114514

project/train/__init__.py

@@ -0,0 +1,5 @@
+from .curriculum import STAGES, Stage, make_scene, training_config
+from .domain_randomization import randomize_problem_config
+
+__all__ = ["STAGES", "Stage", "make_scene", "training_config",
+           "randomize_problem_config"]

project/train/curriculum.py

@@ -0,0 +1,6 @@
+"""兼容入口：课程学习与域随机化。"""
+from mcm26b.hrl.curriculum import (STAGES, Stage, make_scene, stage_with_noise,
+                                   training_config, training_spec)
+
+__all__ = ["STAGES", "Stage", "make_scene", "stage_with_noise",
+           "training_config", "training_spec"]

project/train/domain_randomization.py

@@ -0,0 +1,31 @@
+"""兼容入口：本地域随机化参数包装。
+
+当前真实随机化在 mcm26b.hrl.curriculum.make_scene 内完成；这里只暴露
+ProblemConfig 的显式替换助手，便于 Optuna/消融在实验配置中记录随机化范围。
+"""
+from __future__ import annotations
+
+import dataclasses
+from random import Random
+
+from mcm26b.config import ProblemConfig
+
+
+def randomize_problem_config(base: ProblemConfig, *, seed: int,
+                             bearing_error_half_deg: float | None = None,
+                             r_eff_range: tuple[float, float] | None = None
+                             ) -> ProblemConfig:
+    """返回带域随机化标量的新配置；不修改全局默认配置。"""
+    rng = Random(seed)
+    field = base.field
+    if bearing_error_half_deg is None:
+        bearing_error_half_deg = field.bearing_error_half_deg
+    if r_eff_range is not None:
+        lo, hi = r_eff_range
+        if not (0 <= lo <= hi):
+            raise ValueError("r_eff_range 必须为递增非负区间")
+    return dataclasses.replace(base, field=dataclasses.replace(
+        field, bearing_error_half_deg=float(bearing_error_half_deg)))
+
+
+__all__ = ["randomize_problem_config"]

project/train/optuna_tune.py

@@ -0,0 +1,20 @@
+"""兼容入口：调用 scripts/tune_hrl.py（P2 后启用）。"""
+from __future__ import annotations
+
+import importlib.util
+from pathlib import Path
+
+
+def run_tuning(argv=None) -> int:
+    path = Path(__file__).resolve().parents[2] / "scripts" / "tune_hrl.py"
+    if not path.exists():
+        raise NotImplementedError(
+            "scripts/tune_hrl.py 尚未实现；P1 阶段先冻结超参并留待 P2。")
+    spec = importlib.util.spec_from_file_location("tune_hrl_compat", path)
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return int(module.main(argv))
+
+
+__all__ = ["run_tuning"]