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January 27, 2017 09:43
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| ############################################# | |
| # generated by | |
| # python app/imagenet/build_resnet.py -m bottleneck -n 64 -o /tmp/resnet18bottleneck/ -b 2 2 2 2 --no-fc_layers | |
| # params: 1.4 Millions | |
| # flops: 255 Millions | |
| ############################################# | |
| name: "CaffeNet" | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| # mean pixel / channel-wise mean instead of mean image | |
| transform_param { | |
| crop_size: 224 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| mirror: true | |
| max_rescale_ratio: 0.1 | |
| max_rotate_degree: 10 | |
| blur_jitter: true | |
| max_gamma_light: 5 | |
| base_gamma_light: 5 | |
| distortion_factor: 0.0001 | |
| debug: false | |
| } | |
| data_param { | |
| source: "imagenet2012/TRAIN2" | |
| batch_size: 100 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| # mean pixel / channel-wise mean instead of mean image | |
| transform_param { | |
| crop_size: 224 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| mirror: false | |
| } | |
| data_param { | |
| source: "imagenet2012/VAL" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| ######################################################################################################## | |
| ##################################### TRAIN FROM TEXT FILE | |
| ######################################################################################################## | |
| # layer { | |
| # name: "data" | |
| # type: "ImageData" | |
| # top: "data" | |
| # top: "label" | |
| # include { | |
| # phase: TRAIN | |
| # } | |
| # transform_param { | |
| # crop_size: 224 | |
| # mirror: true | |
| # mean_value: 104 | |
| # mean_value: 117 | |
| # mean_value: 123 | |
| # # scale: 128 | |
| # } | |
| # image_data_param { | |
| # source: "/home/wideeyes/proyectos/caffe/data/ilsvrc12/train.txt" | |
| # batch_size: 100 | |
| # shuffle: true | |
| # new_height: 256 | |
| # new_width: 256 | |
| # root_folder: "/media/wideeyes-data/database/imagenet2012/train/" | |
| # } | |
| # } | |
| # layer { | |
| # name: "data" | |
| # type: "ImageData" | |
| # top: "data" | |
| # top: "label" | |
| # include { | |
| # phase: TEST | |
| # } | |
| # transform_param { | |
| # crop_size: 224 | |
| # mirror: false | |
| # mean_value: 104 | |
| # mean_value: 117 | |
| # mean_value: 123 | |
| # # scale: 128 | |
| # } | |
| # image_data_param { | |
| # source: "/home/wideeyes/proyectos/caffe/data/ilsvrc12/val.txt" | |
| # batch_size: 10 | |
| # #shuffle: true | |
| # new_height: 256 | |
| # new_width: 256 | |
| # root_folder: "/media/wideeyes-data/database/imagenet2012/val/" | |
| # } | |
| # } | |
| layer { | |
| name: "conv_1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_1" | |
| type: "BatchNorm" | |
| bottom: "conv_1" | |
| top: "conv_1" | |
| 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: "scale_1" | |
| type: "Scale" | |
| bottom: "conv_1" | |
| top: "conv_1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_1" | |
| type: "ReLU" | |
| bottom: "conv_1" | |
| top: "conv_1" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv_1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv_stage0_block0_proj_shortcut" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv_stage0_block0_proj_shortcut" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage0_block0_proj_shortcut" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block0_proj_shortcut" | |
| top: "conv_stage0_block0_proj_shortcut" | |
| 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: "scale_stage0_block0_proj_shortcut" | |
| type: "Scale" | |
| bottom: "conv_stage0_block0_proj_shortcut" | |
| top: "conv_stage0_block0_proj_shortcut" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv_stage0_block0_branch2a" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv_stage0_block0_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage0_block0_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block0_branch2a" | |
| top: "conv_stage0_block0_branch2a" | |
| 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: "scale_stage0_block0_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage0_block0_branch2a" | |
| top: "conv_stage0_block0_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage0_block0_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage0_block0_branch2a" | |
| top: "conv_stage0_block0_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage0_block0_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage0_block0_branch2a" | |
| top: "conv_stage0_block0_branch2b" | |
| 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_stage0_block0_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block0_branch2b" | |
| top: "conv_stage0_block0_branch2b" | |
| 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: "scale_stage0_block0_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage0_block0_branch2b" | |
