mirror of
https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2025-12-08 21:44:33 +08:00
* execution: Roll the UI cache into the outputs Currently the UI cache is parallel to the output cache with expectations of being a content superset of the output cache. At the same time the UI and output cache are maintained completely seperately, making it awkward to free the output cache content without changing the behaviour of the UI cache. There are two actual users (getters) of the UI cache. The first is the case of a direct content hit on the output cache when executing a node. This case is very naturally handled by merging the UI and outputs cache. The second case is the history JSON generation at the end of the prompt. This currently works by asking the cache for all_node_ids and then pulling the cache contents for those nodes. all_node_ids is the nodes of the dynamic prompt. So fold the UI cache into the output cache. The current UI cache setter now writes to a prompt-scope dict. When the output cache is set, just get this value from the dict and tuple up with the outputs. When generating the history, simply iterate prompt-scope dict. This prepares support for more complex caching strategies (like RAM pressure caching) where less than 1 workflow will be cached and it will be desirable to keep the UI cache and output cache in sync. * sd: Implement RAM getter for VAE * model_patcher: Implement RAM getter for ModelPatcher * sd: Implement RAM getter for CLIP * Implement RAM Pressure cache Implement a cache sensitive to RAM pressure. When RAM headroom drops down below a certain threshold, evict RAM-expensive nodes from the cache. Models and tensors are measured directly for RAM usage. An OOM score is then computed based on the RAM usage of the node. Note the due to indirection through shared objects (like a model patcher), multiple nodes can account the same RAM as their individual usage. The intent is this will free chains of nodes particularly model loaders and associate loras as they all score similar and are sorted in close to each other. Has a bias towards unloading model nodes mid flow while being able to keep results like text encodings and VAE. * execution: Convert the cache entry to NamedTuple As commented in review. Convert this to a named tuple and abstract away the tuple type completely from graph.py.
381 lines
15 KiB
Python
381 lines
15 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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import itertools
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import utils.extra_config
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import logging
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import sys
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from comfy_execution.progress import get_progress_state
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from comfy_execution.utils import get_executing_context
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from comfy_api import feature_flags
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if __name__ == "__main__":
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#NOTE: These do not do anything on core ComfyUI, they are for custom nodes.
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os.environ['HF_HUB_DISABLE_TELEMETRY'] = '1'
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os.environ['DO_NOT_TRACK'] = '1'
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setup_logger(log_level=args.verbose, use_stdout=args.log_stdout)
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def apply_custom_paths():
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# extra model paths
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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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utils.extra_config.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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utils.extra_config.load_extra_path_config(config_path)
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# --output-directory, --input-directory, --user-directory
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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",
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os.path.join(folder_paths.get_output_directory(), "diffusion_models"))
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folder_paths.add_model_folder_path("loras", os.path.join(folder_paths.get_output_directory(), "loras"))
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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.user_directory:
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user_dir = os.path.abspath(args.user_directory)
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logging.info(f"Setting user directory to: {user_dir}")
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folder_paths.set_user_directory(user_dir)
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def execute_prestartup_script():
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if args.disable_all_custom_nodes and len(args.whitelist_custom_nodes) == 0:
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return
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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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logging.error(f"Failed to execute startup-script: {script_path} / {e}")
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return False
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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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if args.disable_all_custom_nodes and possible_module not in args.whitelist_custom_nodes:
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logging.info(f"Prestartup Skipping {possible_module} due to disable_all_custom_nodes and whitelist_custom_nodes")
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continue
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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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logging.info("\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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logging.info("{:6.1f} seconds{}: {}".format(n[0], import_message, n[1]))
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logging.info("")
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apply_custom_paths()
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execute_prestartup_script()
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# Main code
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import asyncio
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import shutil
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import threading
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import gc
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if os.name == "nt":
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os.environ['MIMALLOC_PURGE_DELAY'] = '0'
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if __name__ == "__main__":
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os.environ['TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL'] = '1'
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if args.default_device is not None:
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default_dev = args.default_device
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devices = list(range(32))
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devices.remove(default_dev)
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devices.insert(0, default_dev)
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devices = ','.join(map(str, devices))
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os.environ['CUDA_VISIBLE_DEVICES'] = str(devices)
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os.environ['HIP_VISIBLE_DEVICES'] = str(devices)
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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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os.environ['HIP_VISIBLE_DEVICES'] = str(args.cuda_device)
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os.environ["ASCEND_RT_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.oneapi_device_selector is not None:
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os.environ['ONEAPI_DEVICE_SELECTOR'] = args.oneapi_device_selector
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logging.info("Set oneapi device selector to: {}".format(args.oneapi_device_selector))
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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 'torch' in sys.modules:
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logging.warning("WARNING: Potential Error in code: Torch already imported, torch should never be imported before this point.")
