results: jobs/20261008-002238-idea-combo-speed-adaptive/** jobs/20261008-013006-idea-combo-all/** jobs/20261008-023954-idea-adaptive-steer/** jobs/20261008-034501-idea-combo-sat/** jobs/20261008-045349-idea-delay-comp/** jobs/20261008-094600-idea-combo-all-dc/** jobs/20261008-095605-idea-combo-final/** jobs/20261008-100502-idea-understeer/** jobs/20261008-100254-idea-combo-final/** index/episodes.jsonl leaderboard/*
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- results/index/episodes.jsonl +0 -0
- results/jobs/20261008-002238-idea-combo-speed-adaptive/breakdown.json +0 -0
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- results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0005.jsonl.gz +3 -0
results/index/episodes.jsonl
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results/jobs/20261008-002238-idea-combo-speed-adaptive/episodes.jsonl
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results/jobs/20261008-002238-idea-combo-speed-adaptive/gautschi/0/done.txt
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26951113db115d7cea4e6bf9d1f6d27635f4bbbe6a0b3460137456b89d212174
|
| 497 |
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|
| 498 |
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|
| 499 |
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|
| 500 |
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|
| 501 |
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|
| 502 |
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|
| 503 |
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62084c9830a1fdfc855be67286809cf67b4cd38e1ea460a011eaf70b45eadee5
|
| 504 |
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6951f741495013742b296a1b6532f5e72e804ef6b5aac8161b227fa3d79d6bb3
|
| 505 |
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|
| 506 |
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|
| 507 |
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|
| 508 |
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2566ca412810f2c0e66f6a3d71a1db438a4d595f1319b4fc0b24d3680cdbe153
|
| 509 |
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50507b05c54c857a359155cd7c46cff80ad77f900049eb0b3f0618439cb4a28d
|
| 510 |
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|
| 511 |
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|
| 512 |
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| 515 |
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|
| 516 |
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|
| 517 |
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4fb8e1d0a569fc901eff2a8122ed09359f4b13d383e5ccc71025a8692dda7b9a
|
| 518 |
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515005d530dc789623b2c0548a18f16eda182d7c996812b407fd558ac01edc18
|
| 519 |
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f7dc8927a0aca9c0f835c084f663363d08b28ae526e70f272f1513998b0a7c40
|
| 520 |
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8b3cc0d35e0b1bdc4b500ab5bdedc7aae642adda70328ca326ac5500af28287c
|
| 521 |
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ce975c0803043fe33cdb90a0645f5971eca158dddff83aa4a91a5d16b1936f48
|
| 522 |
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563f89948bf39bce26a889cf75bc813cf85dd82e2164ad7183fa26160e20caf3
|
| 523 |
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b11333d1c63af43e94a1d6473fc74d2d7bf8cf9f25b4930702671d79e82e173d
|
| 524 |
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af1843ecc5d2cc5bd46ce9df6577e48b35cbf55dfda1b964f259dbbb5e1f27e6
|
| 525 |
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3cac8c8886c75ae49a987a3d03fb9480bad04fedb598ef8050b747f4e63b2a74
|
| 526 |
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|
| 527 |
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|
| 528 |
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23208584b8a683068b226481e7dbbc281c3be3596f96b2d0ea3863379d22b51c
|
| 529 |
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148384b84acef77d1c6682cea190aa9976265ad652cb4a1dc82e28fa00f7f2d0
|
| 530 |
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98720792cedd0d4f0f3545fc41877ddeb2173e7eef3f0b00455080467fd9e422
|
| 531 |
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c217e4a2a7e037e8c08a0d8904969e2530a5d9a281bfb64c736c386e2231f490
|
| 532 |
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836ca3eb14170ace2072a47534fbd28090b3b6ab87c5c7784871eed475a986b2
|
| 533 |
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11eb487a9d6f58caaae0cde96b2209c58148fe1c8efb6fe01ddfb50ffb3c3e36
|
| 534 |
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282c99e17e877a1edab45dfabd769dc1cb26b6560289b0ec0d6e55af32e0943e
|
| 535 |
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6380f02174f8b7f1b8753f53ba7e887cfe6b8e4adeae82859206280a2e6671b8
|
| 536 |
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ef5ae37591eab61586b94e081f16b13f171a44e2879082738db078c68ed55815
|
| 537 |
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44880a70be865d753f2333f3cbe02d942e34fbdfcca133ae0618ff0235ac5aab
|
| 538 |
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bdd336e11be2a7d68204531901be2e19f7c12b51244f1f7f8115afcb7c773dcc
|
| 539 |
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0e6f5ea4a903001b5d73256660944a272000eb0eb77acfc0230e0567014e8a11
|
| 540 |
+
39557f24acc64b1370b0725113ea1eacba80f8dea07065703d2618093b14974e
|
| 541 |
+
01e6e39a37dc7c3f1a2f643e814f8966e39720d807859f42f254f8284fe49e13
|
| 542 |
+
2096bcf2dcd1954317a11af882d464387800c1a1759d9acaec2ace4bab9beaee
|
| 543 |
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a0d7c876f91d735f336eb6887c6d535123d4cf7fe059d878d45cfe1ba6dee474
|
| 544 |
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5a94c3ba608584da496f9b50e7abf87d87a91b38fc65331e92eda3ba9799ff1d
|
| 545 |
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75f969c5f1ec66a0ff94759cf436cfe54a323aa6819788713618e07e4f07d88b
|
| 546 |
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496363cf2c25df4a0f6398c3f09560a489754d44ca4c62f2cbc46fd2d13061a5
|
| 547 |
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2a671015c9a13aee5ac8526c554f9f81efaca3e7b26683afa8a7d30e35306382
|
| 548 |
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0820e41237ac88ef40177582a099d30b34f7b77cc50d792cc222b88bd6960572
|
| 549 |
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42cf821dffbe36331a491d1a9012cc6ce3c038a5f96387992bc9163b9b73aca8
|
| 550 |
+
fea32a4eaa4f5ebab5df27c398196e8ac5245bb9359c54aa99f8f2e9969f9f3a
|
| 551 |
+
412ff4f716fa3f9e6088b68ce12c00b02a7849cec70fae43de90cf292a5b30d7
|
| 552 |
+
987e08623e1dc4d9811a5256068ffd4e4c810261823f7afdae0c5972724d218b
|
| 553 |
+
389b328c791a6bd184616bc4e60193a34e863ab04e8f85480f3a2f20d51e6ff9
|
| 554 |
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51d678f8c6a620666a8610a10a50fd687e1d37a678020002819ec934e46a1106
|
| 555 |
+
6d060b50f25d7d3546b07e48c9565158cf745bd1391519a3037a9550c4c7ba89
|
| 556 |
+
59f72c38087f2c29c237e80bcfd791a391e00135f340fa8583ea9ca696a19c12
|
| 557 |
+
f5dba9c3e0d14b9c5cb9cfc22699e92d6be1c56485fd41063ce95f81ac984543
|
| 558 |
+
2768edb3288f0c7e591ca9f7f55231f687f6543bbd78d3a2acb880711775a0e2
|
results/jobs/20261008-002238-idea-combo-speed-adaptive/gautschi/0/episodes.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/jobs/20261008-002238-idea-combo-speed-adaptive/gautschi/0/gautschi_launch.py
ADDED
|
@@ -0,0 +1,143 @@
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|
|
| 1 |
+
"""Runs on a Gautschi node (stdlib only): episodes from a queue in parallel workers, one contained Apptainer per episode."""