| top: "conv_stage0_block0_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage0_block0_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage0_block0_branch2b" | |
| top: "conv_stage0_block0_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage0_block0_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage0_block0_branch2b" | |
| top: "conv_stage0_block0_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage0_block0_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block0_branch2c" | |
| top: "conv_stage0_block0_branch2c" | |
| 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: "scale_stage0_block0_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage0_block0_branch2c" | |
| top: "conv_stage0_block0_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage0_block0" | |
| type: "Eltwise" | |
| bottom: "conv_stage0_block0_proj_shortcut" | |
| bottom: "conv_stage0_block0_branch2c" | |
| top: "eltwise_stage0_block0" | |
| } | |
| layer { | |
| name: "relu_stage0_block0" | |
| type: "ReLU" | |
| bottom: "eltwise_stage0_block0" | |
| top: "eltwise_stage0_block0" | |
| } | |
| layer { | |
| name: "conv_stage0_block1_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage0_block0" | |
| top: "conv_stage0_block1_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage0_block1_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block1_branch2a" | |
| top: "conv_stage0_block1_branch2a" | |
| 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: "scale_stage0_block1_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage0_block1_branch2a" | |
| top: "conv_stage0_block1_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage0_block1_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage0_block1_branch2a" | |
| top: "conv_stage0_block1_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage0_block1_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage0_block1_branch2a" | |
| top: "conv_stage0_block1_branch2b" | |
| 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_stage0_block1_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block1_branch2b" | |
| top: "conv_stage0_block1_branch2b" | |
| 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: "scale_stage0_block1_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage0_block1_branch2b" | |
| top: "conv_stage0_block1_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage0_block1_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage0_block1_branch2b" | |
| top: "conv_stage0_block1_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage0_block1_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage0_block1_branch2b" | |
| top: "conv_stage0_block1_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage0_block1_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage0_block1_branch2c" | |
| top: "conv_stage0_block1_branch2c" | |
| 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: "scale_stage0_block1_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage0_block1_branch2c" | |
| top: "conv_stage0_block1_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage0_block1" | |
| type: "Eltwise" | |
| bottom: "eltwise_stage0_block0" | |
| bottom: "conv_stage0_block1_branch2c" | |
| top: "eltwise_stage0_block1" | |
| } | |
| layer { | |
| name: "relu_stage0_block1" | |
| type: "ReLU" | |
| bottom: "eltwise_stage0_block1" | |
| top: "eltwise_stage0_block1" | |
| } | |
| layer { | |
| name: "conv_stage1_block0_proj_shortcut" | |
| type: "Convolution" | |
| bottom: "eltwise_stage0_block1" | |
| top: "conv_stage1_block0_proj_shortcut" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage1_block0_proj_shortcut" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block0_proj_shortcut" | |
| top: "conv_stage1_block0_proj_shortcut" | |
| 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: "scale_stage1_block0_proj_shortcut" | |
| type: "Scale" | |
| bottom: "conv_stage1_block0_proj_shortcut" | |
| top: "conv_stage1_block0_proj_shortcut" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv_stage1_block0_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage0_block1" | |
| top: "conv_stage1_block0_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage1_block0_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block0_branch2a" | |
| top: "conv_stage1_block0_branch2a" | |
| 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: "scale_stage1_block0_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage1_block0_branch2a" | |
| top: "conv_stage1_block0_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage1_block0_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage1_block0_branch2a" | |
| top: "conv_stage1_block0_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage1_block0_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage1_block0_branch2a" | |
| top: "conv_stage1_block0_branch2b" | |
| 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: "bn_stage1_block0_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block0_branch2b" | |
