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bmount/Train-densenet.protrototxt

Created December 6, 2016 10:25
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Train-densenet.protrototxt
layer {
name: "Data1"
type: "Data"
top: "Data1"
top: "Data2"
transform_param {
mean_file: "/home/zl499/caffe/examples/cifar10/mean.binaryproto"
}
data_param {
source: "/home/zl499/caffe/examples/cifar10/cifar10_train_lmdb"
batch_size: 64
backend: LMDB
}
}
layer {
name: "Convolution1"
type: "Convolution"
bottom: "Data1"
top: "Convolution1"
convolution_param {
num_output: 16
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "BatchNorm1"
type: "BatchNorm"
bottom: "Convolution1"
top: "BatchNorm1"
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: "BatchNorm1"
top: "BatchNorm1"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU1"
type: "ReLU"
bottom: "BatchNorm1"
top: "BatchNorm1"
}
layer {
name: "Convolution2"
type: "Convolution"
bottom: "BatchNorm1"
top: "Convolution2"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout1"
type: "Dropout"
bottom: "Convolution2"
top: "Dropout1"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat1"
type: "Concat"
bottom: "Convolution1"
bottom: "Dropout1"
top: "Concat1"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm2"
type: "BatchNorm"
bottom: "Concat1"
top: "BatchNorm2"
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: "BatchNorm2"
top: "BatchNorm2"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU2"
type: "ReLU"
bottom: "BatchNorm2"
top: "BatchNorm2"
}
layer {
name: "Convolution3"
type: "Convolution"
bottom: "BatchNorm2"
top: "Convolution3"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout2"
type: "Dropout"
bottom: "Convolution3"
top: "Dropout2"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat2"
type: "Concat"
bottom: "Concat1"
bottom: "Dropout2"
top: "Concat2"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm3"
type: "BatchNorm"
bottom: "Concat2"
top: "BatchNorm3"
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: "BatchNorm3"
top: "BatchNorm3"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU3"
type: "ReLU"
bottom: "BatchNorm3"
top: "BatchNorm3"
}
layer {
name: "Convolution4"
type: "Convolution"
bottom: "BatchNorm3"
top: "Convolution4"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout3"
type: "Dropout"
bottom: "Convolution4"
top: "Dropout3"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat3"
type: "Concat"
bottom: "Concat2"
bottom: "Dropout3"
top: "Concat3"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm4"
type: "BatchNorm"
bottom: "Concat3"
top: "BatchNorm4"
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: "BatchNorm4"
top: "BatchNorm4"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU4"
type: "ReLU"
bottom: "BatchNorm4"
top: "BatchNorm4"
}
layer {
name: "Convolution5"
type: "Convolution"
bottom: "BatchNorm4"
top: "Convolution5"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout4"
type: "Dropout"
bottom: "Convolution5"
top: "Dropout4"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat4"
type: "Concat"
bottom: "Concat3"
bottom: "Dropout4"
top: "Concat4"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm5"
type: "BatchNorm"
bottom: "Concat4"
top: "BatchNorm5"
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: "BatchNorm5"
top: "BatchNorm5"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU5"
type: "ReLU"
bottom: "BatchNorm5"
top: "BatchNorm5"
}
layer {
name: "Convolution6"
type: "Convolution"
bottom: "BatchNorm5"
top: "Convolution6"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout5"
type: "Dropout"
bottom: "Convolution6"
top: "Dropout5"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat5"
type: "Concat"
bottom: "Concat4"
bottom: "Dropout5"
top: "Concat5"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm6"
type: "BatchNorm"
bottom: "Concat5"
top: "BatchNorm6"
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: "BatchNorm6"
top: "BatchNorm6"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU6"
type: "ReLU"
bottom: "BatchNorm6"
top: "BatchNorm6"
}
layer {
name: "Convolution7"
type: "Convolution"
bottom: "BatchNorm6"
top: "Convolution7"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout6"
type: "Dropout"
bottom: "Convolution7"
top: "Dropout6"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat6"
type: "Concat"
bottom: "Concat5"
bottom: "Dropout6"
top: "Concat6"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm7"
type: "BatchNorm"
bottom: "Concat6"
