FlexNN.h

Go to the documentation of this file.

 
#ifndef FlexNN_H
#define FlexNN_H
 
#include <vector>
#include <Eigen/Dense>
 
// New modular headers — must come before legacy Layer.h so `Layers::Layer`
// is visible for the converting constructor.
#include "activations/Activation.hpp"
#include "layers/Layer.hpp"
 
// Legacy monolithic Layer (string activation, Dense-only) — kept for
// backward compat until PR-09 migrates `src/main.cpp` to the new API.
// New code should use `FlexNN::Layers::Dense` + `FlexNN::Activations::Activation`.
#include "Layer.h"
 
namespace FlexNN {
 
class NeuralNetwork {
 public:
  NeuralNetwork(const std::vector<Layers::Layer>& layers) : layers_(layers) {}
  NeuralNetwork(std::vector<Layers::Layer>&& layers) : layers_(std::move(layers)) {}
 
  [[deprecated("use vector<FlexNN::Layers::Layer> with FlexNN::Activations")]]
  NeuralNetwork(const std::vector<Layer>& oldLayers);
 
  void train(const Eigen::MatrixXd& input, const Eigen::VectorXd& target,
             double learningRate, int epochs);
 
  double accuracy(const Eigen::MatrixXd& X, const Eigen::VectorXd& Y);
 
  Eigen::MatrixXd predict(const Eigen::MatrixXd& input) {
    auto outputs = forward(input);
    return outputs.back();
  }
 
  const std::vector<Layers::Layer>& layers() const noexcept { return layers_; }
  std::vector<Layers::Layer>& layers() noexcept { return layers_; }
 
 private:
  // Heterogeneous stack — currently variant<Dense> only, expands in later PRs.
  std::vector<Layers::Layer> layers_;
 
  std::vector<Eigen::MatrixXd> forward(const Eigen::MatrixXd& input);
 
  std::vector<Eigen::MatrixXd> backward(
      const std::vector<Eigen::MatrixXd>& outputs,
      const Eigen::MatrixXd& target);
 
  void updateWeights(const std::vector<Eigen::MatrixXd>& gradients,
                     double learningRate);
};
 
} // namespace FlexNN
 
#endif // FlexNN_H