Last active
December 11, 2018 07:36
-
-
Save zhanglaplace/8856be8e748ba019aa76702522b5a549 to your computer and use it in GitHub Desktop.
mobileNetV2_deploy.prototxt
This file contains 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
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 224 | |
| input_dim: 224 | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv1/scale" | |
| type: "Scale" | |
| bottom: "conv1/bn" | |
| top: "conv1/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1/bn" | |
| top: "conv1/bn" | |
| } | |
| layer { | |
| name: "conv2_1/expand" | |
| type: "Convolution" | |
| bottom: "conv1/bn" | |
| top: "conv2_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/expand/bn" | |
| top: "conv2_1/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_1/expand" | |
| type: "ReLU" | |
| bottom: "conv2_1/expand/bn" | |
| top: "conv2_1/expand/bn" | |
| } | |
| layer { | |
| name: "conv2_1/dwise" | |
| type: "Convolution" | |
| bottom: "conv2_1/expand/bn" | |
| top: "conv2_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 32 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/dwise/bn" | |
| top: "conv2_1/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv2_1/dwise/bn" | |
| top: "conv2_1/dwise/bn" | |
| } | |
| layer { | |
| name: "conv2_1/linear" | |
| type: "Convolution" | |
| bottom: "conv2_1/dwise/bn" | |
| top: "conv2_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/linear" | |
| top: "conv2_1/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/linear/bn" | |
| top: "conv2_1/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand" | |
| type: "Convolution" | |
| bottom: "conv2_1/linear/bn" | |
| top: "conv2_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/expand/bn" | |
| top: "conv2_2/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_2/expand" | |
| type: "ReLU" | |
| bottom: "conv2_2/expand/bn" | |
| top: "conv2_2/expand/bn" | |
| } | |
| layer { | |
| name: "conv2_2/dwise" | |
| type: "Convolution" | |
| bottom: "conv2_2/expand/bn" | |
| top: "conv2_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 96 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/dwise/bn" | |
| top: "conv2_2/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv2_2/dwise/bn" | |
| top: "conv2_2/dwise/bn" | |
| } | |
| layer { | |
| name: "conv2_2/linear" | |
| type: "Convolution" | |
| bottom: "conv2_2/dwise/bn" | |
| top: "conv2_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/linear" | |
| top: "conv2_2/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/linear/bn" | |
| top: "conv2_2/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand" | |
| type: "Convolution" | |
| bottom: "conv2_2/linear/bn" | |
| top: "conv3_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/expand/bn" | |
| top: "conv3_1/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_1/expand" | |
| type: "ReLU" | |
| bottom: "conv3_1/expand/bn" | |
| top: "conv3_1/expand/bn" | |
| } | |
| layer { | |
| name: "conv3_1/dwise" | |
| type: "Convolution" | |
| bottom: "conv3_1/expand/bn" | |
| top: "conv3_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/dwise/bn" | |
| top: "conv3_1/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv3_1/dwise/bn" | |
| top: "conv3_1/dwise/bn" | |
| } | |
| layer { | |
| name: "conv3_1/linear" | |
| type: "Convolution" | |
| bottom: "conv3_1/dwise/bn" | |
| top: "conv3_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/linear" | |
| top: "conv3_1/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/linear/bn" | |
| top: "conv3_1/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_1" | |
| type: "Eltwise" | |
| bottom: "conv2_2/linear/bn" | |
| bottom: "conv3_1/linear/bn" | |
| top: "block_3_1" | |
| } | |
| layer { | |
| name: "conv3_2/expand" | |
| type: "Convolution" | |
| bottom: "block_3_1" | |
| top: "conv3_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/expand/bn" | |
| top: "conv3_2/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_2/expand" | |
| type: "ReLU" | |
| bottom: "conv3_2/expand/bn" | |
| top: "conv3_2/expand/bn" | |
| } | |
| layer { | |
| name: "conv3_2/dwise" | |
| type: "Convolution" | |
| bottom: "conv3_2/expand/bn" | |
| top: "conv3_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/dwise/bn" | |
