replace warning w/ hard error in AutoUnit's fsdp + torch compile

Reviewed By: daniellepintz, rohan-varma

Differential Revision: D47473960

fbshipit-source-id: bbe5017c5eaf1e49a54e3ae14ad114c2df30d984

torchtnt/framework/auto_unit.py

@@ -198,14 +198,14 @@ def __init__(
                 if torch_compile_params and strategy.static_graph is True:
                     # https://dev-discuss.pytorch.org/t/torchdynamo-update-9-making-ddp-work-with-torchdynamo/860
                     raise RuntimeError(
-                        "Torch compile requires DDPStrategy's static_graph to be False"
+                        "Torch compile requires DDPStrategy's static_graph to be False."
                     )
                 module = prepare_ddp(module, self.device, strategy)
             elif isinstance(strategy, FSDPStrategy):
                 if torch_compile_params and strategy.use_orig_params is False:
                     # as stated here https://pytorch.org/get-started/pytorch-2.0/
-                    rank_zero_warn(
-                        "We recommend setting FSDPStrategy's use_orig_params to True when using torch compile."
+                    raise RuntimeError(
+                        "Torch compile requires FSDPStrategy's use_orig_params to be True, since AOTAutograd needs to be aware of the original parameters."
                     )
                 module = prepare_fsdp(
                     module,
@@ -436,18 +436,19 @@ def __init__(
                 if torch_compile_params and strategy.static_graph is True:
                     # https://dev-discuss.pytorch.org/t/torchdynamo-update-9-making-ddp-work-with-torchdynamo/860
                     raise RuntimeError(
-                        "Torch compile requires DDPStrategy's static_graph to be False"
+                        "Torch compile requires DDPStrategy's static_graph to be False."
                     )
                 module = prepare_ddp(module, self.device, strategy)
             elif isinstance(strategy, FSDPStrategy):
                 if swa_params:
                     raise RuntimeError(
                         "Stochastic Weight Averaging is currently not supported with the FSDP strategy"
                     )
-                # as stated here https://pytorch.org/get-started/pytorch-2.0/
-                rank_zero_warn(
-                    "We recommend setting FSDPStrategy's use_original_params to True when using torch compile."
-                )
+                if torch_compile_params and strategy.use_orig_params is False:
+                    # as stated here https://pytorch.org/get-started/pytorch-2.0/
+                    raise RuntimeError(
+                        "Torch compile requires FSDPStrategy's use_orig_params to be True, since AOTAutograd needs to be aware of the original parameters."
+                    )
                 module = prepare_fsdp(module, self.device, strategy, self.precision)
         else:
             module = module.to(self.device)