mirror of
https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2026-11-12 03:20:03 +08:00
Merge remote-tracking branch 'upstream/master' into pr
This commit is contained in:
commit
ff3e6f26cf
@ -7,16 +7,15 @@ import shutil
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from aiohttp import web
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from aiohttp import web
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from urllib import parse
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from urllib import parse
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from comfy.cli_args import args
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from comfy.cli_args import args
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from folder_paths import user_directory
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import folder_paths
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from .app_settings import AppSettings
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from .app_settings import AppSettings
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default_user = "default"
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default_user = "default"
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users_file = os.path.join(user_directory, "users.json")
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class UserManager():
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class UserManager():
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def __init__(self):
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def __init__(self):
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global user_directory
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user_directory = folder_paths.get_user_directory()
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self.settings = AppSettings(self)
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self.settings = AppSettings(self)
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if not os.path.exists(user_directory):
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if not os.path.exists(user_directory):
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@ -26,14 +25,17 @@ class UserManager():
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print("****** For multi-user setups add the --multi-user CLI argument to enable multiple user profiles. ******")
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print("****** For multi-user setups add the --multi-user CLI argument to enable multiple user profiles. ******")
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if args.multi_user:
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if args.multi_user:
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if os.path.isfile(users_file):
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if os.path.isfile(self.get_users_file()):
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with open(users_file) as f:
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with open(self.get_users_file()) as f:
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self.users = json.load(f)
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self.users = json.load(f)
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else:
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else:
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self.users = {}
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self.users = {}
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else:
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else:
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self.users = {"default": "default"}
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self.users = {"default": "default"}
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def get_users_file(self):
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return os.path.join(folder_paths.get_user_directory(), "users.json")
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def get_request_user_id(self, request):
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def get_request_user_id(self, request):
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user = "default"
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user = "default"
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if args.multi_user and "comfy-user" in request.headers:
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if args.multi_user and "comfy-user" in request.headers:
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@ -45,7 +47,7 @@ class UserManager():
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return user
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return user
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def get_request_user_filepath(self, request, file, type="userdata", create_dir=True):
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def get_request_user_filepath(self, request, file, type="userdata", create_dir=True):
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global user_directory
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user_directory = folder_paths.get_user_directory()
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if type == "userdata":
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if type == "userdata":
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root_dir = user_directory
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root_dir = user_directory
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@ -85,8 +87,7 @@ class UserManager():
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self.users[user_id] = name
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self.users[user_id] = name
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global users_file
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with open(self.get_users_file(), "w") as f:
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with open(users_file, "w") as f:
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json.dump(self.users, f)
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json.dump(self.users, f)
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return user_id
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return user_id
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@ -119,23 +120,44 @@ class UserManager():
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async def listuserdata(request):
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async def listuserdata(request):
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directory = request.rel_url.query.get('dir', '')
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directory = request.rel_url.query.get('dir', '')
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if not directory:
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if not directory:
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return web.Response(status=400)
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return web.Response(status=400, text="Directory not provided")
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path = self.get_request_user_filepath(request, directory)
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path = self.get_request_user_filepath(request, directory)
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if not path:
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if not path:
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return web.Response(status=403)
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return web.Response(status=403, text="Invalid directory")
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if not os.path.exists(path):
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if not os.path.exists(path):
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return web.Response(status=404)
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return web.Response(status=404, text="Directory not found")
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recurse = request.rel_url.query.get('recurse', '').lower() == "true"
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recurse = request.rel_url.query.get('recurse', '').lower() == "true"
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results = glob.glob(os.path.join(
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full_info = request.rel_url.query.get('full_info', '').lower() == "true"
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glob.escape(path), '**/*'), recursive=recurse)
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results = [os.path.relpath(x, path) for x in results if os.path.isfile(x)]
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# Use different patterns based on whether we're recursing or not
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if recurse:
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pattern = os.path.join(glob.escape(path), '**', '*')
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else:
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pattern = os.path.join(glob.escape(path), '*')
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results = glob.glob(pattern, recursive=recurse)
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if full_info:
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results = [
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{
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'path': os.path.relpath(x, path).replace(os.sep, '/'),
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'size': os.path.getsize(x),
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'modified': os.path.getmtime(x)
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} for x in results if os.path.isfile(x)
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]
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else:
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results = [
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os.path.relpath(x, path).replace(os.sep, '/')
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for x in results
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if os.path.isfile(x)
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]
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split_path = request.rel_url.query.get('split', '').lower() == "true"
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split_path = request.rel_url.query.get('split', '').lower() == "true"
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if split_path:
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if split_path and not full_info:
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results = [[x] + x.split(os.sep) for x in results]
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results = [[x] + x.split('/') for x in results]
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return web.json_response(results)
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return web.json_response(results)
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@ -6,6 +6,7 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT):
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def __init__(
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def __init__(
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self,
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self,
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num_blocks = None,
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num_blocks = None,
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control_latent_channels = None,
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dtype = None,
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dtype = None,
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device = None,
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device = None,
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operations = None,
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operations = None,
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@ -17,10 +18,13 @@ class ControlNet(comfy.ldm.modules.diffusionmodules.mmdit.MMDiT):
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for _ in range(len(self.joint_blocks)):
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for _ in range(len(self.joint_blocks)):
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self.controlnet_blocks.append(operations.Linear(self.hidden_size, self.hidden_size, device=device, dtype=dtype))
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self.controlnet_blocks.append(operations.Linear(self.hidden_size, self.hidden_size, device=device, dtype=dtype))
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if control_latent_channels is None:
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control_latent_channels = self.in_channels
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self.pos_embed_input = comfy.ldm.modules.diffusionmodules.mmdit.PatchEmbed(
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self.pos_embed_input = comfy.ldm.modules.diffusionmodules.mmdit.PatchEmbed(
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None,
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None,
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self.patch_size,
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self.patch_size,
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self.in_channels,
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control_latent_channels,
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self.hidden_size,
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self.hidden_size,
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bias=True,
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bias=True,
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strict_img_size=False,
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strict_img_size=False,
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@ -171,6 +171,8 @@ parser.add_argument(
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help="The local filesystem path to the directory where the frontend is located. Overrides --front-end-version.",
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help="The local filesystem path to the directory where the frontend is located. Overrides --front-end-version.",
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)
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)
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parser.add_argument("--user-directory", type=is_valid_directory, default=None, help="Set the ComfyUI user directory with an absolute path.")