| top: "conv3_2/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv3_2/dwise/bn" | |
| top: "conv3_2/dwise/bn" | |
| } | |
| layer { | |
| name: "conv3_2/linear" | |
| type: "Convolution" | |
| bottom: "conv3_2/dwise/bn" | |
| top: "conv3_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/linear" | |
| top: "conv3_2/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/linear/bn" | |
| top: "conv3_2/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand" | |
| type: "Convolution" | |
| bottom: "conv3_2/linear/bn" | |
| top: "conv4_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_1/expand/bn" | |
| top: "conv4_1/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_1/expand" | |
| type: "ReLU" | |
| bottom: "conv4_1/expand/bn" | |
| top: "conv4_1/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_1/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_1/expand/bn" | |
| top: "conv4_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_1/dwise/bn" | |
| top: "conv4_1/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_1/dwise/bn" | |
| top: "conv4_1/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_1/linear" | |
| type: "Convolution" | |
| bottom: "conv4_1/dwise/bn" | |
| top: "conv4_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/linear" | |
| top: "conv4_1/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_1/linear/bn" | |
| top: "conv4_1/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_1" | |
| type: "Eltwise" | |
| bottom: "conv3_2/linear/bn" | |
| bottom: "conv4_1/linear/bn" | |
| top: "block_4_1" | |
| } | |
| layer { | |
| name: "conv4_2/expand" | |
| type: "Convolution" | |
| bottom: "block_4_1" | |
| top: "conv4_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_2/expand/bn" | |
| top: "conv4_2/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_2/expand" | |
| type: "ReLU" | |
| bottom: "conv4_2/expand/bn" | |
| top: "conv4_2/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_2/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_2/expand/bn" | |
| top: "conv4_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_2/dwise/bn" | |
| top: "conv4_2/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_2/dwise/bn" | |
| top: "conv4_2/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_2/linear" | |
| type: "Convolution" | |
| bottom: "conv4_2/dwise/bn" | |
| top: "conv4_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/linear" | |
| top: "conv4_2/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_2/linear/bn" | |
| top: "conv4_2/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_2" | |
| type: "Eltwise" | |
| bottom: "block_4_1" | |
| bottom: "conv4_2/linear/bn" | |
| top: "block_4_2" | |
| } | |
| layer { | |
| name: "conv4_3/expand" | |
| type: "Convolution" | |
| bottom: "block_4_2" | |
| top: "conv4_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_3/expand/bn" | |
| top: "conv4_3/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_3/expand" | |
| type: "ReLU" | |
| bottom: "conv4_3/expand/bn" | |
| top: "conv4_3/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_3/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_3/expand/bn" | |
| top: "conv4_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_3/dwise/bn" | |
| top: "conv4_3/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_3/dwise/bn" | |
| top: "conv4_3/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_3/linear" | |
| type: "Convolution" | |
| bottom: "conv4_3/dwise/bn" | |
| top: "conv4_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/linear" | |
| top: "conv4_3/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_3/linear/bn" | |
| top: "conv4_3/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand" | |
| type: "Convolution" | |
| bottom: "conv4_3/linear/bn" | |
| top: "conv4_4/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_4/expand/bn" | |
| top: "conv4_4/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_4/expand" | |
| type: "ReLU" | |
| bottom: "conv4_4/expand/bn" | |
| top: "conv4_4/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_4/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_4/expand/bn" | |
| top: "conv4_4/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_4/dwise/bn" | |
