diff --git a/experiments/e54-boundary-faults/FINDINGS.md b/experiments/e54-boundary-faults/FINDINGS.md new file mode 100644 index 0000000..b28090b --- /dev/null +++ b/experiments/e54-boundary-faults/FINDINGS.md @@ -0,0 +1,143 @@ +# E54: a fault at the boundary passes the status rule almost always; byte-identical weights or reconciliation with an env-side record catches every one + +2026-10-02 · guangzhao (bridges-venv: torch 2.14.1+cpu, SB3 2.9.0, gymnasium +1.3.0, mujoco 3.14.0), 10 runs at a time · protocol: +[`PROTOCOL.md`](PROTOCOL.md), after the pilots in `results/pilot/`, before +the registered runs · no amendment + +--- + +## The result + +590 registered runs. SB3's PPO trained Pendulum and HalfCheetah through the +bridge, as in E50, while the env client changed one field of what crossed, +in one way. There were 21 client faults and 2 faults in the trainer's log, +at doses from one value to every value. + +**Share of runs with a changed value caught by each check**, seeds 0-2, +client and log faults together: + +| env | dose | runs | status rule | strict | weights | record | weights or record | +| --- | --- | --- | --- | --- | --- | --- | --- | +| Pendulum | one value | 69 | 0% | 0% | 91% | 28% | **100%** | +| | 0.1% | 63 | 0% | 8% | 100% | 29% | **100%** | +| | 1% | 69 | 4% | 6% | 91% | 35% | **100%** | +| | 10% | 69 | 4% | 19% | 91% | 35% | **100%** | +| | every value | 69 | 39% | 55% | 91% | 30% | **100%** | +| HalfCheetah | one value | 69 | 4% | 4% | 91% | 33% | **100%** | +| | 1% | 69 | 9% | 9% | 91% | 35% | **100%** | +| | every value | 69 | 32% | 46% | 91% | 33% | **100%** | + +The weights miss exactly the log faults, at 9% of the runs. Counting client +faults alone, they caught 100% at every dose on both envs. + +Every check and prediction holds (`results/verdicts.txt`): +- **V1:** all 590 runs completed but the loud faults', which raised. +- **V2:** the fault-free runs ended on E50's weights at seeds 0-2, for both + envs (`ec5b8226`, `062e92e3`, `3a8d968f`; `8261c03a`, `86564694`, + `65cc8843`), with 10 runs at a time on the machine. +- **P1:** the weights differed in all 504 client-fault runs with a changed + value. +- **P2:** they were the fault-free weights in all 48 control and log-fault + runs. +- **P3:** on Pendulum the status rule caught 0, 0, 3, 3 and 27 of 69, 63, + 69, 69 and 69 runs at the five doses, under the caps of 10% and 60%. +- **P4:** the record caught every run it was predicted to catch, and none it + was predicted not to. +- **P5:** the bridge's own log caught all 42 log-fault runs and none of the + 504 client-fault runs. +- **P6:** weights or record caught all 546 silent runs with a changed value. +- **P7:** both loud faults raised at every seed, about 9.5 s into the run. +- **P8:** the first difference located all 351 traced Pendulum runs: their + step, env and field. +- **P9:** on HalfCheetah the status rule caught 3 and 6 of 69 at one value + and 1%. + +--- + +## What it means + +**A curve cannot tell a fault from a seed.** One changed value in 102,400 +moved Pendulum's final return from its seed's fault-free run by a median of +14, and HalfCheetah's by a median of 67. The fault-free runs at seeds 10-19 +spread with a standard deviation of 11 and 146. So one value changes the +outcome about as much as a change of seed. A run with a fault was at least +as likely to look better as worse: at one value, 43 of 63 Pendulum runs and +33 of 60 HalfCheetah runs ended above the fault-free run at their own seed. +- The status rule asks only whether the policy learned at all. It caught a + fault in two cases: + - when the fault broke learning: zeroed or swapped observations, actions + or rewards at every value, and spurious terminations; + - when it left the log with no episodes: every step skipped, every time + limit dropped. +- The strict check, against ten fault-free seeds, had few false alarms (0 + of 10 and 1 of 10 seeds judged against the other nine). It caught little + more, because it can only see what moves a final return beyond the seeds' + spread. +- Some faults made the log look better. With every reward zeroed, Pendulum + logged its best possible return, 0. Spurious terminations cut Pendulum's + episodes short, and short episodes lose less. + +**Byte identity sees every change to what training receives, and nothing +else.** A fault changed the weights whenever it changed one value that +crossed, at every dose and on both envs. Time (`delay-1ms`) and +representation (`wire-float64`) did not change them, and neither did a +fault in the log. + +**Reconciliation sees what changes the books.** The trainer's log and the +client's record disagreed whenever a fault changed: +- a reward, beyond the record's tolerance; +- an episode end; +- a step; +- the log itself. + +Faults in observations, actions and final observations, and a time limit +sent as a termination, left the episodes as the environment produced them. +It could not see those. It could not see a reward changed by less than its +tolerance either: `reward:f16` at any dose, or `reward:zero` and +`reward:stale` at one value. + +**The two checks cover each other.** Between them they caught every one of +the 546 silent runs. The two faults the bridge rejects raised at once. + +**Where the record is kept matters.** The bridge's own log counts the +rewards as they arrive on the trainer's side of the wire. It caught every +fault in the trainer's log and no fault in the client's: by the time a +client fault reaches the bridge, the bridge counts what it was sent. A +record that is to catch a client's faults has to be kept by the client, +next to the environment. + +**A fault can be located.** On one machine the fault-free run is +deterministic, so a faulted run crosses the same bytes up to the fault. The +first difference named the fault's step, env and field in all 351 traced +runs. + +--- + +## What E54 does not show + +* **Faults on any trainer but SB3, or any env but these two.** Both envs + are forgiving: a policy still learns through most faults. +* **Byte identity across machines.** It needs a fault-free run on the same + machine (E50). E55 tests a check that does not. +* **Faults the protocol's checkers would catch.** Only the bridge's own + validation was in the loop. +* **Faults chosen at random.** The cells were; the faults were chosen to + cover every field that crosses and the ways it goes wrong in practice. The + paper maps each to a fault found in a real library. + +Kept here, in `results/`: +- `runs.jsonl`: every run's `result.json` and `fault.json`, and the last + line of its logs (`merge_runs.py`); +- `runs.csv`: every check's verdict on every run (`summarise.py`), and + `by_dose.csv`, `summary.txt`; +- `localisation.csv` (`localise.py`) and `verdicts.txt` (`verdicts.py`); +- `jobs.txt`, `registered.out`, `load.txt`, and the sources' hashes. + +The per-run directories are kept on guangzhao and not committed: +- the per-episode logs behind the record checks (`monitor.csv`, + `episodes.csv`, `env_record.csv`: 100 MB, 18 MB compressed); +- the traces and the final policies. + +A run is deterministic on its machine, so rerunning its line of `jobs.txt` +there reproduces them byte for byte. diff --git a/experiments/e54-boundary-faults/PROTOCOL.md b/experiments/e54-boundary-faults/PROTOCOL.md new file mode 100644 index 0000000..3d93ba0 --- /dev/null +++ b/experiments/e54-boundary-faults/PROTOCOL.md @@ -0,0 +1,250 @@ +# E54 measurement protocol (pre-registered) + +**Written 2026-10-02, after the pilots in `results/pilot/`, before the +registered runs.** + +This file must not be edited after the first registered data point. Anything +learned afterwards goes in `AMENDMENT.md`, dated. + +--- + +## The question + +Across machines and languages, where byte identity is impossible, E43, E44, +E48 and E49 judge a boundary by a status rule: the policy still learns. E51 +and the failures in the paper's Table III show that faults at a boundary can +raise no error. So: + +**When something goes wrong at the environment-trainer boundary, which +checks notice? For each field that crosses the wire and each way it can go +wrong, from one cell to every cell, does each of these catch it:** +- **the status rule** the paper uses across machines; +- **a strict curve check**: the final return against ten fault-free seeds; +- **byte identity**: the final weights against the fault-free run at the same + seed, on the same machine; +- **reconciliation**: the trainer's log of episodes against a record kept + where the environments produce the rewards; +- **the bridge's own log**, which counts on the trainer's side of the wire? + +**And can the first difference from the fault-free run say where the fault +is?** + +--- + +## Declared in advance: what was already known + +1. **The code**, synced to guangzhao and hashed into each run's directory. + - `train.py`: E50's bridge arm (SB3 2.9.0 PPO, 16 envs, one torch thread, + CPU, VecMonitor, `PPO(seed=s)`), with `--fault`, `--dose` and `--trace`. + Pendulum-v1 at rl-zoo's settings for 102,400 steps; HalfCheetah-v5 at + SB3's defaults for 409,600 steps, both as in E50. The bridge's timeout is + 60 s, so a run whose client is gone stops at once. + - `faulty_client.py`: E50's client, plus the faults, and a record of each + episode's return and length as the environments produced them, before + any fault. + - `jobs.py`, `run.sh`: the runs, 10 at a time, each on its own port. + - `localise.py`, `summarise.py`: the judgements below. +2. **The faults** (`faulty_client.py`'s docstring has each one). + - **Client faults, 21.** Four fields with value operators: + - `obs` (the infer observation), `action` (as the client applies it), + `reward`, and `final-obs` (the observation an episode ended on); + - operators: `zero`, `stale` (the step before's), `swap` (the next + slot's), `f16` (rounded through float16), and for `action` also `clip` + (to half its range). + - Plus `terminated:spurious`, `truncated:drop`, `truncated:as-term` and + `step:fill` (an env not stepped, its feedback filled in). + - **Log faults, 2**, in the trainer's VecMonitor: `log:drop-first` (the + return without the episode's first reward) and `log:short` (the length + one short). E51 found both in Gymnasium 1.3. + - **Loud faults, 2**, which the bridge rejects: `indices:reorder` and + `reward:short-array`. + - **Controls, 3**: `none`, `delay-1ms`, `wire-float64`. +3. **The doses.** `one` is a single cell, in env 0, the first eligible one at + or after vector step 3,250 whose value the operator changes. `0.001`, + `0.01`, `0.1`, `1.0` hit each eligible cell with that probability. The + cells are drawn from a generator seeded 54, so every training seed gets the + same ones. Each run counts the cells its fault changed. +4. **The pilots**, at seed 9, in `results/pilot/`. There were three. + - **v1** (`results/pilot/v1.txt`): 13 hand-picked faults, each at every + cell. + - The fault-free run ended on E50's pilot weights (`3721266c`), as did + `delay-1ms` and `wire-float64`. Every other fault changed the + weights. + - The status rule caught one fault of ten (slot-shifted rewards). + - The fault-free run was the worst of the thirteen, at -680 against + about -200 for most faults: seed 9 is an unlucky seed. + - This pilot led to the design here: every field with every operator, + at five doses. Its client and `train.py` were replaced by this + design's; only its summary is kept. + - **v2** (`results/pilot/v2.txt`): this design at seed 9. Two flaws, fixed + before v3: + - The one-cell dose sat on an episode's last step. That turned + `terminated:spurious` into a time limit sent as a termination. + - The localiser looked at messages before envs. + - Also changed for v3: a one-cell dose moves on to the next cell when + the operator would not change the value (`action:clip` within range + had changed nothing). + - **v3** (`results/pilot/v3.txt`) ran this protocol's code, except the + strict check's false-alarm count, which was added to `summarise.py` + after v3 started. In it: + - **weights** caught every client-fault run at every dose (105 of 105), + and no control or log-fault run; + - **rule** caught 0, 0, 1, 1 and 9 of the 21 client faults at doses + one, 0.001, 0.01, 0.1 and 1.0. Two of those it caught looked better + than the fault-free run, not worse: with every reward zeroed, the log + showed a perfect return of 0, and spurious terminations made short + episodes with small returns; + - **record** caught 4, 6, 6, 6 and 5 of the 21, and both log faults at + every dose with a changed cell. It missed every `reward:f16`, and + `reward:zero` and `reward:stale` at one cell, whose change to a + return is under its tolerance; + - **bridge** caught the log faults and nothing else; + - weights or record caught every run with a changed cell; + - both loud faults raised at once (ClientLost, once the bridge closed + the connection); + - localisation was right in 117 of 117 traced runs; + - HalfCheetah at seed 9: + - `none` ended on E50's pilot weights (`0260ca9d`); + - `reward:stale` at one cell and `obs:f16` at 0.01 changed the + weights and passed the rule; + - record caught the first. + - The strict check could not be judged in the pilots: there was no band. + The seeds' final returns are not normal: E50's seeds 0-2 ended near + -200, and seed 9 at -680. + +--- + +## Design + +On guangzhao, `bash run.sh results registered`: `jobs.py registered`, 10 runs +at a time, ports 8854-8863. +- **Pendulum, seeds 0, 1, 2:** the 3 controls; the 23 client and log faults + at the 5 doses; the 2 loud faults at one cell. Every run traced. That is + 3 x (3 + 115 + 2) = 360 runs. +- **Pendulum, seeds 10-19:** fault-free, for the strict check's band. 10 + runs. +- **HalfCheetah, seeds 0, 1, 2:** `none`; the 23 client and log faults at + doses `one`, `0.01` and `1.0`. Not traced. 3 x (1 + 69) = 210 runs. +- **HalfCheetah, seeds 10-19:** fault-free. 10 runs. + +590 runs in all. Then `python localise.py results` and `python summarise.py +results`. + +--- + +## How each check is judged + +Batches are 16 consecutive episodes of a log. A check **catches** a run's +fault when: +- **raises:** the run stopped on an error. +- **rule:** the trainer's log fails the env's status rule, the one E44 (for + Pendulum) and E43 and E48 (for HalfCheetah) used: + - Pendulum: batches 20 to the last at least 500 above batches 1-2. + - HalfCheetah: batches 21-25 at least 200 above batch 1. + - A log too short to have those batches fails. +- **strict:** the mean of those last batches, in the trainer's log, is more + than 3 standard deviations from the mean over the fault-free runs at seeds + 10-19. +- **weights:** the final weights' SHA-256 differs from the fault-free run's + at the same seed. +- **record:** the trainer's log and the client's record differ in the number + of episodes, or in an episode's length, or in its return by more than + 1e-4 relative plus 0.01 (E49's tolerance). Episodes are compared in the + order they ended, then by env. +- **bridge:** the same comparison, between the trainer's log and the + bridge's. + +A run whose fault changed no cell is reported and counted as neither caught +nor missed. + +**Localisation** (`localise.py`) is judged on every traced run. On one +machine the fault-free run at a seed is deterministic, so a faulted run +crosses the same bytes up to the fault. The localiser finds three things: +- the first vector step at which anything the trainer sent or received + differs; +- the lowest env that differs at that step; +- the first of that env's messages that differs. + +It is **right** when: +- that step and env are the fault's first changed cell; +- the message is the one the fault touches (`localise.py` maps each); +- for a control, a log fault, or a run whose fault changed no cell, the + wire is identical. + +--- + +## Checks that the runs are valid + +- **V1:** every run but the loud faults' reaches its steps, with its client + exiting 0. +- **V2:** `none` ends on E50's weights at seeds 0, 1 and 2, for both envs + (`ec5b8226`, `062e92e3`, `3a8d968f`; `8261c03a`, `86564694`, `65cc8843`). + This holds with 10 runs at a time on the machine. + +A run that fails V1 is a defect to find, not a finding about a check. + +--- + +## Predictions, and what falsifies each + +**P1 - Byte identity sees every change.** Every client-fault run whose +fault changed at least one cell ends on weights that differ from the +fault-free run's at its seed. This holds on both envs, at every dose. +Falsified by one such run on the fault-free weights. + +**P2 - and nothing else.** Every `delay-1ms`, `wire-float64` and log-fault +run ends on the fault-free run's weights at its seed. Falsified by one that +does not. + +**P3 - The status rule misses most faults.** On Pendulum, client- and +log-fault runs with a changed cell: +- at doses one, 0.001, 0.01 and 0.1, the rule catches at most 10% at each + dose; +- at dose 1.0, at most 60%. +Falsified by more at any dose. + +**P4 - Reconciliation sees what changes the books, and only that.** +- It catches every run of these, at every dose with a changed cell except + one cell: + - `reward:zero`, `reward:stale`, `reward:swap`; + - `terminated:spurious`, `truncated:drop`. +- It catches `step:fill` at doses 0.001 to 0.1, and both log faults at every + dose with a changed cell. +- It catches no run of any `obs`, `action` or `final-obs` fault, nor of + `truncated:as-term`. +- Falsified by one run against any of these. +- Reported, not predicted: + - `reward:f16` at every dose; + - the reward faults at one cell; + - `step:fill` at 1.0, where no env ever steps, so no episode is logged on + either side. + +**P5 - The bridge's log sees only the trainer's side.** It disagrees with the +trainer's log in every log-fault run with a changed cell, and in no +client-fault run. Falsified by one run against either. + +**P6 - Byte identity or reconciliation catches every silent fault.** Every +client- and log-fault run with a changed cell is caught by weights or by +record, on both envs. Falsified by one that neither catches. + +**P7 - The bridge rejects the loud faults.** Both raise at every seed, and +end in under 120 s. Falsified by one that does not. + +**P8 - The first difference localises the fault.** Localisation is right in +every traced run. Falsified by one wrong. + +**P9 - HalfCheetah too.** The status rule catches at most 10% of client- and +log-fault runs with a changed cell at doses one and 0.01. Falsified by more +at either dose. + +> Grounds: v3, above. The margins of P3 and P9 are wide because v3 had one +> seed. The exclusions in P4 follow from what the record compares, returns +> and lengths. A fault that changes neither is invisible to it by +> construction: which flag ends an episode, for example. + +**Reported, not predicted:** +- the strict check at every dose, for both envs; +- its false alarms: each fault-free seed in 10-19 judged against the band + of the other nine; +- every run's final return, cells changed and wall clock; +- HalfCheetah at dose 1.0, by every check. diff --git a/experiments/e54-boundary-faults/faulty_client.py b/experiments/e54-boundary-faults/faulty_client.py new file mode 100644 index 0000000..56cbd42 --- /dev/null +++ b/experiments/e54-boundary-faults/faulty_client.py @@ -0,0 +1,361 @@ +"""E54's env client: E50's gym_client.py, with one fault injected at the boundary. + + python faulty_client.py --port 8854 --seed 0 --fault reward:stale --dose 0.01 \ + --record runs/.../env_record.csv + +With --fault none it sends exactly what E50's client sent. Otherwise it +changes one field of what crosses the wire, with one operator, in a share of +the cells (vector step, env) where that field crosses. The environments +themselves are untouched, and --record writes each episode's return and +length as the environments produced them, before any fault: the record a +trainer's log can be checked against. + +Fields and operators. Each field takes the operators that make sense for it: + obs the observation in an infer (what the policy acts on) + action the action the client applies (as it decodes the reply) + reward the reward in a feedback + final-obs the observation an episode ended on, in its feedback (SB3 + bootstraps from it at a time limit) + zero the value replaced by zeros (a default filled in) + stale the value from the step before (a buffer reused) + swap the value from the next slot, (i + 1) mod n (a slot mixed up) + f16 the value rounded through float16 (a lossy encoding) + clip (action only) clipped to half its range: [-1, 1] for Pendulum's + [-2, 2] (a client that assumes another range) + terminated:spurious sent true where the episode did not end + truncated:drop a time limit is not sent: the client resets, the trainer + sees the episode go on + truncated:as-term a time limit is sent as a termination + step:fill the env is not stepped, and its feedback is filled in: + reward 0, the same observation, no episode end +(log:drop-first and log:short are the trainer's log's, in train.py.) + +Faults the bridge rejects, at one cell; the run is expected to fail loudly: + indices:reorder a feedback's rows, env_indices included, in reverse order + reward:short-array a feedback with one reward too few + +Controls, which change nothing training receives: + none, delay-1ms (sleep 1 ms before each feedback), wire-float64 + (observations sent as float64; the values are Pendulum's float32s). + +Doses: "one" is a single cell: in env 0, the first eligible one at or after +vector step 3,250 (no episode ends there) whose value the operator changes; a number p is each eligible cell with probability p, drawn +from a generator seeded 54 whatever the training seed, so every seed gets the +same cells. --record's sibling fault.json counts the cells whose value the +fault actually changed. +""" + +from __future__ import annotations + +import argparse +import csv +import json +import pathlib +import time + +import gymnasium as gym +import numpy as np +import websockets.exceptions +import websockets.sync.client + +from plugrl_protocol import msgpack_numpy + +STOP_REASON = "plugrl-server-stop" +CONTROLS = ("none", "delay-1ms", "wire-float64") +VALUE_OPS = ("zero", "stale", "swap", "f16") +SILENT = ( + tuple(f"obs:{op}" for op in VALUE_OPS) + + tuple(f"action:{op}" for op in VALUE_OPS + ("clip",)) + + tuple(f"reward:{op}" for op in VALUE_OPS) + + tuple(f"final-obs:{op}" for op in VALUE_OPS) + + ("terminated:spurious", "truncated:drop", "truncated:as-term", "step:fill") +) +LOUD = ("indices:reorder", "reward:short-array") +FAULTS = CONTROLS + SILENT + LOUD +ONE_STEP = 3_249 # 0-based: the 3,250th vector step, not an episode's last + + +def observation(obs: np.ndarray, fault: str) -> dict: + if fault == "wire-float64": + obs = obs.astype(np.float64) + return {"images": {}, "states": {"obs": obs}, "text": "gym"} + + +def connect(uri: str, deadline: float): + while True: + try: + return websockets.sync.client.connect( + uri, compression=None, max_size=None, open_timeout=10 + ) + except (OSError, websockets.exceptions.InvalidHandshake): + if