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"active_imu": "back", "use_camera": false, "controller_type": "mpc", "baseline": true}, "notes": "A26 MPC stack (iLQR + adaptive steering gain) with the A27 benchmark's Transformer + online states in place of the A26 EKF; learned models trained on the A26 bags without PWM inputs"}, "scenario": {"type": "clip", "clip_id": "20260919_152803_auto_00230"}, "seed": 1780760178, "tier": "dev", "engine_version": "a3faf45adac1134739a528c9637e4a2d3a389c7e8a667a79df3dc9fddf8e5972"}}] \ No newline at end of file diff --git a/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/gautschi/0/gautschi_launch.py b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/gautschi/0/gautschi_launch.py new file mode 100644 index 0000000000000000000000000000000000000000..c957875c7f9c7efb5fba82d6445aaacc7fd7343b --- /dev/null +++ b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/gautschi/0/gautschi_launch.py @@ -0,0 +1,145 @@ +"""Runs on a Gautschi node (stdlib only): episodes from a queue in parallel workers, one contained Apptainer per episode.""" +import argparse +import json +import os +import queue +import shutil +import subprocess +import threading +import time + +RUN = ("source /opt/ros/humble/setup.bash && source /ws/install/setup.bash" + " && python3 -m simnode.batch /batch.json /out") +CUDA_LIB = "/ws/mpc_cuda/libmpc_cuda.so" # built per stack by runner/gautschi.build_stack for gautschi-gpu +SAMPLE_S = 15 +STAGGER_S = 0.25 # between worker starts: the dev job's one error was a stack starved in the 96-way start burst +EPISODE_TIMEOUT_S = 1200 # about 4x the slowest lap; a killed episode has no outcome and is retried by the host + + +def worker_cmd(i, work, out, ep, sif, engine, stack, gpu=None): + """Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker; + gpu (a host CUDA device) adds the driver and the stack's CUDA MPC kernel.""" + cuda = ["--nv", "--env", f"CUDA_VISIBLE_DEVICES={gpu}", "--env", f"MPC_CUDA_LIB={CUDA_LIB}"] if gpu is not None else [] + if gpu is None and os.path.exists(os.path.join(stack, "mpc_cuda", "libmpc_cuda.so")): + cuda = ["--env", f"MPC_CUDA_LIB={CUDA_LIB}"] # CPU node: the library's native iLQR solve still loads; its MPPI falls back to numpy + return ["apptainer", "exec", *cuda, "--contain", "--cleanenv", "--ipc", "--pid", "--net", "--network", "none", "--workdir", work, + "--env", f"ROS_DOMAIN_ID={i + 1}", "--env", "ROS_HOME=/tmp/ros", "--env", "TMPDIR=/tmp", + "--bind", f"{engine}:/opt/sim:ro", "--bind", f"{stack}:/ws:ro", "--bind", f"{out}:/out", + "--bind", f"{ep}:/batch.json:ro", sif, "bash", "-lc", RUN] + + +def parse_smi(text): + """nvidia-smi 'utilization.gpu, memory.used' csv rows to per-GPU lists.""" + rows = [[int(v) for v in ln.split(",")] for ln in text.strip().splitlines() if ln.strip()] + return {"gpu_util": [r[0] for r in rows], "gpu_mem_mib": [r[1] for r in rows]} + + +def _solver(logdir): + """pathfinder's 'MPC solver: ...' and CUDA fallback lines from the episode's ROS logs.""" + lines = [] + for dp, _, fns in os.walk(logdir): + for fn in fns: + try: + with open(os.path.join(dp, fn), errors="replace") as f: + lines += [ln.strip() for ln in f if "MPC solver:" in ln or "CUDA MPC unavailable" in ln] + except OSError: + pass + return "\n".join(dict.fromkeys(lines)) + + +def main(argv=None): + p = argparse.ArgumentParser() + for a in ("episodes", "out", "sif", "engine", "stack", "work", "timeline", "done"): + p.add_argument("--" + a, required=True) + p.add_argument("--workers", type=int, required=True) + p.add_argument("--gpus", type=int, default=0) + a = p.parse_args(argv) + with open(a.episodes) as f: + q = queue.Queue() + for e in json.load(f): # the host already ordered them, longest first + q.put(e) + os.makedirs(a.out, exist_ok=True) + lock, t0 = threading.Lock(), time.time() + devs = [d for d in os.environ.get("CUDA_VISIBLE_DEVICES", "").split(",") if d][:a.gpus] or [str(n) for n in range(a.gpus)] + + def log(**ev): + with lock, open(a.timeline, "a") as f: + f.write(json.dumps(dict(ev, t=round(time.time() - t0, 