| top: "conv4_4/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_4/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_4/dwise/bn" | |
| top: "conv4_4/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_4/linear" | |
| type: "Convolution" | |
| bottom: "conv4_4/dwise/bn" | |
| top: "conv4_4/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/linear" | |
| top: "conv4_4/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_4/linear/bn" | |
| top: "conv4_4/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_4" | |
| type: "Eltwise" | |
| bottom: "conv4_3/linear/bn" | |
| bottom: "conv4_4/linear/bn" | |
| top: "block_4_4" | |
| } | |
| layer { | |
| name: "conv4_5/expand" | |
| type: "Convolution" | |
| bottom: "block_4_4" | |
| top: "conv4_5/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_5/expand/bn" | |
| top: "conv4_5/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_5/expand" | |
| type: "ReLU" | |
| bottom: "conv4_5/expand/bn" | |
| top: "conv4_5/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_5/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_5/expand/bn" | |
| top: "conv4_5/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_5/dwise/bn" | |
| top: "conv4_5/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_5/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_5/dwise/bn" | |
| top: "conv4_5/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_5/linear" | |
| type: "Convolution" | |
| bottom: "conv4_5/dwise/bn" | |
| top: "conv4_5/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_5/linear" | |
| top: "conv4_5/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_5/linear/bn" | |
| top: "conv4_5/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_5" | |
| type: "Eltwise" | |
| bottom: "block_4_4" | |
| bottom: "conv4_5/linear/bn" | |
| top: "block_4_5" | |
| } | |
| layer { | |
| name: "conv4_6/expand" | |
| type: "Convolution" | |
| bottom: "block_4_5" | |
| top: "conv4_6/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_6/expand/bn" | |
| top: "conv4_6/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_6/expand" | |
| type: "ReLU" | |
| bottom: "conv4_6/expand/bn" | |
| top: "conv4_6/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_6/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_6/expand/bn" | |
| top: "conv4_6/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_6/dwise/bn" | |
| top: "conv4_6/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_6/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_6/dwise/bn" | |
| top: "conv4_6/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_6/linear" | |
| type: "Convolution" | |
| bottom: "conv4_6/dwise/bn" | |
| top: "conv4_6/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_6/linear" | |
| top: "conv4_6/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_6/linear/bn" | |
| top: "conv4_6/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_6" | |
| type: "Eltwise" | |
| bottom: "block_4_5" | |
| bottom: "conv4_6/linear/bn" | |
| top: "block_4_6" | |
| } | |
| layer { | |
| name: "conv4_7/expand" | |
| type: "Convolution" | |
| bottom: "block_4_6" | |
| top: "conv4_7/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/expand/scale" | |
| type: "Scale" | |
| bottom: "conv4_7/expand/bn" | |
| top: "conv4_7/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_7/expand" | |
| type: "ReLU" | |
| bottom: "conv4_7/expand/bn" | |
| top: "conv4_7/expand/bn" | |
| } | |
| layer { | |
| name: "conv4_7/dwise" | |
| type: "Convolution" | |
| bottom: "conv4_7/expand/bn" | |
| top: "conv4_7/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv4_7/dwise/bn" | |
| top: "conv4_7/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4_7/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_7/dwise/bn" | |
| top: "conv4_7/dwise/bn" | |
| } | |
| layer { | |
| name: "conv4_7/linear" | |
| type: "Convolution" | |
| bottom: "conv4_7/dwise/bn" | |
| top: "conv4_7/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_7/linear" | |
| top: "conv4_7/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv4_7/linear/scale" | |
| type: "Scale" | |
| bottom: "conv4_7/linear/bn" | |
| top: "conv4_7/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand" | |