| top: "conv_stage1_block0_branch2b" | |
| 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: "scale_stage1_block0_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage1_block0_branch2b" | |
| top: "conv_stage1_block0_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage1_block0_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage1_block0_branch2b" | |
| top: "conv_stage1_block0_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage1_block0_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage1_block0_branch2b" | |
| top: "conv_stage1_block0_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage1_block0_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block0_branch2c" | |
| top: "conv_stage1_block0_branch2c" | |
| 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: "scale_stage1_block0_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage1_block0_branch2c" | |
| top: "conv_stage1_block0_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage1_block0" | |
| type: "Eltwise" | |
| bottom: "conv_stage1_block0_proj_shortcut" | |
| bottom: "conv_stage1_block0_branch2c" | |
| top: "eltwise_stage1_block0" | |
| } | |
| layer { | |
| name: "relu_stage1_block0" | |
| type: "ReLU" | |
| bottom: "eltwise_stage1_block0" | |
| top: "eltwise_stage1_block0" | |
| } | |
| layer { | |
| name: "conv_stage1_block1_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage1_block0" | |
| top: "conv_stage1_block1_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage1_block1_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block1_branch2a" | |
| top: "conv_stage1_block1_branch2a" | |
| 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: "scale_stage1_block1_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage1_block1_branch2a" | |
| top: "conv_stage1_block1_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage1_block1_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage1_block1_branch2a" | |
| top: "conv_stage1_block1_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage1_block1_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage1_block1_branch2a" | |
| top: "conv_stage1_block1_branch2b" | |
| 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: "bn_stage1_block1_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block1_branch2b" | |
| top: "conv_stage1_block1_branch2b" | |
| 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: "scale_stage1_block1_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage1_block1_branch2b" | |
| top: "conv_stage1_block1_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage1_block1_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage1_block1_branch2b" | |
| top: "conv_stage1_block1_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage1_block1_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage1_block1_branch2b" | |
| top: "conv_stage1_block1_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage1_block1_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage1_block1_branch2c" | |
| top: "conv_stage1_block1_branch2c" | |
| 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: "scale_stage1_block1_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage1_block1_branch2c" | |
| top: "conv_stage1_block1_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage1_block1" | |
| type: "Eltwise" | |
| bottom: "eltwise_stage1_block0" | |
| bottom: "conv_stage1_block1_branch2c" | |
| top: "eltwise_stage1_block1" | |
| } | |
| layer { | |
| name: "relu_stage1_block1" | |
| type: "ReLU" | |
| bottom: "eltwise_stage1_block1" | |
| top: "eltwise_stage1_block1" | |
| } | |
| layer { | |
| name: "conv_stage2_block0_proj_shortcut" | |
| type: "Convolution" | |
| bottom: "eltwise_stage1_block1" | |
| top: "conv_stage2_block0_proj_shortcut" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage2_block0_proj_shortcut" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block0_proj_shortcut" | |
| top: "conv_stage2_block0_proj_shortcut" | |
| 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: "scale_stage2_block0_proj_shortcut" | |
| type: "Scale" | |
| bottom: "conv_stage2_block0_proj_shortcut" | |
| top: "conv_stage2_block0_proj_shortcut" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv_stage2_block0_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage1_block1" | |
| top: "conv_stage2_block0_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage2_block0_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block0_branch2a" | |
| top: "conv_stage2_block0_branch2a" | |
| 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: "scale_stage2_block0_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage2_block0_branch2a" | |
| top: "conv_stage2_block0_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage2_block0_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage2_block0_branch2a" | |
| top: "conv_stage2_block0_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage2_block0_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage2_block0_branch2a" | |