top: "BatchNorm7"
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: "BatchNorm7"
top: "BatchNorm7"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU7"
type: "ReLU"
bottom: "BatchNorm7"
top: "BatchNorm7"
}
layer {
name: "Convolution8"
type: "Convolution"
bottom: "BatchNorm7"
top: "Convolution8"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout7"
type: "Dropout"
bottom: "Convolution8"
top: "Dropout7"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat7"
type: "Concat"
bottom: "Concat6"
bottom: "Dropout7"
top: "Concat7"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm8"
type: "BatchNorm"
bottom: "Concat7"
top: "BatchNorm8"
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: "BatchNorm8"
top: "BatchNorm8"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU8"
type: "ReLU"
bottom: "BatchNorm8"
top: "BatchNorm8"
}
layer {
name: "Convolution9"
type: "Convolution"
bottom: "BatchNorm8"
top: "Convolution9"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout8"
type: "Dropout"
bottom: "Convolution9"
top: "Dropout8"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat8"
type: "Concat"
bottom: "Concat7"
bottom: "Dropout8"
top: "Concat8"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm9"
type: "BatchNorm"
bottom: "Concat8"
top: "BatchNorm9"
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: "BatchNorm9"
top: "BatchNorm9"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU9"
type: "ReLU"
bottom: "BatchNorm9"
top: "BatchNorm9"
}
layer {
name: "Convolution10"
type: "Convolution"
bottom: "BatchNorm9"
top: "Convolution10"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout9"
type: "Dropout"
bottom: "Convolution10"
top: "Dropout9"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat9"
type: "Concat"
bottom: "Concat8"
bottom: "Dropout9"
top: "Concat9"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm10"
type: "BatchNorm"
bottom: "Concat9"
top: "BatchNorm10"
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: "BatchNorm10"
top: "BatchNorm10"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU10"
type: "ReLU"
bottom: "BatchNorm10"
top: "BatchNorm10"
}
layer {
name: "Convolution11"
type: "Convolution"
bottom: "BatchNorm10"
top: "Convolution11"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout10"
type: "Dropout"
bottom: "Convolution11"
top: "Dropout10"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat10"
type: "Concat"
bottom: "Concat9"
bottom: "Dropout10"
top: "Concat10"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm11"
type: "BatchNorm"
bottom: "Concat10"
top: "BatchNorm11"
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: "BatchNorm11"
top: "BatchNorm11"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU11"
type: "ReLU"
bottom: "BatchNorm11"
top: "BatchNorm11"
}
layer {
name: "Convolution12"
type: "Convolution"
bottom: "BatchNorm11"
top: "Convolution12"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout11"
type: "Dropout"
bottom: "Convolution12"
top: "Dropout11"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat11"
type: "Concat"
bottom: "Concat10"
bottom: "Dropout11"
top: "Concat11"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm12"
type: "BatchNorm"
bottom: "Concat11"
top: "BatchNorm12"
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: "BatchNorm12"
top: "BatchNorm12"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU12"
type: "ReLU"
bottom: "BatchNorm12"
top: "BatchNorm12"
}
layer {
name: "Convolution13"
type: "Convolution"
bottom: "BatchNorm12"
top: "Convolution13"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout12"
type: "Dropout"
bottom: "Convolution13"
top: "Dropout12"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat12"
type: "Concat"
bottom: "Concat11"
bottom: "Dropout12"
top: "Concat12"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm13"
type: "BatchNorm"
bottom: "Concat12"
top: "BatchNorm13"
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: "BatchNorm13"
top: "BatchNorm13"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU13"
type: "ReLU"
bottom: "BatchNorm13"
top: "BatchNorm13"
}
layer {
name: "Convolution14"
type: "Convolution"
bottom: "BatchNorm13"
top: "Convolution14"
convolution_param {
num_output: 160
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout13"
type: "Dropout"
bottom: "Convolution14"
top: "Dropout13"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Pooling1"
type: "Pooling"
bottom: "Dropout13"
top: "Pooling1"
pooling_param {
pool: AVE
kernel_size: 2
