refactor: eliminate circular import by separating model management functions

- Create model_management_mgpu.py for centralized model lifecycle tracking
- Move memory management functions from device_utils.py to new module:
  * multigpu_memory_log, track_modelpatcher, trigger_executor_cache_reset
  * check_cpu_memory_threshold, prune_distorch_stores, try_malloc_trim
  * force_full_system_cleanup
- Update imports across codebase (distorch_2.py, distorch.py, __init__.py,
  nodes.py, checkpoint_multigpu.py)
- Resolves device_utils.py ↔ distorch_2.py circular dependency
- Follows established clean coding patterns with fail-fast error handling

Addresses critical CPU memory leak investigation infrastructure by ensuring
proper module separation for comprehensive memory management utilities.

nodes.py

@@ -2,7 +2,8 @@ import torch
 import folder_paths
 from pathlib import Path
 from nodes import NODE_CLASS_MAPPINGS
-from .device_utils import get_device_list, force_full_system_cleanup
+from .device_utils import get_device_list
+from .model_management_mgpu import force_full_system_cleanup
 
 class DeviceSelectorMultiGPU:
     @classmethod