| 3 | using namespace mllm; // NOLINT |
| 4 | |
| 5 | class FooNet final : public nn::Module { |
| 6 | nn::Linear linear_0; |
| 7 | nn::Linear linear_1; |
| 8 | nn::Linear linear_2; |
| 9 | nn::Linear linear_3; |
| 10 | nn::Sequential seq; |
| 11 | |
| 12 | public: |
| 13 | explicit FooNet(const std::string& name) : nn::Module(name) { |
| 14 | linear_0 = reg<nn::Linear>("linear_0", /*in_channels*/ 64, /*out_channels*/ 64); |
| 15 | linear_1 = reg<nn::Linear>("linear_1", /*in_channels*/ 64, /*out_channels*/ 64); |
| 16 | linear_2 = reg<nn::Linear>("linear_2", /*in_channels*/ 64, /*out_channels*/ 64); |
| 17 | linear_3 = reg<nn::Linear>("linear_3", /*in_channels*/ 64, /*out_channels*/ 64); |
| 18 | seq = reg<nn::Sequential>("activation") |
| 19 | .add<nn::SiLU>() |
| 20 | .add<nn::Linear>(/*in_channels*/ 64, /*out_channels*/ 64) |
| 21 | .add<nn::SiLU>(); |
| 22 | } |
| 23 | |
| 24 | std::vector<Tensor> forward(const std::vector<Tensor>& inputs, const std::vector<AnyValue>& args) override { |
| 25 | return seq(linear_3(linear_2(linear_1(linear_0(inputs[0]))))); |
| 26 | } |
| 27 | }; |
| 28 | |
| 29 | int main() { |
| 30 | mllm::initializeContext(); |