stride: 2
}
}
layer {
name: "BatchNorm14"
type: "BatchNorm"
bottom: "Pooling1"
top: "BatchNorm14"
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: "BatchNorm14"
top: "BatchNorm14"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU14"
type: "ReLU"
bottom: "BatchNorm14"
top: "BatchNorm14"
}
layer {
name: "Convolution15"
type: "Convolution"
bottom: "BatchNorm14"
top: "Convolution15"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout14"
type: "Dropout"
bottom: "Convolution15"
top: "Dropout14"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat13"
type: "Concat"
bottom: "Pooling1"
bottom: "Dropout14"
top: "Concat13"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm15"
type: "BatchNorm"
bottom: "Concat13"
top: "BatchNorm15"
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: "BatchNorm15"
top: "BatchNorm15"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU15"
type: "ReLU"
bottom: "BatchNorm15"
top: "BatchNorm15"
}
layer {
name: "Convolution16"
type: "Convolution"
bottom: "BatchNorm15"
top: "Convolution16"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout15"
type: "Dropout"
bottom: "Convolution16"
top: "Dropout15"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat14"
type: "Concat"
bottom: "Concat13"
bottom: "Dropout15"
top: "Concat14"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm16"
type: "BatchNorm"
bottom: "Concat14"
top: "BatchNorm16"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale16"
type: "Scale"
bottom: "BatchNorm16"
top: "BatchNorm16"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU16"
type: "ReLU"
bottom: "BatchNorm16"
top: "BatchNorm16"
}
layer {
name: "Convolution17"
type: "Convolution"
bottom: "BatchNorm16"
top: "Convolution17"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout16"
type: "Dropout"
bottom: "Convolution17"
top: "Dropout16"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat15"
type: "Concat"
bottom: "Concat14"
bottom: "Dropout16"
top: "Concat15"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm17"
type: "BatchNorm"
bottom: "Concat15"
top: "BatchNorm17"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale17"
type: "Scale"
bottom: "BatchNorm17"
top: "BatchNorm17"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU17"
type: "ReLU"
bottom: "BatchNorm17"
top: "BatchNorm17"
}
layer {
name: "Convolution18"
type: "Convolution"
bottom: "BatchNorm17"
top: "Convolution18"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout17"
type: "Dropout"
bottom: "Convolution18"
top: "Dropout17"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat16"
type: "Concat"
bottom: "Concat15"
bottom: "Dropout17"
top: "Concat16"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm18"
type: "BatchNorm"
bottom: "Concat16"
top: "BatchNorm18"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale18"
type: "Scale"
bottom: "BatchNorm18"
top: "BatchNorm18"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU18"
type: "ReLU"
bottom: "BatchNorm18"
top: "BatchNorm18"
}
layer {
name: "Convolution19"
type: "Convolution"
bottom: "BatchNorm18"
top: "Convolution19"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout18"
type: "Dropout"
bottom: "Convolution19"
top: "Dropout18"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat17"
type: "Concat"
bottom: "Concat16"
bottom: "Dropout18"
top: "Concat17"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm19"
type: "BatchNorm"
bottom: "Concat17"
top: "BatchNorm19"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale19"
type: "Scale"
bottom: "BatchNorm19"
top: "BatchNorm19"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU19"
type: "ReLU"
bottom: "BatchNorm19"
top: "BatchNorm19"
}
layer {
name: "Convolution20"
type: "Convolution"
bottom: "BatchNorm19"
top: "Convolution20"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout19"
type: "Dropout"
bottom: "Convolution20"
top: "Dropout19"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat18"
type: "Concat"
bottom: "Concat17"
bottom: "Dropout19"
top: "Concat18"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm20"
type: "BatchNorm"
bottom: "Concat18"
top: "BatchNorm20"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale20"
type: "Scale"
bottom: "BatchNorm20"
top: "BatchNorm20"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU20"
type: "ReLU"
bottom: "BatchNorm20"
top: "BatchNorm20"
}
layer {
name: "Convolution21"
type: "Convolution"
bottom: "BatchNorm20"
top: "Convolution21"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout20"