| top: "conv_stage2_block0_branch2b" | |
| 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: "bn_stage2_block0_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block0_branch2b" | |
| top: "conv_stage2_block0_branch2b" | |
| 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: "scale_stage2_block0_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage2_block0_branch2b" | |
| top: "conv_stage2_block0_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage2_block0_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage2_block0_branch2b" | |
| top: "conv_stage2_block0_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage2_block0_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage2_block0_branch2b" | |
| top: "conv_stage2_block0_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage2_block0_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block0_branch2c" | |
| top: "conv_stage2_block0_branch2c" | |
| 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: "scale_stage2_block0_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage2_block0_branch2c" | |
| top: "conv_stage2_block0_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage2_block0" | |
| type: "Eltwise" | |
| bottom: "conv_stage2_block0_proj_shortcut" | |
| bottom: "conv_stage2_block0_branch2c" | |
| top: "eltwise_stage2_block0" | |
| } | |
| layer { | |
| name: "relu_stage2_block0" | |
| type: "ReLU" | |
| bottom: "eltwise_stage2_block0" | |
| top: "eltwise_stage2_block0" | |
| } | |
| layer { | |
| name: "conv_stage2_block1_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage2_block0" | |
| top: "conv_stage2_block1_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage2_block1_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block1_branch2a" | |
| top: "conv_stage2_block1_branch2a" | |
| 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: "scale_stage2_block1_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage2_block1_branch2a" | |
| top: "conv_stage2_block1_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage2_block1_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage2_block1_branch2a" | |
| top: "conv_stage2_block1_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage2_block1_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage2_block1_branch2a" | |
| top: "conv_stage2_block1_branch2b" | |
| 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: "bn_stage2_block1_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block1_branch2b" | |
| top: "conv_stage2_block1_branch2b" | |
| 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: "scale_stage2_block1_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage2_block1_branch2b" | |
| top: "conv_stage2_block1_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage2_block1_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage2_block1_branch2b" | |
| top: "conv_stage2_block1_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage2_block1_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage2_block1_branch2b" | |
| top: "conv_stage2_block1_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage2_block1_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage2_block1_branch2c" | |
| top: "conv_stage2_block1_branch2c" | |
| 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: "scale_stage2_block1_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage2_block1_branch2c" | |
| top: "conv_stage2_block1_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage2_block1" | |
| type: "Eltwise" | |
| bottom: "eltwise_stage2_block0" | |
| bottom: "conv_stage2_block1_branch2c" | |
| top: "eltwise_stage2_block1" | |
| } | |
| layer { | |
| name: "relu_stage2_block1" | |
| type: "ReLU" | |
| bottom: "eltwise_stage2_block1" | |
| top: "eltwise_stage2_block1" | |
| } | |
| layer { | |
| name: "conv_stage3_block0_proj_shortcut" | |
| type: "Convolution" | |
| bottom: "eltwise_stage2_block1" | |
| top: "conv_stage3_block0_proj_shortcut" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block0_proj_shortcut" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block0_proj_shortcut" | |
| top: "conv_stage3_block0_proj_shortcut" | |
| 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: "scale_stage3_block0_proj_shortcut" | |
| type: "Scale" | |
| bottom: "conv_stage3_block0_proj_shortcut" | |
| top: "conv_stage3_block0_proj_shortcut" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv_stage3_block0_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage2_block1" | |
| top: "conv_stage3_block0_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block0_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block0_branch2a" | |
| top: "conv_stage3_block0_branch2a" | |
| 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: "scale_stage3_block0_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage3_block0_branch2a" | |
