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"""
This file is the main thread that handles all gradio calls for major t2i or i2i processing.
Other gradio calls (like those from extensions) are not influenced.
By using one single thread to process all major calls, model moving is significantly faster.
"""
import threading
import time
import traceback
from modules.shared import cmd_opts
lock = threading.Lock()
last_id = 0
waiting_list = []
finished_list = []
fps = 1.0 / max(1, cmd_opts.fps)
class Task:
def __init__(self, task_id, func, args, kwargs):
self.task_id = task_id
self.func = func
self.args = args
self.kwargs = kwargs
self.result = None
def work(self):
self.result = self.func(*self.args, **self.kwargs)
def loop():
global lock, last_id, waiting_list, finished_list
while True:
time.sleep(fps)
if len(waiting_list) > 0:
with lock:
task = waiting_list.pop(0)
try:
task.work()
except Exception as e:
traceback.print_exc()
print(e)
with lock:
finished_list.append(task)
def async_run(func, *args, **kwargs):
global lock, last_id, waiting_list, finished_list
with lock:
last_id += 1
new_task = Task(task_id=last_id, func=func, args=args, kwargs=kwargs)
waiting_list.append(new_task)
return new_task.task_id
def run_and_wait_result(func, *args, **kwargs):
global lock, last_id, waiting_list, finished_list
current_id = async_run(func, *args, **kwargs)
while True:
time.sleep(fps)
finished_task = None
for t in finished_list.copy(): # thread safe shallow copy without needing a lock
if t.task_id == current_id:
finished_task = t
break
if finished_task is not None:
with lock:
finished_list.remove(finished_task)
return finished_task.result
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