type: "Dropout"
bottom: "Convolution21"
top: "Dropout20"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat19"
type: "Concat"
bottom: "Concat18"
bottom: "Dropout20"
top: "Concat19"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm21"
type: "BatchNorm"
bottom: "Concat19"
top: "BatchNorm21"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale21"
type: "Scale"
bottom: "BatchNorm21"
top: "BatchNorm21"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU21"
type: "ReLU"
bottom: "BatchNorm21"
top: "BatchNorm21"
}
layer {
name: "Convolution22"
type: "Convolution"
bottom: "BatchNorm21"
top: "Convolution22"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout21"
type: "Dropout"
bottom: "Convolution22"
top: "Dropout21"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat20"
type: "Concat"
bottom: "Concat19"
bottom: "Dropout21"
top: "Concat20"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm22"
type: "BatchNorm"
bottom: "Concat20"
top: "BatchNorm22"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale22"
type: "Scale"
bottom: "BatchNorm22"
top: "BatchNorm22"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU22"
type: "ReLU"
bottom: "BatchNorm22"
top: "BatchNorm22"
}
layer {
name: "Convolution23"
type: "Convolution"
bottom: "BatchNorm22"
top: "Convolution23"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout22"
type: "Dropout"
bottom: "Convolution23"
top: "Dropout22"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat21"
type: "Concat"
bottom: "Concat20"
bottom: "Dropout22"
top: "Concat21"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm23"
type: "BatchNorm"
bottom: "Concat21"
top: "BatchNorm23"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale23"
type: "Scale"
bottom: "BatchNorm23"
top: "BatchNorm23"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU23"
type: "ReLU"
bottom: "BatchNorm23"
top: "BatchNorm23"
}
layer {
name: "Convolution24"
type: "Convolution"
bottom: "BatchNorm23"
top: "Convolution24"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout23"
type: "Dropout"
bottom: "Convolution24"
top: "Dropout23"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat22"
type: "Concat"
bottom: "Concat21"
bottom: "Dropout23"
top: "Concat22"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm24"
type: "BatchNorm"
bottom: "Concat22"
top: "BatchNorm24"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale24"
type: "Scale"
bottom: "BatchNorm24"
top: "BatchNorm24"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU24"
type: "ReLU"
bottom: "BatchNorm24"
top: "BatchNorm24"
}
layer {
name: "Convolution25"
type: "Convolution"
bottom: "BatchNorm24"
top: "Convolution25"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout24"
type: "Dropout"
bottom: "Convolution25"
top: "Dropout24"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat23"
type: "Concat"
bottom: "Concat22"
bottom: "Dropout24"
top: "Concat23"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm25"
type: "BatchNorm"
bottom: "Concat23"
top: "BatchNorm25"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale25"
type: "Scale"
bottom: "BatchNorm25"
top: "BatchNorm25"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU25"
type: "ReLU"
bottom: "BatchNorm25"
top: "BatchNorm25"
}
layer {
name: "Convolution26"
type: "Convolution"
bottom: "BatchNorm25"
top: "Convolution26"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout25"
type: "Dropout"
bottom: "Convolution26"
top: "Dropout25"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat24"
type: "Concat"
bottom: "Concat23"
bottom: "Dropout25"
top: "Concat24"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm26"
type: "BatchNorm"
bottom: "Concat24"
top: "BatchNorm26"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale26"
type: "Scale"
bottom: "BatchNorm26"
top: "BatchNorm26"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU26"
type: "ReLU"
bottom: "BatchNorm26"
top: "BatchNorm26"
}
layer {
name: "Convolution27"
type: "Convolution"
bottom: "BatchNorm26"
top: "Convolution27"
convolution_param {
num_output: 304
bias_term: false
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout26"
type: "Dropout"
bottom: "Convolution27"
top: "Dropout26"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Pooling2"
type: "Pooling"
bottom: "Dropout26"
top: "Pooling2"
pooling_param {
pool: AVE
kernel_size: 2
stride: 2
}
}
layer {
name: "BatchNorm27"
type: "BatchNorm"
bottom: "Pooling2"
top: "BatchNorm27"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale27"
