Modify `get_optimizer` to accept a model argument

TTS/utils/trainer_utils.py

@@ -1,5 +1,5 @@
 import importlib
-from typing import Dict
+from typing import Dict, List
 
 import torch
 
@@ -48,7 +48,7 @@ def get_scheduler(
 
 
 def get_optimizer(
-    optimizer_name: str, optimizer_params: dict, lr: float, model: torch.nn.Module
+    optimizer_name: str, optimizer_params: dict, lr: float, model: torch.nn.Module = None, parameters: List = None
 ) -> torch.optim.Optimizer:
     """Find, initialize and return a optimizer.
 
@@ -66,4 +66,6 @@ def get_optimizer(
         optimizer = getattr(module, "RAdam")
     else:
         optimizer = getattr(torch.optim, optimizer_name)
-    return optimizer(model.parameters(), lr=lr, **optimizer_params)
+    if model is not None:
+        parameters = model.parameters()
+    return optimizer(parameters, lr=lr, **optimizer_params)