|
| 2 |
+
import argparse
|
| 3 |
+
import json
|
| 4 |
+
import os
|
| 5 |
+
import queue
|
| 6 |
+
import shutil
|
| 7 |
+
import subprocess
|
| 8 |
+
import threading
|
| 9 |
+
import time
|
| 10 |
+
|
| 11 |
+
RUN = ("source /opt/ros/humble/setup.bash && source /ws/install/setup.bash"
|
| 12 |
+
" && python3 -m simnode.batch /batch.json /out")
|
| 13 |
+
CUDA_LIB = "/ws/mpc_cuda/libmpc_cuda.so" # built per stack by runner/gautschi.build_stack for gautschi-gpu
|
| 14 |
+
SAMPLE_S = 15
|
| 15 |
+
STAGGER_S = 0.25 # between worker starts: the dev job's one error was a stack starved in the 96-way start burst
|
| 16 |
+
EPISODE_TIMEOUT_S = 1200 # about 4x the slowest lap; a killed episode has no outcome and is retried by the host
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
def worker_cmd(i, work, out, ep, sif, engine, stack, gpu=None):
|
| 20 |
+
"""Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker;
|
| 21 |
+
gpu (a host CUDA device) adds the driver and the stack's CUDA MPC kernel."""
|
| 22 |
+
cuda = ["--nv", "--env", f"CUDA_VISIBLE_DEVICES={gpu}", "--env", f"MPC_CUDA_LIB={CUDA_LIB}"] if gpu is not None else []
|
| 23 |
+
return ["apptainer", "exec", *cuda, "--contain", "--cleanenv", "--ipc", "--pid", "--net", "--network", "none", "--workdir", work,
|
| 24 |
+
"--env", f"ROS_DOMAIN_ID={i + 1}", "--env", "ROS_HOME=/tmp/ros", "--env", "TMPDIR=/tmp",
|
| 25 |
+
"--bind", f"{engine}:/opt/sim:ro", "--bind", f"{stack}:/ws:ro", "--bind", f"{out}:/out",
|
| 26 |
+
"--bind", f"{ep}:/batch.json:ro", sif, "bash", "-lc", RUN]
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
def parse_smi(text):
|
| 30 |
+
"""nvidia-smi 'utilization.gpu, memory.used' csv rows to per-GPU lists."""
|
| 31 |
+
rows = [[int(v) for v in ln.split(",")] for ln in text.strip().splitlines() if ln.strip()]
|
| 32 |
+
return {"gpu_util": [r[0] for r in rows], "gpu_mem_mib": [r[1] for r in rows]}
|
| 33 |
+
|
| 34 |
+
|
| 35 |
+
def _solver(logdir):
|
| 36 |
+
"""pathfinder's 'MPC solver: ...' and CUDA fallback lines from the episode's ROS logs."""
|
| 37 |
+
lines = []
|
| 38 |
+
for dp, _, fns in os.walk(logdir):
|
| 39 |
+
for fn in fns:
|
| 40 |
+
try:
|
| 41 |
+
with open(os.path.join(dp, fn), errors="replace") as f:
|
| 42 |
+
lines += [ln.strip() for ln in f if "MPC solver:" in ln or "CUDA MPC unavailable" in ln]
|
| 43 |
+
except OSError:
|
| 44 |
+
pass
|
| 45 |
+
return "\n".join(dict.fromkeys(lines))
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
def main(argv=None):
|
| 49 |
+
p = argparse.ArgumentParser()
|
| 50 |
+
for a in ("episodes", "out", "sif", "engine", "stack", "work", "timeline", "done"):
|
| 51 |
+
p.add_argument("--" + a, required=True)
|
| 52 |
+
p.add_argument("--workers", type=int, required=True)
|
| 53 |
+
p.add_argument("--gpus", type=int, default=0)
|
| 54 |
+
a = p.parse_args(argv)
|
| 55 |
+
with open(a.episodes) as f:
|
| 56 |
+
q = queue.Queue()
|
| 57 |
+
for e in json.load(f): # the host already ordered them, longest first
|
| 58 |
+
q.put(e)
|
| 59 |
+
os.makedirs(a.out, exist_ok=True)
|
| 60 |
+
lock, t0 = threading.Lock(), time.time()
|
| 61 |
+
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)]
|
| 62 |
+
|
| 63 |
+
def log(**ev):
|
| 64 |
+
with lock, open(a.timeline, "a") as f:
|
| 65 |
+
f.write(json.dumps(dict(ev, t=round(time.time() - t0, 3))) + "\n")
|
| 66 |
+
|
| 67 |
+
def worker(i):
|
| 68 |
+
time.sleep(i * STAGGER_S)
|
| 69 |
+
while True:
|
| 70 |
+
try:
|
| 71 |
+
e = q.get_nowait()
|
| 72 |
+
except queue.Empty:
|
| 73 |
+
return
|
| 74 |
+
key, work = e["key"], os.path.join(a.work, e["key"])
|
| 75 |
+
stage, ep = os.path.join(work, "stage"), os.path.join(work, "ep.json")
|
| 76 |
+
os.makedirs(stage)
|
| 77 |
+
with open(ep, "w") as f:
|
| 78 |
+
json.dump([e], f)
|
| 79 |
+
log(ev="start", key=key, worker=i)
|
| 80 |
+
gpu = devs[i % len(devs)] if devs and e["resolved"].get("recipe", {}).get("sim", {}).get("cuda") else None
|
| 81 |
+
limit = EPISODE_TIMEOUT_S * max(1, e["resolved"]["scenario"].get("laps", 1)) # per lap: 5-lap episodes run 5x longer
|
| 82 |
+
try:
|
| 83 |
+
rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack, gpu), stdout=subprocess.DEVNULL,
|
| 84 |
+
stderr=subprocess.DEVNULL, timeout=limit).returncode
|
| 85 |
+
except subprocess.TimeoutExpired:
|
| 86 |
+
rc = "timeout"
|
| 87 |
+
solver = _solver(os.path.join(work, "tmp", "ros", "log"))
|
| 88 |
+
if solver and os.path.isdir(os.path.join(stage, key)):
|
| 89 |
+
with open(os.path.join(stage, key, "solver.txt"), "w") as f:
|
| 90 |
+
f.write(solver + "\n")
|
| 91 |
+
if os.path.exists(os.path.join(stage, key, "outcome.json")):
|
| 92 |
+
tmp, dst = os.path.join(a.out, ".tmp-" + key), os.path.join(a.out, key)
|
| 93 |
+
shutil.rmtree(tmp, ignore_errors=True)
|
| 94 |
+
shutil.copytree(os.path.join(stage, key), tmp)
|
| 95 |
+
shutil.rmtree(dst, ignore_errors=True)
|
| 96 |
+
os.rename(tmp, dst) # the host's rsync sees a key only once its directory is complete
|
| 97 |
+
with lock, open(a.done, "a") as f:
|
| 98 |
+
f.write(key + "\n")
|
| 99 |
+
shutil.rmtree(work, ignore_errors=True)
|
| 100 |
+
log(ev="end", key=key, worker=i, rc=rc, gpu=gpu,
|
| 101 |
+
solver=solver.split("MPC solver: ")[-1] if "MPC solver: " in solver else solver or None)
|
| 102 |
+
|
| 103 |
+
def sampler(stop):
|
| 104 |
+
"""Job CPU use from its cgroup, as busy cores, every SAMPLE_S."""
|
| 105 |
+
try:
|
| 106 |
+
with open("/proc/self/cgroup") as f:
|
| 107 |
+
path = "/sys/fs/cgroup" + f.read().strip().split(":")[-1] + "/cpu.stat"
|
| 108 |
+
prev = None
|
| 109 |
+
while not stop.wait(SAMPLE_S if prev else 0):
|
| 110 |
+
with open(path) as f:
|
| 111 |
+
use = next(int(ln.split()[1]) for ln in f if ln.startswith("usage_usec"))
|
| 112 |
+
now = time.time()
|
| 113 |
+
if prev:
|
| 114 |
+
log(ev="cpu", busy_cores=round((use - prev[0]) / 1e6 / (now - prev[1]), 2))
|
| 115 |
+
prev = (use, now)
|
| 116 |
+
except (OSError, StopIteration, ValueError):
|
| 117 |
+
pass
|
| 118 |
+
|
| 119 |
+
def gpu_sampler(stop):
|
| 120 |
+
"""GPU utilisation and memory of the job's GPUs, every SAMPLE_S."""
|
| 121 |
+
while not stop.wait(SAMPLE_S):
|
| 122 |
+
try:
|
| 123 |
+
p = subprocess.Popen(["nvidia-smi", "--query-gpu=utilization.gpu,memory.used", "--format=csv,noheader,nounits"],
|
| 124 |
+
stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True)
