213 lines
2.8 KiB
Plaintext
213 lines
2.8 KiB
Plaintext
name: "CIFAR10_full"
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layer {
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name: "cifar"
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type: "Data"
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top: "data"
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top: "label"
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include {
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phase: TRAIN
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}
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transform_param {
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mean_file: "examples/cifar10/mean.binaryproto"
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}
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data_param {
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source: "examples/cifar10/cifar10_train_lmdb"
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batch_size: 111
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backend: LMDB
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}
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}
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layer {
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name: "cifar"
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type: "Data"
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top: "data"
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top: "label"
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include {
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phase: TEST
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}
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transform_param {
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mean_file: "examples/cifar10/mean.binaryproto"
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}
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data_param {
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source: "examples/cifar10/cifar10_test_lmdb"
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batch_size: 1000
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backend: LMDB
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}
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}
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layer {
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name: "conv1"
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type: "Convolution"
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bottom: "data"
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top: "conv1"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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convolution_param {
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num_output: 32
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pad: 2
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kernel_size: 5
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.0001
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "pool1"
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type: "Pooling"
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bottom: "conv1"
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top: "pool1"
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pooling_param {
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pool: MAX
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kernel_size: 3
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stride: 2
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}
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}
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layer {
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name: "Sigmoid1"
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type: "Sigmoid"
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bottom: "pool1"
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top: "Sigmoid1"
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}
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layer {
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name: "conv2"
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type: "Convolution"
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bottom: "Sigmoid1"
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top: "conv2"
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 2
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}
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convolution_param {
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num_output: 32
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pad: 2
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kernel_size: 5
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "Sigmoid2"
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type: "Sigmoid"
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bottom: "conv2"
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top: "Sigmoid2"
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}
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layer {
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name: "pool2"
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type: "Pooling"
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bottom: "Sigmoid2"
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top: "pool2"
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pooling_param {
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pool: AVE
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kernel_size: 3
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stride: 2
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}
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}
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layer {
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name: "conv3"
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type: "Convolution"
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bottom: "pool2"
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top: "conv3"
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convolution_param {
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num_output: 64
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pad: 2
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kernel_size: 5
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stride: 1
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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}
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}
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param {
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lr_mult: 1
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}
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param {
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lr_mult: 1
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}
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}
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layer {
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name: "Sigmoid3"
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type: "Sigmoid"
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bottom: "conv3"
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top: "Sigmoid3"
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}
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layer {
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name: "pool3"
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type: "Pooling"
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bottom: "Sigmoid3"
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top: "pool3"
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pooling_param {
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pool: AVE
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kernel_size: 3
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stride: 2
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}
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}
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layer {
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name: "ip1"
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type: "InnerProduct"
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bottom: "pool3"
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top: "ip1"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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inner_product_param {
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num_output: 10
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weight_filler {
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type: "gaussian"
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std: 0.01
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}
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bias_filler {
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type: "constant"
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}
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}
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}
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layer {
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name: "accuracy"
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type: "Accuracy"
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bottom: "ip1"
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bottom: "label"
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top: "accuracy"
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include {
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phase: TEST
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}
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}
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layer {
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name: "loss"
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type: "SoftmaxWithLoss"
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bottom: "ip1"
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bottom: "label"
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top: "loss"
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}
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