu" | |
| type: "ReLU" | |
| bottom: "resx16_conv1" | |
| top: "resx16_conv1" | |
| } | |
| layer { | |
| name: "resx16_conv2" | |
| type: "Convolution" | |
| bottom: "resx16_conv1" | |
| top: "resx16_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| stride: 1 | |
| group: 32 | |
| pad: 1 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "resx16_conv2" | |
| top: "resx16_conv2" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv2_scale" | |
| bottom: "resx16_conv2" | |
| top: "resx16_conv2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv2_relu" | |
| type: "ReLU" | |
| bottom: "resx16_conv2" | |
| top: "resx16_conv2" | |
| } | |
| layer { | |
| name: "resx16_conv3" | |
| type: "Convolution" | |
| bottom: "resx16_conv2" | |
| top: "resx16_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| stride: 1 | |
| pad: 0 | |
| weight_filler { | |
| type: "xavier" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "resx16_conv3" | |
| top: "resx16_conv3" | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| name: "resx16_conv3_scale" | |
| bottom: "resx16_conv3" | |
| top: "resx16_conv3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "resx16_elewise" | |
| type: "Eltwise" | |
| bottom: "resx15_elewise" | |
| bottom: "resx16_conv3" | |
| top: "resx16_elewise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "resx16_elewise_relu" | |
| type: "ReLU" | |
| bottom: "resx16_elewise" | |
| top: "resx16_elewise" | |
| } | |
| layer { | |
| name: "pool_ave" | |
| type: "Pooling" | |
| bottom: "resx16_elewise" | |
| top: "pool_ave" | |
| pooling_param { | |
| global_pooling : true | |
| pool: AVE | |
| } | |
| } | |
| layer { | |
| name: "classifier" | |
| type: "InnerProduct" | |
| bottom: "pool_ave" | |
| top: "classifier" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 1000 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "classifier" | |
| bottom: "label" | |
| top: "loss" | |
| } | |
| layer { | |
| name: "accuracy_top1" | |
| type: "Accuracy" | |
| bottom: "classifier" | |
| bottom: "label" | |
| top: "accuracy_top1" | |
| include { | |
| phase: TEST | |
| } | |
| } |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment