results: jobs/20261005-163445-stack-default/** index/episodes.jsonl leaderboard/*

results/index/episodes.jsonl

@@ -177,3 +177,18 @@
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 {"key": "af8400e41ced380dd2e68b79d882b42117d7903001688f5c5c3557057c7abb95", "job_id": "20261005-164836-stack-default", "shard": "jobs/20261005-164836-stack-default/logs/shard-0000.jsonl.gz"}
 {"key": "78dd1b3249e2c536852cc160ff07b1081bfd2d81b10103e4c9590aedd9db379c", "job_id": "20261005-164836-stack-default", "shard": "jobs/20261005-164836-stack-default/logs/shard-0000.jsonl.gz"}
+{"key": "ed92ccb53967d67d2503eccaf5fb3c1d848362a3930445b48637691f1479c19e", "job_id": "20261005-163445-stack-default", "shard": "jobs/20261005-163445-stack-default/logs/shard-0000.jsonl.gz"}
+{"key": "f36937dc9040e6f26b72bde113aa9406a45c6ea896d28ac97b75df109fd3ab1a", "job_id": "20261005-163445-stack-default", "shard": "jobs/20261005-163445-stack-default/logs/shard-0000.jsonl.gz"}
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results/jobs/20261005-163445-stack-default/breakdown.json

@@ -0,0 +1,232 @@
+{
+ "laps": {
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+    ]
+   }
+  }
+ }
+}

results/jobs/20261005-163445-stack-default/gautschi/0/done.txt

@@ -0,0 +1,12 @@
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results/jobs/20261005-163445-stack-default/gautschi/0/episodes.json

@@ -0,0 +1 @@
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"notes": "Gautschi smoke gate (cached episodes)"}, "scenario": {"type": "clip", "clip_id": "20260520_223739_00263"}, "seed": 130671560, "tier": "smoke", "engine_version": "47060c1a6ce8e8829f5c7dc24f645fae82470006fcdce3eca7882afe7bf0ac30"}}]

results/jobs/20261005-163445-stack-default/gautschi/0/gautschi_launch.py

@@ -0,0 +1,99 @@
+"""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")
+SAMPLE_S = 15
+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):
+    """Private /tmp, HOME, /dev/shm, IPC, PIDs and loopback per episode, plus a distinct ROS_DOMAIN_ID per worker."""
+    return ["apptainer", "exec", "--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 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)
+    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()
+
+    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):
+        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)
+            try:
+                rc = subprocess.run(worker_cmd(i, work, stage, ep, a.sif, a.engine, a.stack), stdout=subprocess.DEVNULL,
+                                    stderr=subprocess.DEVNULL, timeout=EPISODE_TIMEOUT_S).returncode
+            except subprocess.TimeoutExpired:
+                rc = "timeout"
+            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)
+
+    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
+
+    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)]
+    for t in threads + [threading.Thread(target=sampler, args=(stop,), daemon=True)]:
+        t.start()
+    for t in threads:
+        t.join()
+    stop.set()
+    log(ev="done")
+
+
+if __name__ == "__main__":
+    main()

results/jobs/20261005-163445-stack-default/gautschi/0/sbatch.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+#SBATCH -p highmem -A lilly-rob1 -N 1 -n 1 -c 96 --time 15 -J AutoSim-smoke --comment 20261005-163445-stack-default -o AutoSim/jobs/20261005-163445-stack-default/0/slurm-%j.out
+W=/dev/shm/AutoSim-$SLURM_JOB_ID
+trap 'rm -rf "$W"' EXIT
+python3 $HOME/AutoSim/jobs/20261005-163445-stack-default/0/gautschi_launch.py --episodes $HOME/AutoSim/jobs/20261005-163445-stack-default/0/episodes.json --out $HOME/AutoSim/out/20261005-163445-stack-default --sif $HOME/AutoSim/images/AutoSim-99d206f40cb1.sif --engine $HOME/AutoSim/engine/47060c1a6ce8e8829f5c7dc24f645fae82470006fcdce3eca7882afe7bf0ac30 --stack $HOME/AutoSim/stacks/7863aec63eeb92ac0efa1bd4a1a90aa542a058d75c089b3c2b48a8ed249cd2b5 --workers 15 --work $W --timeline $HOME/AutoSim/jobs/20261005-163445-stack-default/0/timeline.jsonl --done $HOME/AutoSim/jobs/20261005-163445-stack-default/0/done.txt

results/jobs/20261005-163445-stack-default/job.json

@@ -0,0 +1,35 @@
+{
+ "id": "20261005-163445-stack-default",
+ "tier": "smoke",
+ "tier_version": 2,
+ "recipe": {
+  "name": "stack-default",
+  "source": {
+   "repo": "AutonomousKart",
+   "ref": "worktree:AutonomousKart-sim"
+  },
+  "params": {
+   "pathfinder_node": {
+    "mpc.num_samples": 128
+   }
+  },
+  "notes": "Gautschi smoke gate (cached episodes)"
+ },
+ "user": "overnight",
+ "notes": "Gautschi smoke gate (cached episodes)",
+ "where": "gautschi",
+ "status": "done",
+ "submitted_at": "2026-10-05T20:34:45.126+00:00",
+ "started_at": "2026-10-05T20:34:45.804+00:00",
+ "finished_at": "2026-10-05T20:54:32.706+00:00",
+ "total": 15,
+ "done": 15,
+ "errors": 0,
+ "build_log": null,
+ "workers": 15,
+ "slurm_id": "16872777",
+ "slurm_ids": [
+  "16872777"
+ ],
+ "engine_version": "47060c1a6ce8e8829f5c7dc24f645fae82470006fcdce3eca7882afe7bf0ac30"
+}

