| """Offline rewards (no GPU needed) for both subsets. |
| |
| With a GPU, the real reward is measured latency (or run the task through KernelGYM). |
| These are the cheap proxies for rollouts without hardware. |
| """ |
|
|
| import difflib |
| import json |
| import re |
|
|
|
|
| |
| def parse_answer(completion: str) -> dict | None: |
| """Last parseable flat JSON object in the completion.""" |
| for m in reversed(re.findall(r"\{[^{}]*\}", completion)): |
| try: |
| return json.loads(m) |
| except json.JSONDecodeError: |
| pass |
| return None |
|
|
|
|
| def config_reward(pred: dict | None, best: dict) -> float: |
| """Score a predicted launch config against the autotuned best config, in [0, 1]. |
| |
| `best` example: {"BLOCK_SIZE_M": 16, "BLOCK_SIZE_N": 64, "BLOCK_SIZE_K": 128, |
| "GROUP_SIZE_M": 1, "num_warps": 4, "num_stages": 5} |
| """ |
| |
| raise NotImplementedError |
|
|
|
|
| def reward(completion: str, best_config: str) -> float: |
| return config_reward(parse_answer(completion), json.loads(best_config)) |
|
|
|
|
| |
| EDIT_RE = re.compile(r"<<<<<<< SEARCH\n(.*?)\n=======\n(.*?)\n?>>>>>>> REPLACE", re.S) |
|
|
|
|
| def apply_edits(code: str, completion: str) -> str | None: |
| """Apply SEARCH/REPLACE blocks in order; None if there are none or any SEARCH text isn't in the file.""" |
| edits = EDIT_RE.findall(completion) |
| if not edits: |
| return None |
| for search, replace in edits: |
| if search not in code: |
| return None |
| code = code.replace(search, replace, 1) |
| return code |
|
|
|
|
| def _changed_lines(before: str, after: str) -> str: |
| diff = difflib.unified_diff(before.splitlines(), after.splitlines(), lineterm="", n=0) |
| return "\n".join(l for l in diff if l[:1] in "+-" and not l.startswith(("+++", "---"))) |
|
|
|
|
| def patch_reward(completion: str, before_code: str, after_code: str) -> float: |
| """SWE-RL-style: -1 for malformed/inapplicable edits, else similarity of the changed lines to the real commit's.""" |
| pred = apply_edits(before_code, completion) |
| if pred is None: |
| return -1.0 |
| return difflib.SequenceMatcher(None, _changed_lines(before_code, pred), _changed_lines(before_code, after_code)).ratio() |
|
|
