extern/easydiffusion
1
0
Fork 1
mirror of https://github.com/easydiffusion/easydiffusion.git synced 2025-06-21 02:18:24 +02:00
Code Issues Packages Projects Releases Wiki Activity

Fixed stopping tasks and more cleaning.

Browse Source
This commit is contained in:
Marc-Andre Ferland 2022-10-21 22:45:19 -04:00
parent ce2b711b1f
commit 3b5f96a133
1 changed files with 49 additions and 46 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

93
ui/sd_internal/task_manager.py
View File

@ -193,6 +193,50 @@ def preload_model(file_path=None):
current_state = ServerStates.Unavailable
print(traceback.format_exc())
def thread_get_next_task():
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
print('Render thread on device', runtime.thread_data.device, 'failed to acquire manager lock.')
return None
if len(tasks_queue) <= 0:
manager_lock.release()
return None
from . import runtime
task = None
try: # Select a render task.
for queued_task in tasks_queue:
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.
if is_alive(0) <= 0: # Allows GFPGANer only on cuda:0.
queued_task.error = Exception('cuda:0 is not available with the current config. Remove GFPGANer filter to run task.')
task = queued_task
break
if queued_task.request.use_cpu:
queued_task.error = Exception('Cpu cannot be used to run this task. Remove GFPGANer filter to run task.')
task = queued_task
break
if not runtime.is_first_cuda_device(runtime.thread_data.device):
continue # Wait for cuda:0
if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu':
if is_alive('cpu') > 0:
continue # CPU Tasks, Skip GPU device
else:
queued_task.error = Exception('Cpu is not enabled in render_devices.')
task = queued_task
break
if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu':
if is_alive() > 1: # cpu is alive, so need more than one.
continue # GPU Tasks, don't run on CPU unless there is nothing else.
else:
queued_task.error = Exception('No active gpu found. Please check the error message in the command-line window at startup.')
task = queued_task
break
task = queued_task
break
if task is not None:
del tasks_queue[tasks_queue.index(task)]
return task
finally:
manager_lock.release()
def thread_render(device):
global current_state, current_state_error, current_model_path
from . import runtime
@ -215,48 +259,7 @@ def thread_render(device):
if isinstance(current_state_error, SystemExit):
current_state = ServerStates.Unavailable
return
task = None
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
print('Render thread on device', runtime.thread_data.device, 'failed to acquire manager lock.')
time.sleep(1)
continue
if len(tasks_queue) <= 0:
manager_lock.release()
time.sleep(1)
continue
try: # Select a render task.
for queued_task in tasks_queue:
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.
if is_alive(0) <= 0: # Allows GFPGANer only on cuda:0.
queued_task.error = Exception('cuda:0 is not available with the current config. Remove GFPGANer filter to run task.')
task = queued_task
continue
if queued_task.request.use_cpu:
queued_task.error = Exception('Cpu cannot be used to run this task. Remove GFPGANer filter to run task.')
task = queued_task
continue
if not runtime.is_first_cuda_device(runtime.thread_data.device):
continue # Wait for cuda:0
if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu':
if is_alive('cpu') > 0:
continue # CPU Tasks, Skip GPU device
else:
queued_task.error = Exception('Cpu is not enabled in render_devices.')
task = queued_task
continue
if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu':
if is_alive() > 1: # cpu is alive, so need more than one.
continue # GPU Tasks, don't run on CPU unless there is nothing else.
else:
queued_task.error = Exception('No active gpu found. Please check the error message in the command-line window at startup.')
task = queued_task
continue
task = queued_task
break
if task is not None:
del tasks_queue[tasks_queue.index(task)]
finally:
manager_lock.release()
task = thread_get_next_task()
if task is None:
time.sleep(1)
continue
@ -265,10 +268,10 @@ def thread_render(device):
task.response = {"status": 'failed', "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
continue
#if current_model_path != task.request.use_stable_diffusion_model:
# preload_model(task.request.use_stable_diffusion_model)
if current_state_error:
task.error = current_state_error
task.response = {"status": 'failed', "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
continue
print(f'Session {task.request.session_id} starting task {id(task)}')
if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
@ -288,7 +291,7 @@ def thread_render(device):
current_state = ServerStates.Rendering
current_model_path = task.request.use_stable_diffusion_model
if isinstance(current_state_error, SystemExit) or isinstance(current_state_error, StopAsyncIteration) or isinstance(task.error, StopAsyncIteration):
runtime.stop_processing = True
runtime.thread_data.stop_processing = True
if isinstance(current_state_error, StopAsyncIteration):
task.error = current_state_error
current_state_error = None