WN.patch

--- /home/dcg-adlr-rafaelvalle-source.cosmos597/repos/nvidia/waveglow/glow.py
+++ /home/dcg-adlr-rafaelvalle-source.cosmos597/repos/nvidia/waveglow/glow.py
@@ -4,7 +4,6 @@
     from WaveNet is the convolutions need not be causal.  There is also no dilation
     size reset.  The dilation only doubles on each layer
     """
-
     def __init__(self, n_in_channels, n_mel_channels, n_layers, n_channels,
                  kernel_size):
         super(WN, self).__init__()
@@ -45,8 +44,7 @@
             else:
                 res_skip_channels = n_channels
             res_skip_layer = torch.nn.Conv1d(n_channels, res_skip_channels, 1)
-            res_skip_layer = torch.nn.utils.weight_norm(
-                res_skip_layer, name='weight')
+            res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name='weight')
             self.res_skip_layers.append(res_skip_layer)
 
     def forward(self, forward_input):
@@ -61,8 +59,8 @@
 
             res_skip_acts = self.res_skip_layers[i](acts)
             if i < self.n_layers - 1:
-                audio = res_skip_acts[:, :self.n_channels, :] + audio
-                skip_acts = res_skip_acts[:, self.n_channels:, :]
+                audio = res_skip_acts[:,:self.n_channels,:] + audio
+                skip_acts = res_skip_acts[:,self.n_channels:,:]
             else:
                 skip_acts = res_skip_acts