|
| 125 |
+
log(ev="gpu", **parse_smi(p.communicate(timeout=30)[0]))
|
| 126 |
+
except Exception: # no driver or a hung query: skip this sample
|
| 127 |
+
pass
|
| 128 |
+
|
| 129 |
+
cores = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count()
|
| 130 |
+
log(ev="launch", workers=a.workers, cores=cores)
|
| 131 |
+
stop = threading.Event()
|
| 132 |
+
threads = [threading.Thread(target=worker, args=(i,)) for i in range(a.workers)]
|
| 133 |
+
samplers = [sampler] + ([gpu_sampler] if a.gpus else [])
|
| 134 |
+
for t in threads + [threading.Thread(target=f, args=(stop,), daemon=True) for f in samplers]:
|
| 135 |
+
t.start()
|
| 136 |
+
for t in threads:
|
| 137 |
+
t.join()
|
| 138 |
+
stop.set()
|
| 139 |
+
log(ev="done")
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
if __name__ == "__main__":
|
| 143 |
+
main()
|
results/jobs/20261008-002238-idea-combo-speed-adaptive/job.json
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"id": "20261008-002238-idea-combo-speed-adaptive",
|
| 3 |
+
"tier": "dev",
|
| 4 |
+
"tier_version": 2,
|
| 5 |
+
"recipe": {
|
| 6 |
+
"name": "idea-combo-speed-adaptive",
|
| 7 |
+
"source": {
|
| 8 |
+
"repo": "AutonomousKart",
|
| 9 |
+
"ref": "worktree:combo-speed-adaptive"
|
| 10 |
+
},
|
| 11 |
+
"params": {
|
| 12 |
+
"pathfinder_node": {
|
| 13 |
+
"mpc.num_samples": 4096
|
| 14 |
+
}
|
| 15 |
+
},
|
| 16 |
+
"sim": {
|
| 17 |
+
"cuda": true
|
| 18 |
+
},
|
| 19 |
+
"notes": "speed-profile + adaptive-steer combined"
|
| 20 |
+
},
|
| 21 |
+
"user": "shay",
|
| 22 |
+
"notes": "combo speed-profile + adaptive-steer dev",
|
| 23 |
+
"where": "ideas",
|
| 24 |
+
"status": "done",
|
| 25 |
+
"submitted_at": "2026-10-08T04:22:38.148+00:00",
|
| 26 |
+
"started_at": "2026-10-08T04:22:38.149+00:00",
|
| 27 |
+
"finished_at": "2026-10-08T05:22:28.078+00:00",
|
| 28 |
+
"total": 558,
|
| 29 |
+
"done": 558,
|
| 30 |
+
"errors": 0,
|
| 31 |
+
"build_log": null,
|
| 32 |
+
"workers": 10,
|
| 33 |
+
"slurm_id": "714069",
|
| 34 |
+
"slurm_ids": [
|
| 35 |
+
"714069"
|
| 36 |
+
],
|
| 37 |
+
"engine_version": "10f2000722b663fb4aff189ffeffaf827254d41cf3fc0dee742b7109ee1ffaf3"
|
| 38 |
+
}
|
results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0000.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
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|
| 3 |
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size 98606571
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0001.jsonl.gz
ADDED
|
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0002.jsonl.gz
ADDED
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ADDED
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0004.jsonl.gz
ADDED
|
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0005.jsonl.gz
ADDED
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0006.jsonl.gz
ADDED
|
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0007.jsonl.gz
ADDED
|
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version https://git-lfs.github.com/spec/v1
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size 29397234
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0008.jsonl.gz
ADDED
|
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0009.jsonl.gz
ADDED
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results/jobs/20261008-002238-idea-combo-speed-adaptive/logs/shard-0010.jsonl.gz
ADDED
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ADDED
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size 4859029
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results/jobs/20261008-002238-idea-combo-speed-adaptive/summary.json
ADDED
|
@@ -0,0 +1,156 @@
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|
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|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
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|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
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|
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|
|
|
|
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|
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|
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|
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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"value": 0.1741692600649752,
|
| 4 |
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|
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}
|
| 10 |
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|
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|
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|
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|
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|
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}
|
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|
| 21 |
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|
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|
| 26 |
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|
| 27 |
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}
|
| 28 |
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},
|
| 29 |
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|
| 30 |
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"value": 0.8802395209580839,
|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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}
|
| 37 |
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},
|
| 38 |
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"recovery_s_median": {
|
| 39 |
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"value": 1.6249999999999991,
|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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}
|
| 46 |
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},
|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
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|
| 53 |
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|
| 54 |
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}
|
| 55 |
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},
|
| 56 |
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|
| 57 |
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"value": 0.0006021783528195738,
|
| 58 |
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|
