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Commit b9332698 authored by Davis King's avatar Davis King
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updated example

parent e5ad9590
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examples/dnn_mnist_advanced_ex.cpp
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...@@ -198,32 +198,32 @@ int main(int argc, char** argv) try ...@@ -198,32 +198,32 @@ int main(int argc, char** argv) try
layer<2> avg_pool (nr=0, nc=0, stride_y=1, stride_x=1, padding_y=0, padding_x=0) layer<2> avg_pool (nr=0, nc=0, stride_y=1, stride_x=1, padding_y=0, padding_x=0)
layer<3> prelu (initial_param_value=0.2) layer<3> prelu (initial_param_value=0.2)
layer<4> add_prev layer<4> add_prev
layer<5> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<5> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
layer<6> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0 layer<6> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<7> prelu (initial_param_value=0.25) layer<7> prelu (initial_param_value=0.25)
layer<8> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<8> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
layer<9> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0 layer<9> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<10> tag1 layer<10> tag1
... ...
layer<34> relu layer<34> relu
layer<35> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<35> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
layer<36> con (num_filters=8, nr=3, nc=3, stride_y=2, stride_x=2, padding_y=0, padding_x=0) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0 layer<36> con (num_filters=8, nr=3, nc=3, stride_y=2, stride_x=2, padding_y=0, padding_x=0) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<37> tag1 layer<37> tag1
layer<38> tag4 layer<38> tag4
layer<39> prelu (initial_param_value=0.3) layer<39> prelu (initial_param_value=0.3)
layer<40> add_prev layer<40> add_prev
layer<41> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<41> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
... ...
layer<118> relu layer<118> relu
layer<119> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<119> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
layer<120> con (num_filters=8, nr=3, nc=3, stride_y=2, stride_x=2, padding_y=0, padding_x=0) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0 layer<120> con (num_filters=8, nr=3, nc=3, stride_y=2, stride_x=2, padding_y=0, padding_x=0) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<121> tag1 layer<121> tag1
layer<122> relu layer<122> relu
layer<123> add_prev layer<123> add_prev
layer<124> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<124> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
layer<125> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0 layer<125> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<126> relu layer<126> relu
layer<127> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 layer<127> bn_con eps=1e-05 learning_rate_mult=1 weight_decay_mult=0 bias_learning_rate_mult=1 bias_weight_decay_mult=1
layer<128> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0 layer<128> con (num_filters=8, nr=3, nc=3, stride_y=1, stride_x=1, padding_y=1, padding_x=1) learning_rate_mult=1 weight_decay_mult=1 bias_learning_rate_mult=1 bias_weight_decay_mult=0
layer<129> tag1 layer<129> tag1
layer<130> input<matrix> layer<130> input<matrix>
......
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