From e8972f66dafc5ecffe0b92ddf524f47b27cf5193 Mon Sep 17 00:00:00 2001 From: Eric Cardozo <126921462+ericcardozo@users.noreply.github.com> Date: Tue, 17 Oct 2023 18:46:28 -0300 Subject: [PATCH] added a few methods in the optimizer and layers. 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z-gWnL$N&0W{|*1*4gH-v{tJ#YfBLKcZvGU1qsM>xI=}V*r1$?1d}Gi5yMLGS_4uEE zrdO6rDE;UKznh%@&B4#|S9<)nPwOw`nBM { Autoencoder() { - encoder.configure_optimizer(std::dynamic_pointer_cast(encoder_optimizer)); - decoder.configure_optimizer(std::dynamic_pointer_cast(decoder_optimizer)); + encoder_optimizer.add_parameter(encoder.parameters()); + decoder_optimizer.add_parameter(decoder.parameters()); } net::layer::Sequence encoder { @@ -38,16 +38,16 @@ struct Autoencoder : public net::Model { } void step() { - encoder_optimizer->step(); - decoder_optimizer->step(); + encoder_optimizer.step(); + decoder_optimizer.step(); } /* you can add different optimizers to different layers or the same, doesn't matter, the optimizer has a shared pointer to it's implementation so you can pass instances of it with value semantics without making deep copies */ - std::shared_ptr encoder_optimizer = std::make_shared(/*learning rate*/ 0.1); - std::shared_ptr decoder_optimizer = std::make_shared(/*learning rate*/ 0.2); + net::optimizer::SGD encoder_optimizer{0.01}; + net::optimizer::SGD decoder_optimizer{0.01}; }; int main() { diff --git a/examples/model.cpp b/examples/model.cpp index acee910..b7589d1 100644 --- a/examples/model.cpp +++ b/examples/model.cpp @@ -1,9 +1,10 @@ #include struct Network : public net::Model { - Network() : net::Model( - std::make_shared(/*learning rate*/ 0.1) - ) {} + + Network() { + optimizer.add_parameter(layers.parameters()); + } net::layer::Sequence layers { net::layer::Linear(784, 128), @@ -15,6 +16,8 @@ struct Network : public net::Model { net::Tensor forward(net::Tensor x) { return layers(x); } + + net::optimizer::SGD optimizer{0.01}; }; int main() { diff --git a/include/CaberNet/layers.h b/include/CaberNet/layers.h index 789b794..92dd3cc 100644 --- a/include/CaberNet/layers.h +++ b/include/CaberNet/layers.h @@ -20,9 +20,14 @@ class Linear : public Model { size_type input_features, size_type output_features, initializer distribution = initializer::He ); - + Tensor forward(Tensor x); + void set_optimizer(std::shared_ptr optimizer); + + std::vector parameters() const { + return { weight_.internal(), bias_.internal() }; + } private: Tensor weight_; @@ -31,6 +36,11 @@ class Linear : public Model { struct ReLU : public Model { ReLU() = default; + + std::vector parameters()const { + return {}; + } + Tensor forward(Tensor input); void set_optimizer(std::shared_ptr optimizer) { return; } }; @@ -38,6 +48,11 @@ struct ReLU : public Model { struct Softmax : public Model { int axis; Softmax(int axis); + + std::vector parameters()const { + return {}; + } + Tensor forward(Tensor input); void set_optimizer(std::shared_ptr optimizer) { return; } }; @@ -45,6 +60,11 @@ struct Softmax : public Model { struct LogSoftmax : public Model { int axis; LogSoftmax(int axis); + + std::vector parameters()const { + return {}; + } + Tensor forward(Tensor input); void set_optimizer(std::shared_ptr optimizer) { return; } }; @@ -70,9 +90,24 @@ class Sequence : public Model { } return input; } + + std::vector parameters() const { + + std::vector parameter_list; + for (auto& layer : layers_) { + std::visit([¶meter_list](auto&& argument) { + for(auto parameter : argument.parameters()) { + parameter_list.push_back(parameter); + } + + }, layer); + } + + return parameter_list; + } + void set_optimizer(std::shared_ptr optimizer) { for (auto& layer : layers_) { - std::cout << "visited" << std::endl; std::visit([optimizer](auto&& argument) { argument.set_optimizer(optimizer); }, layer); } } diff --git a/include/CaberNet/optimizers.h b/include/CaberNet/optimizers.h index 1d280bf..cc61973 100644 --- a/include/CaberNet/optimizers.h +++ b/include/CaberNet/optimizers.h @@ -12,6 +12,7 @@ namespace net::base { struct Optimizer { virtual ~Optimizer() = default; virtual void add_parameter(internal::Tensor* parameter) = 0; + virtual void add_parameter(const std::vector& parameters) = 0; virtual void step() = 0; }; @@ -24,6 +25,10 @@ class Optimize : public Optimizer { parameters_.push_back(parameter); } + void add_parameter(const std::vector& parameters) override final { + parameters_.insert(parameters_.end(), parameters.begin(), parameters.end()); + } + void step() override final { for(internal::Tensor* parameter : parameters_) { static_cast(this)->update(parameter);