3))) + "\n") + + def worker(i): + time.sleep(i * STAGGER_S) + while True: + try: + e = q.get_nowait() + except queue.Empty: + return + key, work = e["key"], os.path.join(a.work, e["key"]) + stage, ep = os.path.join(work, "stage"), os.path.join(work, "ep.json") + os.makedirs(stage) + with open(ep, "w") as f: + json.dump([e], f) + log(ev="start", key=key, worker=i) + gpu = devs[i % len(devs)] if devs and e["resolved"].get("recipe", {}).get("sim", {}).get("cuda") else None + limit = EPISODE_TIMEOUT_S * max(1, e["resolved"]["scenario"].get("laps", 1)) # per lap: 5-lap episodes run 5x longer + try: + rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack, gpu), stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, timeout=limit).returncode + except subprocess.TimeoutExpired: + rc = "timeout" + solver = _solver(os.path.join(work, "tmp", "ros", "log")) + if solver and os.path.isdir(os.path.join(stage, key)): + with open(os.path.join(stage, key, "solver.txt"), "w") as f: + f.write(solver + "\n") + if os.path.exists(os.path.join(stage, key, "outcome.json")): + tmp, dst = os.path.join(a.out, ".tmp-" + key), os.path.join(a.out, key) + shutil.rmtree(tmp, ignore_errors=True) + shutil.copytree(os.path.join(stage, key), tmp) + shutil.rmtree(dst, ignore_errors=True) + os.rename(tmp, dst) # the host's rsync sees a key only once its directory is complete + with lock, open(a.done, "a") as f: + f.write(key + "\n") + shutil.rmtree(work, ignore_errors=True) + log(ev="end", key=key, worker=i, rc=rc, gpu=gpu, + solver=solver.split("MPC solver: ")[-1] if "MPC solver: " in solver else solver or None) + + def sampler(stop): + """Job CPU use from its cgroup, as busy cores, every SAMPLE_S.""" + try: + with open("/proc/self/cgroup") as f: + path = "/sys/fs/cgroup" + f.read().strip().split(":")[-1] + "/cpu.stat" + prev = None + while not stop.wait(SAMPLE_S if prev else 0): + with open(path) as f: + use = next(int(ln.split()[1]) for ln in f if ln.startswith("usage_usec")) + now = time.time() + if prev: + log(ev="cpu", busy_cores=round((use - prev[0]) / 1e6 / (now - prev[1]), 2)) + prev = (use, now) + except (OSError, StopIteration, ValueError): + pass + + def gpu_sampler(stop): + """GPU utilisation and memory of the job's GPUs, every SAMPLE_S.""" + while not stop.wait(SAMPLE_S): + try: + p = subprocess.Popen(["nvidia-smi", "--query-gpu=utilization.gpu,memory.used", "--format=csv,noheader,nounits"], + stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True) + log(ev="gpu", **parse_smi(p.communicate(timeout=30)[0])) + except Exception: # no driver or a hung query: skip this sample + pass + + cores = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count() + log(ev="launch", workers=a.workers, cores=cores) + stop = threading.Event() + threads = [threading.Thread(target=worker, args=(i,)) for i in range(a.workers)] + samplers = [sampler] + ([gpu_sampler] if a.gpus else []) + for t in threads + [threading.Thread(target=f, args=(stop,), daemon=True) for f in samplers]: + t.start() + for t in threads: + t.join() + stop.set() + log(ev="done") + + +if __name__ == "__main__": + main() diff --git a/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/gautschi/0/sbatch.sh b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/gautschi/0/sbatch.sh new file mode 100644 index 0000000000000000000000000000000000000000..e47a24ffc6a5ed163905031736c8d96c0fb351f4 --- /dev/null +++ b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/gautschi/0/sbatch.sh @@ -0,0 +1,5 @@ +#!