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if comfy.options.args_parsing:
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if comfy.options.args_parsing:
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args = parser.parse_args()
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args = parser.parse_args()
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else:
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else:
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@ -79,13 +79,19 @@ class ControlBase:
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self.previous_controlnet = None
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self.previous_controlnet = None
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self.extra_conds = []
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self.extra_conds = []
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self.strength_type = StrengthType.CONSTANT
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self.strength_type = StrengthType.CONSTANT
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self.concat_mask = False
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self.extra_concat_orig = []
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self.extra_concat = None
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def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None):
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def set_cond_hint(self, cond_hint, strength=1.0, timestep_percent_range=(0.0, 1.0), vae=None, extra_concat=[]):
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self.cond_hint_original = cond_hint
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self.cond_hint_original = cond_hint
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self.strength = strength
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self.strength = strength
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self.timestep_percent_range = timestep_percent_range
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self.timestep_percent_range = timestep_percent_range
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if self.latent_format is not None:
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if self.latent_format is not None:
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self.vae = vae
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self.vae = vae
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self.extra_concat_orig = extra_concat.copy()
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if self.concat_mask and len(self.extra_concat_orig) == 0:
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self.extra_concat_orig.append(torch.tensor([[[[1.0]]]]))
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return self
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return self
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def pre_run(self, model, percent_to_timestep_function):
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def pre_run(self, model, percent_to_timestep_function):
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@ -100,9 +106,9 @@ class ControlBase:
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def cleanup(self):
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def cleanup(self):
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if self.previous_controlnet is not None:
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if self.previous_controlnet is not None:
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self.previous_controlnet.cleanup()
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self.previous_controlnet.cleanup()
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if self.cond_hint is not None:
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del self.cond_hint
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self.cond_hint = None
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self.cond_hint = None
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self.extra_concat = None
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self.timestep_range = None
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self.timestep_range = None
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def get_models(self):
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def get_models(self):
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@ -123,6 +129,8 @@ class ControlBase:
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c.vae = self.vae
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c.vae = self.vae
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c.extra_conds = self.extra_conds.copy()
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c.extra_conds = self.extra_conds.copy()
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c.strength_type = self.strength_type
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c.strength_type = self.strength_type
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c.concat_mask = self.concat_mask
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c.extra_concat_orig = self.extra_concat_orig.copy()
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|
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def inference_memory_requirements(self, dtype):
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def inference_memory_requirements(self, dtype):
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if self.previous_controlnet is not None:
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if self.previous_controlnet is not None:
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@ -175,7 +183,7 @@ class ControlBase:
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|
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|
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class ControlNet(ControlBase):
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class ControlNet(ControlBase):
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def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, latent_format=None, device=None, load_device=None, manual_cast_dtype=None, extra_conds=["y"], strength_type=StrengthType.CONSTANT):
|
def __init__(self, control_model=None, global_average_pooling=False, compression_ratio=8, latent_format=None, device=None, load_device=None, manual_cast_dtype=None, extra_conds=["y"], strength_type=StrengthType.CONSTANT, concat_mask=False):
|
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super().__init__(device)
|
super().__init__(device)
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self.control_model = control_model
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self.control_model = control_model
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self.load_device = load_device
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self.load_device = load_device
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@ -189,6 +197,7 @@ class ControlNet(ControlBase):
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self.latent_format = latent_format
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self.latent_format = latent_format
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self.extra_conds += extra_conds
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self.extra_conds += extra_conds
|
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self.strength_type = strength_type
|
self.strength_type = strength_type
|
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|
self.concat_mask = concat_mask
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|
|
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def get_control(self, x_noisy, t, cond, batched_number):
|
def get_control(self, x_noisy, t, cond, batched_number):
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control_prev = None
|
control_prev = None
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@ -220,6 +229,13 @@ class ControlNet(ControlBase):
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comfy.model_management.load_models_gpu(loaded_models)
|
comfy.model_management.load_models_gpu(loaded_models)
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if self.latent_format is not None:
|
if self.latent_format is not None:
|
||||||
self.cond_hint = self.latent_format.process_in(self.cond_hint)
|
self.cond_hint = self.latent_format.process_in(self.cond_hint)
|
||||||
|
if len(self.extra_concat_orig) > 0:
|
||||||
|
to_concat = []
|
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|
for c in self.extra_concat_orig:
|
||||||
|
c = comfy.utils.common_upscale(c, self.cond_hint.shape[3], self.cond_hint.shape[2], self.upscale_algorithm, "center")
|
||||||
|
to_concat.append(comfy.utils.repeat_to_batch_size(c, self.cond_hint.shape[0]))
|
||||||
|
self.cond_hint = torch.cat([self.cond_hint] + to_concat, dim=1)
|
||||||
|
|
||||||
self.cond_hint = self.cond_hint.to(device=self.device, dtype=dtype)
|
self.cond_hint = self.cond_hint.to(device=self.device, dtype=dtype)
|
||||||
if x_noisy.shape[0] != self.cond_hint.shape[0]:
|
if x_noisy.shape[0] != self.cond_hint.shape[0]:
|
||||||
self.cond_hint = broadcast_image_to(self.cond_hint, x_noisy.shape[0], batched_number)
|
self.cond_hint = broadcast_image_to(self.cond_hint, x_noisy.shape[0], batched_number)
|
||||||
@ -410,12 +426,17 @@ def load_controlnet_mmdit(sd):
|
|||||||
for k in sd:
|
for k in sd:
|
||||||
new_sd[k] = sd[k]
|
new_sd[k] = sd[k]
|
||||||
|
|
||||||
control_model = comfy.cldm.mmdit.ControlNet(num_blocks=num_blocks, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
|
concat_mask = False
|
||||||
|
control_latent_channels = new_sd.get("pos_embed_input.proj.weight").shape[1]
|
||||||
|
if control_latent_channels == 17: #inpaint controlnet
|
||||||
|
concat_mask = True
|
||||||
|
|
||||||
|
control_model = comfy.cldm.mmdit.ControlNet(num_blocks=num_blocks, control_latent_channels=control_latent_channels, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
|
||||||
control_model = controlnet_load_state_dict(control_model, new_sd)
|
control_model = controlnet_load_state_dict(control_model, new_sd)
|
||||||
|
|
||||||
latent_format = comfy.latent_formats.SD3()
|
latent_format = comfy.latent_formats.SD3()
|
||||||
latent_format.shift_factor = 0 #SD3 controlnet weirdness
|
latent_format.shift_factor = 0 #SD3 controlnet weirdness
|
||||||
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype)
|
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype)
