Merge branch 'comfyanonymous:master' into master

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patientx 2025-05-21 14:40:30 +03:00 committed by GitHub
commit 9494f23ca5
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8 changed files with 92 additions and 11 deletions

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@ -0,0 +1,5 @@
from .torch_compile import set_torch_compile_wrapper
__all__ = [
"set_torch_compile_wrapper",
]

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@ -0,0 +1,69 @@
from __future__ import annotations
import torch
import comfy.utils
from comfy.patcher_extension import WrappersMP
from typing import TYPE_CHECKING, Callable, Optional
if TYPE_CHECKING:
from comfy.model_patcher import ModelPatcher
from comfy.patcher_extension import WrapperExecutor
COMPILE_KEY = "torch.compile"
TORCH_COMPILE_KWARGS = "torch_compile_kwargs"
def apply_torch_compile_factory(compiled_module_dict: dict[str, Callable]) -> Callable:
'''
Create a wrapper that will refer to the compiled_diffusion_model.
'''
def apply_torch_compile_wrapper(executor: WrapperExecutor, *args, **kwargs):
try:
orig_modules = {}
for key, value in compiled_module_dict.items():
orig_modules[key] = comfy.utils.get_attr(executor.class_obj, key)
comfy.utils.set_attr(executor.class_obj, key, value)
return executor(*args, **kwargs)
finally:
for key, value in orig_modules.items():
comfy.utils.set_attr(executor.class_obj, key, value)
return apply_torch_compile_wrapper
def set_torch_compile_wrapper(model: ModelPatcher, backend: str, options: Optional[dict[str,str]]=None,
mode: Optional[str]=None, fullgraph=False, dynamic: Optional[bool]=None,
keys: list[str]=["diffusion_model"], *args, **kwargs):
'''
Perform torch.compile that will be applied at sample time for either the whole model or specific params of the BaseModel instance.
When keys is None, it will default to using ["diffusion_model"], compiling the whole diffusion_model.
When a list of keys is provided, it will perform torch.compile on only the selected modules.
'''
# clear out any other torch.compile wrappers
model.remove_wrappers_with_key(WrappersMP.APPLY_MODEL, COMPILE_KEY)
# if no keys, default to 'diffusion_model'
if not keys:
keys = ["diffusion_model"]
# create kwargs dict that can be referenced later
compile_kwargs = {
"backend": backend,
"options": options,
"mode": mode,
"fullgraph": fullgraph,
"dynamic": dynamic,
}
# get a dict of compiled keys
compiled_modules = {}
for key in keys:
compiled_modules[key] = torch.compile(
model=model.get_model_object(key),
**compile_kwargs,
)
# add torch.compile wrapper
wrapper_func = apply_torch_compile_factory(
compiled_module_dict=compiled_modules,
)
# store wrapper to run on BaseModel's apply_model function
model.add_wrapper_with_key(WrappersMP.APPLY_MODEL, COMPILE_KEY, wrapper_func)
# keep compile kwargs for reference
model.model_options[TORCH_COMPILE_KWARGS] = compile_kwargs

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@ -1,4 +1,5 @@
import torch
from comfy_api.torch_helpers import set_torch_compile_wrapper
class TorchCompileModel:
@classmethod
@ -14,7 +15,7 @@ class TorchCompileModel:
def patch(self, model, backend):
m = model.clone()
m.add_object_patch("diffusion_model", torch.compile(model=m.get_model_object("diffusion_model"), backend=backend))
set_torch_compile_wrapper(model=m, backend=backend)
return (m, )
NODE_CLASS_MAPPINGS = {

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@ -1,3 +1,3 @@
# This file is automatically generated by the build process when version is
# updated in pyproject.toml.
__version__ = "0.3.34"
__version__ = "0.3.35"

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@ -909,7 +909,6 @@ class PromptQueue:
self.currently_running = {}
self.history = {}
self.flags = {}
server.prompt_queue = self
def put(self, item):
with self.mutex:
@ -954,6 +953,7 @@ class PromptQueue:
self.history[prompt[1]].update(history_result)
self.server.queue_updated()
# Note: slow
def get_current_queue(self):
with self.mutex:
out = []
@ -961,6 +961,13 @@ class PromptQueue:
out += [x]
return (out, copy.deepcopy(self.queue))
# read-safe as long as queue items are immutable
def get_current_queue_volatile(self):
with self.mutex:
running = [x for x in self.currently_running.values()]
queued = copy.copy(self.queue)
return (running, queued)
def get_tasks_remaining(self):
with self.mutex:
return len(self.queue) + len(self.currently_running)

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@ -260,7 +260,6 @@ def start_comfyui(asyncio_loop=None):
asyncio_loop = asyncio.new_event_loop()
asyncio.set_event_loop(asyncio_loop)
prompt_server = server.PromptServer(asyncio_loop)
q = execution.PromptQueue(prompt_server)
hook_breaker_ac10a0.save_functions()
nodes.init_extra_nodes(init_custom_nodes=not args.disable_all_custom_nodes, init_api_nodes=not args.disable_api_nodes)
@ -271,7 +270,7 @@ def start_comfyui(asyncio_loop=None):
prompt_server.add_routes()
hijack_progress(prompt_server)
threading.Thread(target=prompt_worker, daemon=True, args=(q, prompt_server,)).start()
threading.Thread(target=prompt_worker, daemon=True, args=(prompt_server.prompt_queue, prompt_server,)).start()
if args.quick_test_for_ci:
exit(0)

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@ -1,6 +1,6 @@
[project]
name = "ComfyUI"
version = "0.3.34"
version = "0.3.35"
readme = "README.md"
license = { file = "LICENSE" }
requires-python = ">=3.9"

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@ -29,6 +29,7 @@ import comfy.model_management
import node_helpers
from comfyui_version import __version__
from app.frontend_management import FrontendManager
from app.user_manager import UserManager
from app.model_manager import ModelFileManager
from app.custom_node_manager import CustomNodeManager
@ -159,7 +160,7 @@ class PromptServer():
self.custom_node_manager = CustomNodeManager()
self.internal_routes = InternalRoutes(self)
self.supports = ["custom_nodes_from_web"]
self.prompt_queue = None
self.prompt_queue = execution.PromptQueue(self)
self.loop = loop
self.messages = asyncio.Queue()
self.client_session:Optional[aiohttp.ClientSession] = None
@ -226,7 +227,7 @@ class PromptServer():
return response
@routes.get("/embeddings")
def get_embeddings(self):
def get_embeddings(request):
embeddings = folder_paths.get_filename_list("embeddings")
return web.json_response(list(map(lambda a: os.path.splitext(a)[0], embeddings)))
@ -282,7 +283,6 @@ class PromptServer():
a.update(f.read())
b.update(image.file.read())
image.file.seek(0)
f.close()
return a.hexdigest() == b.hexdigest()
return False
@ -621,7 +621,7 @@ class PromptServer():
@routes.get("/queue")
async def get_queue(request):
queue_info = {}
current_queue = self.prompt_queue.get_current_queue()
current_queue = self.prompt_queue.get_current_queue_volatile()
queue_info['queue_running'] = current_queue[0]
queue_info['queue_pending'] = current_queue[1]
return web.json_response(queue_info)