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December 23, 2018 16:47
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| name: "cifar10-resnet32" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 32 | |
| input_dim: 32 | |
| layer { | |
| name: "first_conv" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "first_conv" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "first_conv_bn" | |
| type: "BatchNorm" | |
| bottom: "first_conv" | |
| top: "first_conv/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "first_conv_scale" | |
| type: "Scale" | |
| bottom: "first_conv/bn" | |
| top: "first_conv/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "first_conv_relu" | |
| type: "ReLU" | |
| bottom: "first_conv/bn" | |
| top: "first_conv/bn" | |
| } | |
| layer { | |
| name: "group0_block0_conv0" | |
| type: "Convolution" | |
| bottom: "first_conv/bn" | |
| top: "group0_block0_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block0_conv0" | |
| top: "group0_block0_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_conv0_scale" | |
| type: "Scale" | |
| bottom: "group0_block0_conv0/bn" | |
| top: "group0_block0_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group0_block0_conv0/bn" | |
| top: "group0_block0_conv0/bn" | |
| } | |
| layer { | |
| name: "group0_block0_conv1" | |
| type: "Convolution" | |
| bottom: "group0_block0_conv0/bn" | |
| top: "group0_block0_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block0_conv1" | |
| top: "group0_block0_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_conv1_scale" | |
| type: "Scale" | |
| bottom: "group0_block0_conv1/bn" | |
| top: "group0_block0_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_sum" | |
| type: "Eltwise" | |
| bottom: "group0_block0_conv1/bn" | |
| bottom: "first_conv/bn" | |
| top: "group0_block0_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group0_block0_relu" | |
| type: "ReLU" | |
| bottom: "group0_block0_sum" | |
| top: "group0_block0_sum" | |
| } | |
| layer { | |
| name: "group0_block1_conv0" | |
| type: "Convolution" | |
| bottom: "group0_block0_sum" | |
| top: "group0_block1_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block1_conv0" | |
| top: "group0_block1_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_conv0_scale" | |
| type: "Scale" | |
| bottom: "group0_block1_conv0/bn" | |
| top: "group0_block1_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group0_block1_conv0/bn" | |
| top: "group0_block1_conv0/bn" | |
| } | |
| layer { | |
| name: "group0_block1_conv1" | |
| type: "Convolution" | |
| bottom: "group0_block1_conv0/bn" | |
| top: "group0_block1_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block1_conv1" | |
| top: "group0_block1_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_conv1_scale" | |
| type: "Scale" | |
| bottom: "group0_block1_conv1/bn" | |
| top: "group0_block1_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_sum" | |
| type: "Eltwise" | |
| bottom: "group0_block1_conv1/bn" | |
| bottom: "group0_block0_sum" | |
| top: "group0_block1_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group0_block1_relu" | |
| type: "ReLU" | |
| bottom: "group0_block1_sum" | |
| top: "group0_block1_sum" | |
| } | |
| layer { | |
| name: "group0_block2_conv0" | |
| type: "Convolution" | |
| bottom: "group0_block1_sum" | |
| top: "group0_block2_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block2_conv0" | |
| top: "group0_block2_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_conv0_scale" | |
| type: "Scale" | |
| bottom: "group0_block2_conv0/bn" | |
| top: "group0_block2_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group0_block2_conv0/bn" | |
| top: "group0_block2_conv0/bn" | |
| } | |
| layer { | |
| name: "group0_block2_conv1" | |
| type: "Convolution" | |
| bottom: "group0_block2_conv0/bn" | |
| top: "group0_block2_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block2_conv1" | |
| top: "group0_block2_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_conv1_scale" | |
| type: "Scale" | |
| bottom: "group0_block2_conv1/bn" | |
| top: "group0_block2_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_sum" | |
| type: "Eltwise" | |
| bottom: "group0_block2_conv1/bn" | |
| bottom: "group0_block1_sum" | |
| top: "group0_block2_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group0_block2_relu" | |
| type: "ReLU" | |
| bottom: "group0_block2_sum" | |
| top: "group0_block2_sum" | |
| } | |
| layer { | |
| name: "group0_block3_conv0" | |
| type: "Convolution" | |
| bottom: "group0_block2_sum" | |
| top: "group0_block3_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block3_conv0" | |
| top: "group0_block3_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_conv0_scale" | |
| type: "Scale" | |
| bottom: "group0_block3_conv0/bn" | |
| top: "group0_block3_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group0_block3_conv0/bn" | |
| top: "group0_block3_conv0/bn" | |
| } | |
| layer { | |
| name: "group0_block3_conv1" | |
| type: "Convolution" | |
| bottom: "group0_block3_conv0/bn" | |
| top: "group0_block3_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block3_conv1" | |