|
||||||
return control
|
return control
|
||||||
|
|
||||||
|
|
||||||
@ -449,12 +470,17 @@ def load_controlnet_flux_instantx(sd):
|
|||||||
if union_cnet in new_sd:
|
if union_cnet in new_sd:
|
||||||
num_union_modes = new_sd[union_cnet].shape[0]
|
num_union_modes = new_sd[union_cnet].shape[0]
|
||||||
|
|
||||||
control_model = comfy.ldm.flux.controlnet.ControlNetFlux(latent_input=True, num_union_modes=num_union_modes, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
|
control_latent_channels = new_sd.get("pos_embed_input.weight").shape[1] // 4
|
||||||
|
concat_mask = False
|
||||||
|
if control_latent_channels == 17:
|
||||||
|
concat_mask = True
|
||||||
|
|
||||||
|
control_model = comfy.ldm.flux.controlnet.ControlNetFlux(latent_input=True, num_union_modes=num_union_modes, control_latent_channels=control_latent_channels, operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
|
||||||
control_model = controlnet_load_state_dict(control_model, new_sd)
|
control_model = controlnet_load_state_dict(control_model, new_sd)
|
||||||
|
|
||||||
latent_format = comfy.latent_formats.Flux()
|
latent_format = comfy.latent_formats.Flux()
|
||||||
extra_conds = ['y', 'guidance']
|
extra_conds = ['y', 'guidance']
|
||||||
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
|
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
|
||||||
return control
|
return control
|
||||||
|
|
||||||
def convert_mistoline(sd):
|
def convert_mistoline(sd):
|
||||||
|
|||||||
@ -1101,3 +1101,45 @@ def sample_euler_ancestral_cfg_pp(model, x, sigmas, extra_args=None, callback=No
|
|||||||
if sigmas[i + 1] > 0:
|
if sigmas[i + 1] > 0:
|
||||||
x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * s_noise * sigma_up
|
x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * s_noise * sigma_up
|
||||||
return x
|
return x
|
||||||
|
@torch.no_grad()
|
||||||
|
def sample_dpmpp_2s_ancestral_cfg_pp(model, x, sigmas, extra_args=None, callback=None, disable=None, eta=1., s_noise=1., noise_sampler=None):
|
||||||
|
"""Ancestral sampling with DPM-Solver++(2S) second-order steps."""
|
||||||
|
extra_args = {} if extra_args is None else extra_args
|
||||||
|
noise_sampler = default_noise_sampler(x) if noise_sampler is None else noise_sampler
|
||||||
|
|
||||||
|
temp = [0]
|
||||||
|
def post_cfg_function(args):
|
||||||
|
temp[0] = args["uncond_denoised"]
|
||||||
|
return args["denoised"]
|
||||||
|
|
||||||
|
model_options = extra_args.get("model_options", {}).copy()
|
||||||
|
extra_args["model_options"] = comfy.model_patcher.set_model_options_post_cfg_function(model_options, post_cfg_function, disable_cfg1_optimization=True)
|
||||||
|
|
||||||
|
s_in = x.new_ones([x.shape[0]])
|
||||||
|
sigma_fn = lambda t: t.neg().exp()
|
||||||
|
t_fn = lambda sigma: sigma.log().neg()
|
||||||
|
|
||||||
|
for i in trange(len(sigmas) - 1, disable=disable):
|
||||||
|
denoised = model(x, sigmas[i] * s_in, **extra_args)
|
||||||
|
sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1], eta=eta)
|
||||||
|
if callback is not None:
|
||||||
|
callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigmas[i], 'denoised': denoised})
|
||||||
|
if sigma_down == 0:
|
||||||
|
# Euler method
|
||||||
|
d = to_d(x, sigmas[i], temp[0])
|
||||||
|
dt = sigma_down - sigmas[i]
|
||||||
|
x = denoised + d * sigma_down
|
||||||
|
else:
|
||||||
|
# DPM-Solver++(2S)
|
||||||
|
t, t_next = t_fn(sigmas[i]), t_fn(sigma_down)
|
||||||
|
# r = torch.sinh(1 + (2 - eta) * (t_next - t) / (t - t_fn(sigma_up))) works only on non-cfgpp, weird
|
||||||
|
r = 1 / 2
|
||||||
|
h = t_next - t
|
||||||
|
s = t + r * h
|
||||||
|
x_2 = (sigma_fn(s) / sigma_fn(t)) * (x + (denoised - temp[0])) - (-h * r).expm1() * denoised
|
||||||
|
denoised_2 = model(x_2, sigma_fn(s) * s_in, **extra_args)
|
||||||
|
x = (sigma_fn(t_next) / sigma_fn(t)) * (x + (denoised - temp[0])) - (-h).expm1() * denoised_2
|
||||||
|
# Noise addition
|
||||||
|
if sigmas[i + 1] > 0:
|
||||||
|
x = x + noise_sampler(sigmas[i], sigmas[i + 1]) * s_noise * sigma_up
|
||||||
|
return x
|
||||||
|
|||||||
@ -52,7 +52,7 @@ class MistolineControlnetBlock(nn.Module):
|
|||||||
|
|
||||||
|
|
||||||
class ControlNetFlux(Flux):
|
class ControlNetFlux(Flux):
|
||||||
def __init__(self, latent_input=False, num_union_modes=0, mistoline=False, image_model=None, dtype=None, device=None, operations=None, **kwargs):
|
def __init__(self, latent_input=False, num_union_modes=0, mistoline=False, control_latent_channels=None, image_model=None, dtype=None, device=None, operations=None, **kwargs):
|
||||||
super().__init__(final_layer=False, dtype=dtype, device=device, operations=operations, **kwargs)
|
super().__init__(final_layer=False, dtype=dtype, device=device, operations=operations, **kwargs)
|
||||||
|
|
||||||
self.main_model_double = 19
|
self.main_model_double = 19
|
||||||
@ -80,7 +80,12 @@ class ControlNetFlux(Flux):
|
|||||||
|
|
||||||
self.gradient_checkpointing = False
|
self.gradient_checkpointing = False
|
||||||
self.latent_input = latent_input
|
self.latent_input = latent_input
|
||||||
self.pos_embed_input = operations.Linear(self.in_channels, self.hidden_size, bias=True, dtype=dtype, device=device)
|
if control_latent_channels is None:
|
||||||
|
