🐛 | Misc fixes...

data.py

@@ -11,7 +11,7 @@ import AudioUtils
 class AudioDataset(Dataset):
     audio_sample_rates = [11025]
 
-    def __init__(self, input_dir, device):
+    def __init__(self, input_dir, device, clip_length = 256):
         self.device = device
         input_files = [os.path.join(root, f) for root, _, files in os.walk(input_dir) for f in files if f.endswith('.wav') or f.endswith('.mp3') or f.endswith('.flac')]
 
@@ -28,11 +28,11 @@ class AudioDataset(Dataset):
             low_audio = resample_transform_low(audio)
             low_audio = resample_transform_high(low_audio)
 
-            splitted_high_quality_audio = AudioUtils.split_audio(audio, 128)
-            splitted_high_quality_audio[-1] = AudioUtils.pad_tensor(splitted_high_quality_audio[-1], 128)
+            splitted_high_quality_audio = AudioUtils.split_audio(audio, clip_length)
+            splitted_high_quality_audio[-1] = AudioUtils.pad_tensor(splitted_high_quality_audio[-1], clip_length)
 
-            splitted_low_quality_audio = AudioUtils.split_audio(low_audio, 128)
-            splitted_low_quality_audio[-1] = AudioUtils.pad_tensor(splitted_low_quality_audio[-1], 128)
+            splitted_low_quality_audio = AudioUtils.split_audio(low_audio, clip_length)
+            splitted_low_quality_audio[-1] = AudioUtils.pad_tensor(splitted_low_quality_audio[-1], clip_length)
 
             for high_quality_sample, low_quality_sample in zip(splitted_high_quality_audio, splitted_low_quality_audio):
                 data.append(((high_quality_sample, low_quality_sample), (original_sample_rate, mangled_sample_rate)))

training.py

@@ -76,7 +76,7 @@ os.makedirs(audio_output_dir, exist_ok=True)
 
 # ========= SINGLE =========
 
-train_data_loader = DataLoader(dataset, batch_size=256, shuffle=True)
+train_data_loader = DataLoader(dataset, batch_size=1024, shuffle=True)
 
 
 # ========= MODELS =========