| 59 |
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|
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|
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
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|
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|
| 73 |
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|
| 75 |
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|
| 76 |
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|
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|
| 82 |
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|
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|
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|
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|
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|
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|
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|
| 120 |
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|
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|
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|
| 129 |
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|
| 130 |
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"worst_kart": null,
|
| 131 |
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"per_kart": {
|
| 132 |
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"kart1": 63.1578947368421,
|
| 133 |
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"kart2": 68.42105263157895,
|
| 134 |
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"kart3": 57.89473684210526
|
| 135 |
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}
|
| 136 |
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},
|
| 137 |
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"failures": {
|
| 138 |
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"value": 102,
|
| 139 |
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|
| 140 |
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"per_kart": {
|
| 141 |
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"kart1": 36,
|
| 142 |
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"kart2": 27,
|
| 143 |
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"kart3": 39
|
| 144 |
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}
|
| 145 |
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},
|
| 146 |
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"n": {
|
| 147 |
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"value": 558,
|
| 148 |
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"worst_kart": null,
|
| 149 |
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"per_kart": {}
|
| 150 |
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},
|
| 151 |
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"errors": {
|
| 152 |
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"value": 0,
|
| 153 |
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"worst_kart": null,
|
| 154 |
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"per_kart": {}
|
| 155 |
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}
|
| 156 |
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}
|
results/jobs/20261008-013006-idea-combo-all/breakdown.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/jobs/20261008-013006-idea-combo-all/episodes.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/jobs/20261008-013006-idea-combo-all/gautschi/0/done.txt
ADDED
|
@@ -0,0 +1,543 @@
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82a47edf112eef6c72ad2f3e92138062a1cef2a552cb74ad48ed2dbe63d11834
|
| 530 |
+
ed7da5dbccf026db9fb8af6d1f92bf693a9e9c45865fd93b645a7a7bee0b89f6
|
| 531 |
+
99dd87539d3f2d5e9342478b9155696c590980120796432b2f56ff4d81346994
|
| 532 |
+
abc41733460e14e957cc7a149aa5d3aaf1a7ec9766a81ab6a3847537d462461b
|
| 533 |
+
8e7c4c4c8708c129441846205caa932ee04ec13fbc158b2854954d0c8be6c68a
|
| 534 |
+
1975aeddf6dd6297025b37e2669f3f87f9650bc2ce66b8d31b0926e8db287c1e
|
| 535 |
+
521a1bed5e0637cf0574df0a771fddff8fd46388dbc3cc1b810e56df97ce2d9a
|
| 536 |
+
334244776459e12a3f8f52aafc91594e6f0f815783167c63402190aae8f6f172
|
| 537 |
+
4e2ed5b81ea8b455c19c22a897464ea32a9d589447a47cfcebe7b7bd093fc2a9
|
| 538 |
+
5d83baf37ba8c8a54582e866efbbac8a4498af53d8e2700b6a793fd47c7fa2c2
|
| 539 |
+
39e70720a4f227b5bed5c62129018b9188367766b1520cc0397a36e67bc234d5
|
| 540 |
+
4de2c57c29f3c258babd205015f8e156f4ad598859b10bd978125dcc7bf3daa2
|
| 541 |
+
6daf743aa6ccc314d542f9a5d371420ba1a175b666e495a18903784695cc66e0
|
| 542 |
+
53cf6973ff7415fdf1cef083b283b216057f79a7c8d26a6f8b7fbbf93b3e4c41
|
| 543 |
+
2f9309ed3b91d7cc89043daa9748306b9efaa63dc9ac207b03c38e4a807ea87c
|
results/jobs/20261008-013006-idea-combo-all/gautschi/0/episodes.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
results/jobs/20261008-013006-idea-combo-all/gautschi/0/gautschi_launch.py
ADDED
|
@@ -0,0 +1,143 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
|
|
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|
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|
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|
|
|
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|
|
|
|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Runs on a Gautschi node (stdlib only): episodes from a queue in parallel workers, one contained Apptainer per episode."""
|
| 2 |
+
import argparse
|
| 3 |
+
import json
|
| 4 |
+
import os
|
| 5 |
+
import queue
|
| 6 |
+
import shutil
|
| 7 |
+
import subprocess
|
| 8 |
+
import threading
|
| 9 |
+
import time
|
| 10 |
+
|
| 11 |
+
RUN = ("source /opt/ros/humble/setup.bash && source /ws/install/setup.bash"
|
| 12 |
+
" && python3 -m simnode.batch /batch.json /out")
|
| 13 |
+
CUDA_LIB = "/ws/mpc_cuda/libmpc_cuda.so" # built per stack by runner/gautschi.build_stack for gautschi-gpu
|
| 14 |
+
SAMPLE_S = 15
|
| 15 |
+
STAGGER_S = 0.25 # between worker starts: the dev job's one error was a stack starved in the 96-way start burst
|
| 16 |
+
EPISODE_TIMEOUT_S = 1200 # about 4x the slowest lap; a killed episode has no outcome and is retried by the host
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
def worker_cmd(i, work, out, ep, sif, engine, stack, gpu=None):
|
| 20 |
+
"""Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker;
|
| 21 |
+
gpu (a host CUDA device) adds the driver and the stack's CUDA MPC kernel."""