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import comfy.utils
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import execution
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import server
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from protocol import BinaryEventTypes
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import nodes
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import comfy.model_management
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import comfyui_version
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import app.logger
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import hook_breaker_ac10a0
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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_instance):
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current_time: float = 0.0
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cache_type = execution.CacheType.CLASSIC
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if args.cache_lru > 0:
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cache_type = execution.CacheType.LRU
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elif args.cache_ram > 0:
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cache_type = execution.CacheType.RAM_PRESSURE
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elif args.cache_none:
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cache_type = execution.CacheType.NONE
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e = execution.PromptExecutor(server_instance, cache_type=cache_type, cache_args={ "lru" : args.cache_lru, "ram" : args.cache_ram } )
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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_instance.last_prompt_id = prompt_id
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sensitive = item[5]
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extra_data = item[3].copy()
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for k in sensitive:
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extra_data[k] = sensitive[k]
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e.execute(item[2], prompt_id, extra_data, item[4])
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need_gc = True
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remove_sensitive = lambda prompt: prompt[:5] + prompt[6:]
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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), process_item=remove_sensitive)
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if server_instance.client_id is not None:
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server_instance.send_sync("executing", {"node": None, "prompt_id": prompt_id}, server_instance.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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# Log Time in a more readable way after 10 minutes
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if execution_time > 600:
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execution_time = time.strftime("%H:%M:%S", time.gmtime(execution_time))
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logging.info(f"Prompt executed in {execution_time}")
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else:
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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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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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hook_breaker_ac10a0.restore_functions()
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async def run(server_instance, address='', port=8188, verbose=True, call_on_start=None):
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addresses = []
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for addr in address.split(","):
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addresses.append((addr, port))
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await asyncio.gather(
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server_instance.start_multi_address(addresses, call_on_start, verbose), server_instance.publish_loop()
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)
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def hijack_progress(server_instance):
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def hook(value, total, preview_image, prompt_id=None, node_id=None):
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executing_context = get_executing_context()
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if prompt_id is None and executing_context is not None:
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prompt_id = executing_context.prompt_id
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if node_id is None and executing_context is not None:
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node_id = executing_context.node_id
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comfy.model_management.throw_exception_if_processing_interrupted()
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if prompt_id is None:
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prompt_id = server_instance.last_prompt_id
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if node_id is None:
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node_id = server_instance.last_node_id
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progress = {"value": value, "max": total, "prompt_id": prompt_id, "node": node_id}
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get_progress_state().update_progress(node_id, value, total, preview_image)
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server_instance.send_sync("progress", progress, server_instance.client_id)
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if preview_image is not None:
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# Only send old method if client doesn't support preview metadata
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if not feature_flags.supports_feature(
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server_instance.sockets_metadata,
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server_instance.client_id,
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"supports_preview_metadata",
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):
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server_instance.send_sync(
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BinaryEventTypes.UNENCODED_PREVIEW_IMAGE,
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preview_image,
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server_instance.client_id,
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)
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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 setup_database():
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try:
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from app.database.db import init_db, dependencies_available
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if dependencies_available():
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init_db()
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except Exception as e:
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logging.error(f"Failed to initialize database. Please ensure you have installed the latest requirements. If the error persists, please report this as in future the database will be required: {e}")
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def start_comfyui(asyncio_loop=None):
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"""
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Starts the ComfyUI server using the provided asyncio event loop or creates a new one.
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Returns the event loop, server instance, and a function to start the server asynchronously.
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"""
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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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if not asyncio_loop:
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asyncio_loop = asyncio.new_event_loop()
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asyncio.set_event_loop(asyncio_loop)
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prompt_server = server.PromptServer(asyncio_loop)
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hook_breaker_ac10a0.save_functions()
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asyncio_loop.run_until_complete(nodes.init_extra_nodes(
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init_custom_nodes=(not args.disable_all_custom_nodes) or len(args.whitelist_custom_nodes) > 0,
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init_api_nodes=not args.disable_api_nodes
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))
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hook_breaker_ac10a0.restore_functions()
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cuda_malloc_warning()
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setup_database()
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prompt_server.add_routes()
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hijack_progress(prompt_server)
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threading.Thread(target=prompt_worker, daemon=True, args=(prompt_server.prompt_queue, prompt_server,)).start()
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if args.quick_test_for_ci:
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exit(0)
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os.makedirs(folder_paths.get_temp_directory(), exist_ok=True)
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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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if ':' in address:
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address = "[{}]".format(address)
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webbrowser.open(f"{scheme}://{address}:{port}")
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call_on_start = startup_server
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async def start_all():
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await prompt_server.setup()
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await run(prompt_server, address=args.listen, port=args.port, verbose=not args.dont_print_server, call_on_start=call_on_start)
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# Returning these so that other code can integrate with the ComfyUI loop and server
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return asyncio_loop, prompt_server, start_all
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if __name__ == "__main__":
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# Running directly, just start ComfyUI.
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logging.info("Python version: {}".format(sys.version))
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logging.info("ComfyUI version: {}".format(comfyui_version.__version__))
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if sys.version_info.major == 3 and sys.version_info.minor < 10:
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logging.warning("WARNING: You are using a python version older than 3.10, please upgrade to a newer one. 3.12 and above is recommended.")
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event_loop, _, start_all_func = start_comfyui()
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try:
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x = start_all_func()
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app.logger.print_startup_warnings()
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event_loop.run_until_complete(x)
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except KeyboardInterrupt:
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logging.info("\nStopped server")
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cleanup_temp()
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