time.monotonic() > deadline: + raise + time.sleep(0.1) + + +class Selector: + """Which cells a fault hits: the same ones for every training seed.""" + + def __init__(self, n: int, dose: str) -> None: + self.n = n + self.dose = dose + self.rng = np.random.default_rng(54) + self.one_done = False + self.hit_now = False + self.u = np.ones(n) + + def draw(self) -> None: + self.u = self.rng.random(self.n) # one draw per vector step, always + self.hit_now = False + + def hits(self, step: int, eligible: np.ndarray) -> np.ndarray: + if self.dose == "one": + out = np.zeros(self.n, dtype=np.bool_) + if not self.one_done and step >= ONE_STEP and eligible[0]: + out[0] = True + self.one_done = True + self.hit_now = True + return out + return eligible & (self.u < float(self.dose)) + + +def apply( + op: str, + values: np.ndarray, + hit: np.ndarray, + previous: np.ndarray, + bound: float = 1.0, +) -> np.ndarray: + """Return values with the operator applied in the hit rows.""" + out = values.copy() + if not hit.any(): + return out + if op == "zero": + out[hit] = 0 + elif op == "stale": + out[hit] = previous[hit] + elif op == "swap": + out[hit] = np.roll(values, -1, axis=0)[hit] + elif op == "f16": + out[hit] = values[hit].astype(np.float16).astype(values.dtype) + elif op == "clip": + out[hit] = np.clip(values[hit], -bound / 2, bound / 2) + else: + raise ValueError(op) + return out + + +def changed(new: np.ndarray, old: np.ndarray) -> np.ndarray: + """The rows (envs) in which new differs from old.""" + diff = new != old + return diff.reshape(len(diff), -1).any(axis=1) + + +def main() -> int: + p = argparse.ArgumentParser(description=__doc__) + p.add_argument("--host", default="127.0.0.1") + p.add_argument("--port", type=int, default=8854) + p.add_argument("--num-envs", type=int, default=16) + p.add_argument("--seed", type=int, default=0) + p.add_argument("--env-id", default="Pendulum-v1") + p.add_argument("--action-high", type=float, default=2.0) + p.add_argument("--fault", choices=FAULTS, default="none") + p.add_argument("--dose", default="1.0") + p.add_argument("--record", required=True) + a = p.parse_args() + + n, fault = a.num_envs, a.fault + field, _, op = fault.partition(":") + dose = "one" if fault in LOUD else a.dose + select = Selector(n, dose) + envs = [gym.make(a.env_id) for _ in range(n)] + obs = np.stack([env.reset(seed=a.seed + i)[0] for i, env in enumerate(envs)]) + obs = obs.astype(np.float32) + indices = np.arange(n, dtype=np.int64) + step_ids = np.zeros(n, dtype=np.int64) + packer = msgpack_numpy.Packer() + steps = 0 + cells = 0 + every = np.ones(n, dtype=np.bool_) + first: list[int] | None = None # the first changed cell, [vector step, env] + + def tally(rows: np.ndarray) -> None: + nonlocal cells, first + if select.hit_now and not rows.any(): + select.one_done = ( + False # "one": that cell's value did not change; try the next + ) + if rows.any(): + cells += int(rows.sum()) + if first is None: + first = [steps, int(np.flatnonzero(rows)[0])] + + # What the environments produced, before any fault. + ep_return = np.zeros(n, dtype=np.float64) + ep_length = np.zeros(n, dtype=np.int64) + episodes = np.zeros(n, dtype=np.int64) + record_path = pathlib.Path(a.record) + record = open(record_path, "w", encoding="utf-8", newline="") + writer = csv.writer(record) + writer.writerow(["step", "env", "episode", "return", "length"]) + + prev_obs = obs.copy() + prev_actions = None + prev_rewards = np.zeros(n, dtype=np.float32) + + def finish(reason: str) -> int: + record.close() + (record_path.parent / "fault.json").write_text( + json.dumps( + { + "fault": fault, + "dose": dose, + "cells": cells, + "first": first, + "steps": steps, + } + ) + + "\n" + ) + print( + f"closed after {steps} steps: {reason!r}; {cells} cells changed", flush=True + ) + return 0 if reason == STOP_REASON else 1 + + ws = connect(f"ws://{a.host}:{a.port}", time.monotonic() + 120) + with ws: + msgpack_numpy.unpackb(ws.recv()) # the metadata; nothing in it is needed + try: + while True: + select.draw() + sent = obs + if field == "obs": + sent = apply(op, obs, select.hits(steps, every), prev_obs) + tally(changed(sent, obs)) + ws.send( + packer.pack( + { + "message_type": "infer", + "data": observation(sent, fault), + "env_indices": indices, + "step_ids": step_ids.copy(), + } + ) + ) + prev_obs = obs.copy() + reply = msgpack_numpy.unpackb(ws.recv()) + received = np.asarray(reply["data"]["action"])[0] # [H, n, d] -> [n, d] + actions = received + if field == "action": + previous = ( + np.zeros_like(received) + if prev_actions is None + else prev_actions + ) + actions = apply( + op, received, select.hits(steps, every), previous, a.action_high + ) + tally(changed(actions, received)) + prev_actions = received.copy() + skip = np.zeros(n, dtype=np.bool_) + if field == "step": + skip = select.hits(steps, every) + tally(skip) + ended = np.empty_like(obs) + after = np.empty_like(obs) + rewards = np.zeros(n, dtype=np.float32) + terminated = np.zeros(n, dtype=np.bool_) + truncated = np.zeros(n, dtype=np.bool_) + sent_ids = step_ids.copy() + for i, env in enumerate(envs): + if skip[i]: + ended[i] = obs[i] + after[i] = obs[i] + step_ids[i] += 1 + continue + o, r, te, tr, _ = env.step(actions[i]) + ended[i] = o + rewards[i], terminated[i], truncated[i] = r, te, tr + ep_return[i] += float(rewards[i]) + ep_length[i] += 1 + if te or tr: + episodes[i] += 1 + writer.writerow( + [ + steps + 1, + i, + episodes[i], + f"{ep_return[i]:.6f}", + ep_length[i], + ] + ) + ep_return[i] = 0.0 + ep_length[i] = 0 + after[i] = env.reset()[0] + step_ids[i] = 0 + else: + after[i] = o + step_ids[i] += 1 + true_rewards = rewards + ends = terminated | truncated + final = ended + if field == "reward" and op in VALUE_OPS: + rewards = apply( + op, true_rewards, select.hits(steps, every), prev_rewards + ) + tally(changed(rewards, true_rewards)) + elif field == "final-obs": + final = apply(op, ended, select.hits(steps, ends), obs) + tally(changed(final, ended)) + elif fault == "terminated:spurious": + hit = select.hits(steps, ~terminated) + terminated = terminated | hit + tally(hit) + elif fault == "truncated:drop": + hit = select.hits(steps, truncated) + truncated = truncated & ~hit + tally(hit) + elif fault == "truncated:as-term": + hit = select.hits(steps, truncated) + terminated = terminated | hit + truncated = truncated & ~hit + tally(hit) + prev_rewards = true_rewards.copy() + if fault == "delay-1ms": + time.sleep(0.001) + order = indices + fields = { + "obs": observation(final, fault), + "rewards": rewards, + "terminated": terminated, + "truncated": truncated, + "info": {}, + } + if fault in LOUD and select.hits(steps, every)[0]: + tally(indices == 0) + if fault == "indices:reorder": + order = indices[::-1].copy() + fields["obs"] = observation(final[::-1].copy(), fault) + for key in ("rewards", "terminated", "truncated"): + fields[key] = fields[key][::-1].copy() + sent_ids = sent_ids[::-1].copy() + else: + fields["rewards"] = rewards[:-1].copy() + ws.send( + packer.pack( + { + "message_type": "feedback", + "env_indices": order, + "step_ids": sent_ids, + "data": fields, + } + ) + ) + obs = after + steps += 1 + except websockets.exceptions.ConnectionClosed as closed: + return finish(closed.rcvd.reason if closed.rcvd is not None else "") + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/experiments/e54-boundary-faults/jobs.py b/experiments/e54-boundary-faults/jobs.py new file mode 100644 index 0000000..33a5bee --- /dev/null +++ b/experiments/e54-boundary-faults/jobs.py @@ -0,0 +1,65 @@ +"""E54's runs, one line each: env fault dose seed trace. + + python jobs.py registered > jobs.txt + python jobs.py pilot > jobs.txt + +registered (PROTOCOL.md): +- pendulum, seeds 0-2: the 3 controls; the 23 silent faults (21 the + client's, 2 the log's) at the 5 doses; the 2 loud faults at one cell. All + traced. +- pendulum, seeds 10-19: fault-free, for the strict curve check. +- halfcheetah, seeds 0-2: none; the 23 silent faults at doses one, 0.01, 1.0. +- halfcheetah, seeds 10-19: fault-free. +pilot: pendulum at seed 9 as registered; halfcheetah at seed 9 for none, +reward:stale at one cell and obs:f16 at 0.01. +""" + +from __future__ import annotations + +import sys + +from faulty_client import CONTROLS, LOUD, SILENT + +LOG = ("log:drop-first", "log:short") +DOSES = ("one", "0.001", "0.01", "0.1", "1.0") +CHEETAH_DOSES = ("one", "0.01", "1.0") + + +def pendulum(seed: int) -> list[str]: + jobs = [f"pendulum {c} 1.0 {seed} trace" for c in CONTROLS] + jobs += [f"pendulum {f} {d} {seed} trace" for f in SILENT + LOG for d in DOSES] + jobs += [f"pendulum {f} one {seed} trace" for f in LOUD] + return jobs + + +def main() -> int: + which = sys.argv[1] + if which == "registered": + jobs = [] + for seed in (0, 1, 2): + jobs += pendulum(seed) + jobs += [f"pendulum none 1.0 {s} notrace" for s in range(10, 20)] + for seed in (0, 1, 2): + jobs.append(f"halfcheetah none 1.0 {seed} notrace") + jobs += [ + f"halfcheetah {f} {d} {seed} notrace" + for f in SILENT + LOG + for d in CHEETAH_DOSES + ] + jobs += [f"halfcheetah none 1.0 {s} notrace" for s in range(10, 20)] + elif which == "pilot": + jobs = pendulum(9) + [ + "halfcheetah none 1.0 9 notrace", + "halfcheetah reward:stale one 9 notrace", + "halfcheetah obs:f16 0.01 9 notrace", + ] + else: + raise SystemExit(f"unknown: {which}") + # HalfCheetah's runs are four times longer: start them first. + jobs.sort(key=lambda j: not j.startswith("halfcheetah")) + print("\n".join(jobs)) + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/experiments/e54-boundary-faults/localise.py b/experiments/e54-boundary-faults/localise.py new file mode 100644 index 0000000..fa66c84 --- /dev/null +++ b/experiments/e54-boundary-faults/localise.py @@ -0,0 +1,145 @@ +"""E54: where a traced run first differs from the fault-free run at its seed. + + python localise.py results # writes results/localisation.csv + +On one machine the fault-free run at a seed is deterministic, so a run with a +fault crosses the same bytes until the fault's first cell, and differs from +there on. Within a vector step the trainer sees, in order: the actions it +sends; then the rewards, episode ends, time limits and final observations of +the feedback; then the next infer's observations. The run is localised to +the first step that differs, the lowest env that differs in it, and the first +of that env's messages that differs. + +It is right if that step and env are the fault's first changed cell (the +client's fault.json; the trainer's for the log faults, which change nothing +on the wire), and the message is the one that fault touches: +- obs:* the next observations, one step earlier (the infer that + carried the fault ends the step before, as the trainer + counts); +- action:*, step:fill that step's feedback: the client changed what it did + with an action the trainer sent unchanged; +- reward:* rewards; final-obs:* final observations; +- terminated:spurious, truncated:drop episode ends; +- truncated:as-term time limits; +- log:* nothing: the wire is identical to the fault-free run's. +A run whose fault changed no cell, and a control, is right if its wire is +identical. The faults the bridge rejects are not localised: they raise. +""" + +from __future__ import annotations + +import csv +import json +import pathlib +import sys + +import numpy as np + +ORDER = ("actions", "rewards", "ends", "truncs", "finals", "nexts") +FEEDBACK = ("rewards", "ends", "truncs", "finals", "nexts") +EXPECTED = { + "obs": ("nexts",), + "action": FEEDBACK, + "step": FEEDBACK, + "reward": ("rewards",), + "final-obs": ("finals",), + "terminated": ("ends",), + "truncated:drop": ("ends",), + "truncated:as-term": ("truncs",), +} + + +def first_difference(a, b) -> tuple[int, str, int] | None: + """(vector step, message, env) of the first difference, or None.""" + if not np.array_equal(a["first_obs"], b["first_obs"]): + env = int(np.flatnonzero((a["first_obs"] != b["first_obs"]).any(axis=1))[0]) + return (-1, "nexts", env) + steps = min(len(a["actions"]), len(b["actions"])) + # [key, step, env]: where each message differs + diff = np.stack( + [ + (a[k][:steps] != b[k][:steps]).reshape(steps, a[k].shape[1], -1).any(axis=2) + for k in ORDER + ] + ) + rows = np.flatnonzero(diff.any(axis=(0, 2))) + if len(rows): + t = int(rows[0]) + env = int(np.flatnonzero(diff[:, t].any(axis=0))[0]) # the lowest env first + key = ORDER[int(np.flatnonzero(diff[:, t, env])[0])] # then its first message + return (t, key, env) + if len(a["actions"]) != len(b["actions"]): + return (steps, "length", -1) + return None + + +def load(path: pathlib.Path) -> dict: + with np.load(path) as z: # an NpzFile decompresses on every access + return {k: z[k] for k in z.files} + + +def expected(fault: str) -> tuple[str, ...]: + if fault in EXPECTED: + return EXPECTED[fault] + return EXPECTED.get(fault.partition(":")[0], ()) + + +def main() -> int: + root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else pathlib.Path("results") + rows = [] + for trace in sorted(root.glob("pendulum/*/*/seed*/trace.npz")): + run = trace.parent + seed = run.name.removeprefix("seed") + fault = run.parent.parent.name.replace("__", ":") + if fault in ("none", "indices:reorder", "reward:short-array"): + continue # the reference, and the faults the bridge rejects + clean = root / "pendulum" / "none" / "1.0" / f"seed{seed}" / "trace.npz" + where = first_difference(load(trace), load(clean)) + info_path = run / "fault.json" + info = json.loads(info_path.read_text()) if info_path.exists() else {} + first = info.get("first") + cells = info.get("cells", 0) + if fault.startswith("log:"): + result = json.loads((run / "result.json").read_text()) + cells = result.get("log_cells", 0) + if ( + cells == 0 + or fault.startswith("log:") + or fault in ("delay-1ms", "wire-float64") + ): + right = where is None # nothing on the wire changed + elif where is None or first is None: + right = False + else: + t, key, env = where + step = first[0] - 1 if fault.startswith("obs:") else first[0] + right = t == step and env == first[1] and key in expected(fault) + rows.append( + dict( + fault=fault, + dose=run.parent.name, + seed=seed, + cells=cells, + injected="" if first is None else f"{first[0]}/{first[1]}", + found="identical" + if where is None + else f"{where[0]}/{where[2]} {where[1]}", + right=int(right), + ) + ) + out = root / "localisation.csv" + with open(out, "w", encoding="utf-8", newline="") as f: + w = csv.DictWriter(f, fieldnames=list(rows[0])) + w.writeheader() + w.writerows(rows) + wrong = [r for r in rows if not r["right"]] + print( + f"{len(rows)} traced runs with a fault; localised right: {len(rows) - len(wrong)}" + ) + for r in wrong: + print(" not right:", r) + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/experiments/e54-boundary-faults/merge_runs.py b/experiments/e54-boundary-faults/merge_runs.py new file mode 100644 index 0000000..490ece7 --- /dev/null +++ b/experiments/e54-boundary-faults/merge_runs.py @@ -0,0 +1,47 @@ +"""E54: merge each run's result.json, fault.json and log tails into one file. + + python merge_runs.py results # writes results/runs.jsonl + +One line per run: its env, fault, dose and seed (from its directory), its +result.json and fault.json, and the last line of its client.log and +train.log. +""" + +from __future__ import annotations + +import json +import pathlib +import sys + + +def last_line(path: pathlib.Path) -> str: + if not path.exists(): + return "" + lines = path.read_text(encoding="utf-8", errors="replace").strip().splitlines() + return lines[-1] if lines else "" + + +def main() -> int: + root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else pathlib.Path("results") + out = [] + for res in sorted(root.glob("*/*/*/seed*/result.json")): + run = res.parent + line = { + "env": run.parent.parent.parent.name, + "fault": run.parent.parent.name.replace("__", ":"), + "dose": run.parent.name, + "seed": int(run.name.removeprefix("seed")), + "result": json.loads(res.read_text()), + } + if (run / "fault.json").exists(): + line["fault_json"] = json.loads((run / "fault.json").read_text()) + line["client_log"] = last_line(run / "client.log") + line["train_log"] = last_line(run / "train.log") + out.append(json.dumps(line, sort_keys=True)) + (root / "runs.jsonl").write_text("\n".join(out) + "\n", encoding="utf-8") + print(len(out), "runs") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/experiments/e54-boundary-faults/results/bridges-src.sha256 b/experiments/e54-boundary-faults/results/bridges-src.sha256 new file mode 100644 index 0000000..755002f --- /dev/null +++ b/experiments/e54-boundary-faults/results/bridges-src.sha256 @@ -0,0 +1,6 @@ +766ad3d83be9696dff26543ce2fb35c3c31cb845fc42cb148d411b263e8bf9b5 src/plugrl_bridges/gym.py +e89ebb2c4ed69ed5788cd945bc4d36ecc023949627433818b98d9ea43d1fa7d5 src/plugrl_bridges/__init__.py +4001b6400d4031504525949fa721ad425fa0cb16a91cf30537dfd6d5859d8336 src/plugrl_bridges/observations.py +1c22fca6e0f01e8ec730ee893568cc301d2d21c3e16cc2102c22959ced00ff08 src/plugrl_bridges/rlinf.py +f02264e551925eed72ba2e4dfb5159f7e174e4ac7231aa122689ef2172484646 src/plugrl_bridges/sb3.py +0e56388fea17a73d4defcb437d3a4b6c8392c609dfca07efe92343e6cac72656 src/plugrl_bridges/server.py diff --git a/experiments/e54-boundary-faults/results/by_dose.csv b/experiments/e54-boundary-faults/results/by_dose.csv new file mode 100644 index 0000000..23a5178 --- /dev/null +++ b/experiments/e54-boundary-faults/results/by_dose.csv @@ -0,0 +1,24 @@ +env,kind,dose,runs,raises,rule,strict,weights,record,bridge,either +pendulum,client,one,63,0.0,0.0,0.0,1.0,0.206,0.0,1.0 +pendulum,client,0.001,63,0.0,0.0,0.079,1.0,0.286,0.0,1.0 +pendulum,client,0.01,63,0.0,0.048,0.063,1.0,0.286,0.0,1.0 +pendulum,client,0.1,63,0.0,0.048,0.206,1.0,0.286,0.0,1.0 +pendulum,client,1.0,63,0.0,0.429,0.603,1.0,0.238,0.0,1.0 +pendulum,log,one,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +pendulum,log,0.01,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +pendulum,log,0.1,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +pendulum,log,1.0,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +pendulum,all,one,69,0.0,0.0,0.0,0.913,0.275,0.087,1.0 +pendulum,all,0.001,63,0.0,0.0,0.079,1.0,0.286,0.0,1.0 +pendulum,all,0.01,69,0.0,0.043,0.058,0.913,0.348,0.087,1.0 +pendulum,all,0.1,69,0.0,0.043,0.188,0.913,0.348,0.087,1.0 +pendulum,all,1.0,69,0.0,0.391,0.551,0.913,0.304,0.087,1.0 +halfcheetah,client,one,63,0.0,0.048,0.048,1.0,0.27,0.0,1.0 +halfcheetah,client,0.01,63,0.0,0.095,0.095,1.0,0.286,0.0,1.0 +halfcheetah,client,1.0,63,0.0,0.349,0.508,1.0,0.27,0.0,1.0 +halfcheetah,log,one,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +halfcheetah,log,0.01,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +halfcheetah,log,1.0,6,0.0,0.0,0.0,0.0,1.0,1.0,1.0 +halfcheetah,all,one,69,0.0,0.043,0.043,0.913,0.333,0.087,1.0 +halfcheetah,all,0.01,69,0.0,0.087,0.087,0.913,0.348,0.087,1.0 +halfcheetah,all,1.0,69,0.0,0.319,0.464,0.913,0.333,0.087,1.0 diff --git a/experiments/e54-boundary-faults/results/e54-src.sha256 b/experiments/e54-boundary-faults/results/e54-src.sha256 new file mode 100644 index 0000000..62413a1 --- /dev/null +++ b/experiments/e54-boundary-faults/results/e54-src.sha256 @@ -0,0 +1,3 @@ +f1ba1cc97ff4b42fc142ce254149732c46f7cd55a3c961f2e55cbcca34c3bbba train.py +5b0074f1b906b8671fb55fdd40d7d830be8351f2394e924ebe41ed6bbc6bac4f faulty_client.py +083716bcddefd87ad4fc6a041dfe08f33a0e423bfbf52e5005be6f9c7902b218 jobs.py diff --git a/experiments/e54-boundary-faults/results/jobs.txt b/experiments/e54-boundary-faults/results/jobs.txt new file mode 100644 index 0000000..d0b0a62 --- /dev/null +++ b/experiments/e54-boundary-faults/results/jobs.txt @@ -0,0 +1,590 @@ +halfcheetah none 1.0 0 notrace +halfcheetah obs:zero one 0 notrace +halfcheetah obs:zero 0.01 0 notrace +halfcheetah obs:zero 1.0 0 notrace +halfcheetah obs:stale one 0 notrace +halfcheetah obs:stale 0.01 0 notrace +halfcheetah obs:stale 1.0 0 notrace +halfcheetah obs:swap one 0 notrace +halfcheetah obs:swap 0.01 0 notrace +halfcheetah obs:swap 1.0 0 notrace +halfcheetah obs:f16 one 0 notrace 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file mode 100644 index 0000000..dafd4f5 --- /dev/null +++ b/experiments/e54-boundary-faults/results/pilot/v1.txt @@ -0,0 +1,33 @@ +fault seed learns(log) weights record bridge-log really learns episodes time +none 9 pass +544 -680 pass 3721266c pass pass yes +544 -680 512 17.6 +delay-1ms 9 pass +544 -680 pass 3721266c pass pass yes +544 -680 512 26.3 +wire-float64 9 pass +544 -680 pass 3721266c pass pass yes +544 -680 512 17.8 +obs-float16 9 pass +1010 -213 CAUGHT 216cc106 pass pass yes +1010 -213 512 17.6 +obs-stale 9 pass +1039 -199 CAUGHT ae8dc584 pass pass yes +1039 -199 512 18.0 +reset-obs-terminal 9 pass +999 -233 CAUGHT 398a2869 pass pass yes +999 -233 512 18.0 +trunc-as-term 9 pass +1025 -209 CAUGHT dd054830 pass pass yes +1025 -209 512 17.4 +action-clip 9 pass +820 -395 CAUGHT e1084bea pass pass yes +820 -395 512 17.4 +reward-first-zero 9 pass +1015 -213 CAUGHT a3098bd2 CAUGHT pass yes +1015 -216 512 17.6 +reward-late 9 pass +1022 -207 CAUGHT 82ee3cdd CAUGHT pass yes +1025 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+pendulum,action:clip,0.1,9,5586,0,0,,1,0,0,1017.2,-221.1,512,47f6ab43,20.841,,1 +pendulum,action:clip,1.0,9,65640,0,0,,1,0,0,820.3,-395.4,512,e1084bea,20.612,,1 +pendulum,action:clip,one,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,19.834,,1 +pendulum,action:f16,0.001,9,78,0,0,,1,0,0,1021.6,-202.0,512,147109f1,19.956,,1 +pendulum,action:f16,0.01,9,709,0,0,,1,0,0,991.8,-231.8,512,8c0f4a77,20.356,,1 +pendulum,action:f16,0.1,9,6964,0,0,,1,0,0,992.8,-237.0,512,c24e6b8f,20.223,,1 +pendulum,action:f16,1.0,9,64943,0,0,,1,0,0,975.9,-255.3,512,8eebd6ca,20.282,,1 +pendulum,action:f16,one,9,1,0,0,,1,0,0,936.4,-287.2,512,15c1a06b,20.016,,1 +pendulum,action:stale,0.001,9,88,0,0,,1,0,0,1029.0,-202.0,512,bb0a97a5,19.974,,1 +pendulum,action:stale,0.01,9,784,0,0,,1,0,0,1018.6,-208.1,512,6a00e075,20.075,,1 +pendulum,action:stale,0.1,9,7428,0,0,,1,0,0,999.4,-245.4,512,654fe124,20.677,,1 +pendulum,action:stale,1.0,9,75433,0,0,,1,0,0,1035.1,-212.3,512,fe3d6d54,20.281,,1 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+pendulum,final-obs:f16,0.001,9,1,0,0,,1,0,0,567.3,-656.4,512,f5e0a88b,20.527,,1 +pendulum,final-obs:f16,0.01,9,9,0,0,,1,0,0,1008.2,-215.4,512,37698b9a,20.904,,1 +pendulum,final-obs:f16,0.1,9,55,0,0,,1,0,0,1002.5,-221.1,512,5e0f6925,20.784,,1 +pendulum,final-obs:f16,1.0,9,512,0,0,,1,0,0,1013.7,-209.9,512,5346322a,19.766,,1 +pendulum,final-obs:f16,one,9,1,0,0,,1,0,0,985.9,-237.7,512,8da258ef,20.684,,1 +pendulum,final-obs:stale,0.001,9,1,0,0,,1,0,0,624.3,-599.3,512,c7fae122,19.913,,1 +pendulum,final-obs:stale,0.01,9,9,0,0,,1,0,0,1002.4,-218.8,512,ac7dcc04,20.235,,1 +pendulum,final-obs:stale,0.1,9,55,0,0,,1,0,0,1010.7,-210.6,512,57307710,20.176,,1 +pendulum,final-obs:stale,1.0,9,512,0,0,,1,0,0,1029.3,-193.5,512,0f7b066e,19.885,,1 +pendulum,final-obs:stale,one,9,1,0,0,,1,0,0,943.2,-280.4,512,f919d8d0,20.168,,1 +pendulum,final-obs:swap,0.001,9,1,0,0,,1,0,0,543.4,-680.2,512,5aba21e8,20.37,,1 +pendulum,final-obs:swap,0.01,9,9,0,0,,1,0,0,1036.0,-187.5,512,5e4c40c5,21.024,,1 +pendulum,final-obs:swap,0.1,9,55,0,0,,1,0,0,974.4,-249.1,512,bd64bdd7,20.421,,1 +pendulum,final-obs:swap,1.0,9,512,0,0,,1,0,0,1021.2,-212.8,512,a5298567,20.645,,1 +pendulum,final-obs:swap,one,9,1,0,0,,1,0,0,1016.7,-206.9,512,389de086,19.962,,1 +pendulum,final-obs:zero,0.001,9,1,0,0,,1,0,0,619.5,-604.2,512,fad9a8fd,20.334,,1 +pendulum,final-obs:zero,0.01,9,9,0,0,,1,0,0,1011.7,-218.6,512,c02cc3a6,20.652,,1 +pendulum,final-obs:zero,0.1,9,55,0,0,,1,0,0,1021.6,-208.8,512,317cfab1,20.366,,1 +pendulum,final-obs:zero,1.0,9,512,0,0,,1,0,0,983.0,-251.3,512,fb4a46a7,19.953,,1 +pendulum,final-obs:zero,one,9,1,0,0,,1,0,0,1017.6,-206.0,512,b6378ded,20.371,,1 +pendulum,indices:reorder,one,9,1,1,0,,,0,0,,,240,c00dbcf5,9.426,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,log:drop-first,0.001,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,19.25,,1 +pendulum,log:drop-first,0.01,9,2,0,0,,0,1,1,543.6,-680.0,512,3721266c,20.536,,1 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+pendulum,reward:stale,0.001,9,110,0,0,,1,1,0,999.2,-227.7,512,c32cab87,20.312,,1 +pendulum,reward:stale,0.01,9,1068,0,0,,1,1,0,1015.0,-219.7,512,c6f386c4,20.299,,1 +pendulum,reward:stale,0.1,9,10296,0,0,,1,1,0,1020.6,-201.0,512,b7b1eac0,20.727,,1 +pendulum,reward:stale,1.0,9,102400,0,0,,1,1,0,1022.1,-206.9,512,82ee3cdd,20.82,,1 +pendulum,reward:stale,one,9,1,0,0,,1,0,0,876.1,-347.6,512,4184b119,19.954,,1 +pendulum,reward:swap,0.001,9,110,0,0,,1,1,0,983.7,-244.1,512,3271779a,20.425,,1 +pendulum,reward:swap,0.01,9,1068,0,0,,1,1,0,980.6,-241.5,512,dc34b515,20.194,,1 +pendulum,reward:swap,0.1,9,10296,0,0,,1,1,0,1008.4,-246.2,512,f6007e06,20.453,,1 +pendulum,reward:swap,1.0,9,102400,0,1,,1,1,0,74.5,-1180.7,512,4d7817df,20.373,,1 +pendulum,reward:swap,one,9,1,0,0,,1,1,0,862.5,-361.2,512,5add710d,20.271,,1 +pendulum,reward:zero,0.001,9,110,0,0,,1,1,0,1016.7,-214.1,512,5432b13b,20.559,,1 +pendulum,reward:zero,0.01,9,1068,0,0,,1,1,0,995.1,-223.1,512,35c8690f,20.197,,1 +pendulum,reward:zero,0.1,9,10296,0,0,,1,1,0,888.4,-213.7,512,9184838f,20.324,,1 +pendulum,reward:zero,1.0,9,102400,0,1,,1,1,0,0.0,0.0,512,4e451436,20.715,,1 +pendulum,reward:zero,one,9,1,0,0,,1,0,0,1032.6,-191.0,512,e621d47b,20.852,,1 +pendulum,step:fill,0.001,9,110,0,0,,1,1,0,939.3,-280.0,496,4a833258,20.396,,1 +pendulum,step:fill,0.01,9,1068,0,0,,1,1,0,978.9,-247.5,496,8b0356a1,20.418,,1 +pendulum,step:fill,0.1,9,10296,0,0,,1,1,0,984.0,-228.2,448,4bf8fb5e,20.114,,1 +pendulum,step:fill,1.0,9,102400,0,1,,1,0,0,,,0,c1db1e9b,18.419,,1 +pendulum,step:fill,one,9,1,0,0,,1,1,0,1009.7,-214.0,511,2d849d90,20.461,,1 +pendulum,terminated:spurious,0.001,9,110,0,0,,1,1,0,877.6,-165.8,621,2dff920f,19.242,,1 +pendulum,terminated:spurious,0.01,9,1068,0,1,,1,1,0,227.6,-158.6,1571,f33a49d0,20.649,,1 +pendulum,terminated:spurious,0.1,9,10296,0,1,,1,1,0,-23.8,-53.3,10753,bf58bfe6,20.513,,1 +pendulum,terminated:spurious,1.0,9,102400,0,1,,1,1,0,-3.9,-6.9,102400,fbd83720,22.027,,1 +pendulum,terminated:spurious,one,9,1,0,0,,1,0,0,875.4,-348.2,512,fe14d14a,19.1,,1 +pendulum,truncated:as-term,0.001,9,1,0,0,,1,0,0,577.1,-646.5,512,62a84ecd,19.912,,1 +pendulum,truncated:as-term,0.01,9,9,0,0,,1,0,0,1017.7,-212.7,512,7513b6b1,20.367,,1 +pendulum,truncated:as-term,0.1,9,55,0,0,,1,0,0,1012.2,-218.2,512,3f82a43f,20.076,,1 +pendulum,truncated:as-term,1.0,9,512,0,0,,1,0,0,1025.1,-209.3,512,dd054830,20.797,,1 +pendulum,truncated:as-term,one,9,1,0,0,,1,0,0,875.4,-348.2,512,fe14d14a,19.525,,1 +pendulum,truncated:drop,0.001,9,1,0,0,,1,1,0,564.1,-659.5,511,18800bc4,20.51,,1 +pendulum,truncated:drop,0.01,9,9,0,0,,1,1,0,1009.6,-248.2,503,90c3d626,20.63,,1 +pendulum,truncated:drop,0.1,9,55,0,0,,1,1,0,1055.0,-228.5,457,1921c4a2,21.036,,1 +pendulum,truncated:drop,1.0,9,512,0,1,,1,1,0,,,0,c6b90d35,18.851,,1 +pendulum,truncated:drop,one,9,1,0,0,,1,1,0,1006.3,-217.3,511,20999bc7,20.578,,1 +pendulum,wire-float64,1.0,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,22.456,,1 diff --git a/experiments/e54-boundary-faults/results/pilot/v2.txt b/experiments/e54-boundary-faults/results/pilot/v2.txt new file mode 100644 index 0000000..6a29783 --- /dev/null +++ b/experiments/e54-boundary-faults/results/pilot/v2.txt @@ -0,0 +1,144 @@ +117 traced runs with a fault; localised right: 115 + not right: {'fault': 'action:f16', 'dose': '1.0', 'seed': '9', 'cells': 64943, 'injected': '0/0', 'found': '0/2 rewards', 'right': 0} + not right: {'fault': 'terminated:spurious', 'dose': 'one', 'seed': '9', 'cells': 1, 'injected': '3199/0', 'found': '3199/0 truncs', 'right': 0} + +real 0m2.229s +user 0m3.515s +sys 0m0.331s +env fault dose cells raises rule strict weights record bridge +halfcheetah none 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +halfcheetah obs:f16 0.01 4049 0/1 0/1 - 1/1 0/1 0/1 +halfcheetah reward:stale one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum none 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum delay-1ms 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum wire-float64 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum obs:zero 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:zero 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:zero 0.1 10297 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:zero 1.0 102416 0/1 1/1 - 1/1 0/1 0/1 +pendulum obs:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 0.1 10295 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 1.0 102400 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 0.1 10297 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 1.0 102416 0/1 1/1 - 1/1 0/1 0/1 +pendulum obs:swap one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 0.1 10297 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 1.0 102416 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 0.1 10296 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 1.0 102400 0/1 1/1 - 1/1 0/1 0/1 +pendulum action:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 0.001 88 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 0.01 784 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 0.1 7428 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 1.0 75433 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 0.001 99 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 0.01 969 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 0.1 9468 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 1.0 87162 0/1 1/1 - 1/1 0/1 0/1 +pendulum action:swap one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 0.001 78 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 0.01 709 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 0.1 6964 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 1.0 64943 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 0.001 62 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 0.01 570 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 0.1 5586 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 1.0 65640 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip one 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum reward:zero 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:zero 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:zero 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:zero 1.0 102400 0/1 1/1 - 1/1 1/1 0/1 +pendulum reward:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:stale 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale 1.0 102400 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:swap 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:swap 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:swap 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:swap 1.0 102400 0/1 1/1 - 1/1 1/1 0/1 +pendulum reward:swap one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:f16 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 0.1 10295 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 1.0 102388 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum terminated:spurious 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum terminated:spurious 0.01 1068 0/1 1/1 - 1/1 1/1 0/1 +pendulum terminated:spurious 0.1 10296 0/1 1/1 - 1/1 1/1 0/1 +pendulum terminated:spurious 1.0 102400 0/1 1/1 - 1/1 1/1 0/1 +pendulum terminated:spurious one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:drop 0.001 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 0.01 9 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 0.1 55 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 1.0 512 0/1 1/1 - 1/1 1/1 0/1 +pendulum truncated:drop one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:as-term 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum step:fill 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum step:fill 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum step:fill 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum step:fill 1.0 102400 0/1 1/1 - 1/1 0/1 0/1 +pendulum step:fill one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum log:drop-first 0.001 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum log:drop-first 0.01 2 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:drop-first 0.1 55 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:drop-first 1.0 512 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:drop-first one 1 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short 0.001 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum log:short 0.01 2 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short 0.1 55 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short 1.0 512 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short one 1 0/1 0/1 - 0/1 1/1 1/1 +pendulum indices:reorder one 1 1/1 0/1 - - 0/1 0/1 +pendulum reward:short-array one 1 1/1 0/1 - - 0/1 0/1 + +share of silent runs caught, by dose (runs with a changed cell) + pendulum one n= 22 raises 0.0 rule 0.0 strict weights 0.909 record 0.227 bridge 0.091 + pendulum 0.001 n= 21 raises 0.0 rule 0.0 strict weights 1.0 record 0.286 bridge 0.0 + pendulum 0.01 n= 23 raises 0.0 rule 0.043 strict weights 0.913 record 0.348 bridge 0.087 + pendulum 0.1 n= 23 raises 0.0 rule 0.043 strict weights 0.913 record 0.348 bridge 0.087 + pendulum 1.0 n= 23 raises 0.0 rule 0.391 strict weights 0.913 record 0.304 bridge 0.087 + halfcheetah one n= 1 raises 0.0 rule 0.0 strict weights 1.0 record 1.0 bridge 0.0 + halfcheetah 0.01 n= 1 raises 0.0 rule 0.0 strict weights 1.0 record 0.0 bridge 0.0 + +halfcheetah none at seed 9: 0260ca9d, E50's 0260ca9d: same +pendulum none at seed 9: 3721266c, E50's 3721266c: same +incomplete without an error: none diff --git a/experiments/e54-boundary-faults/results/pilot/v3-localisation.csv b/experiments/e54-boundary-faults/results/pilot/v3-localisation.csv new file mode 100644 index 0000000..51582b1 --- /dev/null +++ b/experiments/e54-boundary-faults/results/pilot/v3-localisation.csv @@ -0,0 +1,118 @@ +fault,dose,seed,cells,injected,found,right +action:clip,0.001,9,62,110/3,110/3 rewards,1 +action:clip,0.01,9,570,5/7,5/7 rewards,1 +action:clip,0.1,9,5586,0/2,0/2 rewards,1 +action:clip,1.0,9,65640,0/2,0/2 rewards,1 +action:clip,one,9,1,3256/0,3256/0 rewards,1 +action:f16,0.001,9,78,184/1,184/1 nexts,1 +action:f16,0.01,9,709,50/10,50/10 nexts,1 +action:f16,0.1,9,6964,0/2,0/2 rewards,1 +action:f16,1.0,9,64943,0/0,0/0 nexts,1 +action:f16,one,9,1,3249/0,3249/0 rewards,1 +action:stale,0.001,9,88,184/1,184/1 rewards,1 +action:stale,0.01,9,784,50/10,50/10 rewards,1 +action:stale,0.1,9,7428,0/2,0/2 rewards,1 +action:stale,1.0,9,75433,0/0,0/0 rewards,1 +action:stale,one,9,1,3249/0,3249/0 rewards,1 +action:swap,0.001,9,99,110/3,110/3 nexts,1 +action:swap,0.01,9,969,5/7,5/7 rewards,1 +action:swap,0.1,9,9468,0/2,0/2 rewards,1 +action:swap,1.0,9,87162,0/0,0/0 rewards,1 +action:swap,one,9,1,3249/0,3249/0 rewards,1 +action:zero,0.001,9,110,110/3,110/3 rewards,1 +action:zero,0.01,9,1068,5/7,5/7 rewards,1 +action:zero,0.1,9,10296,0/2,0/2 rewards,1 +action:zero,1.0,9,102400,0/0,0/0 rewards,1 +action:zero,one,9,1,3249/0,3249/0 rewards,1 +delay-1ms,1.0,9,0,,identical,1 +final-obs:f16,0.001,9,1,4599/8,4599/8 finals,1 +final-obs:f16,0.01,9,9,199/12,199/12 finals,1 +final-obs:f16,0.1,9,55,199/12,199/12 finals,1 +final-obs:f16,1.0,9,512,199/0,199/0 finals,1 +final-obs:f16,one,9,1,3399/0,3399/0 finals,1 +final-obs:stale,0.001,9,1,4599/8,4599/8 finals,1 +final-obs:stale,0.01,9,9,199/12,199/12 finals,1 +final-obs:stale,0.1,9,55,199/12,199/12 finals,1 +final-obs:stale,1.0,9,512,199/0,199/0 finals,1 +final-obs:stale,one,9,1,3399/0,3399/0 finals,1 +final-obs:swap,0.001,9,1,4599/8,4599/8 finals,1 +final-obs:swap,0.01,9,9,199/12,199/12 finals,1 +final-obs:swap,0.1,9,55,199/12,199/12 finals,1 +final-obs:swap,1.0,9,512,199/0,199/0 finals,1 +final-obs:swap,one,9,1,3399/0,3399/0 finals,1 +final-obs:zero,0.001,9,1,4599/8,4599/8 finals,1 +final-obs:zero,0.01,9,9,199/12,199/12 finals,1 +final-obs:zero,0.1,9,55,199/12,199/12 finals,1 +final-obs:zero,1.0,9,512,199/0,199/0 finals,1 +final-obs:zero,one,9,1,3399/0,3399/0 finals,1 +log:drop-first,0.001,9,0,,identical,1 +log:drop-first,0.01,9,2,,identical,1 +log:drop-first,0.1,9,55,,identical,1 +log:drop-first,1.0,9,512,,identical,1 +log:drop-first,one,9,1,,identical,1 +log:short,0.001,9,0,,identical,1 +log:short,0.01,9,2,,identical,1 +log:short,0.1,9,55,,identical,1 +log:short,1.0,9,512,,identical,1 +log:short,one,9,1,,identical,1 +obs:f16,0.001,9,110,110/3,109/3 nexts,1 +obs:f16,0.01,9,1068,5/7,4/7 nexts,1 +obs:f16,0.1,9,10297,0/2,-1/2 nexts,1 +obs:f16,1.0,9,102416,0/0,-1/0 nexts,1 +obs:f16,one,9,1,3249/0,3248/0 nexts,1 +obs:stale,0.001,9,110,110/3,109/3 nexts,1 +obs:stale,0.01,9,1068,5/7,4/7 nexts,1 +obs:stale,0.1,9,10295,1/7,0/7 nexts,1 +obs:stale,1.0,9,102400,1/0,0/0 nexts,1 +obs:stale,one,9,1,3249/0,3248/0 nexts,1 +obs:swap,0.001,9,110,110/3,109/3 nexts,1 +obs:swap,0.01,9,1068,5/7,4/7 nexts,1 +obs:swap,0.1,9,10297,0/2,-1/2 nexts,1 +obs:swap,1.0,9,102416,0/0,-1/0 nexts,1 +obs:swap,one,9,1,3249/0,3248/0 nexts,1 +obs:zero,0.001,9,110,110/3,109/3 nexts,1 +obs:zero,0.01,9,1068,5/7,4/7 nexts,1 +obs:zero,0.1,9,10297,0/2,-1/2 nexts,1 +obs:zero,1.0,9,102416,0/0,-1/0 nexts,1 +obs:zero,one,9,1,3249/0,3248/0 nexts,1 +reward:f16,0.001,9,110,110/3,110/3 rewards,1 +reward:f16,0.01,9,1068,5/7,5/7 rewards,1 +reward:f16,0.1,9,10295,0/2,0/2 rewards,1 +reward:f16,1.0,9,102388,0/0,0/0 rewards,1 +reward:f16,one,9,1,3249/0,3249/0 rewards,1 +reward:stale,0.001,9,110,110/3,110/3 rewards,1 +reward:stale,0.01,9,1068,5/7,5/7 rewards,1 +reward:stale,0.1,9,10296,0/2,0/2 rewards,1 +reward:stale,1.0,9,102400,0/0,0/0 rewards,1 +reward:stale,one,9,1,3249/0,3249/0 rewards,1 +reward:swap,0.001,9,110,110/3,110/3 rewards,1 +reward:swap,0.01,9,1068,5/7,5/7 rewards,1 +reward:swap,0.1,9,10296,0/2,0/2 rewards,1 +reward:swap,1.0,9,102400,0/0,0/0 rewards,1 +reward:swap,one,9,1,3249/0,3249/0 rewards,1 +reward:zero,0.001,9,110,110/3,110/3 rewards,1 +reward:zero,0.01,9,1068,5/7,5/7 rewards,1 +reward:zero,0.1,9,10296,0/2,0/2 rewards,1 +reward:zero,1.0,9,102400,0/0,0/0 rewards,1 +reward:zero,one,9,1,3249/0,3249/0 rewards,1 +step:fill,0.001,9,110,110/3,110/3 rewards,1 +step:fill,0.01,9,1068,5/7,5/7 rewards,1 +step:fill,0.1,9,10296,0/2,0/2 rewards,1 +step:fill,1.0,9,102400,0/0,0/0 rewards,1 +step:fill,one,9,1,3249/0,3249/0 rewards,1 +terminated:spurious,0.001,9,110,110/3,110/3 ends,1 +terminated:spurious,0.01,9,1068,5/7,5/7 ends,1 +terminated:spurious,0.1,9,10296,0/2,0/2 ends,1 +terminated:spurious,1.0,9,102400,0/0,0/0 ends,1 +terminated:spurious,one,9,1,3249/0,3249/0 ends,1 +truncated:as-term,0.001,9,1,4599/8,4599/8 truncs,1 +truncated:as-term,0.01,9,9,199/12,199/12 truncs,1 +truncated:as-term,0.1,9,55,199/12,199/12 truncs,1 +truncated:as-term,1.0,9,512,199/0,199/0 truncs,1 +truncated:as-term,one,9,1,3399/0,3399/0 truncs,1 +truncated:drop,0.001,9,1,4599/8,4599/8 ends,1 +truncated:drop,0.01,9,9,199/12,199/12 ends,1 +truncated:drop,0.1,9,55,199/12,199/12 ends,1 +truncated:drop,1.0,9,512,199/0,199/0 ends,1 +truncated:drop,one,9,1,3399/0,3399/0 ends,1 +wire-float64,1.0,9,0,,identical,1 diff --git a/experiments/e54-boundary-faults/results/pilot/v3-runs.csv b/experiments/e54-boundary-faults/results/pilot/v3-runs.csv new file mode 100644 index 0000000..03a1bf9 --- /dev/null +++ b/experiments/e54-boundary-faults/results/pilot/v3-runs.csv @@ -0,0 +1,124 @@ +env,fault,dose,seed,cells,raises,rule,strict,weights,record,bridge,gain,last,episodes,sha,learn_s,raised,complete +halfcheetah,none,1.0,9,0,0,0,,0,0,0,949.0,600.4,400,0260ca9d,92.392,,1 +halfcheetah,obs:f16,0.01,9,4049,0,0,,1,0,0,1029.4,660.9,400,caabdae4,94.315,,1 +halfcheetah,reward:stale,one,9,1,0,0,,1,1,0,867.9,519.3,400,a255284b,93.819,,1 +pendulum,action:clip,0.001,9,62,0,0,,1,0,0,1014.3,-212.4,512,8560c624,20.513,,1 +pendulum,action:clip,0.01,9,570,0,0,,1,0,0,1000.3,-236.9,512,c4d91b7d,20.568,,1 +pendulum,action:clip,0.1,9,5586,0,0,,1,0,0,1017.2,-221.1,512,47f6ab43,20.529,,1 +pendulum,action:clip,1.0,9,65640,0,0,,1,0,0,820.3,-395.4,512,e1084bea,20.605,,1 +pendulum,action:clip,one,9,1,0,0,,1,0,0,982.7,-240.9,512,ae18586b,21.061,,1 +pendulum,action:f16,0.001,9,78,0,0,,1,0,0,1021.6,-202.0,512,147109f1,20.691,,1 +pendulum,action:f16,0.01,9,709,0,0,,1,0,0,991.8,-231.8,512,8c0f4a77,20.438,,1 +pendulum,action:f16,0.1,9,6964,0,0,,1,0,0,992.8,-237.0,512,c24e6b8f,20.725,,1 +pendulum,action:f16,1.0,9,64943,0,0,,1,0,0,975.9,-255.3,512,8eebd6ca,20.365,,1 +pendulum,action:f16,one,9,1,0,0,,1,0,0,980.2,-243.4,512,55719d91,20.189,,1 +pendulum,action:stale,0.001,9,88,0,0,,1,0,0,1029.0,-202.0,512,bb0a97a5,20.236,,1 +pendulum,action:stale,0.01,9,784,0,0,,1,0,0,1018.6,-208.1,512,6a00e075,20.654,,1 +pendulum,action:stale,0.1,9,7428,0,0,,1,0,0,999.4,-245.4,512,654fe124,21.502,,1 +pendulum,action:stale,1.0,9,75433,0,0,,1,0,0,1035.1,-212.3,512,fe3d6d54,20.624,,1 +pendulum,action:stale,one,9,1,0,0,,1,0,0,863.3,-360.3,512,dca9013b,19.96,,1 +pendulum,action:swap,0.001,9,99,0,0,,1,0,0,1017.9,-213.7,512,5041d18d,20.49,,1 +pendulum,action:swap,0.01,9,969,0,0,,1,0,0,1013.8,-209.6,512,bd7c29a3,20.857,,1 +pendulum,action:swap,0.1,9,9468,0,0,,1,0,0,971.7,-256.4,512,9b9b21d7,20.992,,1 +pendulum,action:swap,1.0,9,87162,0,1,,1,0,0,-50.0,-1229.5,512,b0ffdeae,20.16,,1 +pendulum,action:swap,one,9,1,0,0,,1,0,0,1016.7,-206.9,512,4f480207,20.825,,1 +pendulum,action:zero,0.001,9,110,0,0,,1,0,0,1015.2,-214.7,512,304a1782,20.478,,1 +pendulum,action:zero,0.01,9,1068,0,0,,1,0,0,999.5,-227.2,512,c33d4dc1,20.926,,1 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+pendulum,final-obs:stale,1.0,9,512,0,0,,1,0,0,1029.3,-193.5,512,0f7b066e,19.973,,1 +pendulum,final-obs:stale,one,9,1,0,0,,1,0,0,600.2,-623.4,512,8957ca5e,19.958,,1 +pendulum,final-obs:swap,0.001,9,1,0,0,,1,0,0,543.4,-680.2,512,5aba21e8,20.425,,1 +pendulum,final-obs:swap,0.01,9,9,0,0,,1,0,0,1036.0,-187.5,512,5e4c40c5,19.67,,1 +pendulum,final-obs:swap,0.1,9,55,0,0,,1,0,0,974.4,-249.1,512,bd64bdd7,20.232,,1 +pendulum,final-obs:swap,1.0,9,512,0,0,,1,0,0,1021.2,-212.8,512,a5298567,20.007,,1 +pendulum,final-obs:swap,one,9,1,0,0,,1,0,0,568.2,-655.4,512,78959aa4,19.824,,1 +pendulum,final-obs:zero,0.001,9,1,0,0,,1,0,0,619.5,-604.2,512,fad9a8fd,20.589,,1 +pendulum,final-obs:zero,0.01,9,9,0,0,,1,0,0,1011.7,-218.6,512,c02cc3a6,20.222,,1 +pendulum,final-obs:zero,0.1,9,55,0,0,,1,0,0,1021.6,-208.8,512,317cfab1,20.053,,1 +pendulum,final-obs:zero,1.0,9,512,0,0,,1,0,0,983.0,-251.3,512,fb4a46a7,20.828,,1 +pendulum,final-obs:zero,one,9,1,0,0,,1,0,0,1006.0,-217.6,512,b09eb6c0,20.465,,1 +pendulum,indices:reorder,one,9,1,1,0,,,0,0,,,256,c00dbcf5,9.628,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,log:drop-first,0.001,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,19.41,,1 +pendulum,log:drop-first,0.01,9,2,0,0,,0,1,1,543.6,-680.0,512,3721266c,19.859,,1 +pendulum,log:drop-first,0.1,9,55,0,0,,0,1,1,543.0,-679.7,512,3721266c,19.88,,1 +pendulum,log:drop-first,1.0,9,512,0,0,,0,1,1,544.3,-676.4,512,3721266c,20.069,,1 +pendulum,log:drop-first,one,9,1,0,0,,0,1,1,543.6,-680.0,512,3721266c,18.866,,1 +pendulum,log:short,0.001,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,20.574,,1 +pendulum,log:short,0.01,9,2,0,0,,0,1,1,543.6,-680.0,512,3721266c,19.83,,1 +pendulum,log:short,0.1,9,55,0,0,,0,1,1,543.6,-680.0,512,3721266c,20.495,,1 +pendulum,log:short,1.0,9,512,0,0,,0,1,1,543.6,-680.0,512,3721266c,18.307,,1 +pendulum,log:short,one,9,1,0,0,,0,1,1,543.6,-680.0,512,3721266c,20.837,,1 +pendulum,none,1.0,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,20.651,,1 +pendulum,obs:f16,0.001,9,110,0,0,,1,0,0,1005.1,-218.5,512,4aacd844,20.488,,1 +pendulum,obs:f16,0.01,9,1068,0,0,,1,0,0,1034.2,-189.4,512,c811bc82,20.942,,1 +pendulum,obs:f16,0.1,9,10297,0,0,,1,0,0,1014.0,-219.7,512,09beb98f,20.296,,1 +pendulum,obs:f16,1.0,9,102416,0,0,,1,0,0,1006.7,-216.0,512,fc61fa92,20.56,,1 +pendulum,obs:f16,one,9,1,0,0,,1,0,0,990.0,-233.6,512,30013c92,20.286,,1 +pendulum,obs:stale,0.001,9,110,0,0,,1,0,0,1027.5,-205.4,512,bff93dd3,20.949,,1 +pendulum,obs:stale,0.01,9,1068,0,0,,1,0,0,1023.4,-208.0,512,a7ae8e93,22.138,,1 +pendulum,obs:stale,0.1,9,10295,0,0,,1,0,0,980.2,-252.4,512,5233fff6,20.403,,1 +pendulum,obs:stale,1.0,9,102400,0,0,,1,0,0,1039.2,-199.4,512,ae8dc584,20.094,,1 +pendulum,obs:stale,one,9,1,0,0,,1,0,0,986.1,-237.5,512,3ba703ed,20.591,,1 +pendulum,obs:swap,0.001,9,110,0,0,,1,0,0,1000.4,-219.4,512,d7217dbd,20.469,,1 +pendulum,obs:swap,0.01,9,1068,0,0,,1,0,0,992.3,-222.5,512,93173559,20.863,,1 +pendulum,obs:swap,0.1,9,10297,0,0,,1,0,0,885.0,-329.7,512,33e798c2,20.713,,1 +pendulum,obs:swap,1.0,9,102416,0,1,,1,0,0,7.8,-1209.3,512,69b755ce,20.83,,1 +pendulum,obs:swap,one,9,1,0,0,,1,0,0,999.0,-224.7,512,111db1f1,20.429,,1 +pendulum,obs:zero,0.001,9,110,0,0,,1,0,0,993.0,-228.8,512,8d882560,21.159,,1 +pendulum,obs:zero,0.01,9,1068,0,0,,1,0,0,999.1,-230.0,512,5594d740,20.973,,1 +pendulum,obs:zero,0.1,9,10297,0,0,,1,0,0,885.4,-359.9,512,1c2d54b5,20.717,,1 +pendulum,obs:zero,1.0,9,102416,0,1,,1,0,0,-45.0,-1251.1,512,4a7eeb1b,20.554,,1 +pendulum,obs:zero,one,9,1,0,0,,1,0,0,1010.3,-213.3,512,edfafcea,20.428,,1 +pendulum,reward:f16,0.001,9,110,0,0,,1,0,0,1010.4,-213.2,512,95417c9b,20.063,,1 +pendulum,reward:f16,0.01,9,1068,0,0,,1,0,0,1007.1,-216.5,512,8a61d14c,20.236,,1 +pendulum,reward:f16,0.1,9,10295,0,0,,1,0,0,1026.6,-198.0,512,40134f7b,20.088,,1 +pendulum,reward:f16,1.0,9,102388,0,0,,1,0,0,997.4,-217.9,512,7eaaf73b,20.82,,1 +pendulum,reward:f16,one,9,1,0,0,,1,0,0,731.8,-491.8,512,997b26f0,20.054,,1 +pendulum,reward:short-array,one,9,1,1,0,,,0,0,,,256,c00dbcf5,9.234,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,reward:stale,0.001,9,110,0,0,,1,1,0,999.2,-227.7,512,c32cab87,20.215,,1 +pendulum,reward:stale,0.01,9,1068,0,0,,1,1,0,1015.0,-219.7,512,c6f386c4,20.779,,1 +pendulum,reward:stale,0.1,9,10296,0,0,,1,1,0,1020.6,-201.0,512,b7b1eac0,20.63,,1 +pendulum,reward:stale,1.0,9,102400,0,0,,1,1,0,1022.1,-206.9,512,82ee3cdd,20.456,,1 +pendulum,reward:stale,one,9,1,0,0,,1,0,0,993.0,-230.6,512,0f9c27b9,20.054,,1 +pendulum,reward:swap,0.001,9,110,0,0,,1,1,0,983.7,-244.1,512,3271779a,20.643,,1 +pendulum,reward:swap,0.01,9,1068,0,0,,1,1,0,980.6,-241.5,512,dc34b515,20.444,,1 +pendulum,reward:swap,0.1,9,10296,0,0,,1,1,0,1008.4,-246.2,512,f6007e06,20.397,,1 +pendulum,reward:swap,1.0,9,102400,0,1,,1,1,0,74.5,-1180.7,512,4d7817df,20.469,,1 +pendulum,reward:swap,one,9,1,0,0,,1,1,0,1007.1,-216.5,512,d20c41ab,20.285,,1 +pendulum,reward:zero,0.001,9,110,0,0,,1,1,0,1016.7,-214.1,512,5432b13b,20.355,,1 +pendulum,reward:zero,0.01,9,1068,0,0,,1,1,0,995.1,-223.1,512,35c8690f,20.563,,1 +pendulum,reward:zero,0.1,9,10296,0,0,,1,1,0,888.4,-213.7,512,9184838f,19.945,,1 +pendulum,reward:zero,1.0,9,102400,0,1,,1,1,0,0.0,0.0,512,4e451436,20.47,,1 +pendulum,reward:zero,one,9,1,0,0,,1,0,0,994.2,-229.5,512,5a1d0a1b,19.787,,1 +pendulum,step:fill,0.001,9,110,0,0,,1,1,0,939.3,-280.0,496,4a833258,20.194,,1 +pendulum,step:fill,0.01,9,1068,0,0,,1,1,0,978.9,-247.5,496,8b0356a1,19.818,,1 +pendulum,step:fill,0.1,9,10296,0,0,,1,1,0,984.0,-228.2,448,4bf8fb5e,20.155,,1 +pendulum,step:fill,1.0,9,102400,0,1,,1,0,0,,,0,c1db1e9b,18.17,,1 +pendulum,step:fill,one,9,1,0,0,,1,1,0,1018.4,-205.2,511,26290d17,20.436,,1 +pendulum,terminated:spurious,0.001,9,110,0,0,,1,1,0,877.6,-165.8,621,2dff920f,19.325,,1 +pendulum,terminated:spurious,0.01,9,1068,0,1,,1,1,0,227.6,-158.6,1571,f33a49d0,20.387,,1 +pendulum,terminated:spurious,0.1,9,10296,0,1,,1,1,0,-23.8,-53.3,10753,bf58bfe6,20.333,,1 +pendulum,terminated:spurious,1.0,9,102400,0,1,,1,1,0,-3.9,-6.9,102400,fbd83720,21.665,,1 +pendulum,terminated:spurious,one,9,1,0,0,,1,1,0,1006.3,-217.4,513,5e6f8966,19.334,,1 +pendulum,truncated:as-term,0.001,9,1,0,0,,1,0,0,577.1,-646.5,512,62a84ecd,19.163,,1 +pendulum,truncated:as-term,0.01,9,9,0,0,,1,0,0,1017.7,-212.7,512,7513b6b1,19.781,,1 +pendulum,truncated:as-term,0.1,9,55,0,0,,1,0,0,1012.2,-218.2,512,3f82a43f,20.699,,1 +pendulum,truncated:as-term,1.0,9,512,0,0,,1,0,0,1025.1,-209.3,512,dd054830,19.996,,1 +pendulum,truncated:as-term,one,9,1,0,0,,1,0,0,731.3,-492.4,512,7fbf8a38,19.395,,1 +pendulum,truncated:drop,0.001,9,1,0,0,,1,1,0,564.1,-659.5,511,18800bc4,20.144,,1 +pendulum,truncated:drop,0.01,9,9,0,0,,1,1,0,1009.6,-248.2,503,90c3d626,20.197,,1 +pendulum,truncated:drop,0.1,9,55,0,0,,1,1,0,1055.0,-228.5,457,1921c4a2,19.94,,1 +pendulum,truncated:drop,1.0,9,512,0,1,,1,1,0,,,0,c6b90d35,19.536,,1 +pendulum,truncated:drop,one,9,1,0,0,,1,1,0,983.2,-240.4,511,e5aaf2ca,20.079,,1 +pendulum,wire-float64,1.0,9,0,0,0,,0,0,0,543.6,-680.0,512,3721266c,20.947,,1 diff --git a/experiments/e54-boundary-faults/results/pilot/v3.txt b/experiments/e54-boundary-faults/results/pilot/v3.txt new file mode 100644 index 0000000..c2bf8c2 --- /dev/null +++ b/experiments/e54-boundary-faults/results/pilot/v3.txt @@ -0,0 +1,154 @@ +/dev/nvme0n1p6 3.2T 724G 2.4T 24% / + 16:04:03 up 28 days, 5:05, 1 user, load average: 0.70, 1.75, 2.45 +123 runs, 10 at a time + 16:09:59 up 28 days, 5:11, 1 user, load average: 5.13, 6.40, 4.57 +E54_DONE +117 traced runs with a fault; localised right: 117 +env fault dose cells raises rule strict weights record bridge +halfcheetah none 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +halfcheetah obs:f16 0.01 4049 0/1 0/1 - 1/1 0/1 0/1 +halfcheetah reward:stale one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum none 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum delay-1ms 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum wire-float64 1.0 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum obs:zero 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:zero 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:zero 0.1 10297 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:zero 1.0 102416 0/1 1/1 - 1/1 0/1 0/1 +pendulum obs:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 0.1 10295 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale 1.0 102400 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 0.1 10297 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:swap 1.0 102416 0/1 1/1 - 1/1 0/1 0/1 +pendulum obs:swap one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 0.1 10297 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 1.0 102416 0/1 0/1 - 1/1 0/1 0/1 +pendulum obs:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 0.1 10296 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:zero 1.0 102400 0/1 1/1 - 1/1 0/1 0/1 +pendulum action:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 0.001 88 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 0.01 784 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 0.1 7428 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale 1.0 75433 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 0.001 99 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 0.01 969 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 0.1 9468 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:swap 1.0 87162 0/1 1/1 - 1/1 0/1 0/1 +pendulum action:swap one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 0.001 78 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 0.01 709 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 0.1 6964 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 1.0 64943 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 0.001 62 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 0.01 570 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 0.1 5586 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip 1.0 65640 0/1 0/1 - 1/1 0/1 0/1 +pendulum action:clip one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:zero 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:zero 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:zero 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:zero 1.0 102400 0/1 1/1 - 1/1 1/1 0/1 +pendulum reward:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:stale 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale 1.0 102400 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:swap 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:swap 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:swap 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:swap 1.0 102400 0/1 1/1 - 1/1 1/1 0/1 +pendulum reward:swap one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum reward:f16 0.001 110 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 0.01 1068 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 0.1 10295 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 1.0 102388 0/1 0/1 - 1/1 0/1 0/1 +pendulum reward:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:zero one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:stale one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:swap one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum final-obs:f16 one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum terminated:spurious 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum terminated:spurious 0.01 1068 0/1 1/1 - 1/1 1/1 0/1 +pendulum terminated:spurious 0.1 10296 0/1 1/1 - 1/1 1/1 0/1 +pendulum terminated:spurious 1.0 102400 0/1 1/1 - 1/1 1/1 0/1 +pendulum terminated:spurious one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 0.001 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 0.01 9 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 0.1 55 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:drop 1.0 512 0/1 1/1 - 1/1 1/1 0/1 +pendulum truncated:drop one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum truncated:as-term 0.001 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term 0.01 9 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term 0.1 55 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term 1.0 512 0/1 0/1 - 1/1 0/1 0/1 +pendulum truncated:as-term one 1 0/1 0/1 - 1/1 0/1 0/1 +pendulum step:fill 0.001 110 0/1 0/1 - 1/1 1/1 0/1 +pendulum step:fill 0.01 1068 0/1 0/1 - 1/1 1/1 0/1 +pendulum step:fill 0.1 10296 0/1 0/1 - 1/1 1/1 0/1 +pendulum step:fill 1.0 102400 0/1 1/1 - 1/1 0/1 0/1 +pendulum step:fill one 1 0/1 0/1 - 1/1 1/1 0/1 +pendulum log:drop-first 0.001 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum log:drop-first 0.01 2 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:drop-first 0.1 55 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:drop-first 1.0 512 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:drop-first one 1 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short 0.001 0 0/1 0/1 - 0/1 0/1 0/1 +pendulum log:short 0.01 2 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short 0.1 55 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short 1.0 512 0/1 0/1 - 0/1 1/1 1/1 +pendulum log:short one 1 0/1 0/1 - 0/1 1/1 1/1 +pendulum indices:reorder one 1 1/1 0/1 - - 0/1 0/1 +pendulum reward:short-array one 1 1/1 0/1 - - 0/1 0/1 + +share of runs caught, by dose (runs with a changed cell; either = weights or record) + pendulum client one n= 21 raises 0.0 rule 0.0 strict weights 1.0 record 0.19 bridge 0.0 either 1.0 + pendulum client 0.001 n= 21 raises 0.0 rule 0.0 strict weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum client 0.01 n= 21 raises 0.0 rule 0.048 strict weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum client 0.1 n= 21 raises 0.0 rule 0.048 strict weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum client 1.0 n= 21 raises 0.0 rule 0.429 strict weights 1.0 record 0.238 bridge 0.0 either 1.0 + pendulum log one n= 2 raises 0.0 rule 0.0 strict weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum log 0.01 n= 2 raises 0.0 rule 0.0 strict weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum log 0.1 n= 2 raises 0.0 rule 0.0 strict weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum log 1.0 n= 2 raises 0.0 rule 0.0 strict weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum all one n= 23 raises 0.0 rule 0.0 strict weights 0.913 record 0.261 bridge 0.087 either 1.0 + pendulum all 0.001 n= 21 raises 0.0 rule 0.0 strict weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum all 0.01 n= 23 raises 0.0 rule 0.043 strict weights 0.913 record 0.348 bridge 0.087 either 1.0 + pendulum all 0.1 n= 23 raises 0.0 rule 0.043 strict weights 0.913 record 0.348 bridge 0.087 either 1.0 + pendulum all 1.0 n= 23 raises 0.0 rule 0.391 strict weights 0.913 record 0.304 bridge 0.087 either 1.0 + halfcheetah client one n= 1 raises 0.0 rule 0.0 strict weights 1.0 record 1.0 bridge 0.0 either 1.0 + halfcheetah client 0.01 n= 1 raises 0.0 rule 0.0 strict weights 1.0 record 0.0 bridge 0.0 either 1.0 + halfcheetah all one n= 1 raises 0.0 rule 0.0 strict weights 1.0 record 1.0 bridge 0.0 either 1.0 + halfcheetah all 0.01 n= 1 raises 0.0 rule 0.0 strict weights 1.0 record 0.0 bridge 0.0 either 1.0 + +halfcheetah none at seed 9: 0260ca9d, E50's 0260ca9d: same +pendulum none at seed 9: 3721266c, E50's 3721266c: same +incomplete without an error: none diff --git a/experiments/e54-boundary-faults/results/registered.out b/experiments/e54-boundary-faults/results/registered.out new file mode 100644 index 0000000..b89f2aa --- /dev/null +++ b/experiments/e54-boundary-faults/results/registered.out @@ -0,0 +1,14 @@ + 16:13:44 up 28 days, 5:15, 1 user, load average: 0.39, 3.16, 3.64 +590 runs, 10 at a time +worker 4 done +worker 0 done +worker 9 done +worker 7 done +worker 3 done +worker 1 done +worker 6 done +worker 8 done +worker 5 done +worker 2 done + 17:02:23 up 28 days, 6:04, 1 user, load average: 7.84, 9.97, 10.26 +E54_DONE diff --git a/experiments/e54-boundary-faults/results/runs.csv b/experiments/e54-boundary-faults/results/runs.csv new file mode 100644 index 0000000..96c55bd --- /dev/null +++ b/experiments/e54-boundary-faults/results/runs.csv @@ -0,0 +1,591 @@ +env,fault,dose,seed,cells,raises,rule,strict,weights,record,bridge,gain,last,episodes,sha,learn_s,raised,complete +halfcheetah,action:clip,0.01,0,4039,0,0,0,1,0,0,1060.3,706.5,400,ec5a179d,94.616,,1 +halfcheetah,action:clip,0.01,1,4017,0,0,0,1,0,0,631.2,258.8,400,7eceb0cc,94.479,,1 +halfcheetah,action:clip,0.01,2,4030,0,0,0,1,0,0,889.9,578.3,400,35ecae43,92.453,,1 +halfcheetah,action:clip,1.0,0,408528,0,0,1,1,0,0,1273.8,1118.5,400,8ee6a77d,96.833,,1 +halfcheetah,action:clip,1.0,1,408625,0,0,1,1,0,0,1318.1,1148.4,400,14847897,95.683,,1 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+pendulum,final-obs:stale,1.0,1,512,0,0,0,1,0,0,1021.3,-206.3,512,2a99cc39,19.869,,1 +pendulum,final-obs:stale,1.0,2,512,0,0,0,1,0,0,1006.6,-201.2,512,64ddd2f4,19.72,,1 +pendulum,final-obs:stale,one,0,1,0,0,0,1,0,0,1021.8,-203.0,512,2cd3a46f,19.84,,1 +pendulum,final-obs:stale,one,1,1,0,0,0,1,0,0,1044.1,-190.0,512,3d2b49b0,19.467,,1 +pendulum,final-obs:stale,one,2,1,0,0,0,1,0,0,1012.2,-193.4,512,9080a4bf,19.721,,1 +pendulum,final-obs:swap,0.001,0,1,0,0,0,1,0,0,1026.2,-198.6,512,813800a8,19.619,,1 +pendulum,final-obs:swap,0.001,1,1,0,0,0,1,0,0,1028.2,-205.8,512,e3cb3e06,19.476,,1 +pendulum,final-obs:swap,0.001,2,1,0,0,0,1,0,0,1002.2,-203.4,512,50029099,20.414,,1 +pendulum,final-obs:swap,0.01,0,9,0,0,0,1,0,0,1025.7,-198.7,512,5bd0a6b2,19.879,,1 +pendulum,final-obs:swap,0.01,1,9,0,0,0,1,0,0,1029.2,-199.0,512,c97adf0d,19.803,,1 +pendulum,final-obs:swap,0.01,2,9,0,0,0,1,0,0,1010.8,-200.6,512,56c13906,19.824,,1 +pendulum,final-obs:swap,0.1,0,55,0,0,0,1,0,0,1015.4,-209.1,512,6b23376c,19.58,,1 +pendulum,final-obs:swap,0.1,1,55,0,0,0,1,0,0,1034.5,-193.7,512,95344a14,20.213,,1 +pendulum,final-obs:swap,0.1,2,55,0,0,0,1,0,0,1006.2,-205.2,512,9645d7b2,19.718,,1 +pendulum,final-obs:swap,1.0,0,512,0,0,0,1,0,0,1007.3,-212.6,512,3f8956ed,20.007,,1 +pendulum,final-obs:swap,1.0,1,512,0,0,0,1,0,0,1028.5,-203.2,512,c81ec51a,19.471,,1 +pendulum,final-obs:swap,1.0,2,512,0,0,0,1,0,0,1008.5,-202.0,512,1b6b79fd,19.882,,1 +pendulum,final-obs:swap,one,0,1,0,0,0,1,0,0,1035.3,-189.5,512,4e8492f7,19.775,,1 +pendulum,final-obs:swap,one,1,1,0,0,0,1,0,0,1035.4,-198.7,512,a85f2e22,20.077,,1 +pendulum,final-obs:swap,one,2,1,0,0,0,1,0,0,1014.7,-191.0,512,8f41be4c,19.931,,1 +pendulum,final-obs:zero,0.001,0,1,0,0,0,1,0,0,1016.9,-207.9,512,52f5a966,19.377,,1 +pendulum,final-obs:zero,0.001,1,1,0,0,0,1,0,0,1029.2,-204.8,512,da4ee014,19.875,,1 +pendulum,final-obs:zero,0.001,2,1,0,0,0,1,0,0,1011.7,-193.9,512,97d053b1,19.555,,1 +pendulum,final-obs:zero,0.01,0,9,0,0,0,1,0,0,1035.7,-188.6,512,010adf87,19.859,,1 +pendulum,final-obs:zero,0.01,1,9,0,0,0,1,0,0,1011.9,-217.2,512,fcdec6da,19.923,,1 +pendulum,final-obs:zero,0.01,2,9,0,0,0,1,0,0,968.6,-239.8,512,4e34a328,19.892,,1 +pendulum,final-obs:zero,0.1,0,55,0,0,0,1,0,0,1007.8,-216.6,512,352a0dfc,19.813,,1 +pendulum,final-obs:zero,0.1,1,55,0,0,1,1,0,0,891.7,-337.4,512,b6bda6f1,19.546,,1 +pendulum,final-obs:zero,0.1,2,55,0,0,0,1,0,0,990.2,-218.2,512,72354b6f,19.358,,1 +pendulum,final-obs:zero,1.0,0,512,0,0,1,1,0,0,908.5,-313.6,512,efd619dc,20.067,,1 +pendulum,final-obs:zero,1.0,1,512,0,0,1,1,0,0,982.1,-253.0,512,b56b40ae,20.164,,1 +pendulum,final-obs:zero,1.0,2,512,0,0,1,1,0,0,950.9,-258.0,512,226ab780,20.028,,1 +pendulum,final-obs:zero,one,0,1,0,0,0,1,0,0,1017.8,-207.0,512,bf033c56,19.844,,1 +pendulum,final-obs:zero,one,1,1,0,0,0,1,0,0,1031.6,-202.5,512,d0314318,19.847,,1 +pendulum,final-obs:zero,one,2,1,0,0,0,1,0,0,989.6,-216.0,512,81a24d76,19.579,,1 +pendulum,indices:reorder,one,0,1,1,0,,,0,0,,,256,5333d4e3,9.571,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,indices:reorder,one,1,1,1,0,,,0,0,,,256,afaa8757,9.688,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,indices:reorder,one,2,1,1,0,,,0,0,,,256,fde67d33,9.389,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,log:drop-first,0.001,0,0,0,0,0,0,0,0,1025.1,-199.8,512,ec5b8226,19.513,,1 +pendulum,log:drop-first,0.001,1,0,0,0,0,0,0,0,1025.3,-208.8,512,062e92e3,19.759,,1 +pendulum,log:drop-first,0.001,2,0,0,0,0,0,0,0,959.6,-246.0,512,3a8d968f,19.549,,1 +pendulum,log:drop-first,0.01,0,2,0,0,0,0,1,1,1025.1,-199.8,512,ec5b8226,19.651,,1 +pendulum,log:drop-first,0.01,1,2,0,0,0,0,1,1,1025.3,-208.8,512,062e92e3,19.823,,1 +pendulum,log:drop-first,0.01,2,2,0,0,0,0,1,1,959.6,-246.0,512,3a8d968f,19.331,,1 +pendulum,log:drop-first,0.1,0,55,0,0,0,0,1,1,1024.8,-199.5,512,ec5b8226,19.167,,1 +pendulum,log:drop-first,0.1,1,55,0,0,0,0,1,1,1025.2,-208.4,512,062e92e3,19.756,,1 +pendulum,log:drop-first,0.1,2,55,0,0,0,0,1,1,959.5,-245.7,512,3a8d968f,18.895,,1 +pendulum,log:drop-first,1.0,0,512,0,0,0,0,1,1,1025.0,-196.5,512,ec5b8226,19.854,,1 +pendulum,log:drop-first,1.0,1,512,0,0,0,0,1,1,1025.4,-205.4,512,062e92e3,19.626,,1 +pendulum,log:drop-first,1.0,2,512,0,0,0,0,1,1,959.8,-242.6,512,3a8d968f,19.134,,1 +pendulum,log:drop-first,one,0,1,0,0,0,0,1,1,1025.1,-199.8,512,ec5b8226,19.562,,1 +pendulum,log:drop-first,one,1,1,0,0,0,0,1,1,1025.3,-208.8,512,062e92e3,20.211,,1 +pendulum,log:drop-first,one,2,1,0,0,0,0,1,1,959.6,-246.0,512,3a8d968f,19.518,,1 +pendulum,log:short,0.001,0,0,0,0,0,0,0,0,1025.1,-199.8,512,ec5b8226,19.539,,1 +pendulum,log:short,0.001,1,0,0,0,0,0,0,0,1025.3,-208.8,512,062e92e3,19.567,,1 +pendulum,log:short,0.001,2,0,0,0,0,0,0,0,959.6,-246.0,512,3a8d968f,19.07,,1 +pendulum,log:short,0.01,0,2,0,0,0,0,1,1,1025.1,-199.8,512,ec5b8226,19.531,,1 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+pendulum,none,1.0,2,0,0,0,0,0,0,0,959.6,-246.0,512,3a8d968f,19.747,,1 +pendulum,none,1.0,10,0,0,0,0,0,0,0,1010.1,-226.2,512,4b5c8f2d,19.093,,1 +pendulum,none,1.0,11,0,0,0,0,0,0,0,1013.5,-210.7,512,648cc27f,17.533,,1 +pendulum,none,1.0,12,0,0,0,0,0,0,0,1000.1,-215.4,512,f60c2bd7,18.676,,1 +pendulum,none,1.0,13,0,0,0,0,0,0,0,994.9,-205.0,512,c11211ed,19.927,,1 +pendulum,none,1.0,14,0,0,0,0,0,0,0,1007.2,-225.4,512,c69e3e42,17.581,,1 +pendulum,none,1.0,15,0,0,0,0,0,0,0,975.3,-221.9,512,9e7baf1a,18.894,,1 +pendulum,none,1.0,16,0,0,0,0,0,0,0,1073.4,-205.0,512,b4dafc53,18.806,,1 +pendulum,none,1.0,17,0,0,0,0,0,0,0,1013.4,-234.7,512,ae3c8039,18.937,,1 +pendulum,none,1.0,18,0,0,0,0,0,0,0,1039.4,-200.5,512,af2a0223,19.246,,1 +pendulum,none,1.0,19,0,0,0,0,0,0,0,970.9,-222.0,512,e1b7ed5c,19.148,,1 +pendulum,obs:f16,0.001,0,110,0,0,0,1,0,0,1011.7,-213.1,512,99628584,19.628,,1 +pendulum,obs:f16,0.001,1,110,0,0,0,1,0,0,1040.1,-193.9,512,ae53323b,19.827,,1 +pendulum,obs:f16,0.001,2,110,0,0,0,1,0,0,1013.7,-191.9,512,f66f3be5,19.797,,1 +pendulum,obs:f16,0.01,0,1068,0,0,0,1,0,0,1003.1,-216.6,512,8cdce0a6,19.572,,1 +pendulum,obs:f16,0.01,1,1068,0,0,0,1,0,0,1037.2,-191.9,512,9efc34bd,20.188,,1 +pendulum,obs:f16,0.01,2,1068,0,0,0,1,0,0,1023.2,-184.8,512,a291b401,19.91,,1 +pendulum,obs:f16,0.1,0,10297,0,0,0,1,0,0,1023.7,-198.6,512,e705e552,20.075,,1 +pendulum,obs:f16,0.1,1,10297,0,0,0,1,0,0,1033.1,-195.5,512,458c24ce,19.514,,1 +pendulum,obs:f16,0.1,2,10297,0,0,1,1,0,0,947.4,-259.5,512,67315f13,19.43,,1 +pendulum,obs:f16,1.0,0,102416,0,0,0,1,0,0,1019.9,-200.7,512,6bd93edb,19.289,,1 +pendulum,obs:f16,1.0,1,102416,0,0,0,1,0,0,1047.4,-194.5,512,db006462,19.853,,1 +pendulum,obs:f16,1.0,2,102416,0,0,0,1,0,0,987.4,-214.1,512,0655bd23,19.52,,1 +pendulum,obs:f16,one,0,1,0,0,0,1,0,0,1003.9,-220.9,512,d1484e30,19.717,,1 +pendulum,obs:f16,one,1,1,0,0,0,1,0,0,1042.8,-191.3,512,7809451b,19.819,,1 +pendulum,obs:f16,one,2,1,0,0,0,1,0,0,1012.5,-193.1,512,3026d8df,19.901,,1 +pendulum,obs:stale,0.001,0,110,0,0,0,1,0,0,1026.5,-196.4,512,229c165b,20.06,,1 +pendulum,obs:stale,0.001,1,110,0,0,0,1,0,0,1035.7,-189.4,512,f75dec8d,20.047,,1 +pendulum,obs:stale,0.001,2,110,0,0,0,1,0,0,997.7,-207.8,512,17980b93,19.828,,1 +pendulum,obs:stale,0.01,0,1068,0,0,0,1,0,0,1026.5,-201.1,512,0cbb3296,19.873,,1 +pendulum,obs:stale,0.01,1,1068,0,0,0,1,0,0,1023.7,-208.3,512,2a0550ff,19.845,,1 +pendulum,obs:stale,0.01,2,1068,0,0,0,1,0,0,1027.2,-191.2,512,08b18278,19.63,,1 +pendulum,obs:stale,0.1,0,10295,0,0,0,1,0,0,1020.3,-207.2,512,cf301c7d,20.371,,1 +pendulum,obs:stale,0.1,1,10295,0,0,0,1,0,0,1036.2,-218.8,512,c99edca5,19.999,,1 +pendulum,obs:stale,0.1,2,10295,0,0,0,1,0,0,1023.6,-197.2,512,9a8442c4,20.512,,1 +pendulum,obs:stale,1.0,0,102400,0,0,1,1,0,0,971.8,-270.1,512,bd9261b4,20.027,,1 +pendulum,obs:stale,1.0,1,102400,0,0,0,1,0,0,1056.3,-187.7,512,3b8e0f67,19.603,,1 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+pendulum,reward:f16,0.001,2,110,0,0,0,1,0,0,983.5,-222.1,512,20a63eaf,19.658,,1 +pendulum,reward:f16,0.01,0,1068,0,0,0,1,0,0,1024.1,-200.8,512,957547ea,19.383,,1 +pendulum,reward:f16,0.01,1,1068,0,0,0,1,0,0,1040.1,-188.9,512,ff01fa2a,19.669,,1 +pendulum,reward:f16,0.01,2,1068,0,0,0,1,0,0,1000.6,-207.3,512,1404abe1,19.43,,1 +pendulum,reward:f16,0.1,0,10294,0,0,0,1,0,0,1015.8,-208.7,512,761d3243,19.683,,1 +pendulum,reward:f16,0.1,1,10295,0,0,0,1,0,0,1045.1,-184.4,512,b5be10fa,19.995,,1 +pendulum,reward:f16,0.1,2,10296,0,0,0,1,0,0,1021.0,-190.4,512,6c4077d0,19.373,,1 +pendulum,reward:f16,1.0,0,102385,0,0,0,1,0,0,1018.1,-205.8,512,1d482f24,19.743,,1 +pendulum,reward:f16,1.0,1,102393,0,0,0,1,0,0,987.4,-246.8,512,add3c078,19.785,,1 +pendulum,reward:f16,1.0,2,102378,0,0,0,1,0,0,1005.9,-205.1,512,c6599770,20.226,,1 +pendulum,reward:f16,one,0,1,0,0,0,1,0,0,1012.7,-212.2,512,e95cad4d,20.056,,1 +pendulum,reward:f16,one,1,1,0,0,0,1,0,0,1028.8,-205.3,512,833fe81c,19.293,,1 +pendulum,reward:f16,one,2,1,0,0,0,1,0,0,1007.6,-198.1,512,9bbbf32e,19.67,,1 +pendulum,reward:short-array,one,0,1,1,0,,,0,0,,,256,5333d4e3,9.312,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,reward:short-array,one,1,1,1,0,,,0,0,,,256,afaa8757,9.2,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,reward:short-array,one,2,1,1,0,,,0,0,,,256,fde67d33,9.648,"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ",0 +pendulum,reward:stale,0.001,0,110,0,0,0,1,1,0,1012.1,-212.3,512,bdaacf4d,20.178,,1 +pendulum,reward:stale,0.001,1,110,0,0,0,1,1,0,1051.8,-183.8,512,39c8b7d4,20.079,,1 +pendulum,reward:stale,0.001,2,110,0,0,0,1,1,0,1002.3,-205.8,512,55e6f6cb,19.476,,1 +pendulum,reward:stale,0.01,0,1068,0,0,0,1,1,0,1021.3,-201.5,512,c3ecfd3a,19.637,,1 +pendulum,reward:stale,0.01,1,1068,0,0,0,1,1,0,1046.9,-186.4,512,3d6114f7,20.146,,1 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+pendulum,reward:swap,one,2,1,0,0,0,1,0,0,1016.7,-188.9,512,dd11b659,19.623,,1 +pendulum,reward:zero,0.001,0,110,0,0,0,1,1,0,1028.3,-188.2,512,62b73298,19.634,,1 +pendulum,reward:zero,0.001,1,110,0,0,0,1,1,0,1040.3,-190.5,512,451c93c7,20.038,,1 +pendulum,reward:zero,0.001,2,110,0,0,0,1,1,0,1004.7,-201.6,512,e2a3a84a,19.41,,1 +pendulum,reward:zero,0.01,0,1068,0,0,0,1,1,0,1009.4,-196.9,512,11d1d7dc,19.861,,1 +pendulum,reward:zero,0.01,1,1068,0,0,0,1,1,0,1023.4,-196.3,512,e90c654b,19.361,,1 +pendulum,reward:zero,0.01,2,1068,0,0,0,1,1,0,982.4,-216.0,512,57614cea,19.793,,1 +pendulum,reward:zero,0.1,0,10296,0,0,0,1,1,0,903.0,-194.0,512,6230d345,19.496,,1 +pendulum,reward:zero,0.1,1,10296,0,0,0,1,1,0,889.2,-221.8,512,dc7fc3b4,20.121,,1 +pendulum,reward:zero,0.1,2,10296,0,0,0,1,1,0,875.5,-211.9,512,13b5a9ee,19.789,,1 +pendulum,reward:zero,1.0,0,102400,0,1,1,1,1,0,0.0,0.0,512,f3c1c4c3,19.597,,1 +pendulum,reward:zero,1.0,1,102400,0,1,1,1,1,0,0.0,0.0,512,d483503e,19.678,,1 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+pendulum,step:fill,0.1,2,10296,0,0,0,1,1,0,910.0,-239.3,448,e53add0e,19.312,,1 +pendulum,step:fill,1.0,0,102400,0,1,1,1,0,0,,,0,7c353631,19.2,,1 +pendulum,step:fill,1.0,1,102400,0,1,1,1,0,0,,,0,d303871d,18.418,,1 +pendulum,step:fill,1.0,2,102400,0,1,1,1,0,0,,,0,36f6d91e,18.339,,1 +pendulum,step:fill,one,0,1,0,0,0,1,1,0,1016.2,-208.6,511,1426c402,20.041,,1 +pendulum,step:fill,one,1,1,0,0,0,1,1,0,1021.7,-212.3,511,1b86e0d9,19.461,,1 +pendulum,step:fill,one,2,1,0,0,0,1,1,0,1011.2,-194.4,511,e2d1cee4,19.933,,1 +pendulum,terminated:spurious,0.001,0,110,0,0,1,1,1,0,871.4,-168.1,621,d6f284ed,19.685,,1 +pendulum,terminated:spurious,0.001,1,110,0,0,1,1,1,0,886.9,-163.0,621,1e3f87cc,19.992,,1 +pendulum,terminated:spurious,0.001,2,110,0,0,1,1,1,0,833.6,-178.6,621,eb7e82e2,19.869,,1 +pendulum,terminated:spurious,0.01,0,1068,0,1,1,1,1,0,195.6,-178.6,1571,bfaf6961,19.721,,1 +pendulum,terminated:spurious,0.01,1,1068,0,1,1,1,1,0,242.7,-142.4,1571,d166081a,20.004,,1 +pendulum,terminated:spurious,0.01,2,1068,0,1,1,1,1,0,236.3,-152.5,1571,66d62461,19.51,,1 +pendulum,terminated:spurious,0.1,0,10296,0,1,1,1,1,0,-17.3,-48.8,10753,c336fac8,19.85,,1 +pendulum,terminated:spurious,0.1,1,10296,0,1,1,1,1,0,-16.3,-44.9,10753,f1cfa982,20.247,,1 +pendulum,terminated:spurious,0.1,2,10296,0,1,1,1,1,0,-22.4,-50.6,10753,711b8f59,20.214,,1 +pendulum,terminated:spurious,1.0,0,102400,0,1,1,1,1,0,-2.9,-6.5,102400,f885d396,20.995,,1 +pendulum,terminated:spurious,1.0,1,102400,0,1,1,1,1,0,-2.8,-6.3,102400,ef551e57,20.608,,1 +pendulum,terminated:spurious,1.0,2,102400,0,1,1,1,1,0,-2.1,-6.0,102400,1611c255,20.606,,1 +pendulum,terminated:spurious,one,0,1,0,0,0,1,1,0,1014.4,-210.5,513,44d6e670,19.894,,1 +pendulum,terminated:spurious,one,1,1,0,0,0,1,1,0,1040.4,-193.6,513,ad8c101a,19.48,,1 +pendulum,terminated:spurious,one,2,1,0,0,0,1,1,0,1012.5,-193.1,513,b9f30a62,20.246,,1 +pendulum,truncated:as-term,0.001,0,1,0,0,0,1,0,0,1024.1,-200.8,512,891f5fc9,19.892,,1 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58 cells changed", "dose": "0.001", "env": "pendulum", "fault": "action:clip", "fault_json": {"cells": 58, "dose": "0.001", "fault": "action:clip", "first": [110, 3], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "action:clip", "learn_s": 19.581, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "5f35479aa957fd239df41e4c34281122a40493fd06c1158ae52ea7cd527d2622"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:clip\", \"dose\": \"0.001\", \"seed\": 1, \"weights_sha256\": \"5f35479aa957fd239df41e4c34281122a40493fd06c1158ae52ea7cd527d2622\", \"learn_s\": 19.581, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.001", "env": "pendulum", "fault": "action:clip", "fault_json": {"cells": 55, "dose": "0.001", "fault": "action:clip", "first": [110, 3], "steps": 6400}, "result": {"client_rc": 0, "dose": 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'plugrl-server-stop'; 63417 cells changed", "dose": "1.0", "env": "pendulum", "fault": "action:clip", "fault_json": {"cells": 63417, "dose": "1.0", "fault": "action:clip", "first": [0, 2], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "action:clip", "learn_s": 19.92, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "319f69beae8ffbc924e1a45df5b82928042b55ee0c6e68ed5e8bf84cc3bc3a91"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:clip\", \"dose\": \"1.0\", \"seed\": 1, \"weights_sha256\": \"319f69beae8ffbc924e1a45df5b82928042b55ee0c6e68ed5e8bf84cc3bc3a91\", \"learn_s\": 19.92, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 58306 cells changed", "dose": "1.0", "env": "pendulum", "fault": "action:clip", "fault_json": {"cells": 58306, "dose": "1.0", "fault": "action:clip", "first": [0, 0], "steps": 6400}, "result": 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'plugrl-server-stop'; 707 cells changed", "dose": "0.01", "env": "pendulum", "fault": "action:f16", "fault_json": {"cells": 707, "dose": "0.01", "fault": "action:f16", "first": [32, 11], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "action:f16", "learn_s": 19.953, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "b4f02fd1092798ded1d6b3838885188b18409718e11d62a929596b43a2ac78d0"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:f16\", \"dose\": \"0.01\", \"seed\": 1, \"weights_sha256\": \"b4f02fd1092798ded1d6b3838885188b18409718e11d62a929596b43a2ac78d0\", \"learn_s\": 19.953, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 751 cells changed", "dose": "0.01", "env": "pendulum", "fault": "action:f16", "fault_json": {"cells": 751, "dose": "0.01", "fault": "action:f16", "first": [32, 11], "steps": 6400}, "result": {"client_rc": 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'plugrl-server-stop'; 7664 cells changed", "dose": "0.1", "env": "pendulum", "fault": "action:stale", "fault_json": {"cells": 7664, "dose": "0.1", "fault": "action:stale", "first": [0, 2], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "action:stale", "learn_s": 19.875, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "fefa8cca0dedc5ace5ccc6619f961c1ad348d548a49299ece6c881a2d3d2e4c0"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:stale\", \"dose\": \"0.1\", \"seed\": 1, \"weights_sha256\": \"fefa8cca0dedc5ace5ccc6619f961c1ad348d548a49299ece6c881a2d3d2e4c0\", \"learn_s\": 19.875, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 7745 cells changed", "dose": "0.1", "env": "pendulum", "fault": "action:stale", "fault_json": {"cells": 7745, "dose": "0.1", "fault": "action:stale", "first": [0, 2], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "action:stale", "learn_s": 20.175, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "5e58606eaca284796c5609a5815ccba7ffc1b8863eab37e4e13a699d3a6e60c6"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:stale\", \"dose\": \"0.1\", \"seed\": 2, \"weights_sha256\": \"5e58606eaca284796c5609a5815ccba7ffc1b8863eab37e4e13a699d3a6e60c6\", \"learn_s\": 20.175, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 77023 cells changed", "dose": "1.0", "env": "pendulum", "fault": "action:stale", "fault_json": {"cells": 77023, "dose": "1.0", "fault": "action:stale", "first": [0, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "action:stale", "learn_s": 19.856, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": 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1 cells changed", "dose": "one", "env": "pendulum", "fault": "action:stale", "fault_json": {"cells": 1, "dose": "one", "fault": "action:stale", "first": [3251, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "action:stale", "learn_s": 20.194, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "aa1a75e2c0527e79b38dd9e7f3370c56521baa5489a297ce62c959b719e2e9df"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:stale\", \"dose\": \"one\", \"seed\": 0, \"weights_sha256\": \"aa1a75e2c0527e79b38dd9e7f3370c56521baa5489a297ce62c959b719e2e9df\", \"learn_s\": 20.194, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "action:stale", "fault_json": {"cells": 1, "dose": "one", "fault": "action:stale", "first": [3249, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", 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"dose": "0.001", "fault": "action:swap", "first": [110, 3], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "action:swap", "learn_s": 19.624, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "fb249d01ea3b38688d07819fe6044c1398ac82c7ff7ce836353fd4fee990c633"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:swap\", \"dose\": \"0.001\", \"seed\": 2, \"weights_sha256\": \"fb249d01ea3b38688d07819fe6044c1398ac82c7ff7ce836353fd4fee990c633\", \"learn_s\": 19.624, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 976 cells changed", "dose": "0.01", "env": "pendulum", "fault": "action:swap", "fault_json": {"cells": 976, "dose": "0.01", "fault": "action:swap", "first": [5, 7], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "action:swap", "learn_s": 19.762, "seed": 0, "steps": 102400, "torch": 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'plugrl-server-stop'; 9375 cells changed", "dose": "0.1", "env": "pendulum", "fault": "action:swap", "fault_json": {"cells": 9375, "dose": "0.1", "fault": "action:swap", "first": [0, 2], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "action:swap", "learn_s": 19.928, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "0bd3b36f5ffbd908e9e9d9fb4ef7a3b16125d941f47d24bf7e4d363e37fea1aa"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"action:swap\", \"dose\": \"0.1\", \"seed\": 0, \"weights_sha256\": \"0bd3b36f5ffbd908e9e9d9fb4ef7a3b16125d941f47d24bf7e4d363e37fea1aa\", \"learn_s\": 19.928, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9388 cells changed", "dose": "0.1", "env": "pendulum", "fault": "action:swap", "fault_json": {"cells": 9388, "dose": "0.1", "fault": "action:swap", "first": [0, 2], "steps": 6400}, "result": {"client_rc": 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\"4e8492f728a2071c925c7cd81501a2a2c729c9be743fbedb6a91a70aa80d6644\", \"learn_s\": 19.775, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "final-obs:swap", "fault_json": {"cells": 1, "dose": "one", "fault": "final-obs:swap", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "final-obs:swap", "learn_s": 20.077, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "a85f2e226bb75bda7066bb7416b78c9c0a1b01a8f27e0fd0d03366af8d5013cb"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:swap\", \"dose\": \"one\", \"seed\": 1, \"weights_sha256\": \"a85f2e226bb75bda7066bb7416b78c9c0a1b01a8f27e0fd0d03366af8d5013cb\", \"learn_s\": 20.077, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "final-obs:swap", "fault_json": {"cells": 1, "dose": "one", "fault": "final-obs:swap", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "final-obs:swap", "learn_s": 19.931, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "8f41be4c2c30e0eca95d4872d6595fed1a326a230426151ad07343d2603dbef2"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:swap\", \"dose\": \"one\", \"seed\": 2, \"weights_sha256\": \"8f41be4c2c30e0eca95d4872d6595fed1a326a230426151ad07343d2603dbef2\", \"learn_s\": 19.931, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "0.001", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 1, "dose": "0.001", "fault": "final-obs:zero", "first": [4599, 8], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.377, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "52f5a966e7d5e55feea2703f540c36568ffa2853607177b9aaa3a54531e7d8b6"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.001\", \"seed\": 0, \"weights_sha256\": \"52f5a966e7d5e55feea2703f540c36568ffa2853607177b9aaa3a54531e7d8b6\", \"learn_s\": 19.377, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "0.001", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 1, "dose": "0.001", "fault": "final-obs:zero", "first": [4599, 8], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.875, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "da4ee0149437b653f5f813886e5d1c96d99ea5d260b4159d7660676c5379f3af"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.001\", \"seed\": 1, \"weights_sha256\": \"da4ee0149437b653f5f813886e5d1c96d99ea5d260b4159d7660676c5379f3af\", \"learn_s\": 19.875, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "0.001", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 1, "dose": "0.001", "fault": "final-obs:zero", "first": [4599, 8], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.555, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "97d053b1642d67b5c1528ca678ca814a91699a7e1453f711205dd4906ced3fa2"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.001\", \"seed\": 2, \"weights_sha256\": \"97d053b1642d67b5c1528ca678ca814a91699a7e1453f711205dd4906ced3fa2\", \"learn_s\": 19.555, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9 cells changed", "dose": "0.01", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 9, "dose": "0.01", "fault": "final-obs:zero", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.859, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "010adf8755a199bbfac74753c48f4b8d87ed6e55dab05f8cf37a4b4ebedb19eb"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.01\", \"seed\": 0, \"weights_sha256\": \"010adf8755a199bbfac74753c48f4b8d87ed6e55dab05f8cf37a4b4ebedb19eb\", \"learn_s\": 19.859, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9 cells changed", "dose": "0.01", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 9, "dose": "0.01", "fault": "final-obs:zero", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.923, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "fcdec6dae576622ac43a4c713e1212a9c5534c718751ebeee2a0eec38f36e7ca"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.01\", \"seed\": 1, \"weights_sha256\": \"fcdec6dae576622ac43a4c713e1212a9c5534c718751ebeee2a0eec38f36e7ca\", \"learn_s\": 19.923, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9 cells changed", "dose": "0.01", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 9, "dose": "0.01", "fault": "final-obs:zero", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.892, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "4e34a3288d28eb0360c5d2bba33569949249ffe6799ead1eef30bda7bbdcb97e"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.01\", \"seed\": 2, \"weights_sha256\": \"4e34a3288d28eb0360c5d2bba33569949249ffe6799ead1eef30bda7bbdcb97e\", \"learn_s\": 19.892, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.1", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 55, "dose": "0.1", "fault": "final-obs:zero", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.813, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "352a0dfc4ec067141a0e8d9e4b9bf2e9369fceefe7be3dc15c60c2d80f506d0e"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.1\", \"seed\": 0, \"weights_sha256\": \"352a0dfc4ec067141a0e8d9e4b9bf2e9369fceefe7be3dc15c60c2d80f506d0e\", \"learn_s\": 19.813, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.1", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 55, "dose": "0.1", "fault": "final-obs:zero", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.546, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "b6bda6f1977f21d6b641a9d847c9fe7094909228a26a5a79732580dc2e863b5a"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.1\", \"seed\": 1, \"weights_sha256\": \"b6bda6f1977f21d6b641a9d847c9fe7094909228a26a5a79732580dc2e863b5a\", \"learn_s\": 19.546, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.1", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 55, "dose": "0.1", "fault": "final-obs:zero", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.358, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "72354b6fc8a97c96c04515261c6cc1407bbd7329e4893fdd6e8b76293c26a882"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"0.1\", \"seed\": 2, \"weights_sha256\": \"72354b6fc8a97c96c04515261c6cc1407bbd7329e4893fdd6e8b76293c26a882\", \"learn_s\": 19.358, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 512 cells changed", "dose": "1.0", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 512, "dose": "1.0", "fault": "final-obs:zero", "first": [199, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 20.067, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "efd619dccba3a2882efdb949b98cb67f586bef6ce3ed7d6b4518bc5864d274fa"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"1.0\", \"seed\": 0, \"weights_sha256\": \"efd619dccba3a2882efdb949b98cb67f586bef6ce3ed7d6b4518bc5864d274fa\", \"learn_s\": 20.067, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 512 cells changed", "dose": "1.0", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 512, "dose": "1.0", "fault": "final-obs:zero", "first": [199, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 20.164, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "b56b40aeb286b0f57274d53eb1cb0c93771ac0a82c03d6e3780d61724db7a614"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"1.0\", \"seed\": 1, \"weights_sha256\": \"b56b40aeb286b0f57274d53eb1cb0c93771ac0a82c03d6e3780d61724db7a614\", \"learn_s\": 20.164, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 512 cells changed", "dose": "1.0", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 512, "dose": "1.0", "fault": "final-obs:zero", "first": [199, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 20.028, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "226ab78061bdfa60b64a33cd37ad23bc5978a14207bec12862999debdbdf5729"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"1.0\", \"seed\": 2, \"weights_sha256\": \"226ab78061bdfa60b64a33cd37ad23bc5978a14207bec12862999debdbdf5729\", \"learn_s\": 20.028, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 1, "dose": "one", "fault": "final-obs:zero", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.844, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "bf033c564b5f5a8908143ef2a613f874461337e9f389069d7858995a94f199b4"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"one\", \"seed\": 0, \"weights_sha256\": \"bf033c564b5f5a8908143ef2a613f874461337e9f389069d7858995a94f199b4\", \"learn_s\": 19.844, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 1, "dose": "one", "fault": "final-obs:zero", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.847, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "d031431893d9def8a1744e839b4354b76f92caa2ad817ec5bd3efb05367e4b0d"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"one\", \"seed\": 1, \"weights_sha256\": \"d031431893d9def8a1744e839b4354b76f92caa2ad817ec5bd3efb05367e4b0d\", \"learn_s\": 19.847, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "final-obs:zero", "fault_json": {"cells": 1, "dose": "one", "fault": "final-obs:zero", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "final-obs:zero", "learn_s": 19.579, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "81a24d76a1ef284c301a4b76df3139b72aad27e8028af0ce5286cdc32ccdba39"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"final-obs:zero\", \"dose\": \"one\", \"seed\": 2, \"weights_sha256\": \"81a24d76a1ef284c301a4b76df3139b72aad27e8028af0ce5286cdc32ccdba39\", \"learn_s\": 19.579, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 3250 steps: 'plugrl-server-resync'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "indices:reorder", "fault_json": {"cells": 1, "dose": "one", "fault": "indices:reorder", "first": [3249, 0], "steps": 3250}, "result": {"client_rc": 1, "dose": "one", "env": "pendulum", "fault": "indices:reorder", "learn_s": 9.571, "raised": "ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: this server steps every environment in lockstep, so each feedback must name all of this connection's envs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], in order; got [15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]); RLinf needs every environment for every step, so the run stops", "seed": 0, "steps": 51984, "torch": "2.14.1+cpu", "weights_sha256": "5333d4e3a0fe625f2ecb46f5f76a206aad17c59880785d2e551bef310136c529"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"indices:reorder\", \"dose\": \"one\", \"seed\": 0, \"raised\": \"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: this server steps every environment in lockstep, so each feedback must name all of this connection's envs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], in order; got [15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]); RLinf needs every environment for every step, so the run stops\", \"weights_sha256\": \"5333d4e3a0fe625f2ecb46f5f76a206aad17c59880785d2e551bef310136c529\", \"learn_s\": 9.571, \"steps\": 51984, \"torch\": \"2.14.1+cpu\", \"client_rc\": 1}"} +{"client_log": "closed after 3250 steps: 'plugrl-server-resync'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "indices:reorder", "fault_json": {"cells": 1, "dose": "one", "fault": "indices:reorder", "first": [3249, 0], "steps": 3250}, "result": {"client_rc": 1, "dose": "one", "env": "pendulum", "fault": "indices:reorder", "learn_s": 9.688, "raised": "ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: this server steps every environment in lockstep, so each feedback must name all of this connection's envs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], in order; got [15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]); RLinf needs every environment for every step, so the run stops", "seed": 1, "steps": 51984, "torch": "2.14.1+cpu", "weights_sha256": "afaa875703f32f3d48e0b905d7e703ef640a69ec102713d2e9e881f2ccf37bb9"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"indices:reorder\", \"dose\": \"one\", \"seed\": 1, \"raised\": \"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: this server steps every environment in lockstep, so each feedback must name all of this connection's envs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], in order; got [15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]); RLinf needs every environment for every step, so the run stops\", \"weights_sha256\": \"afaa875703f32f3d48e0b905d7e703ef640a69ec102713d2e9e881f2ccf37bb9\", \"learn_s\": 9.688, \"steps\": 51984, \"torch\": \"2.14.1+cpu\", \"client_rc\": 1}"} +{"client_log": "closed after 3250 steps: 'plugrl-server-resync'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "indices:reorder", "fault_json": {"cells": 1, "dose": "one", "fault": "indices:reorder", "first": [3249, 0], "steps": 3250}, "result": {"client_rc": 1, "dose": "one", "env": "pendulum", "fault": "indices:reorder", "learn_s": 9.389, "raised": "ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: this server steps every environment in lockstep, so each feedback must name all of this connection's envs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], in order; got [15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]); RLinf needs every environment for every step, so the run stops", "seed": 2, "steps": 51984, "torch": "2.14.1+cpu", "weights_sha256": "fde67d33e9d77aade06db02a2ca0b5ac77bf97a08d174365cbe8894d1903c3aa"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"indices:reorder\", \"dose\": \"one\", \"seed\": 2, \"raised\": \"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: this server steps every environment in lockstep, so each feedback must name all of this connection's envs, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], in order; got [15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]); RLinf needs every environment for every step, so the run stops\", \"weights_sha256\": \"fde67d33e9d77aade06db02a2ca0b5ac77bf97a08d174365cbe8894d1903c3aa\", \"learn_s\": 9.389, \"steps\": 51984, \"torch\": \"2.14.1+cpu\", \"client_rc\": 1}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.001", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.001", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.513, "log_cells": 0, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.001\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.513, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 0, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.001", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.001", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.759, "log_cells": 0, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.001\", \"seed\": 1, \"weights_sha256\": \"062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6\", \"learn_s\": 19.759, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 0, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.001", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.001", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.549, "log_cells": 0, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.001\", \"seed\": 2, \"weights_sha256\": \"3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41\", \"learn_s\": 19.549, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 0, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.01", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.01", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.651, "log_cells": 2, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.01\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.651, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 2, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.01", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.01", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.823, "log_cells": 2, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.01\", \"seed\": 1, \"weights_sha256\": \"062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6\", \"learn_s\": 19.823, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 2, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.01", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.01", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.331, "log_cells": 2, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.01\", \"seed\": 2, \"weights_sha256\": \"3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41\", \"learn_s\": 19.331, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 2, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.1", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.1", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.167, "log_cells": 55, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.1\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.167, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 55, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.1", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.1", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.756, "log_cells": 55, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.1\", \"seed\": 1, \"weights_sha256\": \"062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6\", \"learn_s\": 19.756, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 55, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.1", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "0.1", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "log:drop-first", "learn_s": 18.895, "log_cells": 55, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"0.1\", \"seed\": 2, \"weights_sha256\": \"3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41\", \"learn_s\": 18.895, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 55, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "1.0", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "1.0", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.854, "log_cells": 512, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"1.0\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.854, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 512, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "1.0", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "1.0", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.626, "log_cells": 512, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"1.0\", \"seed\": 1, \"weights_sha256\": \"062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6\", \"learn_s\": 19.626, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 512, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "1.0", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "1.0", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.134, "log_cells": 512, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"1.0\", \"seed\": 2, \"weights_sha256\": \"3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41\", \"learn_s\": 19.134, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 512, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "one", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "one", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.562, "log_cells": 1, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"one\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.562, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 1, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "one", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "one", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "log:drop-first", "learn_s": 20.211, "log_cells": 1, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"one\", \"seed\": 1, \"weights_sha256\": \"062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6\", \"learn_s\": 20.211, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 1, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "one", "env": "pendulum", "fault": "log:drop-first", "fault_json": {"cells": 0, "dose": "one", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "log:drop-first", "learn_s": 19.518, "log_cells": 1, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:drop-first\", \"dose\": \"one\", \"seed\": 2, \"weights_sha256\": \"3a8d968f19e2a8b5dc01540e41c4a64c02cb7a8c99ccdedf4a016008cf8bcd41\", \"learn_s\": 19.518, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 1, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.001", "env": "pendulum", "fault": "log:short", "fault_json": {"cells": 0, "dose": "0.001", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "log:short", "learn_s": 19.539, "log_cells": 0, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"log:short\", \"dose\": \"0.001\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.539, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"log_cells\": 0, \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "0.001", "env": "pendulum", "fault": "log:short", "fault_json": {"cells": 0, "dose": "0.001", "fault": "none", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "log:short", "learn_s": 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\"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1068 cells changed", "dose": "0.01", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 1068, "dose": "0.01", "fault": "reward:f16", "first": [5, 7], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.669, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ff01fa2aa13eafbf224ed6a223becc97ff5c899f64cf33386c8ca584d1ff40f4"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"0.01\", \"seed\": 1, \"weights_sha256\": \"ff01fa2aa13eafbf224ed6a223becc97ff5c899f64cf33386c8ca584d1ff40f4\", \"learn_s\": 19.669, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1068 cells changed", "dose": "0.01", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 1068, "dose": "0.01", "fault": "reward:f16", "first": [5, 7], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.43, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "1404abe167649fe5ce336c1622911d02e47ab9d5c2d190ed254d604a29ebadab"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"0.01\", \"seed\": 2, \"weights_sha256\": \"1404abe167649fe5ce336c1622911d02e47ab9d5c2d190ed254d604a29ebadab\", \"learn_s\": 19.43, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 10294 cells changed", "dose": "0.1", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 10294, "dose": "0.1", "fault": "reward:f16", "first": [0, 2], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.683, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": 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cells changed", "dose": "1.0", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 102385, "dose": "1.0", "fault": "reward:f16", "first": [0, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.743, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "1d482f2411705675308f3eb7c079976c9169d1525ea2bbe99f5daa9d0cd5cf7c"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"1.0\", \"seed\": 0, \"weights_sha256\": \"1d482f2411705675308f3eb7c079976c9169d1525ea2bbe99f5daa9d0cd5cf7c\", \"learn_s\": 19.743, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 102393 cells changed", "dose": "1.0", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 102393, "dose": "1.0", "fault": "reward:f16", "first": [0, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.785, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "add3c07891d96792275f5727b50fd158a7c2358b429c343322bac9ce104516f3"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"1.0\", \"seed\": 1, \"weights_sha256\": \"add3c07891d96792275f5727b50fd158a7c2358b429c343322bac9ce104516f3\", \"learn_s\": 19.785, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 102378 cells changed", "dose": "1.0", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 102378, "dose": "1.0", "fault": "reward:f16", "first": [0, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "reward:f16", "learn_s": 20.226, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "c65997706ff6818dac93747664a12ad686358c477d3ae462050eda88c2c3ed57"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"1.0\", \"seed\": 2, \"weights_sha256\": \"c65997706ff6818dac93747664a12ad686358c477d3ae462050eda88c2c3ed57\", \"learn_s\": 20.226, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 1, "dose": "one", "fault": "reward:f16", "first": [3249, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "reward:f16", "learn_s": 20.056, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "e95cad4deb7cbb61a29e7517893cc4c71b58f6176055cdd55002f93fd8a81e88"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"one\", \"seed\": 0, \"weights_sha256\": \"e95cad4deb7cbb61a29e7517893cc4c71b58f6176055cdd55002f93fd8a81e88\", \"learn_s\": 20.056, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 1, "dose": "one", "fault": "reward:f16", "first": [3249, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.293, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "833fe81c6d85bbd8c036aca29efeba2336b38e46b1ef364ab651c7868c3d8652"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"one\", \"seed\": 1, \"weights_sha256\": \"833fe81c6d85bbd8c036aca29efeba2336b38e46b1ef364ab651c7868c3d8652\", \"learn_s\": 19.293, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "reward:f16", "fault_json": {"cells": 1, "dose": "one", "fault": "reward:f16", "first": [3249, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "reward:f16", "learn_s": 19.67, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "9bbbf32e4f41722bbed75eac366a9aea2174d17520c6b2b406886061d6fb3e87"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:f16\", \"dose\": \"one\", \"seed\": 2, \"weights_sha256\": \"9bbbf32e4f41722bbed75eac366a9aea2174d17520c6b2b406886061d6fb3e87\", \"learn_s\": 19.67, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 3250 steps: 'plugrl-server-resync'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "reward:short-array", "fault_json": {"cells": 1, "dose": "one", "fault": "reward:short-array", "first": [3249, 0], "steps": 3250}, "result": {"client_rc": 1, "dose": "one", "env": "pendulum", "fault": "reward:short-array", "learn_s": 9.312, "raised": "ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: rewards is not an array of length 16); RLinf needs every environment for every step, so the run stops", "seed": 0, "steps": 51984, "torch": "2.14.1+cpu", "weights_sha256": "5333d4e3a0fe625f2ecb46f5f76a206aad17c59880785d2e551bef310136c529"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:short-array\", \"dose\": \"one\", \"seed\": 0, \"raised\": \"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: rewards is not an array of length 16); RLinf needs every environment for every step, so the run stops\", \"weights_sha256\": \"5333d4e3a0fe625f2ecb46f5f76a206aad17c59880785d2e551bef310136c529\", \"learn_s\": 9.312, \"steps\": 51984, \"torch\": \"2.14.1+cpu\", \"client_rc\": 1}"} +{"client_log": "closed after 3250 steps: 'plugrl-server-resync'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "reward:short-array", "fault_json": {"cells": 1, "dose": "one", "fault": "reward:short-array", "first": [3249, 0], "steps": 3250}, "result": {"client_rc": 1, "dose": "one", "env": "pendulum", "fault": "reward:short-array", "learn_s": 9.2, "raised": "ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: rewards is not an array of length 16); RLinf needs every environment for every step, so the run stops", "seed": 1, "steps": 51984, "torch": "2.14.1+cpu", "weights_sha256": "afaa875703f32f3d48e0b905d7e703ef640a69ec102713d2e9e881f2ccf37bb9"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:short-array\", \"dose\": \"one\", \"seed\": 1, \"raised\": \"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: rewards is not an array of length 16); RLinf needs every environment for every step, so the run stops\", \"weights_sha256\": \"afaa875703f32f3d48e0b905d7e703ef640a69ec102713d2e9e881f2ccf37bb9\", \"learn_s\": 9.2, \"steps\": 51984, \"torch\": \"2.14.1+cpu\", \"client_rc\": 1}"} +{"client_log": "closed after 3250 steps: 'plugrl-server-resync'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "reward:short-array", "fault_json": {"cells": 1, "dose": "one", "fault": "reward:short-array", "first": [3249, 0], "steps": 3250}, "result": {"client_rc": 1, "dose": "one", "env": "pendulum", "fault": "reward:short-array", "learn_s": 9.648, "raised": "ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: rewards is not an array of length 16); RLinf needs every environment for every step, so the run stops", "seed": 2, "steps": 51984, "torch": "2.14.1+cpu", "weights_sha256": "fde67d33e9d77aade06db02a2ca0b5ac77bf97a08d174365cbe8894d1903c3aa"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:short-array\", \"dose\": \"one\", \"seed\": 2, \"raised\": \"ClientLost: the connection holding slots [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15] closed (protocol error: rewards is not an array of length 16); RLinf needs every environment for every step, so the run stops\", \"weights_sha256\": \"fde67d33e9d77aade06db02a2ca0b5ac77bf97a08d174365cbe8894d1903c3aa\", \"learn_s\": 9.648, \"steps\": 51984, \"torch\": \"2.14.1+cpu\", \"client_rc\": 1}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 110 cells changed", "dose": "0.001", "env": "pendulum", "fault": "reward:stale", "fault_json": {"cells": 110, "dose": "0.001", "fault": "reward:stale", "first": [110, 3], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "reward:stale", "learn_s": 20.178, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "bdaacf4de170c3bbc441656a5c9e5714a68ddde79bebe6fd01f34024b3cb35d6"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:stale\", \"dose\": \"0.001\", \"seed\": 0, \"weights_sha256\": \"bdaacf4de170c3bbc441656a5c9e5714a68ddde79bebe6fd01f34024b3cb35d6\", \"learn_s\": 20.178, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 110 cells changed", "dose": "0.001", "env": "pendulum", "fault": "reward:stale", "fault_json": {"cells": 110, "dose": "0.001", "fault": "reward:stale", "first": [110, 3], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "reward:stale", "learn_s": 20.079, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "39c8b7d45c2aa6bba2b610acd1a16d0acac957d470a70355082276bdcd06ac8c"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:stale\", \"dose\": \"0.001\", \"seed\": 1, \"weights_sha256\": \"39c8b7d45c2aa6bba2b610acd1a16d0acac957d470a70355082276bdcd06ac8c\", \"learn_s\": 20.079, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 110 cells changed", "dose": "0.001", "env": "pendulum", "fault": "reward:stale", "fault_json": {"cells": 110, "dose": "0.001", "fault": "reward:stale", "first": [110, 3], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "reward:stale", "learn_s": 19.476, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "55e6f6cbe5671bd27d7354ee623b0b5972298121e8db8345963d775cfff0ed47"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"reward:stale\", \"dose\": \"0.001\", \"seed\": 2, \"weights_sha256\": \"55e6f6cbe5671bd27d7354ee623b0b5972298121e8db8345963d775cfff0ed47\", \"learn_s\": 19.476, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1068 cells changed", "dose": "0.01", "env": "pendulum", "fault": "reward:stale", "fault_json": {"cells": 1068, "dose": "0.01", "fault": "reward:stale", 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\"dose\": \"0.001\", \"seed\": 1, \"weights_sha256\": \"22cb06b93f77171bc40def0849074948119f289548bbc48b90ee01521a919f01\", \"learn_s\": 19.954, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "0.001", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 1, "dose": "0.001", "fault": "truncated:drop", "first": [4599, 8], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.001", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.819, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "496ca350256258f316d9b314fd79bb15f07b0651efc94bdc628fdf02e6e0efb2"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.001\", \"seed\": 2, \"weights_sha256\": \"496ca350256258f316d9b314fd79bb15f07b0651efc94bdc628fdf02e6e0efb2\", \"learn_s\": 19.819, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9 cells changed", "dose": "0.01", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 9, "dose": "0.01", "fault": "truncated:drop", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "truncated:drop", "learn_s": 20.132, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "bfafb0fbd5c3313b7bc637b85afe4bd6fbc465baa4ba47f9d6ce4135a5f5389e"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.01\", \"seed\": 0, \"weights_sha256\": \"bfafb0fbd5c3313b7bc637b85afe4bd6fbc465baa4ba47f9d6ce4135a5f5389e\", \"learn_s\": 20.132, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9 cells changed", "dose": "0.01", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 9, "dose": "0.01", "fault": "truncated:drop", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "truncated:drop", "learn_s": 20.007, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "db17509e0d55f9f530e3949d3b3ccb9b004cf2066d529c6686b3b2d3be0f6ab5"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.01\", \"seed\": 1, \"weights_sha256\": \"db17509e0d55f9f530e3949d3b3ccb9b004cf2066d529c6686b3b2d3be0f6ab5\", \"learn_s\": 20.007, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 9 cells changed", "dose": "0.01", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 9, "dose": "0.01", "fault": "truncated:drop", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.01", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.797, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "8c5d0450e157dc071c0c7faa326b9af48eaae9eee18077ebd5b4553f27865513"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.01\", \"seed\": 2, \"weights_sha256\": \"8c5d0450e157dc071c0c7faa326b9af48eaae9eee18077ebd5b4553f27865513\", \"learn_s\": 19.797, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.1", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 55, "dose": "0.1", "fault": "truncated:drop", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.291, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "d4b1ea6cf8e1451a4fe6d8a71dcc696311325830fb20c89f6e45a9f08f12a4b8"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.1\", \"seed\": 0, \"weights_sha256\": \"d4b1ea6cf8e1451a4fe6d8a71dcc696311325830fb20c89f6e45a9f08f12a4b8\", \"learn_s\": 19.291, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.1", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 55, "dose": "0.1", "fault": "truncated:drop", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.57, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "2f1eea580790542a740f7a7d8f507a61a5ad7c38f021300bc36f7417d90566e0"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.1\", \"seed\": 1, \"weights_sha256\": \"2f1eea580790542a740f7a7d8f507a61a5ad7c38f021300bc36f7417d90566e0\", \"learn_s\": 19.57, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 55 cells changed", "dose": "0.1", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 55, "dose": "0.1", "fault": "truncated:drop", "first": [199, 12], "steps": 6400}, "result": {"client_rc": 0, "dose": "0.1", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.893, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "48109f2c6807c543d61368f24fab2c15e1ef195e940fb463f6a260735ebb1462"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"0.1\", \"seed\": 2, \"weights_sha256\": \"48109f2c6807c543d61368f24fab2c15e1ef195e940fb463f6a260735ebb1462\", \"learn_s\": 19.893, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 512 cells changed", "dose": "1.0", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 512, "dose": "1.0", "fault": "truncated:drop", "first": [199, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.819, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "1a8332959838731601c25b32641a9c21540b5f0e743f779c57642595326886cf"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"1.0\", \"seed\": 0, \"weights_sha256\": \"1a8332959838731601c25b32641a9c21540b5f0e743f779c57642595326886cf\", \"learn_s\": 19.819, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 512 cells changed", "dose": "1.0", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 512, "dose": "1.0", "fault": "truncated:drop", "first": [199, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.366, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "c077fca8b10f246a0781deffcafd563837645513759cd6131e428fac51cb7185"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"1.0\", \"seed\": 1, \"weights_sha256\": \"c077fca8b10f246a0781deffcafd563837645513759cd6131e428fac51cb7185\", \"learn_s\": 19.366, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 512 cells changed", "dose": "1.0", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 512, "dose": "1.0", "fault": "truncated:drop", "first": [199, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.879, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "85691232578e1d5e1322744d5a6aab1412e64188f3aaad8cd1e188e6ad35da77"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"1.0\", \"seed\": 2, \"weights_sha256\": 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'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 1, "dose": "one", "fault": "truncated:drop", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.717, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "b21d87183b1cbaf2b0c5cf517819a4ba0399d3c277d5373145830c2221a3f0ad"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"one\", \"seed\": 1, \"weights_sha256\": \"b21d87183b1cbaf2b0c5cf517819a4ba0399d3c277d5373145830c2221a3f0ad\", \"learn_s\": 19.717, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 1 cells changed", "dose": "one", "env": "pendulum", "fault": "truncated:drop", "fault_json": {"cells": 1, "dose": "one", "fault": "truncated:drop", "first": [3399, 0], "steps": 6400}, "result": {"client_rc": 0, "dose": "one", "env": "pendulum", "fault": "truncated:drop", "learn_s": 19.751, "seed": 2, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "4bc2ef7bfc184f0b34bcc178630ce2ce93f66667a83e752e83ab6024e2ac8bae"}, "seed": 2, "train_log": "{\"env\": \"pendulum\", \"fault\": \"truncated:drop\", \"dose\": \"one\", \"seed\": 2, \"weights_sha256\": \"4bc2ef7bfc184f0b34bcc178630ce2ce93f66667a83e752e83ab6024e2ac8bae\", \"learn_s\": 19.751, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "1.0", "env": "pendulum", "fault": "wire-float64", "fault_json": {"cells": 0, "dose": "1.0", "fault": "wire-float64", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "wire-float64", "learn_s": 19.956, "seed": 0, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc"}, "seed": 0, "train_log": "{\"env\": \"pendulum\", \"fault\": \"wire-float64\", \"dose\": \"1.0\", \"seed\": 0, \"weights_sha256\": \"ec5b8226b227f3fa58bd771b411e3673b751ec2c062b010cf0dcef60baed42bc\", \"learn_s\": 19.956, \"steps\": 102400, \"torch\": \"2.14.1+cpu\", \"client_rc\": 0}"} +{"client_log": "closed after 6400 steps: 'plugrl-server-stop'; 0 cells changed", "dose": "1.0", "env": "pendulum", "fault": "wire-float64", "fault_json": {"cells": 0, "dose": "1.0", "fault": "wire-float64", "first": null, "steps": 6400}, "result": {"client_rc": 0, "dose": "1.0", "env": "pendulum", "fault": "wire-float64", "learn_s": 19.543, "seed": 1, "steps": 102400, "torch": "2.14.1+cpu", "weights_sha256": "062e92e3bab334bb20d04f963612273166bef926f9edb017a624b133313733d6"}, "seed": 1, "train_log": "{\"env\": \"pendulum\", \"fault\": \"wire-float64\", \"dose\": \"1.0\", \"seed\": 1, \"weights_sha256\": 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b/experiments/e54-boundary-faults/results/summary.txt new file mode 100644 index 0000000..717af99 --- /dev/null +++ b/experiments/e54-boundary-faults/results/summary.txt @@ -0,0 +1,228 @@ +env fault dose cells raises rule strict weights record bridge +halfcheetah none 1.0 0/0/0 0/3 0/3 0/3 0/3 0/3 0/3 +halfcheetah obs:zero 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:zero 1.0 409616/409616/409616 0/3 0/3 3/3 3/3 0/3 0/3 +halfcheetah obs:zero one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:stale 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:stale 1.0 409600/409600/409600 0/3 0/3 1/3 3/3 0/3 0/3 +halfcheetah obs:stale one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:swap 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:swap 1.0 409616/409616/409616 0/3 1/3 3/3 3/3 0/3 0/3 +halfcheetah obs:swap one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:f16 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:f16 1.0 409616/409616/409616 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah obs:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:zero 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:zero 1.0 409600/409600/409600 0/3 3/3 3/3 3/3 0/3 0/3 +halfcheetah action:zero one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:stale 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:stale 1.0 409600/409600/409600 0/3 0/3 1/3 3/3 0/3 0/3 +halfcheetah action:stale one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:swap 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:swap 1.0 409600/409600/409600 0/3 3/3 3/3 3/3 0/3 0/3 +halfcheetah action:swap one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:f16 0.01 4046/4046/4047 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:f16 1.0 409399/409414/409383 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:clip 0.01 4039/4017/4030 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah action:clip 1.0 408528/408625/408554 0/3 0/3 3/3 3/3 0/3 0/3 +halfcheetah action:clip one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah reward:zero 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah reward:zero 1.0 409600/409600/409600 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah reward:zero one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah reward:stale 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah reward:stale 1.0 409600/409600/409600 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah reward:stale one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah reward:swap 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah reward:swap 1.0 409600/409600/409600 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah reward:swap one 1/1/1 0/3 0/3 0/3 3/3 2/3 0/3 +halfcheetah reward:f16 0.01 4048/4048/4048 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah reward:f16 1.0 409547/409555/409545 0/3 0/3 0/3 3/3 2/3 0/3 +halfcheetah reward:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:zero 0.01 5/5/5 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:zero 1.0 400/400/400 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:zero one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:stale 0.01 5/5/5 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:stale 1.0 400/400/400 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:stale one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:swap 0.01 5/5/5 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:swap 1.0 400/400/400 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:swap one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:f16 0.01 5/5/5 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:f16 1.0 400/400/400 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah final-obs:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah terminated:spurious 0.01 4049/4049/4049 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah terminated:spurious 1.0 409600/409600/409600 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah terminated:spurious one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah truncated:drop 0.01 5/5/5 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah truncated:drop 1.0 400/400/400 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah truncated:drop one 1/1/1 0/3 3/3 3/3 3/3 3/3 0/3 +halfcheetah truncated:as-term 0.01 5/5/5 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah truncated:as-term 1.0 400/400/400 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah truncated:as-term one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +halfcheetah step:fill 0.01 4049/4049/4049 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah step:fill 1.0 409600/409600/409600 0/3 3/3 3/3 3/3 0/3 0/3 +halfcheetah step:fill one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +halfcheetah log:drop-first 0.01 2/2/2 0/3 0/3 0/3 0/3 3/3 3/3 +halfcheetah log:drop-first 1.0 400/400/400 0/3 0/3 0/3 0/3 3/3 3/3 +halfcheetah log:drop-first one 1/1/1 0/3 0/3 0/3 0/3 3/3 3/3 +halfcheetah log:short 0.01 2/2/2 0/3 0/3 0/3 0/3 3/3 3/3 +halfcheetah log:short 1.0 400/400/400 0/3 0/3 0/3 0/3 3/3 3/3 +halfcheetah log:short one 1/1/1 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum none 1.0 0/0/0 0/3 0/3 0/3 0/3 0/3 0/3 +pendulum delay-1ms 1.0 0/0/0 0/3 0/3 0/3 0/3 0/3 0/3 +pendulum wire-float64 1.0 0/0/0 0/3 0/3 0/3 0/3 0/3 0/3 +pendulum obs:zero 0.001 110/110/110 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:zero 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:zero 0.1 10297/10297/10297 0/3 0/3 3/3 3/3 0/3 0/3 +pendulum obs:zero 1.0 102416/102416/102416 0/3 3/3 3/3 3/3 0/3 0/3 +pendulum obs:zero one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:stale 0.001 110/110/110 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:stale 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:stale 0.1 10295/10295/10295 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:stale 1.0 102400/102400/102400 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum obs:stale one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:swap 0.001 110/110/110 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:swap 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:swap 0.1 10297/10297/10297 0/3 0/3 3/3 3/3 0/3 0/3 +pendulum obs:swap 1.0 102416/102416/102416 0/3 3/3 3/3 3/3 0/3 0/3 +pendulum obs:swap one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:f16 0.001 110/110/110 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:f16 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:f16 0.1 10297/10297/10297 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum obs:f16 1.0 102416/102416/102416 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum obs:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:zero 0.001 110/110/110 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:zero 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:zero 0.1 10296/10296/10296 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:zero 1.0 102400/102400/102400 0/3 3/3 3/3 3/3 0/3 0/3 +pendulum action:zero one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:stale 0.001 80/77/79 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum action:stale 0.01 817/769/802 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:stale 0.1 7460/7664/7745 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:stale 1.0 77023/74754/78333 0/3 0/3 2/3 3/3 0/3 0/3 +pendulum action:stale one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:swap 0.001 101/107/103 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:swap 0.01 976/979/987 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:swap 0.1 9375/9388/9384 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum action:swap 1.0 85056/84269/82169 0/3 3/3 3/3 3/3 0/3 0/3 +pendulum action:swap one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:f16 0.001 78/72/74 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:f16 0.01 746/707/751 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:f16 0.1 7045/7080/7181 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:f16 1.0 70086/69306/70621 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum action:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:clip 0.001 52/58/55 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum action:clip 0.01 564/518/529 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum action:clip 0.1 4889/4811/5154 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum action:clip 1.0 63653/63417/58306 0/3 0/3 3/3 3/3 0/3 0/3 +pendulum action:clip one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum reward:zero 0.001 110/110/110 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:zero 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:zero 0.1 10296/10296/10296 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:zero 1.0 102400/102400/102400 0/3 3/3 3/3 3/3 3/3 0/3 +pendulum reward:zero one 1/1/1 0/3 0/3 0/3 3/3 1/3 0/3 +pendulum reward:stale 0.001 110/110/110 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:stale 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:stale 0.1 10296/10296/10296 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:stale 1.0 102400/102400/102400 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:stale one 1/1/1 0/3 0/3 0/3 3/3 1/3 0/3 +pendulum reward:swap 0.001 110/110/110 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:swap 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:swap 0.1 10296/10296/10296 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum reward:swap 1.0 102400/102400/102400 0/3 3/3 3/3 3/3 3/3 0/3 +pendulum reward:swap one 1/1/1 0/3 0/3 0/3 3/3 2/3 0/3 +pendulum reward:f16 0.001 110/110/110 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum reward:f16 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum reward:f16 0.1 10294/10295/10296 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum reward:f16 1.0 102385/102393/102378 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum reward:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:zero 0.001 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:zero 0.01 9/9/9 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:zero 0.1 55/55/55 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum final-obs:zero 1.0 512/512/512 0/3 0/3 3/3 3/3 0/3 0/3 +pendulum final-obs:zero one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:stale 0.001 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:stale 0.01 9/9/9 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:stale 0.1 55/55/55 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum final-obs:stale 1.0 512/512/512 0/3 0/3 1/3 3/3 0/3 0/3 +pendulum final-obs:stale one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:swap 0.001 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:swap 0.01 9/9/9 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:swap 0.1 55/55/55 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:swap 1.0 512/512/512 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:swap one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:f16 0.001 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:f16 0.01 9/9/9 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:f16 0.1 55/55/55 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:f16 1.0 512/512/512 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum final-obs:f16 one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum terminated:spurious 0.001 110/110/110 0/3 0/3 3/3 3/3 3/3 0/3 +pendulum terminated:spurious 0.01 1068/1068/1068 0/3 3/3 3/3 3/3 3/3 0/3 +pendulum terminated:spurious 0.1 10296/10296/10296 0/3 3/3 3/3 3/3 3/3 0/3 +pendulum terminated:spurious 1.0 102400/102400/102400 0/3 3/3 3/3 3/3 3/3 0/3 +pendulum terminated:spurious one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum truncated:drop 0.001 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum truncated:drop 0.01 9/9/9 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum truncated:drop 0.1 55/55/55 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum truncated:drop 1.0 512/512/512 0/3 3/3 3/3 3/3 3/3 0/3 +pendulum truncated:drop one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum truncated:as-term 0.001 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum truncated:as-term 0.01 9/9/9 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum truncated:as-term 0.1 55/55/55 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum truncated:as-term 1.0 512/512/512 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum truncated:as-term one 1/1/1 0/3 0/3 0/3 3/3 0/3 0/3 +pendulum step:fill 0.001 110/110/110 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum step:fill 0.01 1068/1068/1068 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum step:fill 0.1 10296/10296/10296 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum step:fill 1.0 102400/102400/102400 0/3 3/3 3/3 3/3 0/3 0/3 +pendulum step:fill one 1/1/1 0/3 0/3 0/3 3/3 3/3 0/3 +pendulum log:drop-first 0.001 0/0/0 0/3 0/3 0/3 0/3 0/3 0/3 +pendulum log:drop-first 0.01 2/2/2 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:drop-first 0.1 55/55/55 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:drop-first 1.0 512/512/512 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:drop-first one 1/1/1 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:short 0.001 0/0/0 0/3 0/3 0/3 0/3 0/3 0/3 +pendulum log:short 0.01 2/2/2 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:short 0.1 55/55/55 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:short 1.0 512/512/512 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum log:short one 1/1/1 0/3 0/3 0/3 0/3 3/3 3/3 +pendulum indices:reorder one 1/1/1 3/3 0/3 - - 0/3 0/3 +pendulum reward:short-array one 1/1/1 3/3 0/3 - - 0/3 0/3 + +share of runs caught, by dose (runs with a changed cell; either = weights or record) + pendulum client one n= 63 raises 0.0 rule 0.0 strict 0.0 weights 1.0 record 0.206 bridge 0.0 either 1.0 + pendulum client 0.001 n= 63 raises 0.0 rule 0.0 strict 0.079 weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum client 0.01 n= 63 raises 0.0 rule 0.048 strict 0.063 weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum client 0.1 n= 63 raises 0.0 rule 0.048 strict 0.206 weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum client 1.0 n= 63 raises 0.0 rule 0.429 strict 0.603 weights 1.0 record 0.238 bridge 0.0 either 1.0 + pendulum log one n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum log 0.01 n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum log 0.1 n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum log 1.0 n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + pendulum all one n= 69 raises 0.0 rule 0.0 strict 0.0 weights 0.913 record 0.275 bridge 0.087 either 1.0 + pendulum all 0.001 n= 63 raises 0.0 rule 0.0 strict 0.079 weights 1.0 record 0.286 bridge 0.0 either 1.0 + pendulum all 0.01 n= 69 raises 0.0 rule 0.043 strict 0.058 weights 0.913 record 0.348 bridge 0.087 either 1.0 + pendulum all 0.1 n= 69 raises 0.0 rule 0.043 strict 0.188 weights 0.913 record 0.348 bridge 0.087 either 1.0 + pendulum all 1.0 n= 69 raises 0.0 rule 0.391 strict 0.551 weights 0.913 record 0.304 bridge 0.087 either 1.0 + halfcheetah client one n= 63 raises 0.0 rule 0.048 strict 0.048 weights 1.0 record 0.27 bridge 0.0 either 1.0 + halfcheetah client 0.01 n= 63 raises 0.0 rule 0.095 strict 0.095 weights 1.0 record 0.286 bridge 0.0 either 1.0 + halfcheetah client 1.0 n= 63 raises 0.0 rule 0.349 strict 0.508 weights 1.0 record 0.27 bridge 0.0 either 1.0 + halfcheetah log one n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + halfcheetah log 0.01 n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + halfcheetah log 1.0 n= 6 raises 0.0 rule 0.0 strict 0.0 weights 0.0 record 1.0 bridge 1.0 either 1.0 + halfcheetah all one n= 69 raises 0.0 rule 0.043 strict 0.043 weights 0.913 record 0.333 bridge 0.087 either 1.0 + halfcheetah all 0.01 n= 69 raises 0.0 rule 0.087 strict 0.087 weights 0.913 record 0.348 bridge 0.087 either 1.0 + halfcheetah all 1.0 n= 69 raises 0.0 rule 0.319 strict 0.464 weights 0.913 record 0.333 bridge 0.087 either 1.0 + +halfcheetah none at seed 0: 8261c03a, E50's 8261c03a: same +halfcheetah none at seed 1: 86564694, E50's 86564694: same +halfcheetah none at seed 2: 65cc8843, E50's 65cc8843: same +pendulum none at seed 0: ec5b8226, E50's ec5b8226: same +pendulum none at seed 1: 062e92e3, E50's 062e92e3: same +pendulum none at seed 2: 3a8d968f, E50's 3a8d968f: same +pendulum fault-free band, seeds 10-19: mean -216.7, sd 11.1, min -234.7, max -200.5 +pendulum strict check on fault-free seeds 10-19, each against the other nine: 0 of 10 flagged +halfcheetah fault-free band, seeds 10-19: mean 485.1, sd 145.6, min 152.4, max 619.8 +halfcheetah strict check on fault-free seeds 10-19, each against the other nine: 1 of 10 flagged +incomplete without an error: none diff --git a/experiments/e54-boundary-faults/results/verdicts.txt b/experiments/e54-boundary-faults/results/verdicts.txt new file mode 100644 index 0000000..8f40f1c --- /dev/null +++ b/experiments/e54-boundary-faults/results/verdicts.txt @@ -0,0 +1,11 @@ +V1: holds - 590 of 590 complete +V2: holds - [('halfcheetah', '0', '8261c03a'), ('halfcheetah', '1', '86564694'), ('halfcheetah', '2', '65cc8843'), ('pendulum', '0', 'ec5b8226'), ('pendulum', '1', '062e92e3'), ('pendulum', '2', '3a8d968f')] +P1: holds - weights differ in 504 of 504 client-fault runs +P2: holds - same weights in 48 of 48 control and log-fault runs +P3: holds - one: 0/69 (0.0%, cap 10%); 0.001: 0/63 (0.0%, cap 10%); 0.01: 3/69 (4.3%, cap 10%); 0.1: 3/69 (4.3%, cap 10%); 1.0: 27/69 (39.1%, cap 60%) +P4: holds - missed 0 it should catch, caught 0 it should not +P5: holds - bridge caught 42 of 42 log-fault runs and 0 of 504 client-fault runs +P6: holds - weights or record caught 546 of 546 +P7: holds - [('indices:reorder', '0', '9.571'), ('indices:reorder', '1', '9.688'), ('indices:reorder', '2', '9.389'), ('reward:short-array', '0', '9.312'), ('reward:short-array', '1', '9.2'), ('reward:short-array', '2', '9.648')] +P8: holds - right in 351 of 351 traced runs +P9: holds - one: 3/69 (4.3%); 0.01: 6/69 (8.7%) diff --git a/experiments/e54-boundary-faults/run.sh b/experiments/e54-boundary-faults/run.sh new file mode 100644 index 0000000..b021676 --- /dev/null +++ b/experiments/e54-boundary-faults/run.sh @@ -0,0 +1,41 @@ +#!