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147 lines
3.6 KiB
C++
147 lines
3.6 KiB
C++
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#ifndef MLPP_HIDDEN_LAYER_H
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#define MLPP_HIDDEN_LAYER_H
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//
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// HiddenLayer.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 "../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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#include <map>
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#include <string>
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#include <vector>
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class MLPPHiddenLayer : public Reference {
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GDCLASS(MLPPHiddenLayer, Reference);
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public:
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int get_n_hidden() const;
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void set_n_hidden(const int val);
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MLPPActivation::ActivationFunction get_activation() const;
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void set_activation(const MLPPActivation::ActivationFunction 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<MLPPMatrix> get_weights();
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void set_weights(const Ref<MLPPMatrix> &val);
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Ref<MLPPVector> get_bias();
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void set_bias(const Ref<MLPPVector> &val);
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Ref<MLPPMatrix> get_z();
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void set_z(const Ref<MLPPMatrix> &val);
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Ref<MLPPMatrix> get_a();
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void set_a(const Ref<MLPPMatrix> &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<MLPPMatrix> get_delta();
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void set_delta(const Ref<MLPPMatrix> &val);
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MLPPReg::RegularizationType get_reg() const;
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void set_reg(const MLPPReg::RegularizationType val);
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real_t get_lambda() const;
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void set_lambda(const real_t val);
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real_t get_alpha() const;
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void set_alpha(const real_t val);
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MLPPUtilities::WeightDistributionType get_weight_init() const;
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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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MLPPHiddenLayer(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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MLPPHiddenLayer();
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~MLPPHiddenLayer();
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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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Ref<MLPPMatrix> input;
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Ref<MLPPMatrix> weights;
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Ref<MLPPVector> bias;
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Ref<MLPPMatrix> z;
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Ref<MLPPMatrix> a;
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Ref<MLPPVector> z_test;
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Ref<MLPPVector> a_test;
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Ref<MLPPMatrix> 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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class MLPPOldHiddenLayer {
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public:
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MLPPOldHiddenLayer(int n_hidden, std::string activation, std::vector<std::vector<real_t>> input, std::string weightInit, std::string reg, real_t lambda, real_t alpha);
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int n_hidden;
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std::string activation;
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std::vector<std::vector<real_t>> input;
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std::vector<std::vector<real_t>> weights;
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std::vector<real_t> bias;
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std::vector<std::vector<real_t>> z;
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std::vector<std::vector<real_t>> a;
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std::map<std::string, std::vector<std::vector<real_t>> (MLPPActivation::*)(std::vector<std::vector<real_t>>, bool)> activation_map;
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std::map<std::string, std::vector<real_t> (MLPPActivation::*)(std::vector<real_t>, bool)> activationTest_map;
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std::vector<real_t> z_test;
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std::vector<real_t> a_test;
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std::vector<std::vector<real_t>> delta;
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// Regularization Params
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std::string 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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std::string weightInit;
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void forwardPass();
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void Test(std::vector<real_t> x);
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};
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#endif /* HiddenLayer_hpp */ |