/bin/bash +#SBATCH -p gpu -A scholar -N 1 -n 1 -c 32 --gres=gpu:1 --time 39 -J AutoSim-dev-gpu --comment 20261108-162315-A26_MPC_stack__loc_Transformer___online_states -o AutoSim/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/0/slurm-%j.out +W=/dev/shm/AutoSim-$SLURM_JOB_ID +trap 'rm -rf "$W"' EXIT +python3 $HOME/AutoSim/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/0/gautschi_launch.py --episodes $HOME/AutoSim/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/0/episodes.json --out /scratch/scholar/manors/AutoSim/out/20261108-162315-A26_MPC_stack__loc_Transformer___online_states --sif $HOME/AutoSim/images/AutoSim-99d206f40cb1.sif --engine $HOME/AutoSim/engine/a3faf45adac1134739a528c9637e4a2d3a389c7e8a667a79df3dc9fddf8e5972 --stack $HOME/AutoSim/stacks/7b65e1230c473170aa4b21cba8150318b941c61c36fa4bc0fc621a9a5f899f44 --workers 16 --work $W --timeline $HOME/AutoSim/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/0/timeline.jsonl --done $HOME/AutoSim/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/0/done.txt --gpus 1 diff --git a/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/job.json b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/job.json new file mode 100644 index 0000000000000000000000000000000000000000..242ce39c92fa4831d2cc0fa241591af9ac4f6b0a --- /dev/null +++ b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/job.json @@ -0,0 +1,48 @@ +{ + "id": "20261108-162315-A26_MPC_stack__loc_Transformer___online_states", + "tier": "dev", + "tier_version": 2, + "recipe": { + "name": "A26 MPC stack, loc Transformer + online states", + "source": { + "repo": "AutonomousKart", + "ref": "worktree:loc-variants" + }, + "params": { + "pathfinder_node": { + "planner": "ilqr", + "mpc.adaptive_gain.enabled": true + }, + "localization_node": { + "estimator": "transformer", + "gps_lag_s": 0.06, + "online_states": true + } + }, + "sim": { + "cuda": true, + "active_imu": "back", + "use_camera": false, + "controller_type": "mpc", + "baseline": true + }, + "notes": "A26 MPC stack (iLQR + adaptive steering gain) with the A27 benchmark's Transformer + online states in place of the A26 EKF; learned models trained on the A26 bags without PWM inputs" + }, + "user": "shay", + "notes": "", + "where": "scholar", + "status": "done", + "submitted_at": "2026-11-08T21:23:15.874+00:00", + "started_at": "2026-11-08T21:23:15.876+00:00", + "finished_at": "2026-11-08T21:33:51.315+00:00", + "total": 186, + "done": 186, + "errors": 0, + "build_log": null, + "workers": 16, + "slurm_id": "486320", + "slurm_ids": [ + "486320" + ], + "engine_version": "a3faf45adac1134739a528c9637e4a2d3a389c7e8a667a79df3dc9fddf8e5972" +} \ No newline at end of file diff --git a/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/summary.json b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b79e0731e9a43eae9b55211c25ba779b4fad3421 --- /dev/null +++ b/results/jobs/20261108-162315-A26_MPC_stack__loc_Transformer___online_states/summary.json @@ -0,0 +1,292 @@ +{ + "cte_p50": { + "value": 0.2141808499455335, + "worst_kart": null, + "per_kart": { + "kart1": 0.2141808499455335 + } + }, + "cte_p90": { + "value": 0.6173760900978504, + "worst_kart": null, + "per_kart": { + "kart1": 0.6173760900978504 + } + }, + "cte_p99": { + "value": 1.2740312640324571, + "worst_kart": null, + "per_kart": { + "kart1": 1.2740312640324571 + } + }, + "recovery_rate": { + "value": 0.8333333333333334, + "worst_kart": null, + "per_kart": { + "kart1": 0.8333333333333334 + } + }, + "recovery_s_median": { + "value": 1.4164999999999992, + "worst_kart": null, + "per_kart": { + "kart1": 1.4164999999999992 + } + }, + "safety": { + "value": 0.858312585257357, + "worst_kart": null, + "per_kart": { + "kart1": 0.858312585257357 + } + }, + "unsafe_lat": { + "value": 0.0010476695286391125, + "worst_kart": null, + "per_kart": { + "kart1": 0.0010476695286391125 + } + }, + "unsafe_rate": { + "value": 0.07526494059250405, + "worst_kart": null, + "per_kart": { + "kart1": 0.07526494059250405 + } + }, + "unsafe_travel": { + "value": 0.0, + "worst_kart": null, + "per_kart": { + "kart1": 0.0 + } + }, + "unsafe_spin": { + "value": 0.0001017154882173895, + "worst_kart": null, + "per_kart": { + "kart1": 0.0001017154882173895 + } + }, + "unsafe_off": { + "value": 0.07614082396326478, + "worst_kart": null, + "per_kart": { + "kart1": 0.07614082396326478 + } + }, + "osc_10": { + "value": 27.912988029514768, + "worst_kart": null, + "per_kart": { + "kart1": 27.912988029514768 + } + }, + "osc_20": { + "value": 11.482493326036082, + "worst_kart": null, + "per_kart": { + "kart1": 11.482493326036082 + } + }, + "osc_30": { + "value": 5.93457174500048, + "worst_kart": null, + "per_kart": { + "kart1": 5.93457174500048 + } + }, + "laps_pct": { + "value": 63.1578947368421, + "worst_kart": null, + "per_kart": { + "kart1": 63.1578947368421 + } + }, + "failures": { + "value": 43, + "worst_kart": null, + "per_kart": { + "kart1": 43 + } + }, + "loc_rms": { + "value": 0.127, + "worst_kart": null, + "per_kart": { + "kart1": 0.127 + } + }, + "loc_p50": { + "value": 0.019, + "worst_kart": null, + "per_kart": { + "kart1": 0.019 + } + }, + "loc_p95": { + "value": 0.053, + "worst_kart": null, + "per_kart": { + "kart1": 0.053 + } + }, + "loc_p99": { + "value": 0.065, + "worst_kart": null, + "per_kart": { + "kart1": 0.065 + } + }, + "best_lap_s": { + "value": 71.85, + "worst_kart": null, + "per_kart": { + "kart1": 71.85 + } + }, + "lap_time_90": { + "value": 91.686, + "worst_kart": null, + "per_kart": { + "kart1": 91.686 + } + }, + "lap_time_99": { + "value": 98.477, + "worst_kart": null, + "per_kart": { + "kart1": 98.477 + } + }, + "lap_time_999": { + "value": 99.158, + "worst_kart": null, + "per_kart": { + "kart1": 99.158 + } + }, + "learned_to_slide_rate": { + "value": 0.0, + "worst_kart": null, + "per_kart": { + "kart1": 0.0 + } + }, + "laps_to_slide": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "slide_pct_p95": { + "value": 51.0, + "worst_kart": null, + "per_kart": { + "kart1": 51.0 + } + }, + "lap_improvement_s": { + "value": 0.0, + "worst_kart": null, + "per_kart": { + "kart1": 0.0 + } + }, + "overtake_rate": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "overtake_s_median": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "min_clearance_m": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "collisions": { + "value": 0, + "worst_kart": null, + "per_kart": { + "kart1": 0 + } + }, + "collision_rate": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "score_control": { + "value": 54.5, + "worst_kart": null, + "per_kart": { + "kart1": 54.5 + } + }, + "score_localization": { + "value": 89.1, + "worst_kart": null, + "per_kart": { + "kart1": 89.1 + } + }, + "score_overtake": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "score_slide": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "score_endurance": { + "value": null, + "worst_kart": null, + "per_kart": { + "kart1": null + } + }, + "score_clips": { + "value": 82.4, + "worst_kart": null, + "per_kart": { + "kart1": 82.4 + } + }, + "composite_score": { + "value": 69.1, + "worst_kart": null, + "per_kart": { + "kart1": 69.1 + } + }, + "n": { + "value": 186, + "worst_kart": null, + "per_kart": {} + }, + "errors": { + "value": 0, + "worst_kart": null, + "per_kart": {} + } +} \ No newline at end of file diff --git a/results/leaderboard/2__a3faf45adac1.json b/results/leaderboard/2__a3faf45adac1.json index 49f0823db9d31d60ef637cd41f75b83a597d1914..8a915669adf1ca7dd4b2ee207ebf6328633d5196 100644 --- a/results/leaderboard/2__a3faf45adac1.json +++ b/results/leaderboard/2__a3faf45adac1.json @@ -280,5 +280,99 @@ "n": 186, "errors": 0 } + }, + { + "job_id": "20261108-162315-A26_MPC_stack__loc_Transformer___online_states", + "recipe": "A26 MPC stack, loc Transformer + online states", + "notes": "", + "user": "shay", + "ran_at": "2026-11-08T21:33:51.315+00:00", + "duration_s": 635.439, + "cte_p50": 0.2141808499455335, + "cte_p90": 0.6173760900978504, + "cte_p99": 1.2740312640324571, + "recovery_rate": 0.8333333333333334, + "recovery_s_median": 1.4164999999999992, + "safety": 0.858312585257357, + "unsafe_lat": 0.0010476695286391125, + "unsafe_rate": 0.07526494059250405, + "unsafe_travel": 0.0, + "unsafe_spin": 0.0001017154882173895, + "unsafe_off": 0.07614082396326478, + "osc_10": 27.912988029514768, + "osc_20": 11.482493326036082, + "osc_30": 5.93457174500048, + "laps_pct": 63.1578947368421, + "failures": 43, + "loc_rms": 0.127, + "loc_p50": 0.019, + "loc_p95": 0.053, + "loc_p99": 0.065, + "best_lap_s": 71.85, + "lap_time_90": 91.686, + "lap_time_99": 98.477, + "lap_time_999": 99.158, + 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