Peyton DeNiro
3ec60ded7d
bootstrap_comfyui_runtime() now uses _load_module_temp() with temporary module names (_bootstrap_options, _bootstrap_cli_args, _bootstrap_cuda_malloc) instead of real module names. This prevents cached stale modules from sys.modules conflicting with ComfyUI's internal import chain (e.g. nodes.py -> comfy.sd -> comfy.model_management -> comfy.cli_args). Fixes the text-to-image runtime e2e failure: ImportError: cannot import name 'args' from 'comfy.cli_args'
378 lines
13 KiB
Python
378 lines
13 KiB
Python
# Imports
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import importlib.util
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import json
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import logging
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import os
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import random
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import sys
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from typing import Sequence, Mapping, Any, Union
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log = logging.getLogger(__name__)
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def _load_module(module_name: str, filepath: str) -> Any:
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"""Load a Python module from an explicit file path, bypassing sys.path.
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This eliminates ALL bare import shadowing attacks by loading modules
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from verified file paths instead of relying on sys.path resolution.
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"""
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if not os.path.isfile(filepath):
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log.debug("Module file not found: %s (%s)", module_name, filepath)
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return None
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try:
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spec = importlib.util.spec_from_file_location(module_name, filepath)
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if spec is None or spec.loader is None:
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log.debug("Could not create spec for %s at %s", module_name, filepath)
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return None
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mod = importlib.util.module_from_spec(spec)
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sys.modules[module_name] = mod
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spec.loader.exec_module(mod)
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return mod
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except Exception as e:
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log.debug("Failed to load %s from %s: %s", module_name, filepath, e)
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return None
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def _load_module_temp(module_name: str, filepath: str) -> Any:
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"""Load a module via _load_module() then remove it from sys.modules.
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Used during bootstrap for modules that ComfyUI's import chain also loads
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normally — prevents the cached copy from conflicting with later imports.
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"""
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mod = _load_module(module_name, filepath)
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sys.modules.pop(module_name, None)
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return mod
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def _is_comfyui_directory(path: str) -> bool:
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"""Verify a directory has ComfyUI structural markers (nodes.py)."""
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if not os.path.isdir(path):
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return False
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return os.path.isfile(os.path.join(path, "nodes.py"))
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def _find_from_extension_location() -> str | None:
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"""Walk up from this file's location to find ComfyUI root."""
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ext_dir = os.path.dirname(os.path.realpath(__file__))
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candidate = ext_dir
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for _ in range(10):
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parent = os.path.dirname(candidate)
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if parent == candidate:
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break
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candidate = parent
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if os.path.basename(candidate) == "ComfyUI":
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if _is_comfyui_directory(candidate):
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return candidate
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return None
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def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
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"""Return a sequence or mapping result item by index."""
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try:
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return obj[index]
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except KeyError:
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return obj["result"][index]
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def get_comfyui_path() -> str | None:
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"""Resolve ComfyUI path via prioritized multi-strategy fallback.
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Strategy order:
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1. COMFYUI_PATH env var (verified with _is_comfyui_directory)
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2. Relative walk from extension location (realpath + verified)
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3. CWD walk (legacy fallback, depth-limited)
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"""
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p = os.environ.get("COMFYUI_PATH")
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if p and _is_comfyui_directory(p):
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return p
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p = _find_from_extension_location()
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if p:
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return p
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return find_path("ComfyUI", max_depth=20)
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def find_path(name: str, max_depth: int = 20) -> str | None:
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"""Iteratively walk up from CWD to find a directory by name.
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Depth-limited to prevent slow startup on deep trees.
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Each candidate verified by _is_comfyui_directory() at the caller.
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"""
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candidate = os.getcwd()
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for _ in range(max_depth):
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parent = os.path.dirname(candidate)
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if parent == candidate:
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break
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candidate = parent
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if os.path.basename(candidate) == name:
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return candidate
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return None
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def add_comfyui_directory_to_sys_path() -> None:
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"""Add the ComfyUI checkout to sys.path (idempotent — insert-once, no gap)."""
