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Surface eval cost in iteration summary

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Append eval_seconds and its share of iteration_seconds to the per-iteration
console summary when evaluation actually ran, so users watching the log can
see how much wall time eval is consuming without parsing JSON metrics.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
coolguy
2026-05-07 16:44:19 +09:00
co-authored by Claude Opus 4.7
parent bac630b50b
commit abfd7298d9
1 changed files with 5 additions and 0 deletions
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src/coolrl_lost_cities/games/classic/deep_cfr/trainer.py
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@@ -139,6 +139,11 @@ def _format_iteration_summary(metrics: IterationMetrics, data: dict[str, float |
f"strategy_loss={_format_summary_value(metrics.strategy_loss)}", f"strategy_loss={_format_summary_value(metrics.strategy_loss)}",
f"iteration_seconds={_format_summary_value(data['iteration_seconds'])}", f"iteration_seconds={_format_summary_value(data['iteration_seconds'])}",
] ]
if metrics.eval_metrics:
eval_seconds = float(data.get("evaluation_seconds", 0.0) or 0.0)
iter_seconds = float(data.get("iteration_seconds", 0.0) or 0.0)
fraction = eval_seconds / iter_seconds if iter_seconds > 0.0 else 0.0
parts.append(f"eval_seconds={_format_summary_value(eval_seconds)}({fraction * 100:.0f}%)")
for key in sorted(metrics.eval_metrics): for key in sorted(metrics.eval_metrics):
if key.endswith("_win_rate0") or key.endswith("_avg_score_diff0"): if key.endswith("_win_rate0") or key.endswith("_avg_score_diff0"):
parts.append(f"{key}={_format_summary_value(metrics.eval_metrics[key])}") parts.append(f"{key}={_format_summary_value(metrics.eval_metrics[key])}")