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aeba3f1 e3d939d aeba3f1 e3d939d aeba3f1 e3d939d aeba3f1 e3d939d aeba3f1 e3d939d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 | """Trackio helpers used by training and evaluation scripts."""
from __future__ import annotations
import os
import subprocess
from contextlib import contextmanager
from datetime import datetime
from pathlib import Path
from typing import Any, Iterator
TRAIN_METRICS = [
"train/reward_total_mean",
"train/reward_discovery_mean",
"train/reward_security_mean",
"train/reward_regression_mean",
"train/reward_public_routes_mean",
"train/reward_patch_quality_mean",
"train/reward_visible_tests_mean",
"train/reward_safety_mean",
"train/reward_anti_cheat_mean",
"train/success_rate",
"train/exploit_block_rate",
"train/regression_preservation_rate",
"train/public_route_preservation_rate",
"train/invalid_action_rate",
"train/timeout_rate",
"train/safety_violation_rate",
"train/reward_hacking_suspected_rate",
"train/episode_length_mean",
"train/episode_length_p95",
"train/rollouts_per_second",
"train/tokens_per_second",
"train/loss",
"train/learning_rate",
"train/kl",
"train/grad_norm",
]
EVAL_METRICS = [
"eval/baseline_success_rate",
"eval/trained_success_rate",
"eval/absolute_success_improvement",
"eval/baseline_mean_reward",
"eval/trained_mean_reward",
"eval/absolute_reward_improvement",
"eval/heldout_success_rate",
"eval/heldout_mean_reward",
"eval/exploit_block_rate",
"eval/regression_preservation_rate",
"eval/public_route_preservation_rate",
"eval/anti_cheat_pass_rate",
"eval/invalid_action_rate",
"eval/timeout_rate",
"eval/safety_violation_rate",
"eval/mean_episode_length",
]
def build_run_name(model: str, algo: str, difficulty: int, git_sha: str = "nogit") -> str:
stamp = datetime.utcnow().strftime("%Y%m%d-%H%M%S")
model_slug = model.replace("/", "-")
return f"CyberSecurity_OWASP-{model_slug}-{algo}-level{difficulty}-{stamp}-{git_sha[:8]}"
def get_git_sha(default: str = "nogit") -> str:
try:
result = subprocess.run(
["git", "rev-parse", "HEAD"],
check=True,
capture_output=True,
text=True,
)
except Exception:
return default
return result.stdout.strip() or default
def _load_trackio():
os.environ.setdefault("TRACKIO_DIR", str((Path.cwd() / "outputs" / "trackio").resolve()))
try:
import trackio
except ImportError as exc:
raise RuntimeError(
"Trackio is required for CyberSecurity_OWASP runs. Install dependencies "
"with `uv sync` and set TRACKIO_SPACE_ID when you want remote HF Spaces tracking."
) from exc
return trackio
def init_trackio_run(
*,
run_name: str,
run_type: str,
config: dict[str, Any] | None = None,
project: str | None = None,
space_id: str | None = None,
group: str | None = None,
):
trackio = _load_trackio()
project = project or os.getenv("TRACKIO_PROJECT", "CyberSecurity_OWASP")
space_id = space_id if space_id is not None else os.getenv("TRACKIO_SPACE_ID", "")
run_config = {
"environment": "CyberSecurity_OWASP",
"run_type": run_type,
**(config or {}),
}
kwargs: dict[str, Any] = {
"project": project,
"name": run_name,
"config": run_config,
}
if space_id:
kwargs["space_id"] = space_id
if group:
kwargs["group"] = group
return trackio.init(**kwargs)
def log_trackio_metrics(metrics: dict[str, Any], step: int | None = None) -> None:
trackio = _load_trackio()
numeric = {
key: value
for key, value in metrics.items()
if isinstance(value, (int, float, bool))
}
if step is None:
trackio.log(numeric)
else:
trackio.log(numeric, step=step)
def finish_trackio_run() -> None:
trackio = _load_trackio()
trackio.finish()
@contextmanager
def trackio_run(
*,
run_name: str,
run_type: str,
config: dict[str, Any] | None = None,
project: str | None = None,
space_id: str | None = None,
group: str | None = None,
) -> Iterator[Any]:
run = init_trackio_run(
run_name=run_name,
run_type=run_type,
config=config,
project=project,
space_id=space_id,
group=group,
)
try:
yield run
finally:
finish_trackio_run()
def log_eval_summary(run_name: str, summary: dict[str, Any], config: dict[str, Any] | None = None) -> None:
metrics = {
f"eval/{key}": float(value)
for key, value in summary.items()
if isinstance(value, (int, float, bool))
}
with trackio_run(run_name=run_name, run_type="eval", config=config, group="eval"):
log_trackio_metrics(metrics, step=0)
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