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ResNet 18 Caffe prototxt file for DIGITS
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| # ResNet18 | |
| name: "ResNet18" | |
| layer { | |
| name: "train-data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| transform_param { | |
| mirror: true | |
| crop_size: 224 | |
| } | |
| data_param { | |
| batch_size: 32 | |
| } | |
| include { stage: "train" } | |
| } | |
| layer { | |
| name: "val-data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| transform_param { | |
| mirror: false | |
| crop_size: 224 | |
| } | |
| data_param { | |
| batch_size: 16 | |
| } | |
| include { stage: "val" } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn_conv1" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv1_bn" | |
| top: "conv1_bn" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1_bn" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "res2a_branch1" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "res2a_branch1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2a_branch1" | |
| type: "BatchNorm" | |
| bottom: "res2a_branch1" | |
| top: "res2a_branch1_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2a_branch2a" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "res2a_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2a_branch2a" | |
| type: "BatchNorm" | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2a_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "res2a_branch2a_bn" | |
| top: "res2a_branch2a_bn" | |
| } | |
| layer { | |
| name: "res2a_branch2b" | |
| type: "Convolution" | |
| bottom: "res2a_branch2a_bn" | |
| top: "res2a_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2a_branch2b" | |
| type: "BatchNorm" | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2a_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "res2a_branch2b_bn" | |
| top: "res2a_branch2b_bn" | |
| } | |
| layer { | |
| name: "res2a_branch2c" | |
| type: "Convolution" | |
| bottom: "res2a_branch2b_bn" | |
| top: "res2a_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2a_branch2c" | |
| type: "BatchNorm" | |
| bottom: "res2a_branch2c" | |
| top: "res2a_branch2c_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2a" | |
| type: "Eltwise" | |
| bottom: "res2a_branch1_bn" | |
| bottom: "res2a_branch2c_bn" | |
| top: "res2a" | |
| } | |
| layer { | |
| name: "res2a_relu" | |
| type: "ReLU" | |
| bottom: "res2a" | |
| top: "res2a" | |
| } | |
| layer { | |
| name: "res2b_branch2a" | |
| type: "Convolution" | |
| bottom: "res2a" | |
| top: "res2b_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2b_branch2a" | |
| type: "BatchNorm" | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2b_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "res2b_branch2a_bn" | |
| top: "res2b_branch2a_bn" | |
| } | |
| layer { | |
| name: "res2b_branch2b" | |
| type: "Convolution" | |
| bottom: "res2b_branch2a_bn" | |
| top: "res2b_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2b_branch2b" | |
| type: "BatchNorm" | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2b_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "res2b_branch2b_bn" | |
| top: "res2b_branch2b_bn" | |
| } | |
| layer { | |
| name: "res2b_branch2c" | |
| type: "Convolution" | |
| bottom: "res2b_branch2b_bn" | |
| top: "res2b_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2b_branch2c" | |
| type: "BatchNorm" | |
| bottom: "res2b_branch2c" | |
| top: "res2b_branch2c_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2b" | |
| type: "Eltwise" | |
| bottom: "res2a" | |
| bottom: "res2b_branch2c_bn" | |
| top: "res2b" | |
| } | |
| layer { | |
| name: "res2b_relu" | |
| type: "ReLU" | |
| bottom: "res2b" | |
| top: "res2b" | |
| } | |
| layer { | |
| name: "res2c_branch2a" | |
| type: "Convolution" | |
| bottom: "res2b" | |
| top: "res2c_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2c_branch2a" | |
| type: "BatchNorm" | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2c_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "res2c_branch2a_bn" | |
| top: "res2c_branch2a_bn" | |
| } | |
| layer { | |
| name: "res2c_branch2b" | |
| type: "Convolution" | |
| bottom: "res2c_branch2a_bn" | |
| top: "res2c_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2c_branch2b" | |
| type: "BatchNorm" | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2c_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "res2c_branch2b_bn" | |
