extern/easydiffusion
1
0
Fork 1
mirror of https://github.com/easydiffusion/easydiffusion.git synced 2024-11-23 16:53:35 +01:00
Code Issues Packages Projects Releases Wiki Activity

Process GPU tasks on CPU when there are no cuda devices at all.

Browse Source
This commit is contained in:
Marc-Andre Ferland 2022-10-17 01:05:27 -04:00
parent d4a348a2b2
commit 012243a880
1 changed files with 21 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

29
ui/sd_internal/task_manager.py
View File

@ -157,7 +157,7 @@ class TaskCache():
finally:
self._lock.release()
manager_lock = threading.Lock()
manager_lock = threading.RLock()
render_threads = []
current_state = ServerStates.Init
current_state_error:Exception = None
@ -212,13 +212,26 @@ def thread_render(device):
continue
try: # Select a render task.
for queued_task in tasks_queue:
if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu':
continue # Cuda Tasks
if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu':
continue # CPU Tasks
if queued_task.request.use_face_correction and not runtime.is_first_cuda_device(runtime.thread_data.device):
if not runtime.thread_data.device == 'cpu' and is_alive(0) > 0: # Allows GFPGANer on cuda:0 and use cpu only when cuda:0 is not available.
continue #TODO Remove when fixed - A bug with GFPGANer and facexlib needs to be fixed before use on other devices.
cpu_alive = is_alive('cpu')
if queued_task.request.use_face_correction: #TODO Remove when fixed - A bug with GFPGANer and facexlib needs to be fixed before use on other devices.
# Allows GFPGANer on cuda:0 and use cpu only when cuda:0 is not available.
first_device_alive = True if is_alive(0) >= 1 else False
if cpu_alive <= 0 and not first_device_alive:
queued_task.request.use_face_correction = False
print('cuda:0 and cpu are not available with the current config. Removed GFPGANer filter to run task.')
continue
if not queued_task.request.use_cpu:
if first_device_alive:
if not runtime.is_first_cuda_device(runtime.thread_data.device):
continue # Wait for cuda:0
elif cpu_alive > 0:
print('cuda:0 is not available with the current config. Forcing task requiring GFPGANer to cpu.')
queued_task.request.use_cpu = True
continue
if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu' and cpu_alive > 0:
continue # CPU Tasks, Skip GPU device
if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu' and is_alive() > 1: # cpu is alive, so need more than one.
continue # GPU Tasks, don't run on CPU unless there is nothing else.
task = queued_task
break
if task is not None: