forked from extern/easydiffusion
Merge pull request #407 from madrang/beta
Wait until device is fully ready before proceeding.
This commit is contained in:
commit
d5a012d49f
@ -20,6 +20,8 @@ ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
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LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
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# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
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DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
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class SymbolClass(type): # Print nicely formatted Symbol names.
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def __repr__(self): return self.__qualname__
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def __str__(self): return self.__name__
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@ -240,9 +242,6 @@ def thread_get_next_task():
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def thread_render(device):
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global current_state, current_state_error, current_model_path
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from . import runtime
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weak_thread_data[threading.current_thread()] = {
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'device': device
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}
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try:
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runtime.device_init(device)
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except:
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@ -251,7 +250,7 @@ def thread_render(device):
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weak_thread_data[threading.current_thread()] = {
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'device': runtime.thread_data.device
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}
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if runtime.thread_data.device != 'cpu':
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if runtime.thread_data.device != 'cpu' or is_alive() == 1:
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preload_model()
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current_state = ServerStates.Online
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while True:
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@ -367,8 +366,8 @@ def start_render_thread(device='auto'):
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rthread.daemon = True
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rthread.name = THREAD_NAME_PREFIX + device
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rthread.start()
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timeout = LOCK_TIMEOUT
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while not rthread.is_alive():
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timeout = DEVICE_START_TIMEOUT
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while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
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if timeout <= 0: raise Exception('render_thread', rthread.name, 'failed to start before timeout or has crashed.')
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timeout -= 1
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time.sleep(1)
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59
ui/server.py
59
ui/server.py
@ -31,7 +31,6 @@ APP_CONFIG_DEFAULT_MODELS = [
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'sd-v1-4', # Default fallback.
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]
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import asyncio
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from fastapi import FastAPI, HTTPException
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from fastapi.staticfiles import StaticFiles
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from starlette.responses import FileResponse, JSONResponse, StreamingResponse
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@ -42,7 +41,6 @@ from typing import Any, Generator, Hashable, List, Optional, Union
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from sd_internal import Request, Response, task_manager
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LOOP = asyncio.get_event_loop()
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app = FastAPI()
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modifiers_cache = None
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@ -362,54 +360,37 @@ logging.getLogger('uvicorn.access').addFilter(LogSuppressFilter())
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config = getConfig()
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async def check_status(): # Task to Validate user config shortly after startup.
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# Check that the loaded config.json yielded a server in a known valid state.
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# When issues are found, try to fix them when possible and warn the user.
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device_count = 0
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# Wait for devices to register and/or change names.
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THREAD_START_DELAY = 5 # seconds - Give time for devices/threads to start.
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for i in range(10): # Maximum number of retry.
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await asyncio.sleep(THREAD_START_DELAY)
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new_count = task_manager.is_alive()
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# Stops retry once no more devices show up.
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if new_count > 0 and device_count == new_count: break
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device_count = new_count
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if 'render_devices' in config and task_manager.is_alive() <= 0: # No running devices, probably invalid user config. Try to apply defaults.
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print('WARNING: No active render devices after loading config. Validate "render_devices" in config.json')
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task_manager.start_render_thread('auto') # Detect best device for renders
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task_manager.start_render_thread('cpu') # Allow CPU to be used for renders
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await asyncio.sleep(THREAD_START_DELAY) # delay message after thread start.
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print('Default render devices loaded to replace missing render_devices', config['render_devices'])
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display_warning = False
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if not 'render_devices' in config and task_manager.is_alive(0) <= 0: # No config set, is on auto mode and without cuda:0
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task_manager.start_render_thread('cuda') # An other cuda device is better and cuda:0 is missing, start it...
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display_warning = True # And warn user to update settings...
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await asyncio.sleep(THREAD_START_DELAY) # delay message after thread start.
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if display_warning or task_manager.is_alive(0) <= 0:
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print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.')
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print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer')
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print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
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print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
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# Start the task_manager
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task_manager.default_model_to_load = resolve_model_to_use()
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if 'render_devices' in config: # Start a new thread for each device.
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if 'render_devices' in config: # Start a new thread for each device.
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if isinstance(config['render_devices'], str):
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config['render_devices'] = config['render_devices'].split(',')
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if not isinstance(config['render_devices'], list):
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raise Exception('Invalid render_devices value in config.')
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for device in config['render_devices']:
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task_manager.start_render_thread(device)
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else:
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if task_manager.is_alive() <= 0: # No running devices, probably invalid user config.
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print('WARNING: No active render devices after loading config. Validate "render_devices" in config.json')
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print('Loading default render devices to replace invalid render_devices field from config', config['render_devices'])
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display_warning = False
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if task_manager.is_alive() <= 0: # Either no defauls or no devices after loading config.
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# Select best GPU device using free memory, if more than one device.
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task_manager.start_render_thread('auto') # Detect best device for renders
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task_manager.start_render_thread('cpu') # Allow CPU to be used for renders
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if task_manager.is_alive(0) <= 0: # without cuda:0
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task_manager.start_render_thread('cuda') # An other cuda device is better and cuda:0 is missing, start it...
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display_warning = True # And warn user to update settings...
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if task_manager.is_alive('cpu') <= 0:
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# Allow CPU to be used for renders
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task_manager.start_render_thread('cpu')
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# Task to Validate user config shortly after startup.
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LOOP.create_task(check_status())
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if display_warning or task_manager.is_alive(0) <= 0:
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print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.')
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print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer')
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print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
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print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
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del display_warning
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# start the browser ui
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import webbrowser; webbrowser.open('http://localhost:9000')
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