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- name: "resnet_cifar10"
- layer {
- name: "Data1"
- type: "Data"
- top: "Data1"
- top: "Data2"
- include {
- phase: TRAIN
- }
- transform_param {
- mean_file: "examples/xor/mean.binaryproto"
- crop_size: 28
- mirror:true
- }
- data_param {
- source: "examples/xor/cifar10_train_lmdb"
- batch_size: 100
- backend: LMDB
- }
- }
- layer {
- name: "Data1"
- type: "Data"
- top: "Data1"
- top: "Data2"
- include {
- phase: TEST
- }
- transform_param {
- mean_file: "examples/xor/mean.binaryproto"
- }
- data_param {
- source: "examples/xor/cifar10_test_lmdb"
- batch_size: 100
- backend: LMDB
- }
- }
- layer {
- name: "Convolution1"
- type: "Convolution"
- bottom: "Data1"
- top: "Convolution1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm1"
- type: "BatchNorm"
- bottom: "Convolution1"
- top: "Convolution1"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale1"
- type: "Scale"
- bottom: "Convolution1"
- top: "Convolution1"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU1"
- type: "ReLU"
- bottom: "Convolution1"
- top: "Convolution1"
- }
- layer {
- name: "Convolution2"
- type: "Convolution"
- bottom: "Convolution1"
- top: "Convolution2"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm2"
- type: "BatchNorm"
- bottom: "Convolution2"
- top: "Convolution2"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale2"
- type: "Scale"
- bottom: "Convolution2"
- top: "Convolution2"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU2"
- type: "ReLU"
- bottom: "Convolution2"
- top: "Convolution2"
- }
- layer {
- name: "Convolution3"
- type: "Convolution"
- bottom: "Convolution2"
- top: "Convolution3"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm3"
- type: "BatchNorm"
- bottom: "Convolution3"
- top: "Convolution3"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale3"
- type: "Scale"
- bottom: "Convolution3"
- top: "Convolution3"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Eltwise1"
- type: "Eltwise"
- bottom: "Convolution1"
- bottom: "Convolution3"
- top: "Eltwise1"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "ReLU3"
- type: "ReLU"
- bottom: "Eltwise1"
- top: "Eltwise1"
- }
- layer {
- name: "Convolution4"
- type: "Convolution"
- bottom: "Eltwise1"
- top: "Convolution4"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm4"
- type: "BatchNorm"
- bottom: "Convolution4"
- top: "Convolution4"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale4"
- type: "Scale"
- bottom: "Convolution4"
- top: "Convolution4"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU4"
- type: "ReLU"
- bottom: "Convolution4"
- top: "Convolution4"
- }
- layer {
- name: "Convolution5"
- type: "Convolution"
- bottom: "Convolution4"
- top: "Convolution5"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm5"
- type: "BatchNorm"
- bottom: "Convolution5"
- top: "Convolution5"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale5"
- type: "Scale"
- bottom: "Convolution5"
- top: "Convolution5"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Eltwise2"
- type: "Eltwise"
- bottom: "Eltwise1"
- bottom: "Convolution5"
- top: "Eltwise2"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "ReLU5"
- type: "ReLU"
- bottom: "Eltwise2"
- top: "Eltwise2"
- }
- layer {
- name: "Convolution6"
- type: "Convolution"
- bottom: "Eltwise2"
- top: "Convolution6"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm6"
- type: "BatchNorm"
- bottom: "Convolution6"
- top: "Convolution6"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale6"
- type: "Scale"
- bottom: "Convolution6"
- top: "Convolution6"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU6"
- type: "ReLU"
- bottom: "Convolution6"
- top: "Convolution6"
- }
- layer {
- name: "Convolution7"
- type: "Convolution"
- bottom: "Convolution6"
- top: "Convolution7"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 16
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.118
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm7"
- type: "BatchNorm"
- bottom: "Convolution7"
- top: "Convolution7"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale7"
- type: "Scale"
- bottom: "Convolution7"
- top: "Convolution7"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Eltwise3"
- type: "Eltwise"
- bottom: "Eltwise2"
- bottom: "Convolution7"
- top: "Eltwise3"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "ReLU7"
- type: "ReLU"
- bottom: "Eltwise3"
- top: "Eltwise3"
- }
- layer {
- name: "Convolution8"
- type: "Convolution"
- bottom: "Eltwise3"
- top: "Convolution8"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 0
