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7.92 kB
| from __future__ import annotations | |
| import hashlib | |
| import json | |
| import tempfile | |
| import unittest | |
| from pathlib import Path | |
| from barbet_bgd.audit import StatsAccumulator, write_manifest, write_report | |
| from barbet_bgd.io import ( | |
| iter_gzip_jsonl, | |
| iter_jsonl_gz, | |
| sha256_file, | |
| write_gzip_jsonl_atomic, | |
| write_jsonl_gz_atomic, | |
| ) | |
| def _record( | |
| record_id: str, | |
| *, | |
| split: str = "train", | |
| source_text: str = "模型將於九月十五日上線。", | |
| evidence: str = "src:w03", | |
| context_bucket: str = "0.5K-4K", | |
| intentional_simplified: bool = False, | |
| ) -> dict: | |
| return { | |
| "record_id": record_id, | |
| "schema_version": "bgd.canonical.v1", | |
| "primitive": "VERIFY", | |
| "mixture_category": "VERIFICATION_QE_ERROR_LOCALIZATION", | |
| "task_family": "ASR_QUALITY", | |
| "domain": "meeting", | |
| "language": ["zh-TW", "en"], | |
| "locale": "zh-TW", | |
| "split": split, | |
| "source_group": "synthetic-test", | |
| "task_spec": {"instruction": "判斷候選是否忠實,並引用證據。"}, | |
| "inputs": [ | |
| { | |
| "id": "src", | |
| "type": "reference_text", | |
| "units": [ | |
| {"id": "src:w01", "text": "模型"}, | |
| {"id": "src:w03", "text": source_text}, | |
| ], | |
| }, | |
| { | |
| "id": "hyp", | |
| "type": "asr_hypothesis", | |
| "units": [{"id": "hyp:w03", "text": "模型將於九月五日上線。"}], | |
| }, | |
| ], | |
| "target": { | |
| "decision": "FAIL", | |
| "confidence_target": 0.98, | |
| "errors": [ | |
| { | |
| "type": "VALUE_CORRUPTION", | |
| "source_evidence": [evidence], | |
| "target_evidence": ["hyp:w03"], | |
| } | |
| ], | |
| "action": {"tool": "EDIT", "arguments": {"target": "hyp:w03"}}, | |
| }, | |
| "component_targets": {}, | |
| "presentation": { | |
| "serializer": "JSON", | |
| "serializer_version": "1", | |
| }, | |
| "provenance": {"source_hash": "0" * 64}, | |
| "quality": { | |
| "context_length_bucket": context_bucket, | |
| "intentional_negative_simplified_hits": ( | |
| [{"unit_id": "src:w03", "hits": ["这"]}] | |
| if intentional_simplified | |
| else [] | |
| ) | |
| }, | |
| } | |
| class AtomicGzipJsonlTests(unittest.TestCase): | |
| def test_round_trip_digest_and_deterministic_bytes(self) -> None: | |
| rows = [_record("bgd-001"), _record("bgd-002", split="validation")] | |
| with tempfile.TemporaryDirectory() as tmp: | |
| root = Path(tmp) | |
| first = write_gzip_jsonl_atomic(root / "first.jsonl.gz", rows) | |
| second = write_gzip_jsonl_atomic(root / "second.jsonl.gz", rows) | |
| self.assertEqual(list(iter_gzip_jsonl(first.path)), rows) | |
| self.assertEqual(first.records, 2) | |
| self.assertEqual(first.record_count, 2) | |
| self.assertEqual(first.sha256, sha256_file(first.path)) | |
| self.assertEqual(first.sha256, second.sha256) | |
| self.assertEqual( | |
| first.sha256, | |
| hashlib.sha256(first.path.read_bytes()).hexdigest(), | |
| ) | |
| self.assertFalse((root / "first.jsonl.gz.incomplete").exists()) | |
| alias = write_jsonl_gz_atomic(root / "alias.jsonl.gz", rows) | |
| self.assertEqual(list(iter_jsonl_gz(alias.path)), rows) | |
| def test_failed_write_preserves_published_file_and_cleans_incomplete(self) -> None: | |
| with tempfile.TemporaryDirectory() as tmp: | |
| path = Path(tmp) / "shard.jsonl.gz" | |
| path.write_bytes(b"published") | |
| def bad_rows(): | |
| yield _record("bgd-001") | |
| yield {"not_json": object()} | |
| with self.assertRaises(TypeError): | |
| write_gzip_jsonl_atomic(path, bad_rows()) | |
