update

examples/clean_unet_aishell/test.py

@@ -0,0 +1,12 @@
+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+
+
+nn.Sequential(
+    nn.Conv1d(channels_h, channels_h * 2, 1),
+    nn.GLU(dim=1),
+    nn.ConvTranspose1d(channels_h, channels_output, kernel_size, stride),
+    # nn.ReLU()
+)
+if __name__ == '__main__':
+    pass

toolbox/torchaudio/models/clean_unet/modeling_clean_unet.py

@@ -126,7 +126,7 @@ class CleanUNet(nn.Module):
         for i in range(encoder_n_layers):
             self.encoder.append(nn.Sequential(
                 nn.Conv1d(channels_input, channels_h, kernel_size, stride),
-                nn.ReLU(),
+                nn.ReLU(inplace=False),
                 nn.Conv1d(channels_h, channels_h * 2, 1),
                 nn.GLU(dim=1)
             ))
@@ -144,7 +144,7 @@ class CleanUNet(nn.Module):
                     nn.Conv1d(channels_h, channels_h * 2, 1),
                     nn.GLU(dim=1),
                     nn.ConvTranspose1d(channels_h, channels_output, kernel_size, stride),
-                    # nn.ReLU()
+                    nn.ReLU(inplace=False)
                 ))
             channels_output = channels_h