pad short samples when loading precomputed features in vocoder trainign

TTS/vocoder/datasets/gan_dataset.py

@@ -73,6 +73,18 @@ class GANDataset(Dataset):
         item1 = self.load_item(idx)
         return item1
 
+    def _pad_short_samples(self, audio, mel=None):
+        """Pad samples shorter than the output sequence length"""
+        if len(audio) < self.seq_len:
+            audio = np.pad(audio, (0, self.seq_len - len(audio)),
+                            mode='constant',
+                            constant_values=0.0)
+
+        if mel is not None and mel.shape[1] < self.feat_frame_len:
+            pad_value = self.ap.melspectrogram(np.zeros([self.ap.win_length]))[:, 0]
+            mel = np.pad(mel, ([0, 0], [0, self.feat_frame_len - mel.shape[1]]), mode='constant', constant_values=pad_value.mean())
+        return audio, mel
+
     def shuffle_mapping(self):
         random.shuffle(self.G_to_D_mappings)
 
@@ -87,11 +99,7 @@ class GANDataset(Dataset):
                 audio, mel = self.cache[idx]
             else:
                 audio = self.ap.load_wav(wavpath)
-
+                audio, _ = self._pad_short_samples(audio)
-                if len(audio) < self.seq_len + self.pad_short:
-                    audio = np.pad(audio, (0, self.seq_len + self.pad_short - len(audio)), \
-                            mode='constant', constant_values=0.0)
-
                 mel = self.ap.melspectrogram(audio)
         else:
 
@@ -103,6 +111,7 @@ class GANDataset(Dataset):
             else:
                 audio = self.ap.load_wav(wavpath)
                 mel = np.load(feat_path)
+                audio, mel= self._pad_short_samples(audio, mel)
 
         # correct the audio length wrt padding applied in stft
         audio = np.pad(audio, (0, self.hop_len), mode="edge")