Improve RAM<->VRAM memory copy performance in LoRA patching and elsewhere (#6490)

* allow model patcher to optimize away the unpatching step when feasible

* remove lazy_offloading functionality

* allow model patcher to optimize away the unpatching step when feasible

* remove lazy_offloading functionality

* do not save original weights if there is a CPU copy of state dict

* Update invokeai/backend/model_manager/load/load_base.py

Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>

* documentation fixes requested during penultimate review

* add non-blocking=True parameters to several torch.nn.Module.to() calls, for slight performance increases

* fix ruff errors

* prevent crash on non-cuda-enabled systems

---------

Co-authored-by: Lincoln Stein <lstein@gmail.com>
Co-authored-by: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>
This commit is contained in:
Lincoln Stein
2024-06-13 13:10:03 -04:00
committed by GitHub
parent 568a4844f7
commit a3cb5da130
7 changed files with 84 additions and 38 deletions

View File

@ -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)
new_dict[k] = v.to(torch.device(target_device), copy=True, non_blocking=True)
cache_entry.model.load_state_dict(new_dict, assign=True)
cache_entry.model.to(target_device)
cache_entry.model.to(target_device, non_blocking=True)
cache_entry.device = target_device
except Exception as e: # blow away cache entry
self._delete_cache_entry(cache_entry)