| top: "conv_stage3_block0_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage3_block0_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage3_block0_branch2a" | |
| top: "conv_stage3_block0_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage3_block0_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage3_block0_branch2a" | |
| top: "conv_stage3_block0_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block0_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block0_branch2b" | |
| top: "conv_stage3_block0_branch2b" | |
| 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: "scale_stage3_block0_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage3_block0_branch2b" | |
| top: "conv_stage3_block0_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage3_block0_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage3_block0_branch2b" | |
| top: "conv_stage3_block0_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage3_block0_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage3_block0_branch2b" | |
| top: "conv_stage3_block0_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block0_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block0_branch2c" | |
| top: "conv_stage3_block0_branch2c" | |
| 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: "scale_stage3_block0_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage3_block0_branch2c" | |
| top: "conv_stage3_block0_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage3_block0" | |
| type: "Eltwise" | |
| bottom: "conv_stage3_block0_proj_shortcut" | |
| bottom: "conv_stage3_block0_branch2c" | |
| top: "eltwise_stage3_block0" | |
| } | |
| layer { | |
| name: "relu_stage3_block0" | |
| type: "ReLU" | |
| bottom: "eltwise_stage3_block0" | |
| top: "eltwise_stage3_block0" | |
| } | |
| layer { | |
| name: "conv_stage3_block1_branch2a" | |
| type: "Convolution" | |
| bottom: "eltwise_stage3_block0" | |
| top: "conv_stage3_block1_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block1_branch2a" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block1_branch2a" | |
| top: "conv_stage3_block1_branch2a" | |
| 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: "scale_stage3_block1_branch2a" | |
| type: "Scale" | |
| bottom: "conv_stage3_block1_branch2a" | |
| top: "conv_stage3_block1_branch2a" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage3_block1_branch2a" | |
| type: "ReLU" | |
| bottom: "conv_stage3_block1_branch2a" | |
| top: "conv_stage3_block1_branch2a" | |
| } | |
| layer { | |
| name: "conv_stage3_block1_branch2b" | |
| type: "Convolution" | |
| bottom: "conv_stage3_block1_branch2a" | |
| top: "conv_stage3_block1_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block1_branch2b" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block1_branch2b" | |
| top: "conv_stage3_block1_branch2b" | |
| 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: "scale_stage3_block1_branch2b" | |
| type: "Scale" | |
| bottom: "conv_stage3_block1_branch2b" | |
| top: "conv_stage3_block1_branch2b" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu_stage3_block1_branch2b" | |
| type: "ReLU" | |
| bottom: "conv_stage3_block1_branch2b" | |
| top: "conv_stage3_block1_branch2b" | |
| } | |
| layer { | |
| name: "conv_stage3_block1_branch2c" | |
| type: "Convolution" | |
| bottom: "conv_stage3_block1_branch2b" | |
| top: "conv_stage3_block1_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_stage3_block1_branch2c" | |
| type: "BatchNorm" | |
| bottom: "conv_stage3_block1_branch2c" | |
| top: "conv_stage3_block1_branch2c" | |
| 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: "scale_stage3_block1_branch2c" | |
| type: "Scale" | |
| bottom: "conv_stage3_block1_branch2c" | |
| top: "conv_stage3_block1_branch2c" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "eltwise_stage3_block1" | |
| type: "Eltwise" | |
| bottom: "eltwise_stage3_block0" | |
| bottom: "conv_stage3_block1_branch2c" | |
| top: "eltwise_stage3_block1" | |
| } | |
| layer { | |
| name: "relu_stage3_block1" | |
| type: "ReLU" | |
| bottom: "eltwise_stage3_block1" | |
| top: "eltwise_stage3_block1" | |
| } | |
| layer { | |
| name: "pool" | |
| type: "Pooling" | |
| bottom: "eltwise_stage3_block1" | |
| top: "pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 7 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc1000" | |
| type: "InnerProduct" | |
| bottom: "pool" | |
| top: "fc1000" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 1000 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "fc1000" | |
| bottom: "label" | |
| top: "loss" | |
| } | |
| layer { | |
| name: "accuracy" | |
| type: "Accuracy" | |
| bottom: "fc1000" | |
| bottom: "label" | |
| top: "accuracy" | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "accuracy-top5" | |
| type: "Accuracy" | |
| bottom: "fc1000" | |
| bottom: "label" | |
| top: "accuracy-top5" | |
| include { | |
| phase: TEST | |
| } | |
| accuracy_param { | |
| top_k: 5 | |
| } | |
| } |
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