control_latent_channels = self.in_channels
|
||||||
|
else:
|
||||||
|
control_latent_channels *= 2 * 2 #patch size
|
||||||
|
|
||||||
|
self.pos_embed_input = operations.Linear(control_latent_channels, self.hidden_size, bias=True, dtype=dtype, device=device)
|
||||||
if not self.latent_input:
|
if not self.latent_input:
|
||||||
if self.mistoline:
|
if self.mistoline:
|
||||||
self.input_cond_block = MistolineCondDownsamplBlock(dtype=dtype, device=device, operations=operations)
|
self.input_cond_block = MistolineCondDownsamplBlock(dtype=dtype, device=device, operations=operations)
|
||||||
|
|||||||
@ -28,7 +28,7 @@ import comfy.utils
|
|||||||
import comfy.float
|
import comfy.float
|
||||||
import comfy.model_management
|
import comfy.model_management
|
||||||
import comfy.lora
|
import comfy.lora
|
||||||
from comfy.types import UnetWrapperFunction
|
from comfy.comfy_types import UnetWrapperFunction
|
||||||
|
|
||||||
def string_to_seed(data):
|
def string_to_seed(data):
|
||||||
crc = 0xFFFFFFFF
|
crc = 0xFFFFFFFF
|
||||||
|
|||||||
@ -570,7 +570,7 @@ class Sampler:
|
|||||||
return math.isclose(max_sigma, sigma, rel_tol=1e-05) or sigma > max_sigma
|
return math.isclose(max_sigma, sigma, rel_tol=1e-05) or sigma > max_sigma
|
||||||
|
|
||||||
KSAMPLER_NAMES = ["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2","dpm_2", "dpm_2_ancestral",
|
KSAMPLER_NAMES = ["euler", "euler_cfg_pp", "euler_ancestral", "euler_ancestral_cfg_pp", "heun", "heunpp2","dpm_2", "dpm_2_ancestral",
|
||||||
"lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu",
|
"lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_2s_ancestral_cfg_pp", "dpmpp_sde", "dpmpp_sde_gpu",
|
||||||
"dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm",
|
"dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm",
|
||||||
"ipndm", "ipndm_v", "deis"]
|
"ipndm", "ipndm_v", "deis"]
|
||||||
|
|
||||||
|
|||||||
@ -445,10 +445,6 @@ def load_text_encoder_state_dicts(state_dicts=[], embedding_directory=None, clip
|
|||||||
clip_target.tokenizer = comfy.text_encoders.sa_t5.SAT5Tokenizer
|
clip_target.tokenizer = comfy.text_encoders.sa_t5.SAT5Tokenizer
|
||||||
else:
|
else:
|
||||||
w = clip_data[0].get("text_model.embeddings.position_embedding.weight", None)
|
w = clip_data[0].get("text_model.embeddings.position_embedding.weight", None)
|
||||||
if w is not None and w.shape[0] == 248:
|
|
||||||
clip_target.clip = comfy.text_encoders.long_clipl.LongClipModel
|
|
||||||
clip_target.tokenizer = comfy.text_encoders.long_clipl.LongClipTokenizer
|
|
||||||
else:
|
|
||||||
clip_target.clip = sd1_clip.SD1ClipModel
|
clip_target.clip = sd1_clip.SD1ClipModel
|
||||||
clip_target.tokenizer = sd1_clip.SD1Tokenizer
|
clip_target.tokenizer = sd1_clip.SD1Tokenizer
|
||||||
elif len(clip_data) == 2:
|
elif len(clip_data) == 2:
|
||||||
@ -475,10 +471,12 @@ def load_text_encoder_state_dicts(state_dicts=[], embedding_directory=None, clip
|
|||||||
clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
|
clip_target.tokenizer = comfy.text_encoders.sd3_clip.SD3Tokenizer
|
||||||
|
|
||||||
parameters = 0
|
parameters = 0
|
||||||
|
tokenizer_data = {}
|
||||||
for c in clip_data:
|
for c in clip_data:
|
||||||
parameters += comfy.utils.calculate_parameters(c)
|
parameters += comfy.utils.calculate_parameters(c)
|
||||||
|
tokenizer_data, model_options = comfy.text_encoders.long_clipl.model_options_long_clip(c, tokenizer_data, model_options)
|
||||||
|
|
||||||
clip = CLIP(clip_target, embedding_directory=embedding_directory, parameters=parameters, model_options=model_options)
|
clip = CLIP(clip_target, embedding_directory=embedding_directory, parameters=parameters, tokenizer_data=tokenizer_data, model_options=model_options)
|
||||||
for c in clip_data:
|
for c in clip_data:
|
||||||
m, u = clip.load_sd(c)
|
m, u = clip.load_sd(c)
|
||||||
if len(m) > 0:
|
if len(m) > 0:
|
||||||
|
|||||||
@ -542,6 +542,7 @@ class SD1Tokenizer:
|
|||||||
def __init__(self, embedding_directory=None, tokenizer_data={}, clip_name="l", tokenizer=SDTokenizer):
|
def __init__(self, embedding_directory=None, tokenizer_data={}, clip_name="l", tokenizer=SDTokenizer):
|
||||||
self.clip_name = clip_name
|
self.clip_name = clip_name
|
||||||
self.clip = "clip_{}".format(self.clip_name)
|
self.clip = "clip_{}".format(self.clip_name)
|
||||||
|
tokenizer = tokenizer_data.get("{}_tokenizer_class".format(self.clip), tokenizer)
|
||||||
setattr(self, self.clip, tokenizer(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data))
|
setattr(self, self.clip, tokenizer(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data))
|
||||||
|
|
||||||
def tokenize_with_weights(self, text:str, return_word_ids=False):
|
def tokenize_with_weights(self, text:str, return_word_ids=False):
|
||||||
@ -570,6 +571,7 @@ class SD1ClipModel(torch.nn.Module):
|
|||||||
self.clip_name = clip_name
|
self.clip_name = clip_name
|
||||||
self.clip = "clip_{}".format(self.clip_name)
|
self.clip = "clip_{}".format(self.clip_name)
|
||||||
|
|
||||||
|
clip_model = model_options.get("{}_class".format(self.clip), clip_model)
|
||||||
setattr(self, self.clip, clip_model(device=device, dtype=dtype, model_options=model_options, **kwargs))
|
setattr(self, self.clip, clip_model(device=device, dtype=dtype, model_options=model_options, **kwargs))
