fix(backend): mps should not use non_blocking

We can get black outputs when moving tensors from CPU to MPS. It appears MPS to CPU is fine. See:
- https://github.com/pytorch/pytorch/issues/107455
- https://discuss.pytorch.org/t/should-we-set-non-blocking-to-true/38234/28

Changes:
- Add properties for each device on `TorchDevice` as a convenience.
- Add `get_non_blocking` static method on `TorchDevice`. This utility takes a torch device and returns the flag to be used for non_blocking when moving a tensor to the device provided.
- Update model patching and caching APIs to use this new utility.

Fixes: #6545

invokeai/backend/model_manager/load/model_cache/model_cache_default.py

@@ -285,9 +285,9 @@ class ModelCache(ModelCacheBase[AnyModel]):
                 else:
                     new_dict: Dict[str, torch.Tensor] = {}
                     for k, v in cache_entry.state_dict.items():
-                        new_dict[k] = v.to(torch.device(target_device), copy=True, non_blocking=True)
+                        new_dict[k] = v.to(target_device, copy=True, non_blocking=TorchDevice.get_non_blocking(target_device))
                     cache_entry.model.load_state_dict(new_dict, assign=True)
-            cache_entry.model.to(target_device, non_blocking=True)
+            cache_entry.model.to(target_device, non_blocking=TorchDevice.get_non_blocking(target_device))
             cache_entry.device = target_device
         except Exception as e:  # blow away cache entry
             self._delete_cache_entry(cache_entry)