Datasets:
Download code/test_v4_intent.py from kitaniai/OpenJudgment-4B-Preview: direct link, hf CLI and curl.
- Browser
- Download file 1.68 kB
-
https://huggingface.co/datasets/kitaniai/OpenJudgment-4B-Preview/resolve/main/code/test_v4_intent.py
- Command line
-
hf download hf://datasets/kitaniai/OpenJudgment-4B-Preview/code/test_v4_intent.py
-
curl -L -o test_v4_intent.py https://huggingface.co/datasets/kitaniai/OpenJudgment-4B-Preview/resolve/main/code/test_v4_intent.py
1.68 kB
| import unittest | |
| from v4_intent import CANDIDATES, adapt | |
| class IntentAdapterTest(unittest.TestCase): | |
| def row(self, label=CANDIDATES[0], split="train"): | |
| return {"content": "Дякую за допомогу!", "final_category": label, | |
| "split": split, "id": 1, "rating": 5, "source": "original"} | |
| def test_exact_taxonomy_and_no_label_leak(self): | |
| for index, label in enumerate(CANDIDATES): | |
| task = adapt(self.row(label))[0] | |
| self.assertEqual(task["target"], [float(i == index) for i in range(5)]) | |
| self.assertEqual(task["state"], "Дякую за допомогу!") | |
| def test_eval_partitions_never_become_train(self): | |
| for split in ("test", "challenge"): | |
| row = self.row(split=split) | |
| task = adapt(row)[0] | |
| self.assertEqual(task["source_split"], split) | |
| self.assertEqual(task["split"], split) | |
| self.assertTrue(task["metadata"]["evaluation_only"]) | |
| with self.assertRaises(ValueError): | |
| adapt(row, expected_split="train") | |
| def test_bad_split_and_label_fail_closed(self): | |
| for split in (None, "validation", ""): | |
| with self.assertRaises(ValueError): | |
| adapt(self.row(split=split)) | |
| with self.assertRaises(ValueError): | |
| adapt(self.row(label="positive")) | |
| def test_groups_ignore_labels_and_split(self): | |
| a = self.row() | |
| b = self.row(CANDIDATES[1], "test") | |
| b["content"] = " ДЯКУЮ за допомогу!\n" | |
| self.assertEqual(adapt(a)[0]["group_key"], adapt(b)[0]["group_key"]) | |
| if __name__ == "__main__": | |
| unittest.main() | |