| type: "Convolution" | |
| bottom: "conv4_7/linear/bn" | |
| top: "conv5_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv5_1/expand/bn" | |
| top: "conv5_1/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_1/expand" | |
| type: "ReLU" | |
| bottom: "conv5_1/expand/bn" | |
| top: "conv5_1/expand/bn" | |
| } | |
| layer { | |
| name: "conv5_1/dwise" | |
| type: "Convolution" | |
| bottom: "conv5_1/expand/bn" | |
| top: "conv5_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv5_1/dwise/bn" | |
| top: "conv5_1/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_1/dwise/bn" | |
| top: "conv5_1/dwise/bn" | |
| } | |
| layer { | |
| name: "conv5_1/linear" | |
| type: "Convolution" | |
| bottom: "conv5_1/dwise/bn" | |
| top: "conv5_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/linear" | |
| top: "conv5_1/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv5_1/linear/bn" | |
| top: "conv5_1/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_5_1" | |
| type: "Eltwise" | |
| bottom: "conv4_7/linear/bn" | |
| bottom: "conv5_1/linear/bn" | |
| top: "block_5_1" | |
| } | |
| layer { | |
| name: "conv5_2/expand" | |
| type: "Convolution" | |
| bottom: "block_5_1" | |
| top: "conv5_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv5_2/expand/bn" | |
| top: "conv5_2/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_2/expand" | |
| type: "ReLU" | |
| bottom: "conv5_2/expand/bn" | |
| top: "conv5_2/expand/bn" | |
| } | |
| layer { | |
| name: "conv5_2/dwise" | |
| type: "Convolution" | |
| bottom: "conv5_2/expand/bn" | |
| top: "conv5_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv5_2/dwise/bn" | |
| top: "conv5_2/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_2/dwise/bn" | |
| top: "conv5_2/dwise/bn" | |
| } | |
| layer { | |
| name: "conv5_2/linear" | |
| type: "Convolution" | |
| bottom: "conv5_2/dwise/bn" | |
| top: "conv5_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/linear" | |
| top: "conv5_2/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv5_2/linear/bn" | |
| top: "conv5_2/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_5_2" | |
| type: "Eltwise" | |
| bottom: "block_5_1" | |
| bottom: "conv5_2/linear/bn" | |
| top: "block_5_2" | |
| } | |
| layer { | |
| name: "conv5_3/expand" | |
| type: "Convolution" | |
| bottom: "block_5_2" | |
| top: "conv5_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv5_3/expand/bn" | |
| top: "conv5_3/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_3/expand" | |
| type: "ReLU" | |
| bottom: "conv5_3/expand/bn" | |
| top: "conv5_3/expand/bn" | |
| } | |
| layer { | |
| name: "conv5_3/dwise" | |
| type: "Convolution" | |
| bottom: "conv5_3/expand/bn" | |
| top: "conv5_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv5_3/dwise/bn" | |
| top: "conv5_3/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_3/dwise/bn" | |
| top: "conv5_3/dwise/bn" | |
| } | |
| layer { | |
| name: "conv5_3/linear" | |
| type: "Convolution" | |
| bottom: "conv5_3/dwise/bn" | |
| top: "conv5_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/linear" | |
| top: "conv5_3/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/linear/scale" | |
| type: "Scale" | |
| bottom: "conv5_3/linear/bn" | |
| top: "conv5_3/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand" | |
| type: "Convolution" | |
| bottom: "conv5_3/linear/bn" | |
| top: "conv6_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand/scale" | |
| type: "Scale" | |
| bottom: "conv6_1/expand/bn" | |
| top: "conv6_1/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_1/expand" | |
| type: "ReLU" | |
| bottom: "conv6_1/expand/bn" | |
| top: "conv6_1/expand/bn" | |
| } | |
| layer { | |
| name: "conv6_1/dwise" | |
| type: "Convolution" | |
| bottom: "conv6_1/expand/bn" | |
| top: "conv6_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv6_1/dwise/bn" | |
| top: "conv6_1/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_1/dwise/bn" | |
| top: "conv6_1/dwise/bn" | |
| } | |
| layer { | |
| name: "conv6_1/linear" | |
| type: "Convolution" | |
| bottom: "conv6_1/dwise/bn" | |
| top: "conv6_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_1/linear" | |
