style: run clang-format and configure pre-commit hooks

include/fces/optimizer.hpp

@@ -5,17 +5,17 @@
  * @brief FCESOptimizer — the main entry point. libtorch-compatible optimizer.
  */
 
-#include <torch/torch.h>
 #include <memory>
-#include <vector>
 #include <string>
+#include <torch/torch.h>
+#include <vector>
 
 #include "config.hpp"
-#include "population.hpp"
-#include "fitness.hpp"
 #include "evolution.hpp"
-#include "spectral.hpp"
+#include "fitness.hpp"
 #include "oscillation.hpp"
+#include "population.hpp"
+#include "spectral.hpp"
 #include "telemetry.hpp"
 
 namespace fces {
@@ -24,7 +24,8 @@ namespace fces {
  * FCESOptimizer — Fuzzy Controlled Evolutionary Search V49.0 (C++ Port).
  *
  * Usage:
- *   auto optimizer = FCESOptimizer(model->parameters(), FCESConfig{}.set_lr(1.6e-3));
+ *   auto optimizer = FCESOptimizer(model->parameters(),
+ * FCESConfig{}.set_lr(1.6e-3));
  *   // In training loop:
  *   optimizer.zero_grad();
  *   auto loss = model->forward(input);
@@ -32,73 +33,72 @@ namespace fces {
  *   optimizer.step();
  *   optimizer.update_fitness(loss.item<float>());
  */
-struct FCESOptimizerOptions : public torch::optim::OptimizerCloneableOptions<FCESOptimizerOptions> {
-    explicit FCESOptimizerOptions(double lr = 0.01) : lr_(lr) {}
+struct FCESOptimizerOptions
+    : public torch::optim::OptimizerCloneableOptions<FCESOptimizerOptions> {
+  explicit FCESOptimizerOptions(double lr = 0.01) : lr_(lr) {}
 
-    double get_lr() const override { return lr_; }
-    void set_lr(const double lr) override { lr_ = lr; }
+  double get_lr() const override { return lr_; }
+  void set_lr(const double lr) override { lr_ = lr; }
 
-    double lr_;
+  double lr_;
 };
 
 class FCESOptimizer : public torch::optim::Optimizer {
 public:
-    explicit FCESOptimizer(
-        std::vector<torch::Tensor> params,
-        FCESConfig config = FCESConfig{}
-    );
+  explicit FCESOptimizer(std::vector<torch::Tensor> params,
+                         FCESConfig config = FCESConfig{});
 
-    /// Perform a single optimization step
-    torch::Tensor step(LossClosure closure = nullptr) override;
+  /// Perform a single optimization step
+  torch::Tensor step(LossClosure closure = nullptr) override;
 
-    /// Update evolutionary fitness with current loss
-    void update_fitness(float loss);
+  /// Update evolutionary fitness with current loss
+  void update_fitness(float loss);
 
-    /// Backup model weights to CPU RAM
-    void backup_to_ram();
+  /// Backup model weights to CPU RAM
+  void backup_to_ram();
 
-    /// Restore model weights from CPU RAM backup
-    void restore_from_ram();
+  /// Restore model weights from CPU RAM backup
+  void restore_from_ram();
 
-    /// Get current step count
-    int step_count() const { return step_counter_; }
+  /// Get current step count
+  int step_count() const { return step_counter_; }
 
-    /// Calculate model sparsity
-    float calculate_sparsity() const;
+  /// Calculate model sparsity
+  float calculate_sparsity() const;
 
 private:
-    FCESConfig config_;
-    Population population_;
-    FitnessEngine fitness_engine_;
-    FuzzyFitnessEvaluator fitness_evaluator_;
-    std::unique_ptr<EvolutionManager> evolution_manager_;
-    OscillationDetector oscillation_detector_;
-    RunningStats grad_norm_tracker_;
+  FCESConfig config_;
+  Population population_;
+  FitnessEngine fitness_engine_;
+  FuzzyFitnessEvaluator fitness_evaluator_;
+  std::unique_ptr<EvolutionManager> evolution_manager_;
+  OscillationDetector oscillation_detector_;
+  RunningStats grad_norm_tracker_;
 
-    // State
-    int step_counter_ = 0;
-    float ema_loss_ = 0.0f;
-    float last_step_loss_ = 0.0f;
-    float best_loss_window_ = std::numeric_limits<float>::infinity();
-    float rollback_ema_ = 0.0f;
-    int stagnation_counter_ = 0;
-    float last_loss_velocity_ = 0.0f;
-    float last_sparsity_ = 0.0f;
+  // State
+  int step_counter_ = 0;
+  float ema_loss_ = 0.0f;
+  float last_step_loss_ = 0.0f;
+  float best_loss_window_ = std::numeric_limits<float>::infinity();
+  float rollback_ema_ = 0.0f;
+  int stagnation_counter_ = 0;
+  float last_loss_velocity_ = 0.0f;
+  float last_sparsity_ = 0.0f;
 
-    // RAM backup
-    std::vector<torch::Tensor> ram_backup_;
+  // RAM backup
+  std::vector<torch::Tensor> ram_backup_;
 
-    // Layer stats and group mappings
-    std::vector<std::vector<float>> layer_stats_;
-    std::vector<int> param_group_mapping_;
-    std::unique_ptr<SpectralSensor> spectral_sensor_;
-    SpectralController spectral_controller_;
-    float last_spectral_rank_ = 0.0f;
+  // Layer stats and group mappings
+  std::vector<std::vector<float>> layer_stats_;
+  std::vector<int> param_group_mapping_;
+  std::unique_ptr<SpectralSensor> spectral_sensor_;
+  SpectralController spectral_controller_;
+  float last_spectral_rank_ = 0.0f;
 
-    // Internal methods
-    void gather_stats();
-    void apply_parameter_updates(const torch::Tensor& actions);
-    void handle_rollback();
+  // Internal methods
+  void gather_stats();
+  void apply_parameter_updates(const torch::Tensor &actions);
+  void handle_rollback();
 };
 
-}  // namespace fces
+} // namespace fces