"""classroom_persistence.py — Guardado de checkpoints, sesiones y grabaciones.""" from __future__ import annotations import json import time from dataclasses import asdict from pathlib import Path from typing import TYPE_CHECKING import torch if TYPE_CHECKING: from classroom_curriculum import ClassroomConfig from classroom_memory import LessonResult def save_checkpoint( model: torch.nn.Module, optimizer: torch.optim.Optimizer, config: "ClassroomConfig", lesson_count: int, current_level: int, total_correct: int, ) -> str: """Guarda checkpoint del modelo. Returns: Ruta del checkpoint guardado. """ project_root = Path(__file__).parent.parent ckpt_path = project_root / config.checkpoint_out torch.save( { "modelo": model.state_dict(), "optimizer": optimizer.state_dict(), "paso_global": lesson_count, "config": asdict(config), "curriculum_level": current_level, "accuracy": total_correct / max(1, lesson_count), }, str(ckpt_path), ) return str(ckpt_path) def save_session(session_log: list["LessonResult"]) -> str: """Guarda la sesión completa como JSONL. Returns: Ruta del archivo guardado. """ project_root = Path(__file__).parent.parent ts = time.strftime("%Y%m%d_%H%M%S") session_path = project_root / f"sessions/classroom_{ts}.jsonl" session_path.parent.mkdir(parents=True, exist_ok=True) with open(session_path, "w", encoding="utf-8") as f: for r in session_log: f.write(json.dumps(asdict(r), ensure_ascii=False) + "\n") return str(session_path) def save_recording( events: list[dict], recording_start: float, config: "ClassroomConfig", lesson_count: int, total_correct: int, current_level: int, ) -> str: """Guarda la grabación completa de eventos como HTML reproducible. Returns: Ruta del archivo HTML o cadena vacía si no hay eventos. """ if not events: return "" project_root = Path(__file__).parent.parent ts = time.strftime("%Y%m%d_%H%M%S") recording_dir = project_root / "sessions" recording_dir.mkdir(parents=True, exist_ok=True) meta = { "model": "PamparV3 (108M)", "teacher_backend": config.teacher_backend, "teacher_model": config.teacher_model, "start_time": time.strftime( "%Y-%m-%d %H:%M:%S", time.localtime(recording_start), ), "duration_s": round(time.time() - recording_start, 1) if recording_start else 0, "total_lessons": lesson_count, "accuracy": round(total_correct / max(1, lesson_count), 4), "final_level": current_level, "ewc_lambda": config.ewc_lambda, "lr_base": config.lr_base, } replay_template = Path(__file__).parent / "classroom_replay.html" if replay_template.exists(): template = replay_template.read_text(encoding="utf-8") else: template = "

No replay template found

" recording_data = json.dumps( {"meta": meta, "events": events}, ensure_ascii=False, ) html = template.replace( "/*__RECORDING_DATA__*/", f"window.__RECORDING__ = {recording_data};", ) out_path = recording_dir / f"classroom_{ts}.html" out_path.write_text(html, encoding="utf-8") return str(out_path)