|
||||||
|
|
||||||
self.dtypes = set()
|
self.dtypes = set()
|
||||||
|
|||||||
@ -22,7 +22,8 @@ class SDXLClipGTokenizer(sd1_clip.SDTokenizer):
|
|||||||
|
|
||||||
class SDXLTokenizer:
|
class SDXLTokenizer:
|
||||||
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
||||||
self.clip_l = sd1_clip.SDTokenizer(embedding_directory=embedding_directory)
|
clip_l_tokenizer_class = tokenizer_data.get("clip_l_tokenizer_class", sd1_clip.SDTokenizer)
|
||||||
|
self.clip_l = clip_l_tokenizer_class(embedding_directory=embedding_directory)
|
||||||
self.clip_g = SDXLClipGTokenizer(embedding_directory=embedding_directory)
|
self.clip_g = SDXLClipGTokenizer(embedding_directory=embedding_directory)
|
||||||
|
|
||||||
def tokenize_with_weights(self, text:str, return_word_ids=False):
|
def tokenize_with_weights(self, text:str, return_word_ids=False):
|
||||||
@ -40,7 +41,8 @@ class SDXLTokenizer:
|
|||||||
class SDXLClipModel(torch.nn.Module):
|
class SDXLClipModel(torch.nn.Module):
|
||||||
def __init__(self, device="cpu", dtype=None, model_options={}):
|
def __init__(self, device="cpu", dtype=None, model_options={}):
|
||||||
super().__init__()
|
super().__init__()
|
||||||
self.clip_l = sd1_clip.SDClipModel(layer="hidden", layer_idx=-2, device=device, dtype=dtype, layer_norm_hidden_state=False, model_options=model_options)
|
clip_l_class = model_options.get("clip_l_class", sd1_clip.SDClipModel)
|
||||||
|
self.clip_l = clip_l_class(layer="hidden", layer_idx=-2, device=device, dtype=dtype, layer_norm_hidden_state=False, model_options=model_options)
|
||||||
self.clip_g = SDXLClipG(device=device, dtype=dtype, model_options=model_options)
|
self.clip_g = SDXLClipG(device=device, dtype=dtype, model_options=model_options)
|
||||||
self.dtypes = set([dtype])
|
self.dtypes = set([dtype])
|
||||||
|
|
||||||
@ -57,7 +59,8 @@ class SDXLClipModel(torch.nn.Module):
|
|||||||
token_weight_pairs_l = token_weight_pairs["l"]
|
token_weight_pairs_l = token_weight_pairs["l"]
|
||||||
g_out, g_pooled = self.clip_g.encode_token_weights(token_weight_pairs_g)
|
g_out, g_pooled = self.clip_g.encode_token_weights(token_weight_pairs_g)
|
||||||
l_out, l_pooled = self.clip_l.encode_token_weights(token_weight_pairs_l)
|
l_out, l_pooled = self.clip_l.encode_token_weights(token_weight_pairs_l)
|
||||||
return torch.cat([l_out, g_out], dim=-1), g_pooled
|
cut_to = min(l_out.shape[1], g_out.shape[1])
|
||||||
|
return torch.cat([l_out[:,:cut_to], g_out[:,:cut_to]], dim=-1), g_pooled
|
||||||
|
|
||||||
def load_sd(self, sd):
|
def load_sd(self, sd):
|
||||||
if "text_model.encoder.layers.30.mlp.fc1.weight" in sd:
|
if "text_model.encoder.layers.30.mlp.fc1.weight" in sd:
|
||||||
|
|||||||
@ -18,7 +18,8 @@ class T5XXLTokenizer(sd1_clip.SDTokenizer):
|
|||||||
|
|
||||||
class FluxTokenizer:
|
class FluxTokenizer:
|
||||||
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
||||||
self.clip_l = sd1_clip.SDTokenizer(embedding_directory=embedding_directory)
|
clip_l_tokenizer_class = tokenizer_data.get("clip_l_tokenizer_class", sd1_clip.SDTokenizer)
|
||||||
|
self.clip_l = clip_l_tokenizer_class(embedding_directory=embedding_directory)
|
||||||
self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory)
|
self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory)
|
||||||
|
|
||||||
def tokenize_with_weights(self, text:str, return_word_ids=False):
|
def tokenize_with_weights(self, text:str, return_word_ids=False):
|
||||||
@ -38,7 +39,8 @@ class FluxClipModel(torch.nn.Module):
|
|||||||
def __init__(self, dtype_t5=None, device="cpu", dtype=None, model_options={}):
|
def __init__(self, dtype_t5=None, device="cpu", dtype=None, model_options={}):
|
||||||
super().__init__()
|
super().__init__()
|
||||||
dtype_t5 = comfy.model_management.pick_weight_dtype(dtype_t5, dtype, device)
|
dtype_t5 = comfy.model_management.pick_weight_dtype(dtype_t5, dtype, device)
|
||||||
self.clip_l = sd1_clip.SDClipModel(device=device, dtype=dtype, return_projected_pooled=False, model_options=model_options)
|
clip_l_class = model_options.get("clip_l_class", sd1_clip.SDClipModel)
|
||||||
|
self.clip_l = clip_l_class(device=device, dtype=dtype, return_projected_pooled=False, model_options=model_options)
|
||||||
self.t5xxl = T5XXLModel(device=device, dtype=dtype_t5, model_options=model_options)
|
self.t5xxl = T5XXLModel(device=device, dtype=dtype_t5, model_options=model_options)
|
||||||
self.dtypes = set([dtype, dtype_t5])
|
self.dtypes = set([dtype, dtype_t5])
|
||||||
|
|
||||||
|
|||||||
@ -6,9 +6,9 @@ class LongClipTokenizer_(sd1_clip.SDTokenizer):
|
|||||||
super().__init__(max_length=248, embedding_directory=embedding_directory, tokenizer_data=tokenizer_data)
|
super().__init__(max_length=248, embedding_directory=embedding_directory, tokenizer_data=tokenizer_data)
|
||||||
|
|
||||||
class LongClipModel_(sd1_clip.SDClipModel):
|
class LongClipModel_(sd1_clip.SDClipModel):
|
||||||
def __init__(self, device="cpu", dtype=None, model_options={}):
|
def __init__(self, *args, **kwargs):
|
||||||
textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "long_clipl.json")
|
textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "long_clipl.json")
|
||||||
