Support compiling a module after it was set up by Fabric (#17529)

Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

(cherry picked from commit a533f68)

Author: awaelchli

src/lightning/fabric/fabric.py

@@ -46,7 +46,13 @@
 from lightning.fabric.utilities.seed import seed_everything
 from lightning.fabric.utilities.types import ReduceOp
 from lightning.fabric.utilities.warnings import PossibleUserWarning
-from lightning.fabric.wrappers import _FabricDataLoader, _FabricModule, _FabricOptimizer, _unwrap_objects
+from lightning.fabric.wrappers import (
+    _FabricDataLoader,
+    _FabricModule,
+    _FabricOptimizer,
+    _unwrap_compiled,
+    _unwrap_objects,
+)
 
 
 class Fabric:
@@ -542,6 +548,7 @@ def no_backward_sync(self, module: _FabricModule, enabled: bool = True) -> Gener
             enabled: Whether the context manager is enabled or not. ``True`` means skip the sync, ``False`` means do not
                 skip.
         """
+        module = _unwrap_compiled(module)
         if not isinstance(module, _FabricModule):
             raise TypeError(
                 "You need to set up the model first before you can call `self.no_backward_sync()`:"

src/lightning/fabric/wrappers.py

@@ -28,6 +28,7 @@
 from lightning.fabric.utilities import move_data_to_device
 from lightning.fabric.utilities.data import _set_sampler_epoch
 from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
+from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
 from lightning.fabric.utilities.types import Optimizable
 from lightning.fabric.utilities.warnings import PossibleUserWarning
 
@@ -218,15 +219,35 @@ def _unwrap_objects(collection: Any) -> Any:
     def _unwrap(
         obj: Union[_FabricModule, _FabricOptimizer, _FabricDataLoader]
     ) -> Union[nn.Module, Optimizer, DataLoader]:
-        if isinstance(obj, _FabricModule):
-            return obj._forward_module
+        if isinstance(unwrapped := _unwrap_compiled(obj), _FabricModule):
+            return unwrapped._forward_module
         if isinstance(obj, _FabricOptimizer):
             return obj.optimizer
         if isinstance(obj, _FabricDataLoader):
             return obj._dataloader
         return obj
 
-    return apply_to_collection(collection, dtype=(_FabricModule, _FabricOptimizer, _FabricDataLoader), function=_unwrap)
+    types = [_FabricModule, _FabricOptimizer, _FabricDataLoader]
+    if _TORCH_GREATER_EQUAL_2_0:
+        from torch._dynamo import OptimizedModule
+
+        types.append(OptimizedModule)
+
+    return apply_to_collection(collection, dtype=tuple(types), function=_unwrap)
+
+
+def _unwrap_compiled(obj: Any) -> Any:
+    """Removes the :class:`torch._dynamo.OptimizedModule` around the object if it is wrapped.
+
+    Use this function before instance checks against e.g. :class:`_FabricModule`.
+    """
+    if not _TORCH_GREATER_EQUAL_2_0:
+        return obj
+    from torch._dynamo import OptimizedModule
+
+    if isinstance(obj, OptimizedModule):
+        return obj._orig_mod
+    return obj
 
 
 def is_wrapped(obj: object) -> bool:
@@ -239,4 +260,5 @@ def is_wrapped(obj: object) -> bool:
     Args:
         obj: The object to test.
     """
+    obj = _unwrap_compiled(obj)
     return isinstance(obj, (_FabricModule, _FabricOptimizer, _FabricDataLoader))

tests/tests_fabric/test_wrappers.py

@@ -23,7 +23,7 @@
 from lightning.fabric.fabric import Fabric
 from lightning.fabric.plugins import Precision
 from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
-from lightning.fabric.wrappers import _FabricDataLoader, _FabricModule, _FabricOptimizer, is_wrapped
+from lightning.fabric.wrappers import _FabricDataLoader, _FabricModule, _FabricOptimizer, _unwrap_objects, is_wrapped
 from tests_fabric.helpers.runif import RunIf
 
 
@@ -358,7 +358,8 @@ def zero_grad(self, set_grads_to_None=False):
     custom_zero_grad.assert_called_with(set_grads_to_None=False)
 
 
-def test_is_wrapped():
+@pytest.mark.parametrize("compile", [False, pytest.param(True, marks=RunIf(dynamo=True))])
+def test_is_wrapped(compile):
     """Test that the `is_wrapped` utility recognizes when an object was wrapped by Fabric."""
     assert not is_wrapped(None)
 
@@ -368,6 +369,15 @@ def test_is_wrapped():
     wrapped = _FabricModule(module, Mock())
     assert is_wrapped(wrapped)
 
+    # _FabricModule inside an OptimizedModule
+    if compile:
+        from torch._dynamo import OptimizedModule
+
+        module = torch.nn.Linear(2, 2)
+        wrapped = torch.compile(_FabricModule(module, Mock()))
+        assert isinstance(wrapped, OptimizedModule)
+        assert is_wrapped(wrapped)
+
     # _FabricOptimizer
     optimizer = torch.optim.Adam(module.parameters())
     assert not is_wrapped(optimizer)
@@ -381,6 +391,43 @@ def test_is_wrapped():
     assert is_wrapped(wrapped)
 
 
+@pytest.mark.parametrize("compile", [False, pytest.param(True, marks=RunIf(dynamo=True))])
+def test_unwrap_objects(compile):
+    # empty container
+    assert _unwrap_objects({}) == {}
+
+    # container with pure objects and wrapped objects
+    module = torch.nn.Linear(1, 1)
+    wrapped_module = _FabricModule(module, Mock())
+    if compile:
+        wrapped_module = torch.compile(wrapped_module)
+    optimizer = torch.optim.Adam(module.parameters())
+    wrapped_optimizer = _FabricOptimizer(optimizer, Mock())
+    dataloader = DataLoader([1, 2, 3])
+    wrapped_dataloader = _FabricDataLoader(dataloader)
+    container = {
+        "int": 1,
+        "module": module,
+        "wrapped_module": wrapped_module,
+        "optimizer": optimizer,
+        "wrapped_optimizer": wrapped_optimizer,
+        "dataloader": dataloader,
+        "wrapped_dataloader": wrapped_dataloader,
+        "nested": [module, wrapped_module, optimizer, wrapped_optimizer, dataloader, wrapped_dataloader],
+    }
+    expected = {
+        "int": 1,
+        "module": module,
+        "wrapped_module": wrapped_module._forward_module,
+        "optimizer": optimizer,
+        "wrapped_optimizer": optimizer,
+        "dataloader": dataloader,
+        "wrapped_dataloader": dataloader,
+        "nested": [module, wrapped_module._forward_module, optimizer, optimizer, dataloader, dataloader],
+    }
+    assert _unwrap_objects(container) == expected
+
+
 def test_step_method_redirection():
     """Test that the FabricModule redirects the special `LightningModule.*_step` methods through the forward-
     module."""