Temporary fix to workaround the mutable decomposition error. (#3636)

Author: lanluo-nvidia

py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py

@@ -1,5 +1,6 @@
 import inspect
 import logging
+import warnings
 from copy import deepcopy
 from enum import Enum, auto
 from typing import Any, Collection, Dict, Iterator, List, Optional, Set, Union
@@ -464,6 +465,12 @@ def _process_kwarg_inputs(inputs: Any) -> Any:
         )
 
     def forward(self, *args: Any, **kwargs: Any) -> Any:
+        warnings.warn(
+            "Direct calls to {self.__class__}.forward() are currently broken by due to https://github.com/pytorch/pytorch/issues/157183. Either call {self.__class__}(...) directly or use {self.__class__}._forward as a work around"
+        )
+        return self._forward(*args, **kwargs)
+
+    def _forward(self, *args: Any, **kwargs: Any) -> Any:
         # Step 1: Check whether the input shape has changed
         kwargs = MutableTorchTensorRTModule._process_kwarg_inputs(kwargs)
         self._validate_inputs(*args, **kwargs)
@@ -513,7 +520,9 @@ def __deepcopy__(self, memo: Any) -> Any:
         return result
 
     def __call__(self, *args: Any, **kwargs: Any) -> Any:
-        return self.forward(*args, **kwargs)
+        # Due to https://github.com/pytorch/pytorch/issues/157183, we cannot use forward call, use _forward as a workaround.
+        # This is a temporary fix.
+        return self._forward(*args, **kwargs)
 
     def __getattr__(self, name: str) -> Any:
         if name in self.__dict__: