275 lines
9.7 KiB
Python
275 lines
9.7 KiB
Python
import comfy.options
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comfy.options.enable_args_parsing()
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import os
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import importlib.util
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import folder_paths
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import time
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from comfy.cli_args import args
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from app.logger import setup_logger
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setup_logger(verbose=args.verbose)
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def execute_prestartup_script():
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def execute_script(script_path):
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module_name = os.path.splitext(script_path)[0]
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try:
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spec = importlib.util.spec_from_file_location(module_name, script_path)
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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return True
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except Exception as e:
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print(f"Failed to execute startup-script: {script_path} / {e}")
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return False
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if args.disable_all_custom_nodes:
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return
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node_paths = folder_paths.get_folder_paths("custom_nodes")
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for custom_node_path in node_paths:
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possible_modules = os.listdir(custom_node_path)
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node_prestartup_times = []
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for possible_module in possible_modules:
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module_path = os.path.join(custom_node_path, possible_module)
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if os.path.isfile(module_path) or module_path.endswith(".disabled") or module_path == "__pycache__":
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continue
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script_path = os.path.join(module_path, "prestartup_script.py")
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if os.path.exists(script_path):
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time_before = time.perf_counter()
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success = execute_script(script_path)
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node_prestartup_times.append((time.perf_counter() - time_before, module_path, success))
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if len(node_prestartup_times) > 0:
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print("\nPrestartup times for custom nodes:")
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for n in sorted(node_prestartup_times):
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if n[2]:
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import_message = ""
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else:
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import_message = " (PRESTARTUP FAILED)"
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print("{:6.1f} seconds{}:".format(n[0], import_message), n[1])
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print()
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execute_prestartup_script()
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# Main code
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import asyncio
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import itertools
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import shutil
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import threading
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import gc
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import logging
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if os.name == "nt":
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logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
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if __name__ == "__main__":
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if args.cuda_device is not None:
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os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
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logging.info("Set cuda device to: {}".format(args.cuda_device))
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if args.deterministic:
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if 'CUBLAS_WORKSPACE_CONFIG' not in os.environ:
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os.environ['CUBLAS_WORKSPACE_CONFIG'] = ":4096:8"
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import cuda_malloc
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if args.windows_standalone_build:
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try:
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import fix_torch
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except:
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pass
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import comfy.utils
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import yaml
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import execution
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import server
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from server import BinaryEventTypes
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import nodes
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import comfy.model_management
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def cuda_malloc_warning():
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device = comfy.model_management.get_torch_device()
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device_name = comfy.model_management.get_torch_device_name(device)
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cuda_malloc_warning = False
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if "cudaMallocAsync" in device_name:
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for b in cuda_malloc.blacklist:
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if b in device_name:
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cuda_malloc_warning = True
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if cuda_malloc_warning:
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logging.warning("\nWARNING: this card most likely does not support cuda-malloc, if you get \"CUDA error\" please run ComfyUI with: --disable-cuda-malloc\n")
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def prompt_worker(q, server):
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e = execution.PromptExecutor(server, lru_size=args.cache_lru)
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last_gc_collect = 0
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need_gc = False
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gc_collect_interval = 10.0
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while True:
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timeout = 1000.0
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if need_gc:
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timeout = max(gc_collect_interval - (current_time - last_gc_collect), 0.0)
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queue_item = q.get(timeout=timeout)
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if queue_item is not None:
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item, item_id = queue_item
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execution_start_time = time.perf_counter()
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prompt_id = item[1]
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server.last_prompt_id = prompt_id
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e.execute(item[2], prompt_id, item[3], item[4])
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need_gc = True
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q.task_done(item_id,
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e.history_result,
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status=execution.PromptQueue.ExecutionStatus(
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status_str='success' if e.success else 'error',
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completed=e.success,
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messages=e.status_messages))
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if server.client_id is not None:
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server.send_sync("executing", { "node": None, "prompt_id": prompt_id }, server.client_id)
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current_time = time.perf_counter()
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execution_time = current_time - execution_start_time
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logging.info("Prompt executed in {:.2f} seconds".format(execution_time))
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flags = q.get_flags()
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free_memory = flags.get("free_memory", False)
