Update noise suppression test-suites.

openlrc/preprocess.py

@@ -69,7 +69,7 @@ def noise_suppression(self, audio_paths: Union[str, Path, List[str], List[Path]]
             if not ns_path.exists():
                 audio, info = load_audio(audio_path, sr=df_state.sr())
 
-                # Split audio into 10 min chunks
+                # Split audio into 3 min chunks
                 audio_chunks = [audio[:, i:i + chunk_size * info.sample_rate]
                                 for i in range(0, audio.shape[1], chunk_size * info.sample_rate)]
 
@@ -79,7 +79,7 @@ def noise_suppression(self, audio_paths: Union[str, Path, List[str], List[Path]]
 
                 enhanced = torch.cat(enhanced_chunks, dim=1)
 
-                assert enhanced.shape == audio.shape, 'Enhanced audio shape does not match original audio shape.'
+                assert enhanced.shape == audio.shape, f'Enhanced audio shape does not match original audio shape: {enhanced.shape} != {audio.shape}'
 
                 save_audio(ns_path, enhanced, sr=df_state.sr())
 

tests/test_preprocess.py

@@ -22,12 +22,15 @@ def tearDown(self) -> None:
     @patch('openlrc.preprocess.release_memory')
     def test_noise_suppression_returns_path_objects(self, mock_release_memory, mock_save_audio, mock_load_audio,
                                                     mock_init_df, mock_enhance):
-        mock_enhance.return_value = torch.zeros((2, 300 * 16000))
+        chunk_size = 180
+        mock_audio_size = chunk_size * 5
+
+        mock_enhance.return_value = torch.zeros((2, chunk_size * 16000))
         mock_init_df.return_value = (Mock(), Mock(), Mock())
 
         mock_info = Mock()
         mock_info.sample_rate = 16000
-        mock_load_audio.return_value = (torch.zeros((2, 1200 * 16000)), mock_info)
+        mock_load_audio.return_value = (torch.zeros((2, mock_audio_size * 16000)), mock_info)
 
         mock_save_audio.return_value = None
         mock_release_memory.return_value = None