fix: guard torch.AcceleratorError for compatibility with torch < 2.8.0 (#12874)

* fix: guard torch.AcceleratorError for compatibility with torch < 2.8.0

torch.AcceleratorError was introduced in PyTorch 2.8.0. Accessing it
directly raises AttributeError on older versions. Use a try/except
fallback at module load time, consistent with the existing pattern used
for OOM_EXCEPTION.


* fix: address review feedback for AcceleratorError compat

- Fall back to RuntimeError instead of type(None) for ACCELERATOR_ERROR,
  consistent with OOM_EXCEPTION fallback pattern and valid for except clauses
- Add "out of memory" message introspection for RuntimeError fallback case
- Use RuntimeError directly in discard_cuda_async_error except clause
---------

comfy/model_management.py

@@ -270,10 +270,15 @@ try:
 except:
     OOM_EXCEPTION = Exception
 
+try:
+    ACCELERATOR_ERROR = torch.AcceleratorError
+except AttributeError:
+    ACCELERATOR_ERROR = RuntimeError
+
 def is_oom(e):
     if isinstance(e, OOM_EXCEPTION):
         return True
-    if isinstance(e, torch.AcceleratorError) and getattr(e, 'error_code', None) == 2:
+    if isinstance(e, ACCELERATOR_ERROR) and (getattr(e, 'error_code', None) == 2 or "out of memory" in str(e).lower()):
         discard_cuda_async_error()
         return True
     return False
@@ -1275,7 +1280,7 @@ def discard_cuda_async_error():
         b = torch.tensor([1], dtype=torch.uint8, device=get_torch_device())
         _ = a + b
         synchronize()
-    except torch.AcceleratorError:
+    except RuntimeError:
         #Dump it! We already know about it from the synchronous return
         pass