|
| 22 |
+
cuda = ["--nv", "--env", f"CUDA_VISIBLE_DEVICES={gpu}", "--env", f"MPC_CUDA_LIB={CUDA_LIB}"] if gpu is not None else []
|
| 23 |
+
return ["apptainer", "exec", *cuda, "--contain", "--cleanenv", "--ipc", "--pid", "--net", "--network", "none", "--workdir", work,
|
| 24 |
+
"--env", f"ROS_DOMAIN_ID={i + 1}", "--env", "ROS_HOME=/tmp/ros", "--env", "TMPDIR=/tmp",
|
| 25 |
+
"--bind", f"{engine}:/opt/sim:ro", "--bind", f"{stack}:/ws:ro", "--bind", f"{out}:/out",
|
| 26 |
+
"--bind", f"{ep}:/batch.json:ro", sif, "bash", "-lc", RUN]
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
def parse_smi(text):
|
| 30 |
+
"""nvidia-smi 'utilization.gpu, memory.used' csv rows to per-GPU lists."""
|
| 31 |
+
rows = [[int(v) for v in ln.split(",")] for ln in text.strip().splitlines() if ln.strip()]
|
| 32 |
+
return {"gpu_util": [r[0] for r in rows], "gpu_mem_mib": [r[1] for r in rows]}
|
| 33 |
+
|
| 34 |
+
|
| 35 |
+
def _solver(logdir):
|
| 36 |
+
"""pathfinder's 'MPC solver: ...' and CUDA fallback lines from the episode's ROS logs."""
|
| 37 |
+
lines = []
|
| 38 |
+
for dp, _, fns in os.walk(logdir):
|
| 39 |
+
for fn in fns:
|
| 40 |
+
try:
|
| 41 |
+
with open(os.path.join(dp, fn), errors="replace") as f:
|
| 42 |
+
lines += [ln.strip() for ln in f if "MPC solver:" in ln or "CUDA MPC unavailable" in ln]
|
| 43 |
+
except OSError:
|
| 44 |
+
pass
|
| 45 |
+
return "\n".join(dict.fromkeys(lines))
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
def main(argv=None):
|
| 49 |
+
p = argparse.ArgumentParser()
|
| 50 |
+
for a in ("episodes", "out", "sif", "engine", "stack", "work", "timeline", "done"):
|
| 51 |
+
p.add_argument("--" + a, required=True)
|
| 52 |
+
p.add_argument("--workers", type=int, required=True)
|
| 53 |
+
p.add_argument("--gpus", type=int, default=0)
|
| 54 |
+
a = p.parse_args(argv)
|
| 55 |
+
with open(a.episodes) as f:
|
| 56 |
+
q = queue.Queue()
|
| 57 |
+
for e in json.load(f): # the host already ordered them, longest first
|
| 58 |
+
q.put(e)
|
| 59 |
+
os.makedirs(a.out, exist_ok=True)
|
| 60 |
+
lock, t0 = threading.Lock(), time.time()
|
| 61 |
+
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)]
|
| 62 |
+
|
| 63 |
+
def log(**ev):
|
| 64 |
+
with lock, open(a.timeline, "a") as f:
|
| 65 |
+
f.write(json.dumps(dict(ev, t=round(time.time() - t0, 3))) + "\n")
|
| 66 |
+
|
| 67 |
+
def worker(i):
|
| 68 |
+
time.sleep(i * STAGGER_S)
|
| 69 |
+
while True:
|
| 70 |
+
try:
|
| 71 |
+
e = q.get_nowait()
|
| 72 |
+
except queue.Empty:
|
| 73 |
+
return
|
| 74 |
+
key, work = e["key"], os.path.join(a.work, e["key"])
|
| 75 |
+
stage, ep = os.path.join(work, "stage"), os.path.join(work, "ep.json")
|
| 76 |
+
os.makedirs(stage)
|
| 77 |
+
with open(ep, "w") as f:
|
| 78 |
+
json.dump([e], f)
|
| 79 |
+
log(ev="start", key=key, worker=i)
|
| 80 |
+
gpu = devs[i % len(devs)] if devs and e["resolved"].get("recipe", {}).get("sim", {}).get("cuda") else None
|
| 81 |
+
limit = EPISODE_TIMEOUT_S * max(1, e["resolved"]["scenario"].get("laps", 1)) # per lap: 5-lap episodes run 5x longer
|
| 82 |
+
try:
|
| 83 |
+
rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack, gpu), stdout=subprocess.DEVNULL,
|
| 84 |
+
stderr=subprocess.DEVNULL, timeout=limit).returncode
|
| 85 |
+
except subprocess.TimeoutExpired:
|
| 86 |
+
rc = "timeout"
|
| 87 |
+
solver = _solver(os.path.join(work, "tmp", "ros", "log"))
|
| 88 |
+
if solver and os.path.isdir(os.path.join(stage, key)):
|
| 89 |
+
with open(os.path.join(stage, key, "solver.txt"), "w") as f:
|
| 90 |
+
f.write(solver + "\n")
|
| 91 |
+
if os.path.exists(os.path.join(stage, key, "outcome.json")):
|
| 92 |
+
tmp, dst = os.path.join(a.out, ".tmp-" + key), os.path.join(a.out, key)
|
| 93 |
+
shutil.rmtree(tmp, ignore_errors=True)
|
| 94 |
+
shutil.copytree(os.path.join(stage, key), tmp)
|
| 95 |
+
shutil.rmtree(dst, ignore_errors=True)
|
| 96 |
+
os.rename(tmp, dst) # the host's rsync sees a key only once its directory is complete
|
| 97 |
+
with lock, open(a.done, "a") as f:
|
| 98 |
+
f.write(key + "\n")
|
| 99 |
+
shutil.rmtree(work, ignore_errors=True)
|
| 100 |
+
log(ev="end", key=key, worker=i, rc=rc, gpu=gpu,
|
| 101 |
+
solver=solver.split("MPC solver: ")[-1] if "MPC solver: " in solver else solver or None)
|
| 102 |
+
|
| 103 |
+
def sampler(stop):
|
| 104 |
+
"""Job CPU use from its cgroup, as busy cores, every SAMPLE_S."""
