#ifndef MLPP_HIDDEN_LAYER_H #define MLPP_HIDDEN_LAYER_H // // HiddenLayer.hpp // // Created by Marc Melikyan on 11/4/20. // #include "core/containers/hash_map.h" #include "core/math/math_defs.h" #include "core/string/ustring.h" #include "core/object/reference.h" #include "../activation/activation.h" #include "../utilities/utilities.h" #include "../lin_alg/mlpp_matrix.h" #include "../lin_alg/mlpp_vector.h" #include #include #include class MLPPHiddenLayer : public Reference { GDCLASS(MLPPHiddenLayer, Reference); public: int n_hidden; MLPPActivation::ActivationFunction activation; Ref input; Ref weights; Ref bias; Ref z; Ref a; Ref z_test; Ref a_test; Ref delta; // Regularization Params String reg; real_t lambda; /* Regularization Parameter */ real_t alpha; /* This is the controlling param for Elastic Net*/ MLPPUtilities::WeightDistributionType weight_init; void forward_pass(); void test(const Ref &x); MLPPHiddenLayer(int p_n_hidden, MLPPActivation::ActivationFunction p_activation, Ref p_input, MLPPUtilities::WeightDistributionType p_weight_init, String p_reg, real_t p_lambda, real_t p_alpha); MLPPHiddenLayer(); ~MLPPHiddenLayer(); }; class MLPPOldHiddenLayer { public: MLPPOldHiddenLayer(int n_hidden, std::string activation, std::vector> input, std::string weightInit, std::string reg, real_t lambda, real_t alpha); int n_hidden; std::string activation; std::vector> input; std::vector> weights; std::vector bias; std::vector> z; std::vector> a; std::map> (MLPPActivation::*)(std::vector>, bool)> activation_map; std::map (MLPPActivation::*)(std::vector, bool)> activationTest_map; std::vector z_test; std::vector a_test; std::vector> delta; // Regularization Params std::string reg; real_t lambda; /* Regularization Parameter */ real_t alpha; /* This is the controlling param for Elastic Net*/ std::string weightInit; void forwardPass(); void Test(std::vector x); }; #endif /* HiddenLayer_hpp */