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comfyui_path = get_comfyui_path()
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if comfyui_path is not None and os.path.isdir(comfyui_path):
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if comfyui_path not in sys.path:
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sys.path.insert(0, comfyui_path)
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log.debug("Added %s to sys.path", comfyui_path)
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def add_extra_model_paths() -> None:
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"""Load ComfyUI extra model paths configuration when available."""
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comfyui_path = get_comfyui_path()
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if comfyui_path is None:
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log.debug("Cannot load extra model paths: ComfyUI path not found")
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return
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# Try main.py first, then utils/extra_config.py — both via _load_module()
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main_mod = _load_module("comfy_main", os.path.join(comfyui_path, "main.py"))
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if main_mod is not None and hasattr(main_mod, "load_extra_path_config"):
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load_extra_path_config = getattr(main_mod, "load_extra_path_config")
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else:
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log.debug("main.py not available, trying utils/extra_config.py")
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extra_config_mod = _load_module(
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"extra_config", os.path.join(comfyui_path, "utils", "extra_config.py")
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)
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if extra_config_mod is None or not hasattr(
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extra_config_mod, "load_extra_path_config"
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):
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log.debug("Could not find load_extra_path_config in either path")
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return
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load_extra_path_config = getattr(extra_config_mod, "load_extra_path_config")
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extra_model_paths = find_path("extra_model_paths.yaml")
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if extra_model_paths is not None:
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load_extra_path_config(extra_model_paths)
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else:
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log.debug("Could not find the extra_model_paths config file.")
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def bootstrap_comfyui_runtime() -> None:
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"""Mirror the allocator-related ComfyUI startup steps before torch import."""
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add_comfyui_directory_to_sys_path()
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comfyui_path = get_comfyui_path()
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if comfyui_path is None:
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log.debug("bootstrap_comfyui_runtime: ComfyUI path not found")
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return
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# Use _load_module for file-based isolation, but with temporary names so
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# the modules are removed from sys.modules after reading values.
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# This prevents conflicts when ComfyUI's internal import chain (e.g.
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# nodes.py -> comfy.cli_args) later loads these modules normally.
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options_mod = _load_module_temp(
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"_bootstrap_options", os.path.join(comfyui_path, "comfy", "options.py")
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)
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if options_mod is not None:
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options_mod.enable_args_parsing()
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cli_args_mod = _load_module_temp(
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"_bootstrap_cli_args", os.path.join(comfyui_path, "comfy", "cli_args.py")
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)
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args = getattr(cli_args_mod, "args", None) if cli_args_mod else None
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if args is None:
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return
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if os.name == "nt":
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os.environ["MIMALLOC_PURGE_DELAY"] = "0"
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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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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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if args.deterministic and "CUBLAS_WORKSPACE_CONFIG" not in os.environ:
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os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8"
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cuda_malloc_mod = _load_module_temp(
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"_bootstrap_cuda_malloc", os.path.join(comfyui_path, "cuda_malloc.py")
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)
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if (
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cuda_malloc_mod is not None
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and hasattr(cuda_malloc_mod, "get_torch_version_noimport")
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and "rocm" in cuda_malloc_mod.get_torch_version_noimport()
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):
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os.environ["OCL_SET_SVM_SIZE"] = "262144"
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def cleanup_comfyui_runtime(unload_models: bool | None = None) -> None:
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"""Best-effort cleanup for embedded or repeated generated-script execution."""