|
| 105 |
+
try:
|
| 106 |
+
with open("/proc/self/cgroup") as f:
|
| 107 |
+
path = "/sys/fs/cgroup" + f.read().strip().split(":")[-1] + "/cpu.stat"
|
| 108 |
+
prev = None
|
| 109 |
+
while not stop.wait(SAMPLE_S if prev else 0):
|
| 110 |
+
with open(path) as f:
|
| 111 |
+
use = next(int(ln.split()[1]) for ln in f if ln.startswith("usage_usec"))
|
| 112 |
+
now = time.time()
|
| 113 |
+
if prev:
|
| 114 |
+
log(ev="cpu", busy_cores=round((use - prev[0]) / 1e6 / (now - prev[1]), 2))
|
| 115 |
+
prev = (use, now)
|
| 116 |
+
except (OSError, StopIteration, ValueError):
|
| 117 |
+
pass
|
| 118 |
+
|
| 119 |
+
def gpu_sampler(stop):
|
| 120 |
+
"""GPU utilisation and memory of the job's GPUs, every SAMPLE_S."""
|
| 121 |
+
while not stop.wait(SAMPLE_S):
|
| 122 |
+
try:
|
| 123 |
+
p = subprocess.Popen(["nvidia-smi", "--query-gpu=utilization.gpu,memory.used", "--format=csv,noheader,nounits"],
|
| 124 |
+
stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True)
|
| 125 |
+
log(ev="gpu", **parse_smi(p.communicate(timeout=30)[0]))
|
| 126 |
+
except Exception: # no driver or a hung query: skip this sample
|
| 127 |
+
pass
|
| 128 |
+
|
| 129 |
+
cores = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count()
|
| 130 |
+
log(ev="launch", workers=a.workers, cores=cores)
|
| 131 |
+
stop = threading.Event()
|
| 132 |
+
threads = [threading.Thread(target=worker, args=(i,)) for i in range(a.workers)]
|
| 133 |
+
samplers = [sampler] + ([gpu_sampler] if a.gpus else [])
|
| 134 |
+
for t in threads + [threading.Thread(target=f, args=(stop,), daemon=True) for f in samplers]:
|
| 135 |
+
t.start()
|
| 136 |
+
for t in threads:
|
| 137 |
+
t.join()
|
| 138 |
+
stop.set()
|
| 139 |
+
log(ev="done")
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
if __name__ == "__main__":
|
| 143 |
+
main()
|
results/jobs/20261008-013006-idea-combo-all/job.json
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"id": "20261008-013006-idea-combo-all",
|
| 3 |
+
"tier": "dev",
|
| 4 |
+
"tier_version": 2,
|
| 5 |
+
"recipe": {
|
| 6 |
+
"name": "idea-combo-all",
|
| 7 |
+
"source": {
|
| 8 |
+
"repo": "AutonomousKart",
|
| 9 |
+
"ref": "worktree:combo-all"
|
| 10 |
+
},
|
| 11 |
+
"params": {
|
| 12 |
+
"pathfinder_node": {
|
| 13 |
+
"mpc.num_samples": 4096
|
| 14 |
+
}
|
| 15 |
+
},
|
| 16 |
+
"sim": {
|
| 17 |
+
"cuda": true
|
| 18 |
+
},
|
| 19 |
+
"notes": "speed-profile + adaptive-steer + traction-control + slip-ekf"
|
| 20 |
+
},
|
| 21 |
+
"user": "shay",
|
| 22 |
+
"notes": "combo speed + adaptive + traction + slip-ekf dev",
|
| 23 |
+
"where": "ideas",
|
| 24 |
+
"status": "done",
|
| 25 |
+
"submitted_at": "2026-10-08T05:30:06.040+00:00",
|
| 26 |
+
"started_at": "2026-10-08T05:30:06.041+00:00",
|
| 27 |
+
"finished_at": "2026-10-08T06:32:15.064+00:00",
|
| 28 |
+
"total": 558,
|
| 29 |
+
"done": 558,
|
| 30 |
+
"errors": 0,
|
| 31 |
+
"build_log": null,
|
| 32 |
+
"workers": 10,
|
| 33 |
+
"slurm_id": "822507",
|
| 34 |
+
"slurm_ids": [
|
| 35 |
+
"822507"
|
| 36 |
+
],
|
| 37 |
+
"engine_version": "10f2000722b663fb4aff189ffeffaf827254d41cf3fc0dee742b7109ee1ffaf3"
|
| 38 |
+
}
|
results/jobs/20261008-013006-idea-combo-all/logs/shard-0000.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9600e60dc27dee02db5497bf3a06b33b41dfbb39f7af89c11d694bd0e0b7614b
|
| 3 |
+
size 116194862
|
results/jobs/20261008-013006-idea-combo-all/logs/shard-0001.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:18d12892345a20738106f580bd180f59a3843304ff873fc06ac9f20302029612
|
| 3 |
+
size 134051675
|
results/jobs/20261008-013006-idea-combo-all/logs/shard-0002.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:968c7fac6cca4d73be9a1e7a37f209c6d379e9b3fb7643bb152f4257e49a9fec
|
| 3 |
+
size 133662404
|
results/jobs/20261008-013006-idea-combo-all/logs/shard-0003.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2ea03fae165d9cd4f2bce44b0de9aa98ef54c8634edd02176f9c00a450425569
|
| 3 |
+
size 76175363
|
results/jobs/20261008-013006-idea-combo-all/logs/shard-0004.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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results/jobs/20261008-023954-idea-adaptive-steer/breakdown.json
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results/jobs/20261008-023954-idea-adaptive-steer/gautschi/0/done.txt
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results/jobs/20261008-023954-idea-adaptive-steer/gautschi/0/episodes.json
ADDED
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results/jobs/20261008-023954-idea-adaptive-steer/gautschi/0/gautschi_launch.py
ADDED
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Runs on a Gautschi node (stdlib only): episodes from a queue in parallel workers, one contained Apptainer per episode."""
