Download common/source/starBenchserver/benchkit/reports/progress.py from JackAILab/assests: direct link, hf CLI and curl.
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https://huggingface.co/datasets/JackAILab/assests/resolve/main/common/source/starBenchserver/benchkit/reports/progress.py
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hf download hf://datasets/JackAILab/assests/common/source/starBenchserver/benchkit/reports/progress.py
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curl -L -o progress.py https://huggingface.co/datasets/JackAILab/assests/resolve/main/common/source/starBenchserver/benchkit/reports/progress.py
4.36 kB
| #!/usr/bin/env python3 | |
| """Record time-to-success from closed event logs, without querying a simulator.""" | |
| from __future__ import annotations | |
| import argparse | |
| import json | |
| from pathlib import Path | |
| NATIVE_SUCCESS_FIELDS = { | |
| "simpler_env": "success", "libero": "native_success", | |
| "robocasa365": "native_success", "simple_humanoid": "native_success", | |
| "robocasa_tabletop": "native_success", "robodojo": "native_success", | |
| } | |
| def summarize_progress(run: Path) -> dict: | |
| run = run.resolve(strict=True) | |
| lifecycle = json.loads((run / "status.json").read_text()) | |
| if lifecycle.get("status") not in ("completed", "completed_with_errors"): | |
| raise ValueError("progress analysis requires a closed run") | |
| manifest = json.loads((run / "manifest.json").read_text()) | |
| field = NATIVE_SUCCESS_FIELDS.get(manifest["benchmark"]["name"]) | |
| rows = [] | |
| for result_path in sorted((run / "episodes").glob("*/result.json")): | |
| if not result_path.resolve().is_relative_to(run): | |
| raise ValueError("episode result must remain inside the run") | |
| result = json.loads(result_path.read_text()) | |
| events_path = result_path.parent / "events.jsonl" | |
| if not events_path.resolve().is_relative_to(run): | |
| raise ValueError("episode events must remain inside the run") | |
| events = [json.loads(line) for line in events_path.read_text().splitlines() if line] | |
| steps = [event for event in events if event.get("event") == "environment_step"] | |
| scored = [event for event in steps if type(event.get("info", {}).get(field)) is bool] if field else [] | |
| coverage = ( | |
| bool(field) and len(scored) == result["environment_steps"] | |
| and [event["environment_step"] for event in scored] == list(range(1, result["environment_steps"] + 1)) | |
| ) | |
| successful = [event for event in scored if event["info"][field]] | |
| first = successful[0] if successful else None | |
| trailing = 0 | |
| for event in reversed(scored): | |
| if not event["info"][field]: | |
| break | |
| trailing += 1 | |
| rows.append({ | |
| "episode": result["episode"], "status": result["status"], | |
| "native_success_field": field, "complete_step_coverage": coverage, | |
| "first_native_success_step": first["environment_step"] if first and coverage else None, | |
| "policy_call_at_first_native_success": first["policy_call"] if first and coverage else None, | |
| "first_native_success_timestamp": first["timestamp"] if first and coverage else None, | |
| "first_logged_success_step": first["environment_step"] if first else None, | |
| "last_native_success_step": successful[-1]["environment_step"] if successful else None, | |
| "successful_logged_steps": len(successful), | |
| "consecutive_success_steps_at_end": trailing if coverage else None, | |
| "final_environment_steps": result["environment_steps"], | |
| "final_policy_calls": result["policy_calls"], "final_success": result["success"], | |
| "termination_reason": result["termination_reason"], "error": result["error"], | |
| "source_events": str(events_path), | |
| }) | |
| if len(rows) != lifecycle.get("episodes_written"): | |
| raise ValueError("closed status and available episode records disagree") | |
| return { | |
| "schema_version": "starvla-rsi.closed-run-progress/v1", | |
| "source_run": str(run), "benchmark": manifest["benchmark"], "protocol": manifest["protocol"], | |
| "method": "existing native step info only; no simulator or extra scorer call", | |
| "interpretation": "First success is diagnostic and does not replace final native scoring. Null is not an estimated step.", | |
| "episodes": rows, | |
| } | |
| def main() -> None: | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("--run-dir", type=Path, required=True) | |
| parser.add_argument("--output", type=Path, required=True, help="new derived report; never overwrite source results") | |
| args = parser.parse_args() | |
| report = summarize_progress(args.run_dir) | |
| args.output.parent.mkdir(parents=True, exist_ok=True) | |
| with args.output.open("x") as handle: | |
| json.dump(report, handle, indent=2, sort_keys=True) | |
| handle.write("\n") | |
| print(args.output) | |
| if __name__ == "__main__": | |
| main() | |