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import gc
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def run_cleanup_hook(name: str, should_run: bool = True) -> None:
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if not should_run or not hasattr(model_management, name):
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return
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cleanup_fn = getattr(model_management, name)
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try:
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cleanup_fn()
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except Exception as exc:
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warnings.warn(
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f"ComfyUI cleanup hook {name} failed during teardown: {exc}",
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RuntimeWarning,
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stacklevel=2,
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)
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should_unload = unload_models
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if should_unload is None:
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should_unload = os.environ.get(
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"COMFYUI_TOPYTHON_UNLOAD_MODELS", ""
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).lower() in {
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"1",
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"true",
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"yes",
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"on",
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}
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try:
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import comfy.model_management as model_management
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except ModuleNotFoundError:
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gc.collect()
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return
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run_cleanup_hook("cleanup_models_gc")
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run_cleanup_hook("unload_all_models", should_run=should_unload)
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run_cleanup_hook("soft_empty_cache")
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gc.collect()
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# Workflow data
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def build_workflow() -> dict[str, Any]:
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return {
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"1": {
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"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors"},
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},
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"2": {
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"class_type": "CLIPTextEncode",
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"inputs": {
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"text": "a small cottage in a meadow, soft daylight",
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"clip": ["1", 1],
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},
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},
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"3": {
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"class_type": "CLIPTextEncode",
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"inputs": {"text": "blurry, low quality", "clip": ["1", 1]},
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},
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"4": {
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"class_type": "EmptyLatentImage",
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"inputs": {"width": 512, "height": 512, "batch_size": 1},
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},
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"5": {
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"class_type": "KSampler",
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"inputs": {
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"seed": 1,
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"steps": 4,
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"cfg": 7,
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"sampler_name": "euler",
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"scheduler": "normal",
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"denoise": 1,
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"model": ["1", 0],
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"positive": ["2", 0],
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"negative": ["3", 0],
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"latent_image": ["4", 0],
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},
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},
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"6": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["5", 0], "vae": ["1", 2]},
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},
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"7": {
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"class_type": "SaveImage",
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"inputs": {"filename_prefix": "E2E_text_to_image", "images": ["6", 0]},
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},
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}
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def build_extra_pnginfo() -> dict[str, Any] | None:
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return None
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workflow = build_workflow()
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prompt = json.loads(json.dumps(workflow))
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extra_pnginfo = build_extra_pnginfo()
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# Workflow execution
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def main(unload_models: bool | None = None):
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bootstrap_comfyui_runtime()
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add_extra_model_paths()
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# Node imports
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from nodes import (
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CLIPTextEncode,
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CheckpointLoaderSimple,
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EmptyLatentImage,
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KSampler,
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NODE_CLASS_MAPPINGS,
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SaveImage,
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VAEDecode,
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)
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import torch
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try:
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with torch.inference_mode():
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checkpointloadersimple = CheckpointLoaderSimple()
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checkpointloadersimple_1 = checkpointloadersimple.load_checkpoint(
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ckpt_name="v1-5-pruned-emaonly-fp16.safetensors"
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)
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cliptextencode = CLIPTextEncode()
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cliptextencode_2 = cliptextencode.encode(
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text="a small cottage in a meadow, soft daylight",
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clip=get_value_at_index(checkpointloadersimple_1, 1),
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)
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cliptextencode_3 = cliptextencode.encode(
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text="blurry, low quality",
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clip=get_value_at_index(checkpointloadersimple_1, 1),
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)
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emptylatentimage = EmptyLatentImage()
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emptylatentimage_4 = emptylatentimage.generate(
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width=512, height=512, batch_size=1
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)
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ksampler = KSampler()
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vaedecode = VAEDecode()
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saveimage = SaveImage()
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for q in range(1):
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node_5_seed = prompt["5"]["inputs"]["seed"] = random.randint(1, 2**64)
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ksampler_5 = ksampler.sample(
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seed=node_5_seed,
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steps=4,
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cfg=7,
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sampler_name="euler",
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scheduler="normal",
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denoise=1,
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model=get_value_at_index(checkpointloadersimple_1, 0),
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positive=get_value_at_index(cliptextencode_2, 0),
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negative=get_value_at_index(cliptextencode_3, 0),
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latent_image=get_value_at_index(emptylatentimage_4, 0),
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)
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vaedecode_6 = vaedecode.decode(
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samples=get_value_at_index(ksampler_5, 0),
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vae=get_value_at_index(checkpointloadersimple_1, 2),
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)
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saveimage_7 = saveimage.save_images(
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filename_prefix="E2E_text_to_image",
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images=get_value_at_index(vaedecode_6, 0),
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prompt=prompt,
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extra_pnginfo=extra_pnginfo,
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)
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finally:
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cleanup_comfyui_runtime(unload_models=unload_models)
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# Entrypoint
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if __name__ == "__main__":
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main()
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