Preserve LavaSR digital silence

CHANGELOG.md

@@ -4,6 +4,15 @@ All notable changes to this project will be documented in this file.
 
 This project follows semantic versioning once published to PyPI.
 
+## Unreleased
+
+### Fixed
+
+- Preserved exact digital silence in `lavasr-compat` instead of passing it through the model and
+  producing deterministic low-level output texture.
+- Made `audio-super-res eval matrix` return a non-zero exit status when any matrix run fails, so
+  remote evidence workflows cannot report success for failed stability checks.
+
 ## 0.6.0 - 2026-07-12
 
 ### Added

ROADMAP.md

@@ -14,7 +14,7 @@ evidence and a smaller number of well-supported paths.
 | Evaluation | Full-reference, no-reference, downstream, listening, matrix, report, and bundle workflows are implemented. |
 | Packaging | Source version is `0.6.0`; build, metadata, wheel, lint, type, and default test gates are available through Pixi. |
 
-## Priority 0: Ship v0.6.0 Cleanly
+## Completed: Ship v0.6.0 Cleanly
 
 The immediate goal is a release-quality package, not another model backend.
 
@@ -24,7 +24,7 @@ Release-preparation status:
 - [x] Run the complete local release checklist in [docs/RELEASE.md](docs/RELEASE.md).
 - [x] Confirm CI on the merge commit and inspect the built wheel/sdist.
 - [x] Run a fresh installed-wheel CLI smoke test outside the source tree.
-- [ ] Tag `v0.6.0`, publish the GitHub release, and verify the trusted-publishing workflow and PyPI
+- [x] Tag `v0.6.0`, publish the GitHub release, and verify the trusted-publishing workflow and PyPI
   installation.
 
 Release scope deliberately excludes new heavyweight evaluators, new model weights, and a new

docs/ACCELERATORS.md

@@ -224,3 +224,17 @@ A fresh Colab Tesla T4 run was recorded on 2026-07-01 UTC at commit
 
 This is historical evidence for the eager CUDA path, not a permanent performance baseline. Repeat
 the workflow on the release commit before making new device/provider claims.
+
+A v0.6.0 Colab CLI run on 2026-07-12 validated the published tag at commit
+`5e4241c5ed7399b29d04bbfe39f04fdfd9f100dc` on the same Tesla T4 environment:
+
+- real-weight download/verification and CUDA torch smoke passed;
+- explicit CUDA device detection passed;
+- four of five generated failure cases passed;
+- exact digital silence exposed deterministic model output around `-75 dBFS` RMS and was correctly
+  reported as `silence_hallucination` by the eval harness;
+- the follow-up exact-silence preservation fix passed all five cases on the same remote session,
+  with zero duration drift for the silence fixture.
+
+The downloaded evidence archive belongs under ignored `runs/` or the associated GitHub issue/PR,
+not in the source distribution.

examples/colab_lavasr_validation.py

@@ -194,6 +194,9 @@ def main() -> int:
             ],
             cwd=REPO_DIR,
         )
+        matrix_manifest = json.loads((matrix_dir / "matrix.json").read_text(encoding="utf-8"))
+        if not matrix_manifest.get("passed"):
+            raise RuntimeError("LavaSR failure-case matrix reported one or more failed runs")
         _write_summary(status="passed")
     except Exception as exc:
         error = f"{type(exc).__name__}: {exc}"

src/audio_super_resolution/backends/lavasr_compat.py

@@ -117,10 +117,13 @@ def enhance(self, audio: np.ndarray, sample_rate: int, target_sample_rate: int)
         device = resolve_device(self.config.device, supported_devices=LAVASR_CAPABILITY.accelerators)
         _require_torch_runtime()
 
+        prepared_audio, was_mono = _prepare_lavasr_input(audio, sample_rate)
+        if not np.any(prepared_audio):
+            return _restore_lavasr_output(np.zeros_like(prepared_audio).T, was_mono=was_mono)
+
         import torch
 
         model = self._load_model(resolved_weights, bundle_info, device=device)
-        prepared_audio, was_mono = _prepare_lavasr_input(audio, sample_rate)
         waveform = torch.from_numpy(prepared_audio.T.copy()).to(device=device, dtype=torch.float32)
 
         with torch.inference_mode():

src/audio_super_resolution/cli.py

@@ -602,7 +602,7 @@ def _run_eval_command(argv: list[str]) -> int:
                 ),
             )
             print(f"Wrote eval matrix {args.output_dir / 'matrix.json'} ({manifest['run_count']} run(s))")
-            return 0
+            return 0 if manifest["passed"] else 1
         if args.eval_command == "run":
             model_cache_dir = args.model_cache_dir if args.model_cache_dir is not None else default_model_cache_dir()
             manifest = run_eval_dataset(

tests/test_cli.py

@@ -423,6 +423,27 @@ def test_cli_eval_matrix(tmp_path: Path, capsys) -> None:
     assert {run["degrader"] for run in matrix["runs"]} == {"lowpass_4k", "mp3_32kbps"}
 
 
+def test_cli_eval_matrix_returns_nonzero_when_a_run_fails(monkeypatch, tmp_path: Path, capsys) -> None:
+    monkeypatch.setattr(
+        "audio_super_resolution.cli.run_eval_matrix",
+        lambda **kwargs: {"passed": False, "run_count": 1},
+    )
+
+    exit_code = main(
+        [
+            "eval",
+            "matrix",
+            "--dataset",
+            str(tmp_path / "dataset"),
+            "--output-dir",
+            str(tmp_path / "matrix"),
+        ]
+    )
+
+    assert exit_code == 1
+    assert "Wrote eval matrix" in capsys.readouterr().out
+
+
 def test_cli_eval_matrix_compare_report_bundle_and_validate_dataset(tmp_path: Path, capsys) -> None:
     evalset = tmp_path / "evalset"
     assert (

tests/test_lavasr_compat.py

@@ -32,3 +32,33 @@ def test_lavasr_backend_rejects_unsupported_precision_before_weight_resolution(t
 
     with pytest.raises(ValueError, match="precision modes"):
         backend.enhance(np.zeros(100, dtype=np.float32), 16000, 48000)
+
+
+def test_lavasr_backend_preserves_exact_digital_silence(monkeypatch, tmp_path) -> None:
+    resolved_weights = object()
+    bundle_info = object()
+    monkeypatch.setattr(
+        "audio_super_resolution.weight_store.resolve_weights_for_spec",
+        lambda *args, **kwargs: resolved_weights,
+    )
+    monkeypatch.setattr(
+        "audio_super_resolution.backends.lavasr_validation.validate_lavasr_v2_weight_bundle",
+        lambda resolved: bundle_info,
+    )
+    monkeypatch.setattr("audio_super_resolution.backends.lavasr_compat.resolve_runtime_provider", lambda *args: None)
+    monkeypatch.setattr("audio_super_resolution.backends.lavasr_compat.resolve_device", lambda *args, **kwargs: "cuda")
+    monkeypatch.setattr("audio_super_resolution.backends.lavasr_compat._require_torch_runtime", lambda: None)
+
+    backend = LavaSRCompatBackend(
+        config=InferenceConfig(
+            device="cuda",
+            runtime_provider="torch-eager",
+            model_cache_dir=tmp_path / "models",
+        )
+    )
+    monkeypatch.setattr(backend, "_load_model", lambda *args, **kwargs: pytest.fail("model should not load"))
+
+    enhanced = backend.enhance(np.zeros(100, dtype=np.float32), 16000, 48000)
+
+    assert enhanced.shape == (300,)
+    assert np.count_nonzero(enhanced) == 0