Rename infer method to forward for WaveRNNInferenceWrapper (#1650)

examples/pipeline_wavernn/inference.py

@@ -73,13 +73,13 @@ def main(args):
     mel_specgram = transforms(waveform)
 
     wavernn_model = wavernn(args.checkpoint_name).eval().to(device)
-    wavernn_model = WaveRNNInferenceWrapper(wavernn_model)
+    wavernn_inference_model = WaveRNNInferenceWrapper(wavernn_model)
 
     if args.jit:
-        wavernn_model = torch.jit.script(wavernn_model)
+        wavernn_inference_model = torch.jit.script(wavernn_inference_model)
 
     with torch.no_grad():
-        output = wavernn_model.infer(mel_specgram.to(device),
+        output = wavernn_inference_model(mel_specgram.to(device),
                                          loss_name=args.loss,
                                          mulaw=(not args.no_mulaw),
                                          batched=(not args.no_batch_inference),

examples/pipeline_wavernn/wavernn_inference_wrapper.py

@@ -160,8 +160,7 @@ class WaveRNNInferenceWrapper(torch.nn.Module):
                             f"Valid choices are 'both', 'before' and 'after'.")
         return padded
 
-    @torch.jit.export
-    def infer(self,
+    def forward(self,
                 specgram: Tensor,
                 loss_name: str = "crossentropy",
                 mulaw: bool = True,