Created
January 31, 2019 10:58
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mobilefacenetv2
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| layer { | |
| name: "data" | |
| type: "Input" | |
| top: "data" | |
| input_param { | |
| shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 112 | |
| dim: 112 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "ConvNd_1" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 1 | |
| stride: 2 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_1" | |
| type: "PReLU" | |
| bottom: "ConvNd_1" | |
| top: "PReLU_1" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_1" | |
| type: "BatchNorm" | |
| bottom: "PReLU_1" | |
| top: "BatchNorm_1" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_2" | |
| type: "Convolution" | |
| bottom: "BatchNorm_1" | |
| top: "ConvNd_2" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 64 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_2" | |
| type: "BatchNorm" | |
| bottom: "ConvNd_2" | |
| top: "BatchNorm_2" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_3" | |
| type: "Convolution" | |
| bottom: "BatchNorm_2" | |
| top: "ConvNd_3" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_2" | |
| type: "PReLU" | |
| bottom: "ConvNd_3" | |
| top: "PReLU_2" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_3" | |
| type: "BatchNorm" | |
| bottom: "PReLU_2" | |
| top: "BatchNorm_3" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_4" | |
| type: "Convolution" | |
| bottom: "BatchNorm_3" | |
| top: "ConvNd_4" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 2 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_3" | |
| type: "PReLU" | |
| bottom: "ConvNd_4" | |
| top: "PReLU_3" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_4" | |
| type: "BatchNorm" | |
| bottom: "PReLU_3" | |
| top: "BatchNorm_4" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_5" | |
| type: "Convolution" | |
| bottom: "BatchNorm_4" | |
| top: "ConvNd_5" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_5" | |
| type: "BatchNorm" | |
| bottom: "ConvNd_5" | |
| top: "BatchNorm_5" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_6" | |
| type: "Convolution" | |
| bottom: "BatchNorm_5" | |
| top: "ConvNd_6" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_4" | |
| type: "PReLU" | |
| bottom: "ConvNd_6" | |
| top: "PReLU_4" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_6" | |
| type: "BatchNorm" | |
| bottom: "PReLU_4" | |
| top: "BatchNorm_6" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_7" | |
| type: "Convolution" | |
| bottom: "BatchNorm_6" | |
| top: "ConvNd_7" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_5" | |
| type: "PReLU" | |
| bottom: "ConvNd_7" | |
| top: "PReLU_5" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_1" | |
| type: "Eltwise" | |
| bottom: "PReLU_5" | |
| bottom: "PReLU_4" | |
| top: "Add_1" | |
| } | |
| layer { | |
| name: "BatchNorm_7" | |
| type: "BatchNorm" | |
| bottom: "Add_1" | |
| top: "BatchNorm_7" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_8" | |
| type: "Convolution" | |
| bottom: "BatchNorm_7" | |
| top: "ConvNd_8" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_2" | |
| type: "Eltwise" | |
| bottom: "ConvNd_5" | |
| bottom: "ConvNd_8" | |
| top: "Add_2" | |
| } | |
| layer { | |
| name: "BatchNorm_8" | |
| type: "BatchNorm" | |
| bottom: "Add_2" | |
| top: "BatchNorm_8" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_9" | |
| type: "Convolution" | |
| bottom: "BatchNorm_8" | |
| top: "ConvNd_9" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_6" | |
| type: "PReLU" | |
| bottom: "ConvNd_9" | |
| top: "PReLU_6" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_9" | |
| type: "BatchNorm" | |
| bottom: "PReLU_6" | |
| top: "BatchNorm_9" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_10" | |
| type: "Convolution" | |
| bottom: "BatchNorm_9" | |
| top: "ConvNd_10" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_7" | |
| type: "PReLU" | |
| bottom: "ConvNd_10" | |
| top: "PReLU_7" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_3" | |
| type: "Eltwise" | |
| bottom: "PReLU_7" | |
| bottom: "PReLU_6" | |
| top: "Add_3" | |
| } | |
| layer { | |
| name: "BatchNorm_10" | |
| type: "BatchNorm" | |
| bottom: "Add_3" | |
| top: "BatchNorm_10" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_11" | |
