remove bn in postnet

parakeet/models/transformer_tts.py

@@ -340,13 +340,13 @@ class CNNPostNet(nn.Layer):
             c_in = d_input if i == 0 else d_hidden
             c_out = d_output if i == n_layers - 1 else d_hidden
             self.convs.append(
-                Conv1dBatchNorm(
+                nn.Conv1D(
                     c_in,
                     c_out,
                     kernel_size,
                     weight_attr=I.XavierUniform(),
                     padding=padding))
-        self.last_bn = nn.BatchNorm1D(d_output)
+        # self.last_bn = nn.BatchNorm1D(d_output)
         # for a layer that ends with a normalization layer that is targeted to
         # output a non zero-central output, it may take a long time to 
         # train the scale and bias
@@ -358,7 +358,9 @@ class CNNPostNet(nn.Layer):
             x = layer(x)
             if i != (len(self.convs) - 1):
                 x = F.tanh(x)
-        x = self.last_bn(x_in + x)
+        # TODO: check it
+        x = x_in + x
+        # x = self.last_bn(x_in + x)
         return x