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94 lines
1.9 KiB
C++
94 lines
1.9 KiB
C++
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#ifndef MLPP_AUTO_ENCODER_H
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#define MLPP_AUTO_ENCODER_H
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//
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// AutoEncoder.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/object/reference.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 "../regularization/reg.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 MLPPAutoEncoder : public Reference {
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GDCLASS(MLPPAutoEncoder, Reference);
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public:
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Ref<MLPPMatrix> get_input_set();
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void set_input_set(const Ref<MLPPMatrix> &val);
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int get_n_hidden();
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void set_n_hidden(const int val);
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Ref<MLPPMatrix> model_set_test(const Ref<MLPPMatrix> &X);
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Ref<MLPPVector> model_test(const Ref<MLPPVector> &x);
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void gradient_descent(real_t learning_rate, int max_epoch, bool ui = false);
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void sgd(real_t learning_rate, int max_epoch, bool ui = false);
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void mbgd(real_t learning_rate, int max_epoch, int mini_batch_size, bool ui = false);
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real_t score();
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void save(const String &file_name);
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MLPPAutoEncoder(const Ref<MLPPMatrix> &p_input_set, int p_n_hidden);
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MLPPAutoEncoder();
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~MLPPAutoEncoder();
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protected:
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real_t cost(const Ref<MLPPMatrix> &y_hat, const Ref<MLPPMatrix> &y);
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Ref<MLPPVector> evaluatev(const Ref<MLPPVector> &x);
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struct PropagateVResult {
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Ref<MLPPVector> z2;
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Ref<MLPPVector> a2;
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};
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PropagateVResult propagatev(const Ref<MLPPVector> &x);
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Ref<MLPPMatrix> evaluatem(const Ref<MLPPMatrix> &X);
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struct PropagateMResult {
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Ref<MLPPMatrix> z2;
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Ref<MLPPMatrix> a2;
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};
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PropagateMResult propagatem(const Ref<MLPPMatrix> &X);
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void forward_pass();
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static void _bind_methods();
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Ref<MLPPMatrix> _input_set;
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Ref<MLPPMatrix> _y_hat;
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Ref<MLPPMatrix> _weights1;
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Ref<MLPPMatrix> _weights2;
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Ref<MLPPVector> _bias1;
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Ref<MLPPVector> _bias2;
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Ref<MLPPMatrix> _z2;
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Ref<MLPPMatrix> _a2;
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int _n;
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int _k;
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int _n_hidden;
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bool _initialized;
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};
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#endif /* AutoEncoder_hpp */
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