|
| 2 |
+
import argparse
|
| 3 |
+
import json
|
| 4 |
+
import os
|
| 5 |
+
import queue
|
| 6 |
+
import shutil
|
| 7 |
+
import subprocess
|
| 8 |
+
import threading
|
| 9 |
+
import time
|
| 10 |
+
|
| 11 |
+
RUN = ("source /opt/ros/humble/setup.bash && source /ws/install/setup.bash"
|
| 12 |
+
" && python3 -m simnode.batch /batch.json /out")
|
| 13 |
+
CUDA_LIB = "/ws/mpc_cuda/libmpc_cuda.so" # built per stack by runner/gautschi.build_stack for gautschi-gpu
|
| 14 |
+
SAMPLE_S = 15
|
| 15 |
+
STAGGER_S = 0.25 # between worker starts: the dev job's one error was a stack starved in the 96-way start burst
|
| 16 |
+
EPISODE_TIMEOUT_S = 1200 # about 4x the slowest lap; a killed episode has no outcome and is retried by the host
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
def worker_cmd(i, work, out, ep, sif, engine, stack, gpu=None):
|
| 20 |
+
"""Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker;
|
| 21 |
+
gpu (a host CUDA device) adds the driver and the stack's CUDA MPC kernel."""
|
| 22 |
+
cuda = ["--nv", "--env", f"CUDA_VISIBLE_DEVICES={gpu}", "--env", f"MPC_CUDA_LIB={CUDA_LIB}"] if gpu is not None else []
|
| 23 |
+
return ["apptainer", "exec", *cuda, "--contain", "--cleanenv", "--ipc", "--pid", "--net", "--network", "none", "--workdir", work,
|
| 24 |
+
"--env", f"ROS_DOMAIN_ID={i + 1}", "--env", "ROS_HOME=/tmp/ros", "--env", "TMPDIR=/tmp",
|
| 25 |
+
"--bind", f"{engine}:/opt/sim:ro", "--bind", f"{stack}:/ws:ro", "--bind", f"{out}:/out",
|
| 26 |
+
"--bind", f"{ep}:/batch.json:ro", sif, "bash", "-lc", RUN]
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
def parse_smi(text):
|
| 30 |
+
"""nvidia-smi 'utilization.gpu, memory.used' csv rows to per-GPU lists."""
|
| 31 |
+
rows = [[int(v) for v in ln.split(",")] for ln in text.strip().splitlines() if ln.strip()]
|
| 32 |
+
return {"gpu_util": [r[0] for r in rows], "gpu_mem_mib": [r[1] for r in rows]}
|
| 33 |
+
|
| 34 |
+
|
| 35 |
+
def _solver(logdir):
|
| 36 |
+
"""pathfinder's 'MPC solver: ...' and CUDA fallback lines from the episode's ROS logs."""
|
| 37 |
+
lines = []
|
| 38 |
+
for dp, _, fns in os.walk(logdir):
|
| 39 |
+
for fn in fns:
|
| 40 |
+
try:
|
| 41 |
+
with open(os.path.join(dp, fn), errors="replace") as f:
|
| 42 |
+
lines += [ln.strip() for ln in f if "MPC solver:" in ln or "CUDA MPC unavailable" in ln]
|
| 43 |
+
except OSError:
|
| 44 |
+
pass
|
| 45 |
+
return "\n".join(dict.fromkeys(lines))
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
def main(argv=None):
|
| 49 |
+
p = argparse.ArgumentParser()
|
| 50 |
+
for a in ("episodes", "out", "sif", "engine", "stack", "work", "timeline", "done"):
|
| 51 |
+
p.add_argument("--" + a, required=True)
|
| 52 |
+
p.add_argument("--workers", type=int, required=True)
|
| 53 |
+
p.add_argument("--gpus", type=int, default=0)
|
| 54 |
+
a = p.parse_args(argv)
|
| 55 |
+
with open(a.episodes) as f:
|
| 56 |
+
q = queue.Queue()
|
| 57 |
+
for e in json.load(f): # the host already ordered them, longest first
|
| 58 |
+
q.put(e)
|
| 59 |
+
os.makedirs(a.out, exist_ok=True)
|
| 60 |
+
lock, t0 = threading.Lock(), time.time()
|
| 61 |
+
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)]
|
| 62 |
+
|
| 63 |
+
def log(**ev):
|
| 64 |
+
with lock, open(a.timeline, "a") as f:
|
| 65 |
+
f.write(json.dumps(dict(ev, t=round(time.time() - t0, 3))) + "\n")
|
| 66 |
+
|
| 67 |
+
def worker(i):
|
| 68 |
+
time.sleep(i * STAGGER_S)
|
| 69 |
+
while True:
|
| 70 |
+
try:
|
| 71 |
+
e = q.get_nowait()
|
| 72 |
+
except queue.Empty:
|
| 73 |
+
return
|
| 74 |
+
key, work = e["key"], os.path.join(a.work, e["key"])
|
| 75 |
+
stage, ep = os.path.join(work, "stage"), os.path.join(work, "ep.json")
|
| 76 |
+
os.makedirs(stage)
|
| 77 |
+
with open(ep, "w") as f:
|
| 78 |
+
json.dump([e], f)
|
| 79 |
+
log(ev="start", key=key, worker=i)
|
| 80 |
+
gpu = devs[i % len(devs)] if devs and e["resolved"].get("recipe", {}).get("sim", {}).get("cuda") else None
|
| 81 |
+
limit = EPISODE_TIMEOUT_S * max(1, e["resolved"]["scenario"].get("laps", 1)) # per lap: 5-lap episodes run 5x longer
|
| 82 |
+
try:
|
| 83 |
+
rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack, gpu), stdout=subprocess.DEVNULL,
|
| 84 |
+
stderr=subprocess.DEVNULL, timeout=limit).returncode
|
| 85 |
+
except subprocess.TimeoutExpired:
|
| 86 |
+
rc = "timeout"
|
| 87 |
+
solver = _solver(os.path.join(work, "tmp", "ros", "log"))
|
| 88 |
+
if solver and os.path.isdir(os.path.join(stage, key)):
|
| 89 |
+
with open(os.path.join(stage, key, "solver.txt"), "w") as f:
|
| 90 |
+
f.write(solver + "\n")
|
| 91 |
+
if os.path.exists(os.path.join(stage, key, "outcome.json")):
|
| 92 |
+
tmp, dst = os.path.join(a.out, ".tmp-" + key), os.path.join(a.out, key)
|
| 93 |
+
shutil.rmtree(tmp, ignore_errors=True)
|
| 94 |
+
shutil.copytree(os.path.join(stage, key), tmp)
|
| 95 |
+
shutil.rmtree(dst, ignore_errors=True)
|
| 96 |
+
os.rename(tmp, dst) # the host's rsync sees a key only once its directory is complete
|
| 97 |
+
with lock, open(a.done, "a") as f:
|
| 98 |
+
f.write(key + "\n")
|
| 99 |
+
shutil.rmtree(work, ignore_errors=True)
|
| 100 |
+
log(ev="end", key=key, worker=i, rc=rc, gpu=gpu,
|
| 101 |
+
solver=solver.split("MPC solver: ")[-1] if "MPC solver: " in solver else solver or None)
|
| 102 |
+
|
| 103 |
+
def sampler(stop):
|
| 104 |
+
"""Job CPU use from its cgroup, as busy cores, every SAMPLE_S."""
