update to align_module_device

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

src/compressed_tensors/utils/offload.py

@@ -30,9 +30,6 @@
     _has_accelerate = True
 except ImportError:
     _has_accelerate = False
-    AlignDevicesHook = None
-    OffloadedWeightsLoader = None
-    PrefixedDataset = None
 
 
 __all__ = [
@@ -45,7 +42,7 @@
     "update_offload_data",
     "delete_offload_parameter",
     "has_offloaded_params",
-    "align_module",
+    "align_module_device",
 ]
 
 
@@ -251,52 +248,45 @@ def has_offloaded_params(module: torch.nn.Module) -> bool:
 
 
 # introduced in accelerate v1.1.0
+@check_accelerate(fallback=contextlib.nullcontext())
 @contextlib.contextmanager
-def align_module(
+def align_module_device(
     module: torch.nn.Module, execution_device: Optional[torch.device] = None
 ):
     """
-    Moves a module's parameters to the specified execution device.
+    Context manager that moves a module's parameters to the specified execution device.
 
     Args:
-        module (torch.nn.Module): Module with parameters to align.
-        execution_device (Optional[torch.device]): If provided, overrides the
-            module's execution device within the context.
-
-    Yields:
-        None: Yields control while the module's parameters are aligned to the execution
-        device.
+        module (`torch.nn.Module`):
+            Module with parameters to align.
+        execution_device (`torch.device`, *optional*):
+            If provided, overrides the module's execution device within the context.
+            Otherwise, use hook execution device or pass
     """
     if has_offloaded_params(module):
         if execution_device is not None:
             original_device = module._hf_hook.execution_device
             module._hf_hook.execution_device = execution_device
 
-        module._hf_hook.pre_forward(module)
-        yield
-        module._hf_hook.post_forward(module, None)
-
-        if execution_device is not None:
-            module._hf_hook.execution_device = original_device
+        try:
+            module._hf_hook.pre_forward(module)
+            yield
+        finally:
+            module._hf_hook.post_forward(module, None)
+            if execution_device is not None:
+                module._hf_hook.execution_device = original_device
 
     elif execution_device is not None:
-        devices = {}
-        for name, param in module.named_parameters():
-            devices[name] = param.device
-            set_module_tensor_to_device(
-                module,
-                name,
-                execution_device,
-            )
-
-        yield
-
-        for name, param in module.named_parameters():
-            set_module_tensor_to_device(
-                module,
-                name,
-                devices[name],
-            )
+        devices = {
+            name: param.device for name, param in module.named_parameters(recurse=False)
+        }
+        try:
+            for name in devices:
+                set_module_tensor_to_device(module, name, execution_device)
+            yield
+        finally:
+            for name, device in devices.items():
+                set_module_tensor_to_device(module, name, device)
 
     else:
         yield