type: "Scale"
bottom: "BatchNorm27"
top: "BatchNorm27"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU27"
type: "ReLU"
bottom: "BatchNorm27"
top: "BatchNorm27"
}
layer {
name: "Convolution28"
type: "Convolution"
bottom: "BatchNorm27"
top: "Convolution28"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout27"
type: "Dropout"
bottom: "Convolution28"
top: "Dropout27"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat25"
type: "Concat"
bottom: "Pooling2"
bottom: "Dropout27"
top: "Concat25"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm28"
type: "BatchNorm"
bottom: "Concat25"
top: "BatchNorm28"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale28"
type: "Scale"
bottom: "BatchNorm28"
top: "BatchNorm28"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU28"
type: "ReLU"
bottom: "BatchNorm28"
top: "BatchNorm28"
}
layer {
name: "Convolution29"
type: "Convolution"
bottom: "BatchNorm28"
top: "Convolution29"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout28"
type: "Dropout"
bottom: "Convolution29"
top: "Dropout28"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat26"
type: "Concat"
bottom: "Concat25"
bottom: "Dropout28"
top: "Concat26"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm29"
type: "BatchNorm"
bottom: "Concat26"
top: "BatchNorm29"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale29"
type: "Scale"
bottom: "BatchNorm29"
top: "BatchNorm29"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU29"
type: "ReLU"
bottom: "BatchNorm29"
top: "BatchNorm29"
}
layer {
name: "Convolution30"
type: "Convolution"
bottom: "BatchNorm29"
top: "Convolution30"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout29"
type: "Dropout"
bottom: "Convolution30"
top: "Dropout29"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat27"
type: "Concat"
bottom: "Concat26"
bottom: "Dropout29"
top: "Concat27"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm30"
type: "BatchNorm"
bottom: "Concat27"
top: "BatchNorm30"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale30"
type: "Scale"
bottom: "BatchNorm30"
top: "BatchNorm30"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU30"
type: "ReLU"
bottom: "BatchNorm30"
top: "BatchNorm30"
}
layer {
name: "Convolution31"
type: "Convolution"
bottom: "BatchNorm30"
top: "Convolution31"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout30"
type: "Dropout"
bottom: "Convolution31"
top: "Dropout30"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat28"
type: "Concat"
bottom: "Concat27"
bottom: "Dropout30"
top: "Concat28"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm31"
type: "BatchNorm"
bottom: "Concat28"
top: "BatchNorm31"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale31"
type: "Scale"
bottom: "BatchNorm31"
top: "BatchNorm31"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU31"
type: "ReLU"
bottom: "BatchNorm31"
top: "BatchNorm31"
}
layer {
name: "Convolution32"
type: "Convolution"
bottom: "BatchNorm31"
top: "Convolution32"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout31"
type: "Dropout"
bottom: "Convolution32"
top: "Dropout31"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat29"
type: "Concat"
bottom: "Concat28"
bottom: "Dropout31"
top: "Concat29"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm32"
type: "BatchNorm"
bottom: "Concat29"
top: "BatchNorm32"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale32"
type: "Scale"
bottom: "BatchNorm32"
top: "BatchNorm32"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU32"
type: "ReLU"
bottom: "BatchNorm32"
top: "BatchNorm32"
}
layer {
name: "Convolution33"
type: "Convolution"
bottom: "BatchNorm32"
top: "Convolution33"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout32"
type: "Dropout"
bottom: "Convolution33"
top: "Dropout32"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat30"
type: "Concat"
bottom: "Concat29"
bottom: "Dropout32"
top: "Concat30"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm33"
type: "BatchNorm"
bottom: "Concat30"
top: "BatchNorm33"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale33"
type: "Scale"
bottom: "BatchNorm33"
top: "BatchNorm33"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU33"
type: "ReLU"
bottom: "BatchNorm33"
top: "BatchNorm33"
}
layer {
name: "Convolution34"
type: "Convolution"
bottom: "BatchNorm33"
top: "Convolution34"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout33"
type: "Dropout"
bottom: "Convolution34"
top: "Dropout33"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat31"