/usr/bin/env bash +# E54's runs on guangzhao, W at a time, each worker on its own port. +# bash run.sh results registered [W] # PROTOCOL.md; W defaults to 10 +# bash run.sh pilot pilot [W] +# Writes DIR////seed/, with train.log in it. +set -uo pipefail +export PATH="$HOME/.local/bin:$PATH" OMP_NUM_THREADS=1 +PY="$HOME/zuogou/plugrl/bridges-venv/bin/python" +cd "$(dirname "$0")" +DIR="${1:?results dir}"; WHICH="${2:?registered or pilot}"; W="${3:-10}" +mkdir -p "$DIR" +"$PY" jobs.py "$WHICH" > "$DIR/jobs.txt" +uptime | tee "$DIR/load.txt" +(cd "$HOME/zuogou/plugrl/plugrl-bridges" && find src -name "*.py" | sort | xargs sha256sum) > "$DIR/bridges-src.sha256" +sha256sum train.py faulty_client.py jobs.py > "$DIR/e54-src.sha256" +echo "$(wc -l < "$DIR/jobs.txt") runs, $W at a time" + +worker() { + local w=$1 port=$((8854 + $1)) n=0 + # Every W-th job, starting at the w-th. + awk -v w="$w" -v W="$W" 'NR % W == w' "$DIR/jobs.txt" | while read -r env fault dose seed trace; do + # A process left on the port would take the next run's client (E53). + if ! "$PY" -c "import socket,sys; s=socket.socket(); sys.exit(0 if s.connect_ex(('127.0.0.1',$port)) else 1)"; then + echo "worker $w: port $port in use; stopping"; return 1 + fi + out="$DIR/$env/${fault//:/__}/$dose/seed$seed" + mkdir -p "$out" + flag=""; [ "$trace" = trace ] && flag="--trace" + "$PY" train.py --env "$env" --fault "$fault" --dose "$dose" --seed "$seed" \ + --out "$out" --port "$port" $flag > "$out/train.log" 2>&1 || echo "worker $w: train.py exited $? on $out" + n=$((n + 1)) + done + echo "worker $w done" +} + +for w in $(seq 0 $((W - 1))); do + worker "$w" & +done +wait +uptime | tee -a "$DIR/load.txt" +echo E54_DONE diff --git a/experiments/e54-boundary-faults/summarise.py b/experiments/e54-boundary-faults/summarise.py new file mode 100644 index 0000000..140d949 --- /dev/null +++ b/experiments/e54-boundary-faults/summarise.py @@ -0,0 +1,268 @@ +"""E54: what each check says about each fault, at each dose. + + python summarise.py results # registered: writes runs.csv, by_dose.csv + python summarise.py pilot + +Runs are DIR////seed/. For each, six checks, +each "catches" the fault or not: +- raises: the run stopped on an error (the bridge rejected a message). +- rule: the trainer's log (monitor.csv) fails the env's status rule, E44's for + Pendulum and E43's for HalfCheetah. Batches are 16 consecutive episodes. + Pendulum: batches 20 to the last at least 500 above batches 1-2. + HalfCheetah: batches 21-25 at least 200 above batch 1. +- strict: the mean of those last batches, in the trainer's log, is more than + 3 standard deviations from the mean of the fault-free runs at seeds 10-19. +- weights: the final weights' SHA-256 differs from the fault-free run's at the + same seed, on the same machine. +- record: the trainer's log disagrees with the client's record of what the + environments produced (env_record.csv, in order of the step each episode + ended on, then env): returns to 1e-4 relative plus 0.01, lengths exactly. +- bridge: the trainer's log disagrees with the bridge's own log + (episodes.csv), which counts where the rewards arrive, on the trainer's side + of the wire. +A fault whose run changed no cell (fault.json; for the log faults, +result.json's log_cells) is reported, and left out of the shares caught. +""" + +from __future__ import annotations + +import csv +import json +import pathlib +import statistics +import sys +from collections import defaultdict + +HERE = pathlib.Path(__file__).resolve().parent +sys.path.insert(0, str(HERE)) +from faulty_client import CONTROLS, LOUD, SILENT # noqa: E402 + +LOG = ("log:drop-first", "log:short") +FAULTS = CONTROLS + SILENT + LOG + LOUD +CHECKS = ("raises", "rule", "strict", "weights", "record", "bridge") +STEPS = {"pendulum": 102_400, "halfcheetah": 409_600} +# E50's fault-free bridge runs on guangzhao (seed 9: E50's pilot). +E50_WEIGHTS = { + ("pendulum", 0): "ec5b8226", + ("pendulum", 1): "062e92e3", + ("pendulum", 2): "3a8d968f", + ("pendulum", 9): "3721266c", + ("halfcheetah", 0): "8261c03a", + ("halfcheetah", 1): "86564694", + ("halfcheetah", 2): "65cc8843", + ("halfcheetah", 9): "0260ca9d", +} +BAND_SEEDS = range(10, 20) + + +def read_csv(path: pathlib.Path, skip_header: bool = False) -> list[dict]: + with open(path, encoding="utf-8", newline="") as f: + if skip_header: + next(f) # VecMonitor's JSON header + return list(csv.DictReader(f)) + + +def monitor(run: pathlib.Path) -> list[tuple[float, int]]: + return [(float(r["r"]), int(r["l"])) for r in read_csv(run / "monitor.csv", True)] + + +def ordered(rows: list[dict], key: str) -> list[tuple[float, int]]: + rows.sort(key=lambda r: (int(r["step"]), int(r[key]))) + return [(float(r["return"]), int(r["length"])) for r in rows] + + +def agree(log, truth) -> bool: + return len(log) == len(truth) and all( + abs(r - t) <= 1e-4 * max(1.0, abs(t)) + 0.01 and n == m + for (r, n), (t, m) in zip(log, truth) + ) + + +def window(env: str, episodes) -> tuple[float, float] | None: + """(gain, last-window mean) by the env's status rule, or None if too short.""" + returns = [r for r, _ in episodes] + batches = [ + statistics.mean(returns[i : i + 16]) for i in range(0, len(returns) - 15, 16) + ] + if env == "pendulum": + if len(batches) < 20: + return None + first, last = statistics.mean(batches[0:2]), statistics.mean(batches[19:]) + else: + if len(batches) < 25: + return None + first, last = batches[0], statistics.mean(batches[20:25]) + return last - first, last + + +def bar(env: str) -> float: + return 500.0 if env == "pendulum" else 200.0 + + +def runs(root: pathlib.Path): + for res in sorted(root.glob("*/*/*/seed*/result.json")): + run = res.parent + env = run.parent.parent.parent.name + fault = run.parent.parent.name.replace("__", ":") + yield env, fault, run.parent.name, int(run.name.removeprefix("seed")), run + + +def main() -> int: + root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else HERE / "results" + table = {} + for env, fault, dose, seed, run in runs(root): + res = json.loads((run / "result.json").read_text()) + info = run / "fault.json" + cells = json.loads(info.read_text())["cells"] if info.exists() else None + if fault in LOG: + cells = res.get("log_cells") + if fault in CONTROLS: + cells = 0 + log = monitor(run) + w = window(env, log) + table[env, fault, dose, seed] = dict( + raised=res.get("raised", ""), + complete=res["steps"] == STEPS[env] and res.get("client_rc") == 0, + sha=res["weights_sha256"], + gain=None if w is None else w[0], + last=None if w is None else w[1], + record=agree(log, ordered(read_csv(run / "env_record.csv"), "env")), + bridge=agree(log, ordered(read_csv(run / "episodes.csv"), "slot")), + cells=cells, + episodes=len(log), + learn_s=res["learn_s"], + ) + + rows = [] + for (env, fault, dose, seed), t in sorted(table.items()): + clean = table.get((env, "none", "1.0", seed)) + band = [table[env, "none", "1.0", s]["last"] for s in BAND_SEEDS + if (env, "none", "1.0", s) in table] # fmt: skip + mu = statistics.mean(band) if len(band) >= 2 else None + sd = statistics.stdev(band) if len(band) >= 2 else None + raised = bool(t["raised"]) + caught = dict( + raises=raised, + rule=not raised and (t["gain"] is None or t["gain"] < bar(env)), + strict=None + if mu is None or raised + else (t["last"] is None or abs(t["last"] - mu) > 3 * sd), + weights=None if clean is None or raised else t["sha"] != clean["sha"], + record=not raised and not t["record"], + bridge=not raised and not t["bridge"], + ) + rows.append( + dict( + env=env, + fault=fault, + dose=dose, + seed=seed, + cells=t["cells"], + **{k: "" if v is None else int(v) for k, v in caught.items()}, + gain="" if t["gain"] is None else round(t["gain"], 1), + last="" if t["last"] is None else round(t["last"], 1), + episodes=t["episodes"], + sha=t["sha"][:8], + learn_s=t["learn_s"], + raised=t["raised"][:80], + complete=int(t["complete"]), + ) + ) + with open(root / "runs.csv", "w", encoding="utf-8", newline="") as f: + out = csv.DictWriter(f, fieldnames=list(rows[0])) + out.writeheader() + out.writerows(rows) + + # Per fault and dose: how many of the seeds each check caught. + groups = defaultdict(list) + for r in rows: + if r["seed"] in BAND_SEEDS: + continue + groups[r["env"], r["fault"], r["dose"]].append(r) + print( + f"{'env':11s} {'fault':20s} {'dose':6s} cells " + + " ".join(f"{c:>7s}" for c in CHECKS) + ) + for (env, fault, dose), rs in sorted( + groups.items(), key=lambda g: (g[0][0], FAULTS.index(g[0][1]), g[0][2]) + ): + cells = "/".join(str(r["cells"]) for r in rs) + counts = [] + for c in CHECKS: + vals = [r[c] for r in rs if r[c] != ""] + counts.append(f"{sum(vals)}/{len(vals)}" if vals else "-") + print( + f"{env:11s} {fault:20s} {dose:6s} {cells:>5s} " + + " ".join(f"{x:>7s}" for x in counts) + ) + + # The figure: per env, dose and kind of fault, the share of runs with a + # changed cell that each check caught; "either" is weights or record. + kinds = {"client": SILENT, "log": LOG, "all": SILENT + LOG} + shares = [] + for env in ("pendulum", "halfcheetah"): + for kind, members in kinds.items(): + for dose in ("one", "0.001", "0.01", "0.1", "1.0"): + rs = [r for r in rows if r["env"] == env and r["dose"] == dose + and r["fault"] in members and r["seed"] not in BAND_SEEDS + and r["cells"] not in (0, None)] # fmt: skip + if not rs: + continue + line = dict(env=env, kind=kind, dose=dose, runs=len(rs)) + for c in CHECKS: + vals = [r[c] for r in rs if r[c] != ""] + line[c] = round(sum(vals) / len(vals), 3) if vals else "" + line["either"] = round( + sum(r["weights"] or r["record"] for r in rs) / len(rs), 3 + ) + shares.append(line) + with open(root / "by_dose.csv", "w", encoding="utf-8", newline="") as f: + out = csv.DictWriter( + f, fieldnames=["env", "kind", "dose", "runs", *CHECKS, "either"] + ) + out.writeheader() + out.writerows(shares) + print() + print( + "share of runs caught, by dose (runs with a changed cell; either = weights or record)" + ) + for s in shares: + print( + f" {s['env']:11s} {s['kind']:6s} {s['dose']:6s} n={s['runs']:3d} " + + " ".join(f"{c} {s[c]}" for c in (*CHECKS, "either")) + ) + + print() + for (env, seed), want in sorted(E50_WEIGHTS.items()): + t = table.get((env, "none", "1.0", seed)) + if t is not None: + print( + f"{env} none at seed {seed}: {t['sha'][:8]}, E50's {want}: " + f"{'same' if t['sha'].startswith(want) else 'DIFFERENT'}" + ) + for env in ("pendulum", "halfcheetah"): + band = [table[env, "none", "1.0", s]["last"] for s in BAND_SEEDS + if (env, "none", "1.0", s) in table] # fmt: skip + if len(band) >= 2: + print( + f"{env} fault-free band, seeds 10-19: mean {statistics.mean(band):.1f}, " + f"sd {statistics.stdev(band):.1f}, min {min(band):.1f}, max {max(band):.1f}" + ) + if len(band) >= 3: + # The strict check's false alarms: each fault-free seed judged by + # the band of the other nine. + alarms = 0 + for i, x in enumerate(band): + rest = band[:i] + band[i + 1 :] + alarms += abs(x - statistics.mean(rest)) > 3 * statistics.stdev(rest) + print( + f"{env} strict check on fault-free seeds 10-19, each against the other " + f"nine: {alarms} of {len(band)} flagged" + ) + incomplete = [k for k, t in table.items() if not t["complete"] and not t["raised"]] + print("incomplete without an error:", incomplete or "none") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/experiments/e54-boundary-faults/train.py b/experiments/e54-boundary-faults/train.py new file mode 100644 index 0000000..ebf9365 --- /dev/null +++ b/experiments/e54-boundary-faults/train.py @@ -0,0 +1,266 @@ +"""E54: SB3's PPO behind the bridge, with one fault at the boundary. + + python train.py --env pendulum --fault reward:stale --dose 0.01 --seed 0 \ + --out runs/... [--port 8854] [--trace] + +E50's bridge arm, unchanged but for the fault: 16 environments in +faulty_client.py, another process, on one connection, behind plugrl-bridges' +PlugRLVecEnv; then VecMonitor, then PPO, one torch thread, CPU. +- pendulum: Pendulum-v1, 102,400 steps, rl-baselines3-zoo's settings, E50's. +- halfcheetah: HalfCheetah-v5, 409,600 steps, SB3's defaults, E50's. + +Every fault but two is the client's (faulty_client.py lists them). The two +here are in the trainer's log, and leave what PPO gets as it came: +- log:drop-first: VecMonitor's logged return leaves out the episode's first + reward (the kind of fault E51 found in Gymnasium's RecordEpisodeStatistics); +- log:short: VecMonitor's logged length is one step short (E51's other half). +Their doses count episodes: "one" is the 256th logged, a number p each with +probability p, from a generator seeded 54. + +With --trace, a pass-through wrapper between the bridge and VecMonitor keeps +what crossed the wire as the trainer saw it, step by step: the actions sent, +and the rewards, episode ends, final observations and next observations +received. trace.npz holds them, for localise.py. + +The run directory gets result.json (the final weights' SHA-256, the time +model.learn() took, and the error if the run raised one), monitor.csv (the +trainer's log), episodes.csv (the bridge's log, counted where the rewards +arrive on the trainer's side of the wire), env_record.csv and fault.json (the +client's), client.log, model.zip (the final policy, saved after its hash is +taken, for rendering), and trace.npz with --trace. +""" + +from __future__ import annotations + +import argparse +import hashlib +import json +import pathlib +import subprocess +import sys +import time + +import gymnasium as gym +import numpy as np +import torch +from stable_baselines3 import PPO +from stable_baselines3.common.vec_env import VecEnvWrapper, VecMonitor + +HERE = pathlib.Path(__file__).resolve().parent +sys.path.insert(0, str(HERE)) +from faulty_client import FAULTS as CLIENT_FAULTS # noqa: E402 + +NUM_ENVS = 16 +ENVS = { + "pendulum": dict( + id="Pendulum-v1", + total=102_400, + action=(1, 2.0), + # plugrl-bridges examples/sb3/ppo.py, preset "pendulum"; E50's. + ppo=dict( + n_steps=256, + gamma=0.9, + gae_lambda=0.95, + n_epochs=10, + ent_coef=0.0, + learning_rate=1e-3, + clip_range=0.2, + use_sde=True, + sde_sample_freq=4, + ), + ), + "halfcheetah": dict( + id="HalfCheetah-v5", + total=409_600, + action=(6, 1.0), + ppo=dict(n_steps=256), + ), +} +LOG_FAULTS = ("log:drop-first", "log:short") +FAULTS = CLIENT_FAULTS + LOG_FAULTS + + +class FaultyLogMonitor(VecMonitor): + """VecMonitor with one fault in the episodes it logs; PPO's data is untouched. + + step_wait is SB3 2.9.0's VecMonitor.step_wait, but for the two marked lines. + """ + + def __init__(self, venv, filename: str, fault: str, dose: str) -> None: + super().__init__(venv, filename=filename) + self.fault, self.dose = fault, dose + self.rng = np.random.default_rng(54) + self.first_reward = np.zeros(self.num_envs, dtype=np.float32) + self.logged = 0 + self.cells = 0 + + def _hit(self) -> bool: + k, u = self.logged, self.rng.random() + self.logged += 1 + return k == 255 if self.dose == "one" else u < float(self.dose) + + def step_wait(self): + starting = self.episode_lengths == 0 + obs, rewards, dones, infos = self.venv.step_wait() + self.first_reward[starting] = rewards[starting] + self.episode_returns += rewards + self.episode_lengths += 1 + new_infos = list(infos[:]) + for i in range(len(dones)): + if dones[i]: + info = infos[i].copy() + episode_return = self.episode_returns[i] + episode_length = self.episode_lengths[i] + if self._hit(): # the fault + self.cells += 1 + if self.fault == "log:drop-first": + episode_return = episode_return - self.first_reward[i] + else: + episode_length = episode_length - 1 + episode_info = { + "r": episode_return, + "l": episode_length, + "t": round(time.time() - self.t_start, 6), + } + for key in self.info_keywords: + episode_info[key] = info[key] + info["episode"] = episode_info + self.episode_count += 1 + self.episode_returns[i] = 0 + self.episode_lengths[i] = 0 + if self.results_writer: + self.results_writer.write_row(episode_info) + new_infos[i] = info + return obs, rewards, dones, new_infos + + +class WireTrace(VecEnvWrapper): + """What crossed the wire, as the trainer saw it; passes everything through.""" + + def __init__(self, venv) -> None: + super().__init__(venv) + self.actions, self.rewards, self.ends, self.truncs = [], [], [], [] + self.finals, self.nexts = [], [] + self.first_obs = None + + def reset(self): + obs = self.venv.reset() + if self.first_obs is None: + self.first_obs = np.array(obs, copy=True) + return obs + + def step_async(self, actions) -> None: + self.actions.append(np.array(actions, dtype=np.float32, copy=True)) + self.venv.step_async(actions) + + def step_wait(self): + obs, rewards, dones, infos = self.venv.step_wait() + final = np.zeros_like(obs) + trunc = np.zeros(len(dones), dtype=np.bool_) + for i in np.flatnonzero(dones): + final[i] = infos[i]["terminal_observation"] + trunc[i] = infos[i]["TimeLimit.truncated"] + self.rewards.append(np.array(rewards, copy=True)) + self.ends.append(np.array(dones, copy=True)) + self.truncs.append(trunc) + self.finals.append(final) + self.nexts.append(np.array(obs, copy=True)) + return obs, rewards, dones, infos + + def save(self, path: pathlib.Path) -> None: + np.savez_compressed( + path, + first_obs=self.first_obs, + actions=np.stack(self.actions), + rewards=np.stack(self.rewards), + ends=np.stack(self.ends), + truncs=np.stack(self.truncs), + finals=np.stack(self.finals), + nexts=np.stack(self.nexts), + ) + + +def weights_sha256(model: PPO) -> str: + h = hashlib.sha256() + for name, tensor in sorted(model.policy.state_dict().items()): + h.update(name.encode()) + h.update(tensor.detach().cpu().contiguous().numpy().tobytes()) + return h.hexdigest() + + +def main() -> int: + p = argparse.ArgumentParser(description=__doc__) + p.add_argument("--env", choices=sorted(ENVS), required=True) + p.add_argument("--fault", choices=FAULTS, required=True) + p.add_argument("--dose", default="1.0") + p.add_argument("--seed", type=int, required=True) + p.add_argument("--out", required=True) + p.add_argument("--port", type=int, default=8854) + p.add_argument("--trace", action="store_true") + a = p.parse_args() + spec = ENVS[a.env] + out = pathlib.Path(a.out).resolve() + out.mkdir(parents=True, exist_ok=True) + torch.set_num_threads(1) + + from plugrl_bridges.sb3 import PlugRLVecEnv + + dim, high = spec["action"] + client_fault = a.fault if a.fault in CLIENT_FAULTS else "none" + client_log = open(out / "client.log", "w", encoding="utf-8") + client = subprocess.Popen( + [sys.executable, str(HERE / "faulty_client.py"), "--port", str(a.port), + "--num-envs", str(NUM_ENVS), "--seed", str(a.seed), "--env-id", spec["id"], + "--action-high", str(high), "--fault", client_fault, "--dose", a.dose, + "--record", str(out / "env_record.csv")], + stdout=client_log, stderr=subprocess.STDOUT, + ) # fmt: skip + env = PlugRLVecEnv( + num_envs=NUM_ENVS, + action_space=gym.spaces.Box(-high, high, (dim,), np.float32), + port=a.port, + host="127.0.0.1", + timeout=60.0, + episode_log=str(out / "episodes.csv"), + ) + trace = WireTrace(env) if a.trace else None + inner = trace if trace is not None else env + if a.fault in LOG_FAULTS: + env = FaultyLogMonitor(inner, str(out / "monitor.csv"), a.fault, a.dose) + else: + env = VecMonitor(inner, filename=str(out / "monitor.csv")) + # PPO(seed=) seeds torch and numpy; the client resets env i with seed + i. + model = PPO("MlpPolicy", env, seed=a.seed, device="cpu", verbose=0, **spec["ppo"]) + result = {"env": a.env, "fault": a.fault, "dose": a.dose, "seed": a.seed} + start = time.perf_counter() + try: + model.learn(total_timesteps=spec["total"]) + except Exception as exc: # a fault the bridge rejects ends the run here + result["raised"] = f"{type(exc).__name__}: {exc}" + result.update( + weights_sha256=weights_sha256(model), + learn_s=round(time.perf_counter() - start, 3), + steps=model.num_timesteps, + torch=torch.__version__, + ) + if isinstance(env, FaultyLogMonitor): + result["log_cells"] = env.cells + model.save(out / "model.zip") + if trace is not None: + trace.save(out / "trace.npz") + try: + env.close() + except Exception as exc: + result["close_raised"] = f"{type(exc).__name__}: {exc}" + try: + result["client_rc"] = client.wait(timeout=60) + except subprocess.TimeoutExpired: + client.kill() + result["client_rc"] = "killed" + (out / "result.json").write_text(json.dumps(result, indent=2) + "\n") + print(json.dumps(result)) + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/experiments/e54-boundary-faults/verdicts.py b/experiments/e54-boundary-faults/verdicts.py new file mode 100644 index 0000000..9b1c9c4 --- /dev/null +++ b/experiments/e54-boundary-faults/verdicts.py @@ -0,0 +1,186 @@ +"""E54: judge PROTOCOL.md's checks and predictions from summarise.py's runs.csv. + + python verdicts.py results # prints, and writes results/verdicts.txt + +Each prediction is judged as PROTOCOL.md words it, on the registered seeds +(0-2), over runs whose fault changed at least one cell. +""" + +from __future__ import annotations + +import csv +import pathlib +import sys + +HERE = pathlib.Path(__file__).resolve().parent +sys.path.insert(0, str(HERE)) +from faulty_client import LOUD, SILENT # noqa: E402 +from summarise import E50_WEIGHTS # noqa: E402 + +LOG = ("log:drop-first", "log:short") +SEEDS = {"0", "1", "2"} + + +def main() -> int: + root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else HERE / "results" + with open(root / "runs.csv", encoding="utf-8", newline="") as f: + rows = [r for r in csv.DictReader(f)] + reg = [r for r in rows if r["seed"] in SEEDS] + changed = [r for r in reg if r["cells"] not in ("", "0", "None")] + out = [] + + def verdict(name: str, ok: bool, detail: str) -> None: + out.append(f"{name}: {'holds' if ok else 'FAILS'} - {detail}") + + # V1: every run but the loud faults' completes. + bad = [r for r in rows if r["fault"] not in LOUD and r["complete"] != "1"] + verdict( + "V1", + not bad, + f"{len(rows) - len(bad)} of {len(rows)} complete" + + (f"; not: {bad[:3]}" if bad else ""), + ) + # V2: none reproduces E50's weights at seeds 0-2. + v2 = [(r["env"], r["seed"], r["sha"]) for r in reg if r["fault"] == "none"] + v2_ok = all( + E50_WEIGHTS[env, int(s)].startswith(sha) + or sha.startswith(E50_WEIGHTS[env, int(s)]) + for env, s, sha in v2 + ) + verdict("V2", v2_ok and len(v2) == 6, f"{v2}") + + client = [r for r in changed if r["fault"] in SILENT] + p1_bad = [r for r in client if r["weights"] != "1"] + verdict( + "P1", + not p1_bad, + f"weights differ in {len(client) - len(p1_bad)} of {len(client)} client-fault runs" + + ( + f"; not: {[(r['env'], r['fault'], r['dose'], r['seed']) for r in p1_bad]}" + if p1_bad + else "" + ), + ) + + p2 = [ + r + for r in reg + if r["fault"] in ("delay-1ms", "wire-float64") + or (r["fault"] in LOG and r in changed) + ] + p2_bad = [r for r in p2 if r["weights"] != "0"] + verdict( + "P2", + not p2_bad, + f"same weights in {len(p2) - len(p2_bad)} of {len(p2)} control and log-fault runs", + ) + + pend = [r for r in changed if r["env"] == "pendulum" and r["fault"] in SILENT + LOG] + p3_ok, parts = True, [] + for dose, cap in ( + ("one", 0.10), + ("0.001", 0.10), + ("0.01", 0.10), + ("0.1", 0.10), + ("1.0", 0.60), + ): + rs = [r for r in pend if r["dose"] == dose] + share = sum(r["rule"] == "1" for r in rs) / len(rs) + p3_ok &= share <= cap + parts.append( + f"{dose}: {sum(r['rule'] == '1' for r in rs)}/{len(rs)} ({share:.1%}, cap {cap:.0%})" + ) + verdict("P3", p3_ok, "; ".join(parts)) + + must = ( + "reward:zero", + "reward:stale", + "reward:swap", + "terminated:spurious", + "truncated:drop", + ) + never = tuple( + f for f in SILENT if f.split(":")[0] in ("obs", "action", "final-obs") + ) + ("truncated:as-term",) + p4_miss = [ + r + for r in changed + if r["fault"] in must and r["dose"] != "one" and r["record"] != "1" + ] + p4_miss += [ + r + for r in changed + if r["fault"] == "step:fill" + and r["dose"] in ("0.001", "0.01", "0.1") + and r["record"] != "1" + ] + p4_miss += [r for r in changed if r["fault"] in LOG and r["record"] != "1"] + p4_false = [r for r in changed if r["fault"] in never and r["record"] == "1"] + verdict( + "P4", + not p4_miss and not p4_false, + f"missed {len(p4_miss)} it should catch, caught {len(p4_false)} it should not" + + ( + f"; missed: {[(r['env'], r['fault'], r['dose'], r['seed']) for r in p4_miss][:8]}" + if p4_miss + else "" + ) + + ( + f"; caught: {[(r['env'], r['fault'], r['dose'], r['seed']) for r in p4_false][:8]}" + if p4_false + else "" + ), + ) + + log_runs = [r for r in changed if r["fault"] in LOG] + p5_ok = all(r["bridge"] == "1" for r in log_runs) and all( + r["bridge"] == "0" for r in client + ) + verdict( + "P5", + p5_ok, + f"bridge caught {sum(r['bridge'] == '1' for r in log_runs)} of {len(log_runs)} log-fault runs and {sum(r['bridge'] == '1' for r in client)} of {len(client)} client-fault runs", + ) + + silent = client + log_runs + p6_bad = [r for r in silent if r["weights"] != "1" and r["record"] != "1"] + verdict( + "P6", + not p6_bad, + f"weights or record caught {len(silent) - len(p6_bad)} of {len(silent)}", + ) + + loud = [r for r in reg if r["fault"] in LOUD] + p7_ok = len(loud) == 6 and all( + r["raises"] == "1" and float(r["learn_s"]) < 120 for r in loud + ) + verdict("P7", p7_ok, f"{[(r['fault'], r['seed'], r['learn_s']) for r in loud]}") + + with open(root / "localisation.csv", encoding="utf-8", newline="") as f: + loc = [r for r in csv.DictReader(f) if r["seed"] in SEEDS] + p8_bad = [r for r in loc if r["right"] != "1"] + verdict( + "P8", not p8_bad, f"right in {len(loc) - len(p8_bad)} of {len(loc)} traced runs" + ) + + cheetah = [ + r for r in changed if r["env"] == "halfcheetah" and r["fault"] in SILENT + LOG + ] + p9_ok, parts = True, [] + for dose in ("one", "0.01"): + rs = [r for r in cheetah if r["dose"] == dose] + share = sum(r["rule"] == "1" for r in rs) / len(rs) + p9_ok &= share <= 0.10 + parts.append( + f"{dose}: {sum(r['rule'] == '1' for r in rs)}/{len(rs)} ({share:.1%})" + ) + verdict("P9", p9_ok, "; ".join(parts)) + + text = "\n".join(out) + print(text) + (root / "verdicts.txt").write_text(text + "\n", encoding="utf-8") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main())