Add missing kernel size attr to transformer layer

TTS/tts/layers/generic/transformer.py

@@ -36,7 +36,7 @@ class FFTransformer(nn.Module):
 
 
 class FFTransformerBlock(nn.Module):
-    def __init__(self, in_out_channels, num_heads, hidden_channels_ffn, num_layers, dropout_p):
+    def __init__(self, in_out_channels, num_heads, hidden_channels_ffn, num_layers, dropout_p, kernel_size_fft):
         super().__init__()
         self.fft_layers = nn.ModuleList(
             [
@@ -45,6 +45,7 @@ class FFTransformerBlock(nn.Module):
                     num_heads=num_heads,
                     hidden_channels_ffn=hidden_channels_ffn,
                     dropout_p=dropout_p,
+                    kernel_size_fft=kernel_size_fft,
                 )
                 for _ in range(num_layers)
             ]
@@ -71,9 +72,16 @@ class FFTransformerBlock(nn.Module):
 
 class FFTDurationPredictor:
     def __init__(
-        self, in_channels, hidden_channels, num_heads, num_layers, dropout_p=0.1, cond_channels=None
+        self, in_channels, hidden_channels, num_heads, num_layers, dropout_p=0.1, cond_channels=None, kernel_size_fft=3
     ):  # pylint: disable=unused-argument
-        self.fft = FFTransformerBlock(in_channels, num_heads, hidden_channels, num_layers, dropout_p)
+        self.fft = FFTransformerBlock(
+            in_out_channels=in_channels,
+            num_heads=num_heads,
+            hidden_channels=hidden_channels,
+            num_layers=num_layers,
+            dropout_p=dropout_p,
+            kernel_size_fft=kernel_size_fft,
+        )
         self.proj = nn.Linear(in_channels, 1)
 
     def forward(self, x, mask=None, g=None):  # pylint: disable=unused-argument