mirror of https://github.com/Relintai/pmlpp.git
115 lines
2.6 KiB
C++
115 lines
2.6 KiB
C++
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#ifndef MLPP_OUTPUT_LAYER_H
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#define MLPP_OUTPUT_LAYER_H
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//
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// OutputLayer.hpp
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//
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// Created by Marc Melikyan on 11/4/20.
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//
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#include "core/math/math_defs.h"
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#include "core/string/ustring.h"
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#include "core/object/reference.h"
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#include "../activation/activation.h"
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#include "../cost/cost.h"
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#include "../regularization/reg.h"
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#include "../utilities/utilities.h"
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#include "../lin_alg/mlpp_matrix.h"
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#include "../lin_alg/mlpp_vector.h"
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class MLPPOutputLayer : public Reference {
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GDCLASS(MLPPOutputLayer, Reference);
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public:
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int get_n_hidden();
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void set_n_hidden(const int val);
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MLPPActivation::ActivationFunction get_activation();
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void set_activation(const MLPPActivation::ActivationFunction val);
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MLPPCost::CostTypes get_cost();
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void set_cost(const MLPPCost::CostTypes val);
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Ref<MLPPMatrix> get_input();
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void set_input(const Ref<MLPPMatrix> &val);
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Ref<MLPPVector> get_weights();
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void set_weights(const Ref<MLPPVector> &val);
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real_t get_bias();
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void set_bias(const real_t val);
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Ref<MLPPVector> get_z();
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void set_z(const Ref<MLPPVector> &val);
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Ref<MLPPVector> get_a();
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void set_a(const Ref<MLPPVector> &val);
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Ref<MLPPVector> get_z_test();
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void set_z_test(const Ref<MLPPVector> &val);
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Ref<MLPPVector> get_a_test();
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void set_a_test(const Ref<MLPPVector> &val);
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Ref<MLPPVector> get_delta();
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void set_delta(const Ref<MLPPVector> &val);
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MLPPReg::RegularizationType get_reg();
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void set_reg(const MLPPReg::RegularizationType val);
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real_t get_lambda();
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void set_lambda(const real_t val);
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real_t get_alpha();
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void set_alpha(const real_t val);
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MLPPUtilities::WeightDistributionType get_weight_init();
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void set_weight_init(const MLPPUtilities::WeightDistributionType val);
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bool is_initialized();
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void initialize();
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void forward_pass();
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void test(const Ref<MLPPVector> &x);
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MLPPOutputLayer(int p_n_hidden, MLPPActivation::ActivationFunction p_activation, Ref<MLPPMatrix> p_input, MLPPUtilities::WeightDistributionType p_weight_init, MLPPReg::RegularizationType p_reg, real_t p_lambda, real_t p_alpha);
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MLPPOutputLayer();
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~MLPPOutputLayer();
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protected:
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static void _bind_methods();
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int _n_hidden;
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MLPPActivation::ActivationFunction _activation;
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MLPPCost::CostTypes _cost;
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Ref<MLPPMatrix> _input;
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Ref<MLPPVector> _weights;
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real_t _bias;
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Ref<MLPPVector> _z;
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Ref<MLPPVector> _a;
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Ref<MLPPVector> _z_test;
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Ref<MLPPVector> _a_test;
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Ref<MLPPVector> _delta;
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// Regularization Params
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MLPPReg::RegularizationType _reg;
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real_t _lambda; /* Regularization Parameter */
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real_t _alpha; /* This is the controlling param for Elastic Net*/
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MLPPUtilities::WeightDistributionType _weight_init;
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bool _initialized;
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};
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#endif /* OutputLayer_hpp */
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