| top: "res2c_branch2b_bn" | |
| } | |
| layer { | |
| name: "res2c_branch2c" | |
| type: "Convolution" | |
| bottom: "res2c_branch2b_bn" | |
| top: "res2c_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2c_branch2c" | |
| type: "BatchNorm" | |
| bottom: "res2c_branch2c" | |
| top: "res2c_branch2c_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res2c" | |
| type: "Eltwise" | |
| bottom: "res2b" | |
| bottom: "res2c_branch2c_bn" | |
| top: "res2c" | |
| } | |
| layer { | |
| name: "res2c_relu" | |
| type: "ReLU" | |
| bottom: "res2c" | |
| top: "res2c" | |
| } | |
| layer { | |
| name: "res3a_branch1" | |
| type: "Convolution" | |
| bottom: "res2c" | |
| top: "res3a_branch1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3a_branch1" | |
| type: "BatchNorm" | |
| bottom: "res3a_branch1" | |
| top: "res3a_branch1_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3a_branch2a" | |
| type: "Convolution" | |
| bottom: "res2c" | |
| top: "res3a_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3a_branch2a" | |
| type: "BatchNorm" | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3a_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "res3a_branch2a_bn" | |
| top: "res3a_branch2a_bn" | |
| } | |
| layer { | |
| name: "res3a_branch2b" | |
| type: "Convolution" | |
| bottom: "res3a_branch2a_bn" | |
| top: "res3a_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3a_branch2b" | |
| type: "BatchNorm" | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3a_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "res3a_branch2b_bn" | |
| top: "res3a_branch2b_bn" | |
| } | |
| layer { | |
| name: "res3a_branch2c" | |
| type: "Convolution" | |
| bottom: "res3a_branch2b_bn" | |
| top: "res3a_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3a_branch2c" | |
| type: "BatchNorm" | |
| bottom: "res3a_branch2c" | |
| top: "res3a_branch2c_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3a" | |
| type: "Eltwise" | |
| bottom: "res3a_branch1_bn" | |
| bottom: "res3a_branch2c_bn" | |
| top: "res3a" | |
| } | |
| layer { | |
| name: "res3a_relu" | |
| type: "ReLU" | |
| bottom: "res3a" | |
| top: "res3a" | |
| } | |
| layer { | |
| name: "res3b_branch2a" | |
| type: "Convolution" | |
| bottom: "res3a" | |
| top: "res3b_branch2a" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3b_branch2a" | |
| type: "BatchNorm" | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3b_branch2a_relu" | |
| type: "ReLU" | |
| bottom: "res3b_branch2a_bn" | |
| top: "res3b_branch2a_bn" | |
| } | |
| layer { | |
| name: "res3b_branch2b" | |
| type: "Convolution" | |
| bottom: "res3b_branch2a_bn" | |
| top: "res3b_branch2b" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3b_branch2b" | |
| type: "BatchNorm" | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3b_branch2b_relu" | |
| type: "ReLU" | |
| bottom: "res3b_branch2b_bn" | |
| top: "res3b_branch2b_bn" | |
| } | |
| layer { | |
| name: "res3b_branch2c" | |
| type: "Convolution" | |
| bottom: "res3b_branch2b_bn" | |
| top: "res3b_branch2c" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.0005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3b_branch2c" | |
| type: "BatchNorm" | |
| bottom: "res3b_branch2c" | |
| top: "res3b_branch2c_bn" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| scale_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "res3b" | |
| type: "Eltwise" | |
| bottom: "res3a" | |
| bottom: "res3b_branch2c_bn" | |
| top: "res3b" | |
| } | |
| layer { | |
| name: "res3b_relu" | |
| type: "ReLU" | |
| bottom: "res3b" | |
| top: "res3b" | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "res3b" | |
| top: "pool2" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 7 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "fclayer" | |
| type: "InnerProduct" | |
| bottom: "pool2" | |
| top: "fclayer" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "accuracy" | |
| type: "Accuracy" | |
| bottom: "fclayer" | |
| bottom: "label" | |
| top: "accuracy" | |
| include { stage: "val" } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "fclayer" | |
| bottom: "label" | |
| top: "loss" | |
| exclude { stage: "deploy" } | |
| } | |
| layer { | |
| name: "softmax" | |
| type: "Softmax" | |
| bottom: "fclayer" | |
| top: "softmax" | |
| include { stage: "deploy" } | |
| } |
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