super().__init__(device=device, textmodel_json_config=textmodel_json_config, return_projected_pooled=False, dtype=dtype, model_options=model_options)
|
super().__init__(*args, textmodel_json_config=textmodel_json_config, **kwargs)
|
||||||
|
|
||||||
class LongClipTokenizer(sd1_clip.SD1Tokenizer):
|
class LongClipTokenizer(sd1_clip.SD1Tokenizer):
|
||||||
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
||||||
@ -17,3 +17,14 @@ class LongClipTokenizer(sd1_clip.SD1Tokenizer):
|
|||||||
class LongClipModel(sd1_clip.SD1ClipModel):
|
class LongClipModel(sd1_clip.SD1ClipModel):
|
||||||
def __init__(self, device="cpu", dtype=None, model_options={}, **kwargs):
|
def __init__(self, device="cpu", dtype=None, model_options={}, **kwargs):
|
||||||
super().__init__(device=device, dtype=dtype, model_options=model_options, clip_model=LongClipModel_, **kwargs)
|
super().__init__(device=device, dtype=dtype, model_options=model_options, clip_model=LongClipModel_, **kwargs)
|
||||||
|
|
||||||
|
def model_options_long_clip(sd, tokenizer_data, model_options):
|
||||||
|
w = sd.get("clip_l.text_model.embeddings.position_embedding.weight", None)
|
||||||
|
if w is None:
|
||||||
|
w = sd.get("text_model.embeddings.position_embedding.weight", None)
|
||||||
|
if w is not None and w.shape[0] == 248:
|
||||||
|
tokenizer_data = tokenizer_data.copy()
|
||||||
|
model_options = model_options.copy()
|
||||||
|
tokenizer_data["clip_l_tokenizer_class"] = LongClipTokenizer_
|
||||||
|
model_options["clip_l_class"] = LongClipModel_
|
||||||
|
return tokenizer_data, model_options
|
||||||
|
|||||||
@ -20,7 +20,8 @@ class T5XXLTokenizer(sd1_clip.SDTokenizer):
|
|||||||
|
|
||||||
class SD3Tokenizer:
|
class SD3Tokenizer:
|
||||||
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
def __init__(self, embedding_directory=None, tokenizer_data={}):
|
||||||
self.clip_l = sd1_clip.SDTokenizer(embedding_directory=embedding_directory)
|
clip_l_tokenizer_class = tokenizer_data.get("clip_l_tokenizer_class", sd1_clip.SDTokenizer)
|
||||||
|
self.clip_l = clip_l_tokenizer_class(embedding_directory=embedding_directory)
|
||||||
self.clip_g = sdxl_clip.SDXLClipGTokenizer(embedding_directory=embedding_directory)
|
self.clip_g = sdxl_clip.SDXLClipGTokenizer(embedding_directory=embedding_directory)
|
||||||
self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory)
|
self.t5xxl = T5XXLTokenizer(embedding_directory=embedding_directory)
|
||||||
|
|
||||||
@ -42,7 +43,8 @@ class SD3ClipModel(torch.nn.Module):
|
|||||||
super().__init__()
|
super().__init__()
|
||||||
self.dtypes = set()
|
self.dtypes = set()
|
||||||
if clip_l:
|
if clip_l:
|
||||||
self.clip_l = sd1_clip.SDClipModel(layer="hidden", layer_idx=-2, device=device, dtype=dtype, layer_norm_hidden_state=False, return_projected_pooled=False, model_options=model_options)
|
clip_l_class = model_options.get("clip_l_class", sd1_clip.SDClipModel)
|
||||||
|
self.clip_l = clip_l_class(layer="hidden", layer_idx=-2, device=device, dtype=dtype, layer_norm_hidden_state=False, return_projected_pooled=False, model_options=model_options)
|
||||||
self.dtypes.add(dtype)
|
self.dtypes.add(dtype)
|
||||||
else:
|
else:
|
||||||
self.clip_l = None
|
self.clip_l = None
|
||||||
@ -95,7 +97,8 @@ class SD3ClipModel(torch.nn.Module):
|
|||||||
if self.clip_g is not None:
|
if self.clip_g is not None:
|
||||||
g_out, g_pooled = self.clip_g.encode_token_weights(token_weight_pairs_g)
|
g_out, g_pooled = self.clip_g.encode_token_weights(token_weight_pairs_g)
|
||||||
if lg_out is not None:
|
if lg_out is not None:
|
||||||
lg_out = torch.cat([lg_out, g_out], dim=-1)
|
cut_to = min(lg_out.shape[1], g_out.shape[1])
|
||||||
|
lg_out = torch.cat([lg_out[:,:cut_to], g_out[:,:cut_to]], dim=-1)
|
||||||
else:
|
else:
|
||||||
lg_out = torch.nn.functional.pad(g_out, (768, 0))
|
lg_out = torch.nn.functional.pad(g_out, (768, 0))
|
||||||
else:
|
else:
|
||||||
|
|||||||
@ -1,11 +1,21 @@
|
|||||||
import itertools
|
import itertools
|
||||||
from typing import Sequence, Mapping
|
from typing import Sequence, Mapping, Dict
|
||||||
from comfy_execution.graph import DynamicPrompt
|
from comfy_execution.graph import DynamicPrompt
|
||||||
|
|
||||||
import nodes
|
import nodes
|
||||||
|
|
||||||
from comfy_execution.graph_utils import is_link
|
from comfy_execution.graph_utils import is_link
|
||||||
|
|
||||||
|
NODE_CLASS_CONTAINS_UNIQUE_ID: Dict[str, bool] = {}
|
||||||
|
|
||||||
|
|
||||||
|
def include_unique_id_in_input(class_type: str) -> bool:
|
||||||
|
if class_type in NODE_CLASS_CONTAINS_UNIQUE_ID:
|
||||||
|
return NODE_CLASS_CONTAINS_UNIQUE_ID[class_type]
|
||||||
|
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
|
||||||
|
NODE_CLASS_CONTAINS_UNIQUE_ID[class_type] = "UNIQUE_ID" in class_def.INPUT_TYPES().get("hidden", {}).values()
|
||||||
|
return NODE_CLASS_CONTAINS_UNIQUE_ID[class_type]
|
||||||
|
|
||||||
class CacheKeySet:
|
class CacheKeySet:
|
||||||
def __init__(self, dynprompt, node_ids, is_changed_cache):
|
def __init__(self, dynprompt, node_ids, is_changed_cache):
|
||||||
self.keys = {}
|
self.keys = {}
|
||||||
@ -98,7 +108,7 @@ class CacheKeySetInputSignature(CacheKeySet):
|
|||||||
class_type = node["class_type"]
|
class_type = node["class_type"]
|
||||||
