add sequence_mask to utils.data

TTS/tts/layers/losses.py

@@ -5,7 +5,7 @@ import torch
 from torch import nn
 from torch.nn import functional
 
-from TTS.tts.utils.generic_utils import sequence_mask
+from TTS.tts.utils.data import sequence_mask
 from TTS.tts.utils.ssim import ssim
 
 

TTS/tts/utils/data.py

@@ -1,3 +1,4 @@
+import torch
 import numpy as np
 
 
@@ -65,3 +66,12 @@ class StandardScaler:
         X *= self.scale_
         X += self.mean_
         return X
+
+
+# from https://gist.github.com/jihunchoi/f1434a77df9db1bb337417854b398df1
+def sequence_mask(sequence_length, max_len=None):
+    if max_len is None:
+        max_len = sequence_length.data.max()
+    seq_range = torch.arange(max_len, dtype=sequence_length.dtype, device=sequence_length.device)
+    # B x T_max
+    return seq_range.unsqueeze(0) < sequence_length.unsqueeze(1)