type: "Concat"
bottom: "Concat30"
bottom: "Dropout33"
top: "Concat31"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm34"
type: "BatchNorm"
bottom: "Concat31"
top: "BatchNorm34"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale34"
type: "Scale"
bottom: "BatchNorm34"
top: "BatchNorm34"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU34"
type: "ReLU"
bottom: "BatchNorm34"
top: "BatchNorm34"
}
layer {
name: "Convolution35"
type: "Convolution"
bottom: "BatchNorm34"
top: "Convolution35"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout34"
type: "Dropout"
bottom: "Convolution35"
top: "Dropout34"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat32"
type: "Concat"
bottom: "Concat31"
bottom: "Dropout34"
top: "Concat32"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm35"
type: "BatchNorm"
bottom: "Concat32"
top: "BatchNorm35"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale35"
type: "Scale"
bottom: "BatchNorm35"
top: "BatchNorm35"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU35"
type: "ReLU"
bottom: "BatchNorm35"
top: "BatchNorm35"
}
layer {
name: "Convolution36"
type: "Convolution"
bottom: "BatchNorm35"
top: "Convolution36"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout35"
type: "Dropout"
bottom: "Convolution36"
top: "Dropout35"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat33"
type: "Concat"
bottom: "Concat32"
bottom: "Dropout35"
top: "Concat33"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm36"
type: "BatchNorm"
bottom: "Concat33"
top: "BatchNorm36"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale36"
type: "Scale"
bottom: "BatchNorm36"
top: "BatchNorm36"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU36"
type: "ReLU"
bottom: "BatchNorm36"
top: "BatchNorm36"
}
layer {
name: "Convolution37"
type: "Convolution"
bottom: "BatchNorm36"
top: "Convolution37"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout36"
type: "Dropout"
bottom: "Convolution37"
top: "Dropout36"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat34"
type: "Concat"
bottom: "Concat33"
bottom: "Dropout36"
top: "Concat34"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm37"
type: "BatchNorm"
bottom: "Concat34"
top: "BatchNorm37"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale37"
type: "Scale"
bottom: "BatchNorm37"
top: "BatchNorm37"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU37"
type: "ReLU"
bottom: "BatchNorm37"
top: "BatchNorm37"
}
layer {
name: "Convolution38"
type: "Convolution"
bottom: "BatchNorm37"
top: "Convolution38"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout37"
type: "Dropout"
bottom: "Convolution38"
top: "Dropout37"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat35"
type: "Concat"
bottom: "Concat34"
bottom: "Dropout37"
top: "Concat35"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm38"
type: "BatchNorm"
bottom: "Concat35"
top: "BatchNorm38"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale38"
type: "Scale"
bottom: "BatchNorm38"
top: "BatchNorm38"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU38"
type: "ReLU"
bottom: "BatchNorm38"
top: "BatchNorm38"
}
layer {
name: "Convolution39"
type: "Convolution"
bottom: "BatchNorm38"
top: "Convolution39"
convolution_param {
num_output: 12
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "Dropout38"
type: "Dropout"
bottom: "Convolution39"
top: "Dropout38"
dropout_param {
dropout_ratio: 0.2
}
}
layer {
name: "Concat36"
type: "Concat"
bottom: "Concat35"
bottom: "Dropout38"
top: "Concat36"
concat_param {
axis: 1
}
}
layer {
name: "BatchNorm39"
type: "BatchNorm"
bottom: "Concat36"
top: "BatchNorm39"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "Scale39"
type: "Scale"
bottom: "BatchNorm39"
top: "BatchNorm39"
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "ReLU39"
type: "ReLU"
bottom: "BatchNorm39"
top: "BatchNorm39"
}
layer {
name: "Pooling3"
type: "Pooling"
bottom: "BatchNorm39"
top: "Pooling3"
pooling_param {
pool: AVE
global_pooling: true
}
}
layer {
name: "InnerProduct1"
type: "InnerProduct"
bottom: "Pooling3"
top: "InnerProduct1"
inner_product_param {
num_output: 10
bias_term: true
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
}
}
}
layer {
name: "SoftmaxWithLoss1"
type: "SoftmaxWithLoss"
bottom: "InnerProduct1"
bottom: "Data2"
top: "SoftmaxWithLoss1"
}
layer {
name: "Accuracy1"
type: "Accuracy"
bottom: "InnerProduct1"
bottom: "Data2"
top: "Accuracy1"
}
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