| self.assertEqual(path.read_bytes(), b"published") | |
| self.assertFalse(Path(f"{path}.incomplete").exists()) | |
| class StatsAccumulatorTests(unittest.TestCase): | |
| def test_ingest_counts_distributions_and_integrity_findings(self) -> None: | |
| stats = StatsAccumulator() | |
| stats.ingest(_record("same-id")) | |
| stats.ingest( | |
| _record( | |
| "same-id", | |
| split="test", | |
| source_text="这个模型将上线。", | |
| evidence="src:missing", | |
| context_bucket="4K-16K", | |
| ) | |
| ) | |
| result = stats.to_dict() | |
| self.assertEqual(result["total_records"], 2) | |
| self.assertEqual(result["split"], {"test": 1, "train": 1}) | |
| self.assertEqual(result["primitive"], {"VERIFY": 2}) | |
| self.assertEqual( | |
| result["mixture_category"], {"VERIFICATION_QE_ERROR_LOCALIZATION": 2} | |
| ) | |
| self.assertEqual(result["task_family"], {"ASR_QUALITY": 2}) | |
| self.assertEqual(result["domain"], {"meeting": 2}) | |
| self.assertEqual(result["serializer"], {"JSON": 2}) | |
| self.assertEqual(result["decision"], {"FAIL": 2}) | |
| self.assertEqual(result["error_type"], {"VALUE_CORRUPTION": 2}) | |
| self.assertEqual(result["action"], {"EDIT": 2}) | |
| self.assertEqual(result["context_bucket"], {"0.5K-4K": 1, "4K-16K": 1}) | |
| self.assertEqual(result["primary_zh_tw_records"], 2) | |
| self.assertEqual(result["primary_zh_tw_ratio"], 1.0) | |
| self.assertEqual(result["simplified_only_hit_records"], 1) | |
| self.assertEqual(result["duplicate_record_ids"], 1) | |
| self.assertEqual(result["duplicate_record_id_occurrences"], 1) | |
| self.assertEqual(result["evidence_reference_missing"], 1) | |
| self.assertEqual(result["evidence_reference_missing_records"], 1) | |
| def test_merge_detects_cross_shard_duplicates_and_annotations(self) -> None: | |
| left = StatsAccumulator().ingest(_record("shared")) | |
| right = StatsAccumulator().ingest( | |
| _record( | |
| "shared", | |
| source_text="这个模型将上线。", | |
| intentional_simplified=True, | |
| ) | |
| ) | |
| merged = left.merge(right).to_dict() | |
| self.assertEqual(merged["total_records"], 2) | |
| self.assertEqual(merged["duplicate_record_ids"], 1) | |
| self.assertEqual(merged["duplicate_record_id_occurrences"], 1) | |
| self.assertEqual(merged["simplified_only_hit_records"], 1) | |
| self.assertEqual(merged["intentional_negative_simplified_hit_records"], 1) | |
| self.assertEqual(merged["unannotated_simplified_only_hit_records"], 0) | |
| def test_manifest_and_report_are_atomic_json(self) -> None: | |
| rows = [_record("bgd-001")] | |
| with tempfile.TemporaryDirectory() as tmp: | |
| root = Path(tmp) | |
| shard = write_gzip_jsonl_atomic(root / "shard.jsonl.gz", rows) | |
| stats = StatsAccumulator().ingest(rows[0]) | |
| manifest_path = write_manifest( | |
| root / "manifest.json", | |
| [shard], | |
| stats=stats, | |
| metadata={"dataset_name": "unit-test"}, | |
| ) | |
| report_path = write_report(root / "report.json", stats) | |
| manifest = json.loads(manifest_path.read_text(encoding="utf-8")) | |
| report = json.loads(report_path.read_text(encoding="utf-8")) | |
| self.assertEqual(manifest["totals"]["records"], 1) | |
| self.assertEqual(manifest["shards"][0]["sha256"], shard.sha256) | |
| self.assertEqual(manifest["metadata"]["dataset_name"], "unit-test") | |
| self.assertTrue(report["checks"]["all_records_primary_zh_tw"]) | |
| self.assertTrue(report["checks"]["record_ids_unique"]) | |
| self.assertFalse(Path(f"{manifest_path}.incomplete").exists()) | |
| self.assertFalse(Path(f"{report_path}.incomplete").exists()) | |
| if __name__ == "__main__": | |
| unittest.main() | |