refactor: remove duplicate convert_pad_shape

TTS/tts/layers/glow_tts/transformer.py

@@ -5,6 +5,7 @@ from torch import nn
 from torch.nn import functional as F
 
 from TTS.tts.layers.generic.normalization import LayerNorm, LayerNorm2
+from TTS.tts.utils.helpers import convert_pad_shape
 
 
 class RelativePositionMultiHeadAttention(nn.Module):
@@ -300,7 +301,7 @@ class FeedForwardNetwork(nn.Module):
         pad_l = self.kernel_size - 1
         pad_r = 0
         padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, self._pad_shape(padding))
+        x = F.pad(x, convert_pad_shape(padding))
         return x
 
     def _same_padding(self, x):
@@ -309,15 +310,9 @@ class FeedForwardNetwork(nn.Module):
         pad_l = (self.kernel_size - 1) // 2
         pad_r = self.kernel_size // 2
         padding = [[0, 0], [0, 0], [pad_l, pad_r]]
-        x = F.pad(x, self._pad_shape(padding))
+        x = F.pad(x, convert_pad_shape(padding))
         return x
 
-    @staticmethod
-    def _pad_shape(padding):
-        l = padding[::-1]
-        pad_shape = [item for sublist in l for item in sublist]
-        return pad_shape
-
 
 class RelativePositionTransformer(nn.Module):
     """Transformer with Relative Potional Encoding.

TTS/tts/layers/vits/networks.py

@@ -10,12 +10,6 @@ from TTS.tts.utils.helpers import sequence_mask
 LRELU_SLOPE = 0.1
 
 
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
 def init_weights(m, mean=0.0, std=0.01):
     classname = m.__class__.__name__
     if classname.find("Conv") != -1:

TTS/tts/utils/helpers.py

@@ -145,10 +145,9 @@ def average_over_durations(values, durs):
     return avg
 
 
-def convert_pad_shape(pad_shape):
+def convert_pad_shape(pad_shape: list[list]) -> list:
     l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
+    return [item for sublist in l for item in sublist]
 
 
 def generate_path(duration, mask):

TTS/vc/modules/freevc/commons.py

@@ -3,6 +3,8 @@ import math
 import torch
 from torch.nn import functional as F
 
+from TTS.tts.utils.helpers import convert_pad_shape
+
 
 def init_weights(m, mean=0.0, std=0.01):
     classname = m.__class__.__name__
@@ -14,12 +16,6 @@ def get_padding(kernel_size, dilation=1):
     return int((kernel_size * dilation - dilation) / 2)
 
 
-def convert_pad_shape(pad_shape):
-    l = pad_shape[::-1]
-    pad_shape = [item for sublist in l for item in sublist]
-    return pad_shape
-
-
 def intersperse(lst, item):
     result = [item] * (len(lst) * 2 + 1)
     result[1::2] = lst