Temporary fix to workaround the mutable decomposition error. by lanluo-nvidia · Pull Request #3636 · pytorch/TensorRT
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2025-06-30 20:42:14.145185+00:00 +++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.py 2025-06-30 20:42:41.576462+00:00 @@ -475,11 +475,13 @@ f"Invalid input type {type(inputs)} encountered in the input. " + "Allowed input types: {torch_tensorrt.Input, torch.Tensor, list, tuple, dict}" ) 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") + 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)