| top: "group0_block3_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_conv1_scale" | |
| type: "Scale" | |
| bottom: "group0_block3_conv1/bn" | |
| top: "group0_block3_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_sum" | |
| type: "Eltwise" | |
| bottom: "group0_block3_conv1/bn" | |
| bottom: "group0_block2_sum" | |
| top: "group0_block3_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group0_block3_relu" | |
| type: "ReLU" | |
| bottom: "group0_block3_sum" | |
| top: "group0_block3_sum" | |
| } | |
| layer { | |
| name: "group0_block4_conv0" | |
| type: "Convolution" | |
| bottom: "group0_block3_sum" | |
| top: "group0_block4_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block4_conv0" | |
| top: "group0_block4_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_conv0_scale" | |
| type: "Scale" | |
| bottom: "group0_block4_conv0/bn" | |
| top: "group0_block4_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group0_block4_conv0/bn" | |
| top: "group0_block4_conv0/bn" | |
| } | |
| layer { | |
| name: "group0_block4_conv1" | |
| type: "Convolution" | |
| bottom: "group0_block4_conv0/bn" | |
| top: "group0_block4_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group0_block4_conv1" | |
| top: "group0_block4_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_conv1_scale" | |
| type: "Scale" | |
| bottom: "group0_block4_conv1/bn" | |
| top: "group0_block4_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_sum" | |
| type: "Eltwise" | |
| bottom: "group0_block4_conv1/bn" | |
| bottom: "group0_block3_sum" | |
| top: "group0_block4_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group0_block4_relu" | |
| type: "ReLU" | |
| bottom: "group0_block4_sum" | |
| top: "group0_block4_sum" | |
| } | |
| layer { | |
| name: "group1_block0_conv0" | |
| type: "Convolution" | |
| bottom: "group0_block4_sum" | |
| top: "group1_block0_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block0_conv0" | |
| top: "group1_block0_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_conv0_scale" | |
| type: "Scale" | |
| bottom: "group1_block0_conv0/bn" | |
| top: "group1_block0_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group1_block0_conv0/bn" | |
| top: "group1_block0_conv0/bn" | |
| } | |
| layer { | |
| name: "group1_block0_conv1" | |
| type: "Convolution" | |
| bottom: "group1_block0_conv0/bn" | |
| top: "group1_block0_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block0_conv1" | |
| top: "group1_block0_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_conv1_scale" | |
| type: "Scale" | |
| bottom: "group1_block0_conv1/bn" | |
| top: "group1_block0_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_proj" | |
| type: "Convolution" | |
| bottom: "group0_block4_sum" | |
| top: "group1_block0_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block0_proj" | |
| top: "group1_block0_proj/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_proj_scale" | |
| type: "Scale" | |
| bottom: "group1_block0_proj/bn" | |
| top: "group1_block0_proj/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_sum" | |
| type: "Eltwise" | |
| bottom: "group1_block0_proj/bn" | |
| bottom: "group1_block0_conv1/bn" | |
| top: "group1_block0_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group1_block0_relu" | |
| type: "ReLU" | |
| bottom: "group1_block0_sum" | |
| top: "group1_block0_sum" | |
| } | |
| layer { | |
| name: "group1_block1_conv0" | |
| type: "Convolution" | |
| bottom: "group1_block0_sum" | |
| top: "group1_block1_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block1_conv0" | |
| top: "group1_block1_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_conv0_scale" | |
| type: "Scale" | |
| bottom: "group1_block1_conv0/bn" | |
| top: "group1_block1_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group1_block1_conv0/bn" | |
| top: "group1_block1_conv0/bn" | |
| } | |
| layer { | |
| name: "group1_block1_conv1" | |
| type: "Convolution" | |
| bottom: "group1_block1_conv0/bn" | |
| top: "group1_block1_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block1_conv1" | |
| top: "group1_block1_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_conv1_scale" | |
| type: "Scale" | |
| bottom: "group1_block1_conv1/bn" | |
| top: "group1_block1_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_sum" | |
| type: "Eltwise" | |
| bottom: "group1_block1_conv1/bn" | |
| bottom: "group1_block0_sum" | |
| top: "group1_block1_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group1_block1_relu" | |
| type: "ReLU" | |
| bottom: "group1_block1_sum" | |
| top: "group1_block1_sum" | |
| } | |
| layer { | |
| name: "group1_block2_conv0" | |
| type: "Convolution" | |
| bottom: "group1_block1_sum" | |
| top: "group1_block2_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block2_conv0" | |
| top: "group1_block2_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_conv0_scale" | |
| type: "Scale" | |
| bottom: "group1_block2_conv0/bn" | |
| top: "group1_block2_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group1_block2_conv0/bn" | |
| top: "group1_block2_conv0/bn" | |
| } | |
| layer { | |
| name: "group1_block2_conv1" | |
| type: "Convolution" | |
| bottom: "group1_block2_conv0/bn" | |
| top: "group1_block2_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block2_conv1" | |
| top: "group1_block2_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_conv1_scale" | |
| type: "Scale" | |
| bottom: "group1_block2_conv1/bn" | |
| top: "group1_block2_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_sum" | |
| type: "Eltwise" | |
| bottom: "group1_block2_conv1/bn" | |
| bottom: "group1_block1_sum" | |
| top: "group1_block2_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group1_block2_relu" | |
| type: "ReLU" | |
| bottom: "group1_block2_sum" | |
| top: "group1_block2_sum" | |
| } | |
| layer { | |
| name: "group1_block3_conv0" | |
| type: "Convolution" | |
| bottom: "group1_block2_sum" | |
| top: "group1_block3_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block3_conv0" | |
| top: "group1_block3_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_conv0_scale" | |
| type: "Scale" | |
| bottom: "group1_block3_conv0/bn" | |
| top: "group1_block3_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group1_block3_conv0/bn" | |
| top: "group1_block3_conv0/bn" | |
| } | |
| layer { | |
| name: "group1_block3_conv1" | |
| type: "Convolution" | |
| bottom: "group1_block3_conv0/bn" | |
| top: "group1_block3_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block3_conv1" | |
| top: "group1_block3_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_conv1_scale" | |
| type: "Scale" | |
| bottom: "group1_block3_conv1/bn" | |
| top: "group1_block3_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_sum" | |
| type: "Eltwise" | |
| bottom: "group1_block3_conv1/bn" | |
| bottom: "group1_block2_sum" | |
| top: "group1_block3_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group1_block3_relu" | |
| type: "ReLU" | |
| bottom: "group1_block3_sum" | |
| top: "group1_block3_sum" | |
| } | |
| layer { | |
| name: "group1_block4_conv0" | |
| type: "Convolution" | |
| bottom: "group1_block3_sum" | |
| top: "group1_block4_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block4_conv0" | |
| top: "group1_block4_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_conv0_scale" | |
| type: "Scale" | |
| bottom: "group1_block4_conv0/bn" | |
| top: "group1_block4_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group1_block4_conv0/bn" | |
| top: "group1_block4_conv0/bn" | |
| } | |
| layer { | |
| name: "group1_block4_conv1" | |
| type: "Convolution" | |
| bottom: "group1_block4_conv0/bn" | |
| top: "group1_block4_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group1_block4_conv1" | |
| top: "group1_block4_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_conv1_scale" | |
| type: "Scale" | |
| bottom: "group1_block4_conv1/bn" | |
| top: "group1_block4_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_sum" | |
| type: "Eltwise" | |
| bottom: "group1_block4_conv1/bn" | |
| bottom: "group1_block3_sum" | |
| top: "group1_block4_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group1_block4_relu" | |
| type: "ReLU" | |
| bottom: "group1_block4_sum" | |
| top: "group1_block4_sum" | |
| } | |
| layer { | |
| name: "group2_block0_conv0" | |
| type: "Convolution" | |
| bottom: "group1_block4_sum" | |
| top: "group2_block0_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block0_conv0" | |
| top: "group2_block0_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_conv0_scale" | |
| type: "Scale" | |
| bottom: "group2_block0_conv0/bn" | |
| top: "group2_block0_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group2_block0_conv0/bn" | |
| top: "group2_block0_conv0/bn" | |
| } | |
| layer { | |
| name: "group2_block0_conv1" | |
| type: "Convolution" | |
| bottom: "group2_block0_conv0/bn" | |
| top: "group2_block0_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block0_conv1" | |
| top: "group2_block0_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_conv1_scale" | |
| type: "Scale" | |
| bottom: "group2_block0_conv1/bn" | |
| top: "group2_block0_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_proj" | |
| type: "Convolution" | |
| bottom: "group1_block4_sum" | |
| top: "group2_block0_proj" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_proj_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block0_proj" | |
| top: "group2_block0_proj/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_proj_scale" | |
| type: "Scale" | |
| bottom: "group2_block0_proj/bn" | |
| top: "group2_block0_proj/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_sum" | |
| type: "Eltwise" | |
| bottom: "group2_block0_proj/bn" | |
| bottom: "group2_block0_conv1/bn" | |
| top: "group2_block0_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group2_block0_relu" | |
| type: "ReLU" | |
| bottom: "group2_block0_sum" | |
| top: "group2_block0_sum" | |
| } | |
| layer { | |
| name: "group2_block1_conv0" | |
| type: "Convolution" | |
| bottom: "group2_block0_sum" | |
| top: "group2_block1_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block1_conv0" | |
| top: "group2_block1_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_conv0_scale" | |
| type: "Scale" | |
| bottom: "group2_block1_conv0/bn" | |
| top: "group2_block1_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group2_block1_conv0/bn" | |
| top: "group2_block1_conv0/bn" | |
| } | |
| layer { | |
| name: "group2_block1_conv1" | |
| type: "Convolution" | |
| bottom: "group2_block1_conv0/bn" | |
| top: "group2_block1_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block1_conv1" | |
| top: "group2_block1_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_conv1_scale" | |
| type: "Scale" | |
| bottom: "group2_block1_conv1/bn" | |
| top: "group2_block1_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_sum" | |
| type: "Eltwise" | |
| bottom: "group2_block1_conv1/bn" | |
| bottom: "group2_block0_sum" | |
| top: "group2_block1_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group2_block1_relu" | |
| type: "ReLU" | |
| bottom: "group2_block1_sum" | |
| top: "group2_block1_sum" | |
| } | |
| layer { | |
| name: "group2_block2_conv0" | |
| type: "Convolution" | |
| bottom: "group2_block1_sum" | |
| top: "group2_block2_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block2_conv0" | |
| top: "group2_block2_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_conv0_scale" | |
| type: "Scale" | |
| bottom: "group2_block2_conv0/bn" | |
| top: "group2_block2_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group2_block2_conv0/bn" | |
| top: "group2_block2_conv0/bn" | |
| } | |
| layer { | |
| name: "group2_block2_conv1" | |
| type: "Convolution" | |
| bottom: "group2_block2_conv0/bn" | |
| top: "group2_block2_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block2_conv1" | |
| top: "group2_block2_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_conv1_scale" | |
| type: "Scale" | |
| bottom: "group2_block2_conv1/bn" | |
| top: "group2_block2_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_sum" | |
| type: "Eltwise" | |
| bottom: "group2_block2_conv1/bn" | |
| bottom: "group2_block1_sum" | |
| top: "group2_block2_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group2_block2_relu" | |
| type: "ReLU" | |
| bottom: "group2_block2_sum" | |
| top: "group2_block2_sum" | |
| } | |
| layer { | |
| name: "group2_block3_conv0" | |
| type: "Convolution" | |
| bottom: "group2_block2_sum" | |
| top: "group2_block3_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block3_conv0" | |
| top: "group2_block3_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_conv0_scale" | |
| type: "Scale" | |
| bottom: "group2_block3_conv0/bn" | |
| top: "group2_block3_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group2_block3_conv0/bn" | |
| top: "group2_block3_conv0/bn" | |
| } | |
| layer { | |
| name: "group2_block3_conv1" | |
| type: "Convolution" | |
| bottom: "group2_block3_conv0/bn" | |
| top: "group2_block3_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block3_conv1" | |
| top: "group2_block3_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_conv1_scale" | |
| type: "Scale" | |
| bottom: "group2_block3_conv1/bn" | |
| top: "group2_block3_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_sum" | |
| type: "Eltwise" | |
| bottom: "group2_block3_conv1/bn" | |
| bottom: "group2_block2_sum" | |
| top: "group2_block3_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group2_block3_relu" | |
| type: "ReLU" | |
| bottom: "group2_block3_sum" | |
| top: "group2_block3_sum" | |
| } | |
| layer { | |
| name: "group2_block4_conv0" | |
| type: "Convolution" | |
| bottom: "group2_block3_sum" | |
| top: "group2_block4_conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block4_conv0" | |
| top: "group2_block4_conv0/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_conv0_scale" | |
| type: "Scale" | |
| bottom: "group2_block4_conv0/bn" | |
| top: "group2_block4_conv0/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_conv0_relu" | |
| type: "ReLU" | |
| bottom: "group2_block4_conv0/bn" | |
| top: "group2_block4_conv0/bn" | |
| } | |
| layer { | |
| name: "group2_block4_conv1" | |
| type: "Convolution" | |
| bottom: "group2_block4_conv0/bn" | |
| top: "group2_block4_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "group2_block4_conv1" | |
| top: "group2_block4_conv1/bn" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_conv1_scale" | |
| type: "Scale" | |
| bottom: "group2_block4_conv1/bn" | |
| top: "group2_block4_conv1/bn" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_sum" | |
| type: "Eltwise" | |
| bottom: "group2_block4_conv1/bn" | |
| bottom: "group2_block3_sum" | |
| top: "group2_block4_sum" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "group2_block4_relu" | |
| type: "ReLU" | |
| bottom: "group2_block4_sum" | |
| top: "group2_block4_sum" | |
| } | |
| layer { | |
| name: "global_avg_pool" | |
| type: "Pooling" | |
| bottom: "group2_block4_sum" | |
| top: "global_avg_pool" | |
| pooling_param { | |
| pool: AVE | |
| global_pooling: true | |
| } | |
| } | |
| layer { | |
| name: "fc" | |
| type: "InnerProduct" | |
| bottom: "global_avg_pool" | |
| top: "fc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 10 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } |
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