Update train_tacotron.py

When attempting to fine-tune a model with "prenet_type": "bn" that was originally trained with "prenet_type": "original", a RuntimeError is thrown that stops the training.

By catching the RuntimeError, the required layers can be partially restored and the training will continue without any problems.

TTS/bin/train_tacotron.py

@@ -549,7 +549,7 @@ def main(args):  # pylint: disable=redefined-outer-name
                 scaler.load_state_dict(checkpoint["scaler"])
             if c.reinit_layers:
                 raise RuntimeError
-        except KeyError:
+        except (KeyError, RuntimeError):
             print(" > Partial model initialization.")
             model_dict = model.state_dict()
             model_dict = set_init_dict(model_dict, checkpoint['model'], c)