| type: "Convolution" | |
| bottom: "BatchNorm_10" | |
| top: "ConvNd_11" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_4" | |
| type: "Eltwise" | |
| bottom: "Add_2" | |
| bottom: "ConvNd_11" | |
| top: "Add_4" | |
| } | |
| layer { | |
| name: "BatchNorm_11" | |
| type: "BatchNorm" | |
| bottom: "Add_4" | |
| top: "BatchNorm_11" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_12" | |
| type: "Convolution" | |
| bottom: "BatchNorm_11" | |
| top: "ConvNd_12" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_8" | |
| type: "PReLU" | |
| bottom: "ConvNd_12" | |
| top: "PReLU_8" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_12" | |
| type: "BatchNorm" | |
| bottom: "PReLU_8" | |
| top: "BatchNorm_12" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_13" | |
| type: "Convolution" | |
| bottom: "BatchNorm_12" | |
| top: "ConvNd_13" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_9" | |
| type: "PReLU" | |
| bottom: "ConvNd_13" | |
| top: "PReLU_9" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_5" | |
| type: "Eltwise" | |
| bottom: "PReLU_9" | |
| bottom: "PReLU_8" | |
| top: "Add_5" | |
| } | |
| layer { | |
| name: "BatchNorm_13" | |
| type: "BatchNorm" | |
| bottom: "Add_5" | |
| top: "BatchNorm_13" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_14" | |
| type: "Convolution" | |
| bottom: "BatchNorm_13" | |
| top: "ConvNd_14" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_6" | |
| type: "Eltwise" | |
| bottom: "Add_4" | |
| bottom: "ConvNd_14" | |
| top: "Add_6" | |
| } | |
| layer { | |
| name: "BatchNorm_14" | |
| type: "BatchNorm" | |
| bottom: "Add_6" | |
| top: "BatchNorm_14" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_15" | |
| type: "Convolution" | |
| bottom: "BatchNorm_14" | |
| top: "ConvNd_15" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_10" | |
| type: "PReLU" | |
| bottom: "ConvNd_15" | |
| top: "PReLU_10" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_15" | |
| type: "BatchNorm" | |
| bottom: "PReLU_10" | |
| top: "BatchNorm_15" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_16" | |
| type: "Convolution" | |
| bottom: "BatchNorm_15" | |
| top: "ConvNd_16" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_11" | |
| type: "PReLU" | |
| bottom: "ConvNd_16" | |
| top: "PReLU_11" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_7" | |
| type: "Eltwise" | |
| bottom: "PReLU_11" | |
| bottom: "PReLU_10" | |
| top: "Add_7" | |
| } | |
| layer { | |
| name: "BatchNorm_16" | |
| type: "BatchNorm" | |
| bottom: "Add_7" | |
| top: "BatchNorm_16" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_17" | |
| type: "Convolution" | |
| bottom: "BatchNorm_16" | |
| top: "ConvNd_17" | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_8" | |
| type: "Eltwise" | |
| bottom: "Add_6" | |
| bottom: "ConvNd_17" | |
| top: "Add_8" | |
| } | |
| layer { | |
| name: "BatchNorm_17" | |
| type: "BatchNorm" | |
| bottom: "Add_8" | |
| top: "BatchNorm_17" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_18" | |
| type: "Convolution" | |
| bottom: "BatchNorm_17" | |
| top: "ConvNd_18" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_12" | |
| type: "PReLU" | |
| bottom: "ConvNd_18" | |
| top: "PReLU_12" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_18" | |
| type: "BatchNorm" | |
| bottom: "PReLU_12" | |
| top: "BatchNorm_18" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_19" | |
| type: "Convolution" | |
| bottom: "BatchNorm_18" | |
| top: "ConvNd_19" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 2 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_13" | |
| type: "PReLU" | |
| bottom: "ConvNd_19" | |
| top: "PReLU_13" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_19" | |
| type: "BatchNorm" | |
| bottom: "PReLU_13" | |
| top: "BatchNorm_19" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_20" | |
| type: "Convolution" | |
| bottom: "BatchNorm_19" | |
| top: "ConvNd_20" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_20" | |
| type: "BatchNorm" | |
| bottom: "ConvNd_20" | |
| top: "BatchNorm_20" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_21" | |
| type: "Convolution" | |
| bottom: "BatchNorm_20" | |
| top: "ConvNd_21" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_14" | |
| type: "PReLU" | |
| bottom: "ConvNd_21" | |
| top: "PReLU_14" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_21" | |
| type: "BatchNorm" | |
| bottom: "PReLU_14" | |
| top: "BatchNorm_21" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_22" | |
| type: "Convolution" | |
| bottom: "BatchNorm_21" | |
| top: "ConvNd_22" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_15" | |
| type: "PReLU" | |
| bottom: "ConvNd_22" | |
| top: "PReLU_15" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_9" | |
| type: "Eltwise" | |
| bottom: "PReLU_15" | |
| bottom: "PReLU_14" | |
| top: "Add_9" | |
| } | |
| layer { | |
| name: "BatchNorm_22" | |
| type: "BatchNorm" | |
| bottom: "Add_9" | |
| top: "BatchNorm_22" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_23" | |
| type: "Convolution" | |
| bottom: "BatchNorm_22" | |
| top: "ConvNd_23" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_10" | |
| type: "Eltwise" | |
| bottom: "ConvNd_20" | |
| bottom: "ConvNd_23" | |
| top: "Add_10" | |
| } | |
| layer { | |
| name: "BatchNorm_23" | |
| type: "BatchNorm" | |
| bottom: "Add_10" | |
| top: "BatchNorm_23" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_24" | |
| type: "Convolution" | |
| bottom: "BatchNorm_23" | |
| top: "ConvNd_24" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_16" | |
| type: "PReLU" | |
| bottom: "ConvNd_24" | |
| top: "PReLU_16" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_24" | |
| type: "BatchNorm" | |
| bottom: "PReLU_16" | |
| top: "BatchNorm_24" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_25" | |
| type: "Convolution" | |
| bottom: "BatchNorm_24" | |
| top: "ConvNd_25" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_17" | |
| type: "PReLU" | |
| bottom: "ConvNd_25" | |
| top: "PReLU_17" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_11" | |
| type: "Eltwise" | |
| bottom: "PReLU_17" | |
| bottom: "PReLU_16" | |
| top: "Add_11" | |
| } | |
| layer { | |
| name: "BatchNorm_25" | |
| type: "BatchNorm" | |
| bottom: "Add_11" | |
| top: "BatchNorm_25" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_26" | |
| type: "Convolution" | |
| bottom: "BatchNorm_25" | |
| top: "ConvNd_26" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_12" | |
| type: "Eltwise" | |
| bottom: "Add_10" | |
| bottom: "ConvNd_26" | |
| top: "Add_12" | |
| } | |
| layer { | |
| name: "BatchNorm_26" | |
| type: "BatchNorm" | |
| bottom: "Add_12" | |
| top: "BatchNorm_26" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_27" | |
| type: "Convolution" | |
| bottom: "BatchNorm_26" | |
| top: "ConvNd_27" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_18" | |
| type: "PReLU" | |
| bottom: "ConvNd_27" | |
| top: "PReLU_18" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_27" | |
| type: "BatchNorm" | |
| bottom: "PReLU_18" | |
| top: "BatchNorm_27" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_28" | |
| type: "Convolution" | |
| bottom: "BatchNorm_27" | |
| top: "ConvNd_28" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_19" | |
| type: "PReLU" | |
| bottom: "ConvNd_28" | |
| top: "PReLU_19" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_13" | |
| type: "Eltwise" | |
| bottom: "PReLU_19" | |
| bottom: "PReLU_18" | |
| top: "Add_13" | |
| } | |
| layer { | |
| name: "BatchNorm_28" | |
| type: "BatchNorm" | |
| bottom: "Add_13" | |
| top: "BatchNorm_28" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_29" | |
| type: "Convolution" | |
| bottom: "BatchNorm_28" | |
| top: "ConvNd_29" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_14" | |
| type: "Eltwise" | |
| bottom: "Add_12" | |
| bottom: "ConvNd_29" | |
| top: "Add_14" | |
| } | |
| layer { | |
| name: "BatchNorm_29" | |
| type: "BatchNorm" | |
| bottom: "Add_14" | |
| top: "BatchNorm_29" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_30" | |
| type: "Convolution" | |
| bottom: "BatchNorm_29" | |
| top: "ConvNd_30" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_20" | |
| type: "PReLU" | |
| bottom: "ConvNd_30" | |
| top: "PReLU_20" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_30" | |
| type: "BatchNorm" | |
| bottom: "PReLU_20" | |
| top: "BatchNorm_30" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_31" | |
| type: "Convolution" | |
| bottom: "BatchNorm_30" | |
| top: "ConvNd_31" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_21" | |
| type: "PReLU" | |
| bottom: "ConvNd_31" | |
| top: "PReLU_21" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_15" | |
| type: "Eltwise" | |
| bottom: "PReLU_21" | |
| bottom: "PReLU_20" | |
| top: "Add_15" | |
| } | |
| layer { | |
| name: "BatchNorm_31" | |
| type: "BatchNorm" | |
| bottom: "Add_15" | |
| top: "BatchNorm_31" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_32" | |
| type: "Convolution" | |
| bottom: "BatchNorm_31" | |
| top: "ConvNd_32" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_16" | |
| type: "Eltwise" | |
| bottom: "Add_14" | |
| bottom: "ConvNd_32" | |
| top: "Add_16" | |
| } | |
| layer { | |
| name: "BatchNorm_32" | |
| type: "BatchNorm" | |
| bottom: "Add_16" | |
| top: "BatchNorm_32" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_33" | |
| type: "Convolution" | |
| bottom: "BatchNorm_32" | |
| top: "ConvNd_33" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_22" | |
| type: "PReLU" | |
| bottom: "ConvNd_33" | |
| top: "PReLU_22" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_33" | |
| type: "BatchNorm" | |
| bottom: "PReLU_22" | |
| top: "BatchNorm_33" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_34" | |
| type: "Convolution" | |
| bottom: "BatchNorm_33" | |
| top: "ConvNd_34" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_23" | |
| type: "PReLU" | |
| bottom: "ConvNd_34" | |
| top: "PReLU_23" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_17" | |
| type: "Eltwise" | |
| bottom: "PReLU_23" | |
| bottom: "PReLU_22" | |
| top: "Add_17" | |
| } | |
| layer { | |
| name: "BatchNorm_34" | |
| type: "BatchNorm" | |
| bottom: "Add_17" | |
| top: "BatchNorm_34" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_35" | |
| type: "Convolution" | |
| bottom: "BatchNorm_34" | |
| top: "ConvNd_35" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_18" | |
| type: "Eltwise" | |
| bottom: "Add_16" | |
| bottom: "ConvNd_35" | |
| top: "Add_18" | |
| } | |
| layer { | |
| name: "BatchNorm_35" | |
| type: "BatchNorm" | |
| bottom: "Add_18" | |
| top: "BatchNorm_35" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_36" | |
| type: "Convolution" | |
| bottom: "BatchNorm_35" | |
| top: "ConvNd_36" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_24" | |
| type: "PReLU" | |
| bottom: "ConvNd_36" | |
| top: "PReLU_24" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_36" | |
| type: "BatchNorm" | |
| bottom: "PReLU_24" | |
| top: "BatchNorm_36" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_37" | |
| type: "Convolution" | |
| bottom: "BatchNorm_36" | |
| top: "ConvNd_37" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_25" | |
| type: "PReLU" | |
| bottom: "ConvNd_37" | |
| top: "PReLU_25" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_19" | |
| type: "Eltwise" | |
| bottom: "PReLU_25" | |
| bottom: "PReLU_24" | |
| top: "Add_19" | |
| } | |
| layer { | |
| name: "BatchNorm_37" | |
| type: "BatchNorm" | |
| bottom: "Add_19" | |
| top: "BatchNorm_37" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_38" | |
| type: "Convolution" | |
| bottom: "BatchNorm_37" | |
| top: "ConvNd_38" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_20" | |
| type: "Eltwise" | |
| bottom: "Add_18" | |
| bottom: "ConvNd_38" | |
| top: "Add_20" | |
| } | |
| layer { | |
| name: "BatchNorm_38" | |
| type: "BatchNorm" | |
| bottom: "Add_20" | |
| top: "BatchNorm_38" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_39" | |
| type: "Convolution" | |
| bottom: "BatchNorm_38" | |
| top: "ConvNd_39" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_26" | |
| type: "PReLU" | |
| bottom: "ConvNd_39" | |
| top: "PReLU_26" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_39" | |
| type: "BatchNorm" | |
| bottom: "PReLU_26" | |
| top: "BatchNorm_39" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_40" | |
| type: "Convolution" | |
| bottom: "BatchNorm_39" | |
| top: "ConvNd_40" | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| stride: 2 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_27" | |
| type: "PReLU" | |
| bottom: "ConvNd_40" | |
| top: "PReLU_27" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_40" | |
| type: "BatchNorm" | |
| bottom: "PReLU_27" | |
| top: "BatchNorm_40" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_41" | |
| type: "Convolution" | |
| bottom: "BatchNorm_40" | |
| top: "ConvNd_41" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_41" | |
| type: "BatchNorm" | |
| bottom: "ConvNd_41" | |
| top: "BatchNorm_41" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_42" | |
| type: "Convolution" | |
| bottom: "BatchNorm_41" | |
| top: "ConvNd_42" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_28" | |
| type: "PReLU" | |
| bottom: "ConvNd_42" | |
| top: "PReLU_28" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_42" | |
| type: "BatchNorm" | |
| bottom: "PReLU_28" | |
| top: "BatchNorm_42" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_43" | |
| type: "Convolution" | |
| bottom: "BatchNorm_42" | |
| top: "ConvNd_43" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_29" | |
| type: "PReLU" | |
| bottom: "ConvNd_43" | |
| top: "PReLU_29" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_21" | |
| type: "Eltwise" | |
| bottom: "PReLU_29" | |
| bottom: "PReLU_28" | |
| top: "Add_21" | |
| } | |
| layer { | |
| name: "BatchNorm_43" | |
| type: "BatchNorm" | |
| bottom: "Add_21" | |
| top: "BatchNorm_43" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_44" | |
| type: "Convolution" | |
| bottom: "BatchNorm_43" | |
| top: "ConvNd_44" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_22" | |
| type: "Eltwise" | |
| bottom: "ConvNd_41" | |
| bottom: "ConvNd_44" | |
| top: "Add_22" | |
| } | |
| layer { | |
| name: "BatchNorm_44" | |
| type: "BatchNorm" | |
| bottom: "Add_22" | |
| top: "BatchNorm_44" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_45" | |
| type: "Convolution" | |
| bottom: "BatchNorm_44" | |
| top: "ConvNd_45" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_30" | |
| type: "PReLU" | |
| bottom: "ConvNd_45" | |
| top: "PReLU_30" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_45" | |
| type: "BatchNorm" | |
| bottom: "PReLU_30" | |
| top: "BatchNorm_45" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_46" | |
| type: "Convolution" | |
| bottom: "BatchNorm_45" | |
| top: "ConvNd_46" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "PReLU_31" | |
| type: "PReLU" | |
| bottom: "ConvNd_46" | |
| top: "PReLU_31" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "Add_23" | |
| type: "Eltwise" | |
| bottom: "PReLU_31" | |
| bottom: "PReLU_30" | |
| top: "Add_23" | |
| } | |
| layer { | |
| name: "BatchNorm_46" | |
| type: "BatchNorm" | |
| bottom: "Add_23" | |
| top: "BatchNorm_46" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_47" | |
| type: "Convolution" | |
| bottom: "BatchNorm_46" | |
| top: "ConvNd_47" | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "Add_24" | |
| type: "Eltwise" | |
| bottom: "Add_22" | |
| bottom: "ConvNd_47" | |
| top: "Add_24" | |
| } | |
| layer { | |
| name: "ConvNd_48" | |
| type: "Convolution" | |
| bottom: "Add_24" | |
| top: "ConvNd_48" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_47" | |
| type: "BatchNorm" | |
| bottom: "ConvNd_48" | |
| top: "BatchNorm_47" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_47_scale" | |
| type: "Scale" | |
| bottom: "BatchNorm_47" | |
| top: "BatchNorm_47" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "PReLU_32" | |
| type: "PReLU" | |
| bottom: "BatchNorm_47" | |
| top: "PReLU_32" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "ConvNd_49" | |
| type: "Convolution" | |
| bottom: "PReLU_32" | |
| top: "ConvNd_49" | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 7 | |
| group: 512 | |
| stride: 1 | |
| dilation: 1 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_48" | |
| type: "BatchNorm" | |
| bottom: "ConvNd_49" | |
| top: "BatchNorm_48" | |
| batch_norm_param { | |
| use_global_stats: true | |
| eps: 9.99999974738e-06 | |
| } | |
| } | |
| layer { | |
| name: "BatchNorm_48_scale" | |
| type: "Scale" | |
| bottom: "BatchNorm_48" | |
| top: "BatchNorm_48" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "PReLU_33" | |
| type: "PReLU" | |
| bottom: "BatchNorm_48" | |
| top: "PReLU_33" | |
| prelu_param { | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "View_1" | |
| type: "Flatten" | |
| bottom: "PReLU_33" | |
| top: "View_1" | |
| } | |
| layer { | |
| name: "Addmm_1" | |
| type: "InnerProduct" | |
| bottom: "View_1" | |
| top: "Addmm_1" | |
| inner_product_param { | |
| num_output: 128 | |
| bias_term: true | |
| } | |
| } |
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