optimize(infer.synthesizer): all modules inherit from one

infer/modules/vc/pipeline.py

@@ -290,10 +290,15 @@ class Pipeline(object):
             feats = feats.to(feats0.dtype)
         p_len = torch.tensor([p_len], device=self.device).long()
         with torch.no_grad():
-            hasp = pitch is not None and pitchf is not None
-            arg = (feats, p_len, pitch, pitchf, sid) if hasp else (feats, p_len, sid)
-            audio1 = (net_g.infer(*arg)[0][0, 0]).data.cpu().float().numpy()
-            del arg
+            audio1 = (
+                net_g.infer(
+                    feats,
+                    p_len,
+                    sid,
+                    pitch=pitch,
+                    pitchf=pitchf,
+                )[0, 0]
+            ).data.cpu().float().numpy()
         del feats, p_len, padding_mask
         if torch.cuda.is_available():
             torch.cuda.empty_cache()