init (not checked bat script yet)

modules.py

@@ -1,15 +1,19 @@
 import math
+import warnings
+
 import torch
 from torch import nn
+from torch.nn import Conv1d
 from torch.nn import functional as F
 
-from torch.nn import Conv1d
-from torch.nn.utils import weight_norm, remove_weight_norm
-
 import commons
-from commons import init_weights, get_padding
-from transforms import piecewise_rational_quadratic_transform
 from attentions import Encoder
+from commons import get_padding, init_weights
+from transforms import piecewise_rational_quadratic_transform
+
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore")
+    from torch.nn.utils import remove_weight_norm, weight_norm
 
 LRELU_SLOPE = 0.1
 
@@ -578,20 +582,3 @@ class TransformerCouplingLayer(nn.Module):
             x1 = (x1 - m) * torch.exp(-logs) * x_mask
             x = torch.cat([x0, x1], 1)
             return x
-
-        x1, logabsdet = piecewise_rational_quadratic_transform(
-            x1,
-            unnormalized_widths,
-            unnormalized_heights,
-            unnormalized_derivatives,
-            inverse=reverse,
-            tails="linear",
-            tail_bound=self.tail_bound,
-        )
-
-        x = torch.cat([x0, x1], 1) * x_mask
-        logdet = torch.sum(logabsdet * x_mask, [1, 2])
-        if not reverse:
-            return x, logdet
-        else:
-            return x