| top: "conv6_1/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/linear/scale" | |
| type: "Scale" | |
| bottom: "conv6_1/linear/bn" | |
| top: "conv6_1/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_6_1" | |
| type: "Eltwise" | |
| bottom: "conv5_3/linear/bn" | |
| bottom: "conv6_1/linear/bn" | |
| top: "block_6_1" | |
| } | |
| layer { | |
| name: "conv6_2/expand" | |
| type: "Convolution" | |
| bottom: "block_6_1" | |
| top: "conv6_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/expand/scale" | |
| type: "Scale" | |
| bottom: "conv6_2/expand/bn" | |
| top: "conv6_2/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_2/expand" | |
| type: "ReLU" | |
| bottom: "conv6_2/expand/bn" | |
| top: "conv6_2/expand/bn" | |
| } | |
| layer { | |
| name: "conv6_2/dwise" | |
| type: "Convolution" | |
| bottom: "conv6_2/expand/bn" | |
| top: "conv6_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv6_2/dwise/bn" | |
| top: "conv6_2/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_2/dwise/bn" | |
| top: "conv6_2/dwise/bn" | |
| } | |
| layer { | |
| name: "conv6_2/linear" | |
| type: "Convolution" | |
| bottom: "conv6_2/dwise/bn" | |
| top: "conv6_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_2/linear" | |
| top: "conv6_2/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2/linear/scale" | |
| type: "Scale" | |
| bottom: "conv6_2/linear/bn" | |
| top: "conv6_2/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_6_2" | |
| type: "Eltwise" | |
| bottom: "block_6_1" | |
| bottom: "conv6_2/linear/bn" | |
| top: "block_6_2" | |
| } | |
| layer { | |
| name: "conv6_3/expand" | |
| type: "Convolution" | |
| bottom: "block_6_2" | |
| top: "conv6_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/expand/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/expand/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/expand/scale" | |
| type: "Scale" | |
| bottom: "conv6_3/expand/bn" | |
| top: "conv6_3/expand/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_3/expand" | |
| type: "ReLU" | |
| bottom: "conv6_3/expand/bn" | |
| top: "conv6_3/expand/bn" | |
| } | |
| layer { | |
| name: "conv6_3/dwise" | |
| type: "Convolution" | |
| bottom: "conv6_3/expand/bn" | |
| top: "conv6_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/dwise/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/dwise/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/dwise/scale" | |
| type: "Scale" | |
| bottom: "conv6_3/dwise/bn" | |
| top: "conv6_3/dwise/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_3/dwise/bn" | |
| top: "conv6_3/dwise/bn" | |
| } | |
| layer { | |
| name: "conv6_3/linear" | |
| type: "Convolution" | |
| bottom: "conv6_3/dwise/bn" | |
| top: "conv6_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/linear/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_3/linear" | |
| top: "conv6_3/linear/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_3/linear/scale" | |
| type: "Scale" | |
| bottom: "conv6_3/linear/bn" | |
| top: "conv6_3/linear/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv6_4" | |
| type: "Convolution" | |
| bottom: "conv6_3/linear/bn" | |
| top: "conv6_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1280 | |
| bias_term: false | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_4/bn" | |
| type: "BatchNorm" | |
| bottom: "conv6_4" | |
| top: "conv6_4/bn" | |
| 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: true | |
| eps: 1e-5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_4/scale" | |
| type: "Scale" | |
| bottom: "conv6_4/bn" | |
| top: "conv6_4/bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6_4" | |
| type: "ReLU" | |
| bottom: "conv6_4/bn" | |
| top: "conv6_4/bn" | |
| } | |
| layer { | |
| name: "pool6" | |
| type: "Pooling" | |
| bottom: "conv6_4/bn" | |
| top: "pool6" | |
| pooling_param { | |
| pool: AVE | |
| global_pooling: true | |
| } | |
| } | |
| layer { | |
| name: "fc7" | |
| type: "Convolution" | |
| bottom: "pool6" | |
| top: "fc7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1000 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "prob" | |
| type: "Softmax" | |
| bottom: "fc7" | |
| top: "prob" | |
| } |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment