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| name: "WRN-28-10_deploy" | |
| layer { | |
| name: "data" | |
| type: "Input" | |
| top: "data" | |
| input_param { | |
| shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 32 | |
| dim: 32 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "block_2_1_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_1_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_2_1_branch2a_bn" | |
| top: "block_2_1_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_2_1_branch2a_bn" | |
| top: "block_2_1_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_1_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_2_1_branch2a_bn" | |
| top: "block_2_1_branch2a_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_dropout" | |
| type: "Dropout" | |
| bottom: "block_2_1_branch2a_conv" | |
| top: "block_2_1_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_1_dropout" | |
| top: "block_2_1_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_1_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_2_1_branch2b_bn" | |
| top: "block_2_1_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_2_1_branch2b_bn" | |
| top: "block_2_1_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_1_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_2_1_branch2b_bn" | |
| top: "block_2_1_branch2b_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_branch1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "block_2_1_branch1_bn" | |
| } | |
| layer { | |
| name: "block_2_1_branch1_scale" | |
| type: "Scale" | |
| bottom: "block_2_1_branch1_bn" | |
| top: "block_2_1_branch1_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_branch1_relu" | |
| type: "ReLU" | |
| bottom: "block_2_1_branch1_bn" | |
| top: "block_2_1_branch1_bn" | |
| } | |
| layer { | |
| name: "block_2_1_branch1_conv" | |
| type: "Convolution" | |
| bottom: "block_2_1_branch1_bn" | |
| top: "block_2_1_branch1_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_1_addition" | |
| type: "Eltwise" | |
| bottom: "block_2_1_branch1_conv" | |
| bottom: "block_2_1_branch2b_conv" | |
| top: "block_2_1_addition" | |
| } | |
| layer { | |
| name: "block_2_2_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_1_addition" | |
| top: "block_2_2_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_2_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_2_2_branch2a_bn" | |
| top: "block_2_2_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_2_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_2_2_branch2a_bn" | |
| top: "block_2_2_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_2_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_2_2_branch2a_bn" | |
| top: "block_2_2_branch2a_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_2_dropout" | |
| type: "Dropout" | |
| bottom: "block_2_2_branch2a_conv" | |
| top: "block_2_2_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_2_2_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_2_dropout" | |
| top: "block_2_2_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_2_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_2_2_branch2b_bn" | |
| top: "block_2_2_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_2_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_2_2_branch2b_bn" | |
| top: "block_2_2_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_2_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_2_2_branch2b_bn" | |
| top: "block_2_2_branch2b_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_2_addition" | |
| type: "Eltwise" | |
| bottom: "block_2_1_addition" | |
| bottom: "block_2_2_branch2b_conv" | |
| top: "block_2_2_addition" | |
| } | |
| layer { | |
| name: "block_2_3_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_2_addition" | |
| top: "block_2_3_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_3_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_2_3_branch2a_bn" | |
| top: "block_2_3_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_3_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_2_3_branch2a_bn" | |
| top: "block_2_3_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_3_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_2_3_branch2a_bn" | |
| top: "block_2_3_branch2a_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_3_dropout" | |
| type: "Dropout" | |
| bottom: "block_2_3_branch2a_conv" | |
| top: "block_2_3_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_2_3_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_3_dropout" | |
| top: "block_2_3_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_3_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_2_3_branch2b_bn" | |
| top: "block_2_3_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_3_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_2_3_branch2b_bn" | |
| top: "block_2_3_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_3_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_2_3_branch2b_bn" | |
| top: "block_2_3_branch2b_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_3_addition" | |
| type: "Eltwise" | |
| bottom: "block_2_2_addition" | |
| bottom: "block_2_3_branch2b_conv" | |
| top: "block_2_3_addition" | |
| } | |
| layer { | |
| name: "block_2_4_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_3_addition" | |
| top: "block_2_4_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_4_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_2_4_branch2a_bn" | |
| top: "block_2_4_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_4_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_2_4_branch2a_bn" | |
| top: "block_2_4_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_2_4_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_2_4_branch2a_bn" | |
| top: "block_2_4_branch2a_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_4_dropout" | |
| type: "Dropout" | |
| bottom: "block_2_4_branch2a_conv" | |
| top: "block_2_4_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_2_4_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_4_dropout" | |
| top: "block_2_4_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_4_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_2_4_branch2b_bn" | |
| top: "block_2_4_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_2_4_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_2_4_branch2b_bn" | |
| top: "block_2_4_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_2_4_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_2_4_branch2b_bn" | |
| top: "block_2_4_branch2b_conv" | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_2_4_addition" | |
| type: "Eltwise" | |
| bottom: "block_2_3_addition" | |
| bottom: "block_2_4_branch2b_conv" | |
| top: "block_2_4_addition" | |
| } | |
| layer { | |
| name: "block_3_1_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_4_addition" | |
| top: "block_3_1_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_1_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_3_1_branch2a_bn" | |
| top: "block_3_1_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_3_1_branch2a_bn" | |
| top: "block_3_1_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_1_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_3_1_branch2a_bn" | |
| top: "block_3_1_branch2a_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_dropout" | |
| type: "Dropout" | |
| bottom: "block_3_1_branch2a_conv" | |
| top: "block_3_1_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_1_dropout" | |
| top: "block_3_1_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_1_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_3_1_branch2b_bn" | |
| top: "block_3_1_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_3_1_branch2b_bn" | |
| top: "block_3_1_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_1_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_3_1_branch2b_bn" | |
| top: "block_3_1_branch2b_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_branch1_bn" | |
| type: "BatchNorm" | |
| bottom: "block_2_4_addition" | |
| top: "block_3_1_branch1_bn" | |
| } | |
| layer { | |
| name: "block_3_1_branch1_scale" | |
| type: "Scale" | |
| bottom: "block_3_1_branch1_bn" | |
| top: "block_3_1_branch1_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_branch1_relu" | |
| type: "ReLU" | |
| bottom: "block_3_1_branch1_bn" | |
| top: "block_3_1_branch1_bn" | |
| } | |
| layer { | |
| name: "block_3_1_branch1_conv" | |
| type: "Convolution" | |
| bottom: "block_3_1_branch1_bn" | |
| top: "block_3_1_branch1_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "block_3_1_addition" | |
| type: "Eltwise" | |
| bottom: "block_3_1_branch1_conv" | |
| bottom: "block_3_1_branch2b_conv" | |
| top: "block_3_1_addition" | |
| } | |
| layer { | |
| name: "block_3_2_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_1_addition" | |
| top: "block_3_2_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_2_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_3_2_branch2a_bn" | |
| top: "block_3_2_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_2_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_3_2_branch2a_bn" | |
| top: "block_3_2_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_2_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_3_2_branch2a_bn" | |
| top: "block_3_2_branch2a_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_2_dropout" | |
| type: "Dropout" | |
| bottom: "block_3_2_branch2a_conv" | |
| top: "block_3_2_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_3_2_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_2_dropout" | |
| top: "block_3_2_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_2_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_3_2_branch2b_bn" | |
| top: "block_3_2_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_2_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_3_2_branch2b_bn" | |
| top: "block_3_2_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_2_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_3_2_branch2b_bn" | |
| top: "block_3_2_branch2b_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_2_addition" | |
| type: "Eltwise" | |
| bottom: "block_3_1_addition" | |
| bottom: "block_3_2_branch2b_conv" | |
| top: "block_3_2_addition" | |
| } | |
| layer { | |
| name: "block_3_3_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_2_addition" | |
| top: "block_3_3_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_3_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_3_3_branch2a_bn" | |
| top: "block_3_3_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_3_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_3_3_branch2a_bn" | |
| top: "block_3_3_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_3_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_3_3_branch2a_bn" | |
| top: "block_3_3_branch2a_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_3_dropout" | |
| type: "Dropout" | |
| bottom: "block_3_3_branch2a_conv" | |
| top: "block_3_3_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_3_3_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_3_dropout" | |
| top: "block_3_3_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_3_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_3_3_branch2b_bn" | |
| top: "block_3_3_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_3_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_3_3_branch2b_bn" | |
| top: "block_3_3_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_3_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_3_3_branch2b_bn" | |
| top: "block_3_3_branch2b_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_3_addition" | |
| type: "Eltwise" | |
| bottom: "block_3_2_addition" | |
| bottom: "block_3_3_branch2b_conv" | |
| top: "block_3_3_addition" | |
| } | |
| layer { | |
| name: "block_3_4_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_3_addition" | |
| top: "block_3_4_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_4_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_3_4_branch2a_bn" | |
| top: "block_3_4_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_4_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_3_4_branch2a_bn" | |
| top: "block_3_4_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_3_4_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_3_4_branch2a_bn" | |
| top: "block_3_4_branch2a_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_4_dropout" | |
| type: "Dropout" | |
| bottom: "block_3_4_branch2a_conv" | |
| top: "block_3_4_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_3_4_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_4_dropout" | |
| top: "block_3_4_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_4_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_3_4_branch2b_bn" | |
| top: "block_3_4_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_3_4_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_3_4_branch2b_bn" | |
| top: "block_3_4_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_3_4_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_3_4_branch2b_bn" | |
| top: "block_3_4_branch2b_conv" | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_3_4_addition" | |
| type: "Eltwise" | |
| bottom: "block_3_3_addition" | |
| bottom: "block_3_4_branch2b_conv" | |
| top: "block_3_4_addition" | |
| } | |
| layer { | |
| name: "block_4_1_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_4_addition" | |
| top: "block_4_1_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_1_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_4_1_branch2a_bn" | |
| top: "block_4_1_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_4_1_branch2a_bn" | |
| top: "block_4_1_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_1_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_4_1_branch2a_bn" | |
| top: "block_4_1_branch2a_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_dropout" | |
| type: "Dropout" | |
| bottom: "block_4_1_branch2a_conv" | |
| top: "block_4_1_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_1_dropout" | |
| top: "block_4_1_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_1_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_4_1_branch2b_bn" | |
| top: "block_4_1_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_4_1_branch2b_bn" | |
| top: "block_4_1_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_1_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_4_1_branch2b_bn" | |
| top: "block_4_1_branch2b_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_branch1_bn" | |
| type: "BatchNorm" | |
| bottom: "block_3_4_addition" | |
| top: "block_4_1_branch1_bn" | |
| } | |
| layer { | |
| name: "block_4_1_branch1_scale" | |
| type: "Scale" | |
| bottom: "block_4_1_branch1_bn" | |
| top: "block_4_1_branch1_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_branch1_relu" | |
| type: "ReLU" | |
| bottom: "block_4_1_branch1_bn" | |
| top: "block_4_1_branch1_bn" | |
| } | |
| layer { | |
| name: "block_4_1_branch1_conv" | |
| type: "Convolution" | |
| bottom: "block_4_1_branch1_bn" | |
| top: "block_4_1_branch1_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "block_4_1_addition" | |
| type: "Eltwise" | |
| bottom: "block_4_1_branch1_conv" | |
| bottom: "block_4_1_branch2b_conv" | |
| top: "block_4_1_addition" | |
| } | |
| layer { | |
| name: "block_4_2_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_1_addition" | |
| top: "block_4_2_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_2_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_4_2_branch2a_bn" | |
| top: "block_4_2_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_2_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_4_2_branch2a_bn" | |
| top: "block_4_2_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_2_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_4_2_branch2a_bn" | |
| top: "block_4_2_branch2a_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_2_dropout" | |
| type: "Dropout" | |
| bottom: "block_4_2_branch2a_conv" | |
| top: "block_4_2_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_4_2_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_2_dropout" | |
| top: "block_4_2_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_2_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_4_2_branch2b_bn" | |
| top: "block_4_2_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_2_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_4_2_branch2b_bn" | |
| top: "block_4_2_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_2_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_4_2_branch2b_bn" | |
| top: "block_4_2_branch2b_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_2_addition" | |
| type: "Eltwise" | |
| bottom: "block_4_1_addition" | |
| bottom: "block_4_2_branch2b_conv" | |
| top: "block_4_2_addition" | |
| } | |
| layer { | |
| name: "block_4_3_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_2_addition" | |
| top: "block_4_3_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_3_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_4_3_branch2a_bn" | |
| top: "block_4_3_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_3_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_4_3_branch2a_bn" | |
| top: "block_4_3_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_3_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_4_3_branch2a_bn" | |
| top: "block_4_3_branch2a_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_3_dropout" | |
| type: "Dropout" | |
| bottom: "block_4_3_branch2a_conv" | |
| top: "block_4_3_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_4_3_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_3_dropout" | |
| top: "block_4_3_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_3_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_4_3_branch2b_bn" | |
| top: "block_4_3_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_3_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_4_3_branch2b_bn" | |
| top: "block_4_3_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_3_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_4_3_branch2b_bn" | |
| top: "block_4_3_branch2b_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_3_addition" | |
| type: "Eltwise" | |
| bottom: "block_4_2_addition" | |
| bottom: "block_4_3_branch2b_conv" | |
| top: "block_4_3_addition" | |
| } | |
| layer { | |
| name: "block_4_4_branch2a_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_3_addition" | |
| top: "block_4_4_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_4_branch2a_scale" | |
| type: "Scale" | |
| bottom: "block_4_4_branch2a_bn" | |
| top: "block_4_4_branch2a_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_4_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "block_4_4_branch2a_bn" | |
| top: "block_4_4_branch2a_bn" | |
| } | |
| layer { | |
| name: "block_4_4_branch2a_conv" | |
| type: "Convolution" | |
| bottom: "block_4_4_branch2a_bn" | |
| top: "block_4_4_branch2a_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_4_dropout" | |
| type: "Dropout" | |
| bottom: "block_4_4_branch2a_conv" | |
| top: "block_4_4_dropout" | |
| dropout_param { | |
| dropout_ratio: 0.3 | |
| } | |
| } | |
| layer { | |
| name: "block_4_4_branch2b_bn" | |
| type: "BatchNorm" | |
| bottom: "block_4_4_dropout" | |
| top: "block_4_4_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_4_branch2b_scale" | |
| type: "Scale" | |
| bottom: "block_4_4_branch2b_bn" | |
| top: "block_4_4_branch2b_bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "block_4_4_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "block_4_4_branch2b_bn" | |
| top: "block_4_4_branch2b_bn" | |
| } | |
| layer { | |
| name: "block_4_4_branch2b_conv" | |
| type: "Convolution" | |
| bottom: "block_4_4_branch2b_bn" | |
| top: "block_4_4_branch2b_conv" | |
| convolution_param { | |
| num_output: 640 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "block_4_4_addition" | |
| type: "Eltwise" | |
| bottom: "block_4_3_addition" | |
| bottom: "block_4_4_branch2b_conv" | |
| top: "block_4_4_addition" | |
| } | |
| layer { | |
| name: "bn5" | |
| type: "BatchNorm" | |
| bottom: "block_4_4_addition" | |
| top: "bn5" | |
| } | |
| layer { | |
| name: "scale5" | |
| type: "Scale" | |
| bottom: "bn5" | |
| top: "bn5" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5" | |
| type: "ReLU" | |
| bottom: "bn5" | |
| top: "bn5" | |
| } | |
| layer { | |
| name: "pool5" | |
| type: "Pooling" | |
| bottom: "bn5" | |
| top: "pool5" | |
| pooling_param { | |
| pool: AVE | |
| global_pooling: true | |
| } | |
| } | |
| layer { | |
| name: "fc6" | |
| type: "InnerProduct" | |
| bottom: "pool5" | |
| top: "fc6" | |
| inner_product_param { | |
| num_output: 10 | |
| } | |
| } | |
| layer { | |
| name: "prob" | |
| type: "Softmax" | |
| bottom: "fc6" | |
| top: "prob" | |
| } |
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