|
| 105 |
+
try:
|
| 106 |
+
with open("/proc/self/cgroup") as f:
|
| 107 |
+
path = "/sys/fs/cgroup" + f.read().strip().split(":")[-1] + "/cpu.stat"
|
| 108 |
+
prev = None
|
| 109 |
+
while not stop.wait(SAMPLE_S if prev else 0):
|
| 110 |
+
with open(path) as f:
|
| 111 |
+
use = next(int(ln.split()[1]) for ln in f if ln.startswith("usage_usec"))
|
| 112 |
+
now = time.time()
|
| 113 |
+
if prev:
|
| 114 |
+
log(ev="cpu", busy_cores=round((use - prev[0]) / 1e6 / (now - prev[1]), 2))
|
| 115 |
+
prev = (use, now)
|
| 116 |
+
except (OSError, StopIteration, ValueError):
|
| 117 |
+
pass
|
| 118 |
+
|
| 119 |
+
def gpu_sampler(stop):
|
| 120 |
+
"""GPU utilisation and memory of the job's GPUs, every SAMPLE_S."""
|
| 121 |
+
while not stop.wait(SAMPLE_S):
|
| 122 |
+
try:
|
| 123 |
+
p = subprocess.Popen(["nvidia-smi", "--query-gpu=utilization.gpu,memory.used", "--format=csv,noheader,nounits"],
|
| 124 |
+
stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True)
|
| 125 |
+
log(ev="gpu", **parse_smi(p.communicate(timeout=30)[0]))
|
| 126 |
+
except Exception: # no driver or a hung query: skip this sample
|
| 127 |
+
pass
|
| 128 |
+
|
| 129 |
+
cores = len(os.sched_getaffinity(0)) if hasattr(os, "sched_getaffinity") else os.cpu_count()
|
| 130 |
+
log(ev="launch", workers=a.workers, cores=cores)
|
| 131 |
+
stop = threading.Event()
|
| 132 |
+
threads = [threading.Thread(target=worker, args=(i,)) for i in range(a.workers)]
|
| 133 |
+
samplers = [sampler] + ([gpu_sampler] if a.gpus else [])
|
| 134 |
+
for t in threads + [threading.Thread(target=f, args=(stop,), daemon=True) for f in samplers]:
|
| 135 |
+
t.start()
|
| 136 |
+
for t in threads:
|
| 137 |
+
t.join()
|
| 138 |
+
stop.set()
|
| 139 |
+
log(ev="done")
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
if __name__ == "__main__":
|
| 143 |
+
main()
|
results/jobs/20261008-023954-idea-adaptive-steer/job.json
ADDED
|
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"id": "20261008-023954-idea-adaptive-steer",
|
| 3 |
+
"tier": "dev",
|
| 4 |
+
"tier_version": 2,
|
| 5 |
+
"recipe": {
|
| 6 |
+
"name": "idea-adaptive-steer",
|
| 7 |
+
"source": {
|
| 8 |
+
"repo": "AutonomousKart",
|
| 9 |
+
"ref": "worktree:adaptive-steer"
|
| 10 |
+
},
|
| 11 |
+
"params": {
|
| 12 |
+
"pathfinder_node": {
|
| 13 |
+
"mpc.num_samples": 4096
|
| 14 |
+
}
|
| 15 |
+
},
|
| 16 |
+
"sim": {
|
| 17 |
+
"cuda": true
|
| 18 |
+
},
|
| 19 |
+
"notes": "Base + online RLS steering-to-yaw gain from IMU yaw rate rescales the MPC rollout steer map (mpc.adaptive_gain.enabled)"
|
| 20 |
+
},
|
| 21 |
+
"user": "shay",
|
| 22 |
+
"notes": "adaptive-steer dev",
|
| 23 |
+
"where": "ideas",
|
| 24 |
+
"status": "done",
|
| 25 |
+
"submitted_at": "2026-10-08T06:39:54.396+00:00",
|
| 26 |
+
"started_at": "2026-10-08T06:39:54.396+00:00",
|
| 27 |
+
"finished_at": "2026-10-08T07:37:35.356+00:00",
|
| 28 |
+
"total": 558,
|
| 29 |
+
"done": 558,
|
| 30 |
+
"errors": 0,
|
| 31 |
+
"build_log": null,
|
| 32 |
+
"workers": 10,
|
| 33 |
+
"slurm_id": "928232",
|
| 34 |
+
"slurm_ids": [
|
| 35 |
+
"928232"
|
| 36 |
+
],
|
| 37 |
+
"engine_version": "10f2000722b663fb4aff189ffeffaf827254d41cf3fc0dee742b7109ee1ffaf3"
|
| 38 |
+
}
|
results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0000.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c0cf8b729adff29143988a5b7e2122434b2b33fd9f2d112c5418f91141b0fedf
|
| 3 |
+
size 98765055
|
results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0001.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e23084f7144d17e67ca26408c6ebffa94e66881e1e893b2bdb17296ae931678c
|
| 3 |
+
size 111859077
|
results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0002.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:50b1582f1e8d0e2be66225d6ec6151dddd9d980ef0c7631ad46f98b6994eca9b
|
| 3 |
+
size 120494262
|
results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0003.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:69abcbe8b9e8c827456e6f31b38cdd6d033db60cb08b47d803c07996390f8380
|
| 3 |
+
size 78147307
|
results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0004.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:635298a1de68bafc50cde3e6336cec0a819ba62488e01ef3fbc25d35088ef751
|
| 3 |
+
size 29165427
|
results/jobs/20261008-023954-idea-adaptive-steer/logs/shard-0005.jsonl.gz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4febd6cc535934adbed44c7f67faf37eb2f2d186166f7187ebce79bb705382d4
|
| 3 |
+
size 27599772
|