Datasets:
Download code/test_v4_helpsteer.py from kitaniai/OpenJudgment-4B-Preview: direct link, hf CLI and curl.
- Browser
- Download file 3.3 kB
-
https://huggingface.co/datasets/kitaniai/OpenJudgment-4B-Preview/resolve/main/code/test_v4_helpsteer.py
- Command line
-
hf download hf://datasets/kitaniai/OpenJudgment-4B-Preview/code/test_v4_helpsteer.py
-
curl -L -o test_v4_helpsteer.py https://huggingface.co/datasets/kitaniai/OpenJudgment-4B-Preview/resolve/main/code/test_v4_helpsteer.py
3.3 kB
| """Run with: python -m unittest discover -s openjudgment -p test_v4_helpsteer.py""" | |
| from copy import deepcopy | |
| import json | |
| import unittest | |
| from v4_helpsteer import adapt | |
| def example(votes): | |
| return dict(context=[dict(role="user", content="Compare these answers.")], | |
| response1="First response", response2="Second response", | |
| overall_preference=2, | |
| individual_preference=[dict(score=v, reasoning="SECRET_RATIONALE", | |
| feedback1="SECRET_FEEDBACK", feedback2="SECRET_FEEDBACK") for v in votes]) | |
| class HelpSteerTests(unittest.TestCase): | |
| def test_feedback_rubric_and_strict_ambiguity(self): | |
| source = example([1]) | |
| source["feedback1"] = ["The response is not helpful. SECRET", "The response is perfectly helpful. SECRET"] | |
| source["feedback2"] = ["The response is mostly helpful. SECRET", "I think it is mostly helpful."] | |
| task, = adapt(source, "feedback") | |
| self.assertEqual(task["target"], [0.5, 0, 0, 0, 0.5]) | |
| self.assertNotIn("SECRET", task["state"]) | |
| self.assertEqual(set(json.loads(task["state"])), {"context", "response"}) | |
| source["feedback1"] = ["The response is partially helpful."] | |
| self.assertEqual(adapt(source, "feedback"), []) | |
| def test_boundaries_and_sign(self): | |
| for score in range(-3, 4): | |
| task, = adapt(example([score])) | |
| self.assertEqual(task["target"], [float(i == score) for i in range(-3, 4)]) | |
| self.assertIn("Response 1 is much better", adapt(example([-3]))[0]["candidates"][0]) | |
| self.assertIn("Response 2 is much better", adapt(example([3]))[0]["candidates"][-1]) | |
| def test_disagreement_and_swap(self): | |
| source = example([-3, 0, 1]) | |
| original = deepcopy(source) | |
| task, = adapt(source) | |
| self.assertEqual(task["target"], [1/3, 0, 0, 1/3, 1/3, 0, 0]) | |
| self.assertEqual(source, original) | |
| swapped = deepcopy(source) | |
| swapped["response1"], swapped["response2"] = source["response2"], source["response1"] | |
| for vote in swapped["individual_preference"]: | |
| vote["score"] *= -1 | |
| other, = adapt(swapped) | |
| self.assertEqual(other["target"], task["target"][::-1]) | |
| self.assertEqual(other["group_key"], task["group_key"]) | |
| def test_no_label_leakage_and_no_aggregate_fallback(self): | |
| task, = adapt(example([-1, -1, 3])) | |
| self.assertEqual(set(json.loads(task["state"])), {"context", "response1", "response2"}) | |
| self.assertNotIn("SECRET", task["state"] + task["instructions"]) | |
| self.assertNotIn("overall_preference", task["state"]) | |
| self.assertEqual(adapt(example([])), []) | |
| for bad in [4, -4, True, 1.0, "1", None]: | |
| self.assertEqual(adapt(example([-1, bad])), []) | |
| def test_context_normalization_preserves_semantics(self): | |
| source = example([0]) | |
| source["context"][0]["content"] = "Code:\r\n Pass" | |
| a, = adapt(source) | |
| source["context"][0]["content"] = "Code:\n Pass" | |
| b, = adapt(source) | |
| self.assertEqual(a["group_key"], b["group_key"]) | |
| source["context"][0]["content"] = "code:\n pass" | |
| self.assertNotEqual(a["group_key"], adapt(source)[0]["group_key"]) | |
| if __name__ == "__main__": | |
| unittest.main() | |