140 lines
3.3 KiB
C++
140 lines
3.3 KiB
C++
#pragma once
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/**
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* @file fitness.hpp
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* @brief Fitness evaluation — loss signal processing and multi-objective evaluation.
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*
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* Port of: packages/fces/core/fitness_engine.py + fitness.py
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*/
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#include <cmath>
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#include <vector>
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#include <string>
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namespace fces {
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/**
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* Running statistics tracker (Welford's algorithm).
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* Thread-safe, O(1) memory, numerically stable.
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*/
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class RunningStats {
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public:
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void update(float value);
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float z_score(float value) const;
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float get_mean() const { return mean_; }
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float get_std() const;
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int get_count() const { return count_; }
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void reset();
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private:
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int count_ = 0;
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float mean_ = 0.0f;
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float m2_ = 0.0f;
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};
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/**
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* FitnessEngine — processes raw loss values into controller fitness signals.
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*/
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class FitnessEngine {
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public:
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explicit FitnessEngine(float grokking_coefficient = 0.1f);
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/**
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* Calculate loss velocity signal.
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*
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* @param current_loss Current step loss
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* @param ema_loss Exponential moving average loss
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* @param mode "relative" or "absolute"
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* @return Velocity signal (negative = improving)
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*/
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float calculate_loss_signal(float current_loss, float ema_loss, const std::string& mode = "relative") const;
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/**
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* Compute Kibble-Zurek Mechanism damping factor.
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* Prevents topological defects during phase transitions.
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*/
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float compute_kzm_damping(float spectral_alpha) const;
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private:
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float grokking_coefficient_;
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};
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/**
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* FuzzySet represents a fuzzy set with a trapezoidal membership function.
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*/
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class FuzzySet {
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public:
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FuzzySet(std::string name, float a, float b, float c, float d) noexcept
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: name_(std::move(name)), a_(a), b_(b), c_(c), d_(d) {}
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float membership(float x) const noexcept {
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if (!std::isfinite(x)) {
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return 0.0f;
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}
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if (x <= a_ || x >= d_) {
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return 0.0f;
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}
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if (x >= b_ && x <= c_) {
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return 1.0f;
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}
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if (x > a_ && x < b_) {
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float range = b_ - a_;
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return (x - a_) / (range > 0.0f ? range : 1e-9f);
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}
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if (x > c_ && x < d_) {
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float range = d_ - c_;
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return (d_ - x) / (range > 0.0f ? range : 1e-9f);
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}
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return 0.0f;
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}
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const std::string& name() const noexcept { return name_; }
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private:
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std::string name_;
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float a_;
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float b_;
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float c_;
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float d_;
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};
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/**
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* Fitness metrics for multi-objective evaluation.
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*/
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struct FitnessMetrics {
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float training_advantage = 0.0f;
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float validation_advantage = 0.0f;
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float grad_cv = 0.0f;
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float sparsity_delta = 0.0f;
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float consistency_gap = 0.0f;
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float stable_rank = 0.0f;
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};
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/**
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* FuzzyFitnessEvaluator — multi-objective fitness evaluation with fuzzy weighting.
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*/
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class FuzzyFitnessEvaluator {
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public:
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FuzzyFitnessEvaluator() noexcept;
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float evaluate(const FitnessMetrics& metrics) const noexcept;
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private:
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FuzzySet stability_set_;
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FuzzySet train_set_;
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FuzzySet val_set_;
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FuzzySet sparsity_set_;
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FuzzySet consistency_set_;
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FuzzySet rank_set_;
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float w_stability_ = 0.2f;
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float w_train_ = 0.2f;
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float w_val_ = 0.3f;
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float w_sparsity_ = 0.1f;
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float w_consistency_ = 0.2f;
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float w_rank_ = 0.1f;
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};
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} // namespace fces
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