refactoring training spc setup and benchmarking

engine/telemetry/metrics.py

@@ -0,0 +1,57 @@
+from __future__ import annotations
+
+from typing import Any, Mapping
+
+from ..spec import TrainSpec
+
+
+_ALIASES = {
+    "train/reward": "train/reward_mean",
+    "train/revenue": "train/revenue_mean",
+    "train/dqn_loss": "train/loss",
+    "eval/reward": "eval/reward_mean",
+    "eval/revenue": "eval/revenue_mean",
+    "train/steps_per_second": "runtime/steps_per_second",
+}
+
+
+def _as_float(value: Any, default: float | None = None) -> float | None:
+    if value is None:
+        return default
+    try:
+        return float(value)
+    except (TypeError, ValueError):
+        return default
+
+
+def canonicalize_metrics(raw: Mapping[str, Any], spec: TrainSpec) -> dict[str, Any]:
+    metrics: dict[str, Any] = {}
+    for key, value in raw.items():
+        canonical = _ALIASES.get(str(key), str(key))
+        if canonical in metrics and canonical != key:
+            continue
+        metrics[canonical] = value
+
+    metrics.setdefault("train/global_step", spec.runtime.total_timesteps)
+
+    eval_reward = _as_float(metrics.get("eval/reward_mean"), 0.0) or 0.0
+    eval_revenue = _as_float(metrics.get("eval/revenue_mean"), 0.0) or 0.0
+    metrics["objective/score"] = eval_reward + spec.study.revenue_weight * eval_revenue
+
+    margin_mean = _as_float(metrics.get("eval/margin_mean"), None)
+    if margin_mean is not None:
+        metrics["objective/constraint_margin"] = margin_mean - spec.env.margin_floor
+
+    coi_level = _as_float(metrics.get("eval/coi_level_mean"), None)
+    metrics["objective/coi_preserved"] = 0.0 if coi_level is None else coi_level
+
+    metrics["study/alpha"] = spec.study.alpha
+    metrics["study/lambda_coi"] = spec.study.lambda_coi
+    metrics["study/robust_radius"] = spec.study.robust_radius
+    metrics["study/info_value"] = spec.study.info_value
+
+    metrics["runtime/backend"] = spec.runtime.backend
+    metrics["runtime/device"] = spec.runtime.device
+    metrics["runtime/seed"] = spec.runtime.seed
+
+    return metrics