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if flags.get("unload_models", free_memory):
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comfy.model_management.unload_all_models()
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need_gc = True
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last_gc_collect = 0
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if free_memory:
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e.reset()
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need_gc = True
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last_gc_collect = 0
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if need_gc:
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current_time = time.perf_counter()
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if (current_time - last_gc_collect) > gc_collect_interval:
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comfy.model_management.cleanup_models()
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gc.collect()
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comfy.model_management.soft_empty_cache()
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last_gc_collect = current_time
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need_gc = False
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async def run(server, address='', port=8188, verbose=True, call_on_start=None):
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await asyncio.gather(server.start(address, port, verbose, call_on_start), server.publish_loop())
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def hijack_progress(server):
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def hook(value, total, preview_image):
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comfy.model_management.throw_exception_if_processing_interrupted()
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progress = {"value": value, "max": total, "prompt_id": server.last_prompt_id, "node": server.last_node_id}
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server.send_sync("progress", progress, server.client_id)
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if preview_image is not None:
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server.send_sync(BinaryEventTypes.UNENCODED_PREVIEW_IMAGE, preview_image, server.client_id)
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comfy.utils.set_progress_bar_global_hook(hook)
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def cleanup_temp():
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temp_dir = folder_paths.get_temp_directory()
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if os.path.exists(temp_dir):
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shutil.rmtree(temp_dir, ignore_errors=True)
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def load_extra_path_config(yaml_path):
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with open(yaml_path, 'r') as stream:
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config = yaml.safe_load(stream)
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for c in config:
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conf = config[c]
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if conf is None:
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continue
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base_path = None
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if "base_path" in conf:
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base_path = conf.pop("base_path")
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for x in conf:
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for y in conf[x].split("\n"):
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if len(y) == 0:
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continue
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full_path = y
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if base_path is not None:
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full_path = os.path.join(base_path, full_path)
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logging.info("Adding extra search path {} {}".format(x, full_path))
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folder_paths.add_model_folder_path(x, full_path)
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if __name__ == "__main__":
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if args.temp_directory:
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temp_dir = os.path.join(os.path.abspath(args.temp_directory), "temp")
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logging.info(f"Setting temp directory to: {temp_dir}")
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folder_paths.set_temp_directory(temp_dir)
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cleanup_temp()
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if args.windows_standalone_build:
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try:
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import new_updater
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new_updater.update_windows_updater()
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except:
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pass
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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server = server.PromptServer(loop)
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q = execution.PromptQueue(server)
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extra_model_paths_config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "extra_model_paths.yaml")
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if os.path.isfile(extra_model_paths_config_path):
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load_extra_path_config(extra_model_paths_config_path)
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if args.extra_model_paths_config:
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for config_path in itertools.chain(*args.extra_model_paths_config):
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load_extra_path_config(config_path)
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nodes.init_extra_nodes(init_custom_nodes=not args.disable_all_custom_nodes)
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cuda_malloc_warning()
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server.add_routes()
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hijack_progress(server)
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threading.Thread(target=prompt_worker, daemon=True, args=(q, server,)).start()
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if args.output_directory:
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output_dir = os.path.abspath(args.output_directory)
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logging.info(f"Setting output directory to: {output_dir}")
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folder_paths.set_output_directory(output_dir)
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#These are the default folders that checkpoints, clip and vae models will be saved to when using CheckpointSave, etc.. nodes
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folder_paths.add_model_folder_path("checkpoints", os.path.join(folder_paths.get_output_directory(), "checkpoints"))
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folder_paths.add_model_folder_path("clip", os.path.join(folder_paths.get_output_directory(), "clip"))
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folder_paths.add_model_folder_path("vae", os.path.join(folder_paths.get_output_directory(), "vae"))
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folder_paths.add_model_folder_path("diffusion_models", os.path.join(folder_paths.get_output_directory(), "diffusion_models"))
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if args.input_directory:
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input_dir = os.path.abspath(args.input_directory)
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logging.info(f"Setting input directory to: {input_dir}")
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folder_paths.set_input_directory(input_dir)
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if args.quick_test_for_ci:
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exit(0)
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call_on_start = None
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if args.auto_launch:
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def startup_server(scheme, address, port):
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import webbrowser
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if os.name == 'nt' and address == '0.0.0.0':
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address = '127.0.0.1'
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webbrowser.open(f"{scheme}://{address}:{port}")
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call_on_start = startup_server
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try:
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loop.run_until_complete(server.setup())
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loop.run_until_complete(run(server, address=args.listen, port=args.port, verbose=not args.dont_print_server, call_on_start=call_on_start))
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except KeyboardInterrupt:
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logging.info("\nStopped server")
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cleanup_temp()
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