- kernel_size: 1
- stride: 2
- weight_filler {
- type: "gaussian"
- std: 0.25
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm8"
- type: "BatchNorm"
- bottom: "Convolution8"
- top: "Convolution8"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale8"
- type: "Scale"
- bottom: "Convolution8"
- top: "Convolution8"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Convolution9"
- type: "Convolution"
- bottom: "Eltwise3"
- top: "Convolution9"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 1
- kernel_size: 3
- stride: 2
- weight_filler {
- type: "gaussian"
- std: 0.083
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm9"
- type: "BatchNorm"
- bottom: "Convolution9"
- top: "Convolution9"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale9"
- type: "Scale"
- bottom: "Convolution9"
- top: "Convolution9"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU8"
- type: "ReLU"
- bottom: "Convolution9"
- top: "Convolution9"
- }
- layer {
- name: "Convolution10"
- type: "Convolution"
- bottom: "Convolution9"
- top: "Convolution10"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.083
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm10"
- type: "BatchNorm"
- bottom: "Convolution10"
- top: "Convolution10"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale10"
- type: "Scale"
- bottom: "Convolution10"
- top: "Convolution10"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Eltwise4"
- type: "Eltwise"
- bottom: "Convolution8"
- bottom: "Convolution10"
- top: "Eltwise4"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "ReLU9"
- type: "ReLU"
- bottom: "Eltwise4"
- top: "Eltwise4"
- }
- layer {
- name: "Convolution11"
- type: "Convolution"
- bottom: "Eltwise4"
- top: "Convolution11"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.083
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm11"
- type: "BatchNorm"
- bottom: "Convolution11"
- top: "Convolution11"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale11"
- type: "Scale"
- bottom: "Convolution11"
- top: "Convolution11"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU10"
- type: "ReLU"
- bottom: "Convolution11"
- top: "Convolution11"
- }
- layer {
- name: "Convolution12"
- type: "Convolution"
- bottom: "Convolution11"
- top: "Convolution12"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.083
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm12"
- type: "BatchNorm"
- bottom: "Convolution12"
- top: "Convolution12"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale12"
- type: "Scale"
- bottom: "Convolution12"
- top: "Convolution12"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Eltwise5"
- type: "Eltwise"
- bottom: "Eltwise4"
- bottom: "Convolution12"
- top: "Eltwise5"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "ReLU11"
- type: "ReLU"
- bottom: "Eltwise5"
- top: "Eltwise5"
- }
- layer {
- name: "Convolution13"
- type: "Convolution"
- bottom: "Eltwise5"
- top: "Convolution13"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.083
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm13"
- type: "BatchNorm"
- bottom: "Convolution13"
- top: "Convolution13"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale13"
- type: "Scale"
- bottom: "Convolution13"
- top: "Convolution13"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "ReLU12"
- type: "ReLU"
- bottom: "Convolution13"
- top: "Convolution13"
- }
- layer {
- name: "Convolution14"
- type: "Convolution"
- bottom: "Convolution13"
- top: "Convolution14"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 0
- }
- convolution_param {
- num_output: 32
- pad: 1
- kernel_size: 3
- stride: 1
- weight_filler {
- type: "gaussian"
- std: 0.083
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm14"
- type: "BatchNorm"
- bottom: "Convolution14"
- top: "Convolution14"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale14"
- type: "Scale"
- bottom: "Convolution14"
- top: "Convolution14"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "Eltwise6"
- type: "Eltwise"
- bottom: "Eltwise5"
- bottom: "Convolution14"
- top: "Eltwise6"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "ReLU13"
- type: "ReLU"
- bottom: "Eltwise6"
- top: "Eltwise6"
- }
- layer {
- name: "Convolution15"
- type: "Convolution"
- bottom: "Eltwise6"
- top: "Convolution15"
- 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: 2
- weight_filler {
- type: "gaussian"
- std: 0.176776695297
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm15"
- type: "BatchNorm"
- bottom: "Convolution15"
- top: "Convolution15"
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- param {
- lr_mult: 0
- decay_mult: 0
- }
- }
- layer {
- name: "Scale15"
- type: "Scale"
- bottom: "Convolution15"
- top: "Convolution15"
- scale_param {
- bias_term: true
- }
- }
- layer {
- name: "BinBatchNorm16"
- type: "BatchNorm"
- bottom: "Eltwise6"
- top: "Eltwise6_1"
- }
- layer {
- name: "Binactiv16"
- type: "BinActiv"
- bottom: "Eltwise6_1"
- top: "bin-eltwise6"
- binactiv_param{
- no_k: true
- }
- }
- layer {
- name: "BinConvolution16"
- type: "BinaryConvolution"
- bottom: "bin-eltwise6"
- top: "Convolution16"
- 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: 2
- weight_filler {
- type: "gaussian"
- std: 0.059
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BinBatchNorm17"
- type: "BatchNorm"
- bottom: "Convolution16"
- top: "Convolution16"
- }
- layer {
- name: "Binactiv17"
- type: "BinActiv"
- bottom: "Convolution16"
- top: "B-Convolution16"
- binactiv_param{
- no_k: true
- }
- }
- layer {
- name: "BinConvolution17"
- type: "BinaryConvolution"
- bottom: "B-Convolution16"
- top: "Convolution17"
- 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: "gaussian"
- std: 0.059
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "Eltwise7"
- type: "Eltwise"
- bottom: "Convolution15"
- bottom: "Convolution17"
- top: "Eltwise7"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "PReLU15"
- type: "PReLU"
- bottom: "Eltwise7"
- top: "Eltwise7"
- }
- layer {
- name: "BatchNorm18"
- type: "BatchNorm"
- bottom: "Eltwise7"
- top: "Eltwise7"
- }
- layer {
- name: "Binactiv18"
- type: "BinActiv"
- bottom: "Eltwise7"
- top: "B-Eltwise7"
- binactiv_param{
- no_k: true
- }
- }
- layer {
- name: "BinConvolution18"
- type: "BinaryConvolution"
- bottom: "B-Eltwise7"
- top: "Convolution18"
- 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: "gaussian"
- std: 0.059
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm19"
- type: "BatchNorm"
- bottom: "Convolution18"
- top: "Convolution18"
- }
- layer {
- name: "Binactiv19"
- type: "BinActiv"
- bottom: "Convolution18"
- top: "B-Convolution18"
- binactiv_param{
- no_k: true
- }
- }
- layer {
- name: "BinConvolution19"
- type: "BinaryConvolution"
- bottom: "B-Convolution18"
- top: "Convolution19"
- 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: "gaussian"
- std: 0.059
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "Eltwise8"
- type: "Eltwise"
- bottom: "Eltwise7"
- bottom: "Convolution19"
- top: "Eltwise8"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "PReLU17"
- type: "PReLU"
- bottom: "Eltwise8"
- top: "Eltwise8"
- }
- layer {
- name: "BatchNorm20"
- type: "BatchNorm"
- bottom: "Eltwise8"
- top: "BEltwise8"
- }
- layer {
- name: "Binactiv20"
- type: "BinActiv"
- bottom: "BEltwise8"
- top: "B-Eltwise8"
- binactiv_param{
- no_k:true
- }
- }
- layer {
- name: "BinConvolution20"
- type: "BinaryConvolution"
- bottom: "B-Eltwise8"
- top: "Convolution20"
- 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: "gaussian"
- std: 0.059
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "BatchNorm21"
- type: "BatchNorm"
- bottom: "Convolution20"
- top: "Convolution20"
- }
- layer {
- name: "Binactiv21"
- type: "BinActiv"
- bottom: "Convolution20"
- top: "B-Convolution20"
- binactiv_param{
- no_k:true
- }
- }
- layer {
- name: "BinConvolution21"
- type: "BinaryConvolution"
- bottom: "B-Convolution20"
- top: "Convolution21"
- 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: "gaussian"
- std: 0.059
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "Eltwise9"
- type: "Eltwise"
- bottom: "Eltwise8"
- bottom: "Convolution21"
- top: "Eltwise9"
- eltwise_param {
- operation: SUM
- }
- }
- layer {
- name: "PReLU19"
- type: "PReLU"
- bottom: "Eltwise9"
- top: "Eltwise9"
- }
- layer {
- name: "Pooling1"
- type: "Pooling"
- bottom: "Eltwise9"
- top: "Pooling1"
- pooling_param {
- pool: AVE
- global_pooling: true
- }
- }
- layer {
- name: "InnerProduct1"
- type: "InnerProduct"
- bottom: "Pooling1"
- top: "InnerProduct1"
- param {
- lr_mult: 1
- decay_mult: 1
- }
- param {
- lr_mult: 2
- decay_mult: 1
- }
- inner_product_param {
- num_output: 10
- weight_filler {
- type: "gaussian"
- std: 0.01
- }
- bias_filler {
- type: "constant"
- value: 0
- }
- }
- }
- layer {
- name: "SoftmaxWithLoss1"
- type: "SoftmaxWithLoss"
- bottom: "InnerProduct1"
- bottom: "Data2"
- top: "SoftmaxWithLoss1"
- }
- layer {
- name: "Accuracy1"
- type: "Accuracy"
- bottom: "InnerProduct1"
- bottom: "Data2"
- top: "Accuracy1"
- include {
- phase: TEST
- }
- }
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