refactor: simplify model retention logic in multi-GPU unload

- Renamed `keep_loaded` variable to `should_retain` for improved clarity
- Simplified assignment by directly retrieving `_mgpu_keep_loaded` attribute with default False
- Updated logging accordingly; may alter behavior for non-DisTorch models to no longer retain automatically

model_management_mgpu.py

@@ -395,14 +395,13 @@ if hasattr(mm, 'unload_all_models') and not hasattr(mm.unload_all_models, '_mgpu
             mp = lm.model  # weakref call to ModelPatcher
             if mp is not None and hasattr(mp, 'model'):
                 # Check if this is a DisTorch model with keep_loaded flag
-                keep_loaded = getattr(mp.model, '_mgpu_keep_loaded', False)
+                should_retain = getattr(mp.model, '_mgpu_keep_loaded', False)
                 model_name = type(getattr(mp, 'model', mp)).__name__
-                logger.mgpu_mm_log(f"[UNLOAD_DEBUG] Model {i}: {model_name}, keep_loaded={keep_loaded}")
+                logger.mgpu_mm_log(f"[UNLOAD_DEBUG] Model {i}: {model_name}, keep_loaded={should_retain}")
                 
                 # Retain models that either:
                 # 1. Are non-DisTorch models (missing _mgpu_keep_loaded attribute)
                 # 2. Are DisTorch models with keep_loaded=True
-                should_retain = not hasattr(mp.model, '_mgpu_keep_loaded') or keep_loaded
 
                 if should_retain:
                     kept_models.append(lm)