results/jobs/20261005-163445-stack-default/logs/shard-0000.jsonl.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e22c651f31f1e7f6581e6ed58f6b6e76e8d50dd78872c623810ba1f12afb9b4e
+size 1736919

results/jobs/20261005-163445-stack-default/summary.json

@@ -0,0 +1,156 @@
+{
+ "cte_p50": {
+  "value": 0.21981491620242388,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.31756862483185877,
+   "kart2": 0.12936335987227482,
+   "kart3": 0.26091713005371253
+  }
+ },
+ "cte_p90": {
+  "value": 0.9554030297434453,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.9740012187811011,
+   "kart2": 1.1803039324305087,
+   "kart3": 0.8841605086770282
+  }
+ },
+ "cte_p99": {
+  "value": 2.1861458427069578,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 1.6425442099899141,
+   "kart2": 2.9162904389070863,
+   "kart3": 1.5334141075318903
+  }
+ },
+ "recovery_rate": {
+  "value": 0.3333333333333333,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.3333333333333333,
+   "kart2": 0.3333333333333333,
+   "kart3": 0.3333333333333333
+  }
+ },
+ "recovery_s_median": {
+  "value": 2.833500000000001,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 2.867000000000001,
+   "kart2": 0.8335000000000008,
+   "kart3": 2.833500000000001
+  }
+ },
+ "safety": {
+  "value": 0.2778175662478027,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.2785802723895998,
+   "kart2": 0.275207806288399,
+   "kart3": 0.2799758987748546
+  }
+ },
+ "unsafe_lat": {
+  "value": 0.004622696790155488,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.005365249690466223,
+   "kart2": 0.0,
+   "kart3": 0.009037959429604102
+  }
+ },
+ "unsafe_rate": {
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+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.7063557573256293,
+   "kart2": 0.7099747018431516,
+   "kart3": 0.7055633661377786
+  }
+ },
+ "unsafe_travel": {
+  "value": 0.0,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.0,
+   "kart2": 0.0,
+   "kart3": 0.0
+  }
+ },
+ "unsafe_spin": {
+  "value": 0.00032554202747574033,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.00041271151465124796,
+   "kart2": 0.0,
+   "kart3": 0.0006025306286402788
+  }
+ },
+ "unsafe_off": {
+  "value": 0.05169607396314835,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 0.05076351630210455,
+   "kart2": 0.06396819660281859,
+   "kart3": 0.038963647318738436
+  }
+ },
+ "osc_10": {
+  "value": 45.70207102093434,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 49.422497173715136,
+   "kart2": 42.22026767726184,
+   "kart3": 45.95093918070698
+  }
+ },
+ "osc_20": {
+  "value": 23.089263073281273,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 26.32895997369315,
+   "kart2": 13.671099765693434,
+   "kart3": 30.40409427729717
+  }
+ },
+ "osc_30": {
+  "value": 12.507476171823306,
+  "worst_kart": null,
+  "per_kart": {
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+   "kart2": 6.687532938167334,
+   "kart3": 17.18927610939883
+  }
+ },
+ "laps_pct": {
+  "value": 100.0,
+  "worst_kart": null,
+  "per_kart": {
+   "kart1": 100.0,
+   "kart2": 100.0,
+   "kart3": 100.0
+  }
+ },
+ "failures": {
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+  "worst_kart": null,
+  "per_kart": {
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+   "kart2": 3,
+   "kart3": 3
+  }
+ },
+ "n": {
+  "value": 15,
+  "worst_kart": null,
+  "per_kart": {}
+ },
+ "errors": {
+  "value": 0,
+  "worst_kart": null,
+  "per_kart": {}
+ }
+}

results/leaderboard/smoke-2__47060c1a6ce8.json

@@ -0,0 +1,48 @@
+[
+ {
+  "job_id": "20261005-163445-stack-default",
+  "recipe": "stack-default",
+  "notes": "Gautschi smoke gate (cached episodes)",
+  "user": "overnight",
+  "ran_at": "2026-10-05T20:54:32.706+00:00",
+  "duration_s": 1186.902,
+  "cte_p50": 0.21981491620242388,
+  "cte_p90": 0.9554030297434453,
+  "cte_p99": 2.1861458427069578,
+  "recovery_rate": 0.3333333333333333,
+  "recovery_s_median": 2.833500000000001,
+  "safety": 0.2778175662478027,
+  "unsafe_lat": 0.004622696790155488,
+  "unsafe_rate": 0.7074028257047984,
+  "unsafe_travel": 0.0,
+  "unsafe_spin": 0.00032554202747574033,
+  "unsafe_off": 0.05169607396314835,
+  "osc_10": 45.70207102093434,
+  "osc_20": 23.089263073281273,
+  "osc_30": 12.507476171823306,
+  "laps_pct": 100.0,
+  "failures": 9,
+  "n": 15,
+  "errors": 0,
+  "worst": {
+   "cte_p50": 0.31756862483185877,
+   "cte_p90": 1.1803039324305087,
+   "cte_p99": 2.9162904389070863,
+   "recovery_rate": 0.3333333333333333,
+   "recovery_s_median": 2.867000000000001,
+   "safety": 0.275207806288399,
+   "unsafe_lat": 0.009037959429604102,
+   "unsafe_rate": 0.7099747018431516,
+   "unsafe_travel": 0.0,
+   "unsafe_spin": 0.0006025306286402788,
+   "unsafe_off": 0.06396819660281859,
+   "osc_10": 49.422497173715136,
+   "osc_20": 30.40409427729717,
+   "osc_30": 17.18927610939883,
+   "laps_pct": 100.0,
+   "failures": 3,
+   "n": 15,
+   "errors": 0
+  }
+ }
+]