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
|
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
|
||||||
signature = [class_type, self.is_changed_cache.get(node_id)]
|
signature = [class_type, self.is_changed_cache.get(node_id)]
|
||||||
if self.include_node_id_in_input() or (hasattr(class_def, "NOT_IDEMPOTENT") and class_def.NOT_IDEMPOTENT) or "UNIQUE_ID" in class_def.INPUT_TYPES().get("hidden", {}).values():
|
if self.include_node_id_in_input() or (hasattr(class_def, "NOT_IDEMPOTENT") and class_def.NOT_IDEMPOTENT) or include_unique_id_in_input(class_type):
|
||||||
signature.append(node_id)
|
signature.append(node_id)
|
||||||
inputs = node["inputs"]
|
inputs = node["inputs"]
|
||||||
for key in sorted(inputs.keys()):
|
for key in sorted(inputs.keys()):
|
||||||
|
|||||||
@ -99,15 +99,22 @@ class TopologicalSort:
|
|||||||
self.add_strong_link(from_node_id, from_socket, to_node_id)
|
self.add_strong_link(from_node_id, from_socket, to_node_id)
|
||||||
|
|
||||||
def add_strong_link(self, from_node_id, from_socket, to_node_id):
|
def add_strong_link(self, from_node_id, from_socket, to_node_id):
|
||||||
|
if not self.is_cached(from_node_id):
|
||||||
self.add_node(from_node_id)
|
self.add_node(from_node_id)
|
||||||
if to_node_id not in self.blocking[from_node_id]:
|
if to_node_id not in self.blocking[from_node_id]:
|
||||||
self.blocking[from_node_id][to_node_id] = {}
|
self.blocking[from_node_id][to_node_id] = {}
|
||||||
self.blockCount[to_node_id] += 1
|
self.blockCount[to_node_id] += 1
|
||||||
self.blocking[from_node_id][to_node_id][from_socket] = True
|
self.blocking[from_node_id][to_node_id][from_socket] = True
|
||||||
|
|
||||||
def add_node(self, unique_id, include_lazy=False, subgraph_nodes=None):
|
def add_node(self, node_unique_id, include_lazy=False, subgraph_nodes=None):
|
||||||
|
node_ids = [node_unique_id]
|
||||||
|
links = []
|
||||||
|
|
||||||
|
while len(node_ids) > 0:
|
||||||
|
unique_id = node_ids.pop()
|
||||||
if unique_id in self.pendingNodes:
|
if unique_id in self.pendingNodes:
|
||||||
return
|
continue
|
||||||
|
|
||||||
self.pendingNodes[unique_id] = True
|
self.pendingNodes[unique_id] = True
|
||||||
self.blockCount[unique_id] = 0
|
self.blockCount[unique_id] = 0
|
||||||
self.blocking[unique_id] = {}
|
self.blocking[unique_id] = {}
|
||||||
@ -121,8 +128,15 @@ class TopologicalSort:
|
|||||||
continue
|
continue
|
||||||
input_type, input_category, input_info = self.get_input_info(unique_id, input_name)
|
input_type, input_category, input_info = self.get_input_info(unique_id, input_name)
|
||||||
is_lazy = input_info is not None and "lazy" in input_info and input_info["lazy"]
|
is_lazy = input_info is not None and "lazy" in input_info and input_info["lazy"]
|
||||||
if include_lazy or not is_lazy:
|
if (include_lazy or not is_lazy) and not self.is_cached(from_node_id):
|
||||||
self.add_strong_link(from_node_id, from_socket, unique_id)
|
node_ids.append(from_node_id)
|
||||||
|
links.append((from_node_id, from_socket, unique_id))
|
||||||
|
|
||||||
|
for link in links:
|
||||||
|
self.add_strong_link(*link)
|
||||||
|
|
||||||
|
def is_cached(self, node_id):
|
||||||
|
return False
|
||||||
|
|
||||||
def get_ready_nodes(self):
|
def get_ready_nodes(self):
|
||||||
return [node_id for node_id in self.pendingNodes if self.blockCount[node_id] == 0]
|
return [node_id for node_id in self.pendingNodes if self.blockCount[node_id] == 0]
|
||||||
@ -146,11 +160,8 @@ class ExecutionList(TopologicalSort):
|
|||||||
self.output_cache = output_cache
|
self.output_cache = output_cache
|
||||||
self.staged_node_id = None
|
self.staged_node_id = None
|
||||||
|
|
||||||
def add_strong_link(self, from_node_id, from_socket, to_node_id):
|
def is_cached(self, node_id):
|
||||||
if self.output_cache.get(from_node_id) is not None:
|
return self.output_cache.get(node_id) is not None
|
||||||
# Nothing to do
|
|
||||||
return
|
|
||||||
super().add_strong_link(from_node_id, from_socket, to_node_id)
|
|
||||||
|
|
||||||
def stage_node_execution(self):
|
def stage_node_execution(self):
|
||||||
assert self.staged_node_id is None
|
assert self.staged_node_id is None
|
||||||
|
|||||||
@ -183,17 +183,10 @@ class PreviewAudio(SaveAudio):
|
|||||||
}
|
}
|
||||||
|
|
||||||
class LoadAudio:
|
class LoadAudio:
|
||||||
SUPPORTED_FORMATS = ('.wav', '.mp3', '.ogg', '.flac', '.aiff', '.aif')
|
|
||||||
|
|
||||||
@classmethod
|
@classmethod
|
||||||
def INPUT_TYPES(s):
|
def INPUT_TYPES(s):
|
||||||
input_dir = folder_paths.get_input_directory()
|
input_dir = folder_paths.get_input_directory()
|
||||||
files = [
|
files = folder_paths.filter_files_content_types(os.listdir(input_dir), ["audio", "video"])
|
||||||
f for f in os.listdir(input_dir)
|
|
||||||
if (os.path.isfile(os.path.join(input_dir, f))
|
|
||||||
and f.endswith(LoadAudio.SUPPORTED_FORMATS)
|
|
||||||
)
|
|
||||||
]
|
|
||||||
return {"required": {"audio": (sorted(files), {"audio_upload": True})}}
|
return {"required": {"audio": (sorted(files), {"audio_upload": True})}}
|
||||||
|
|
||||||
CATEGORY = "audio"
|
CATEGORY = "audio"
|
||||||
|
|||||||
@ -1,4 +1,6 @@
|
|||||||
from comfy.cldm.control_types import UNION_CONTROLNET_TYPES
|
from comfy.cldm.control_types import UNION_CONTROLNET_TYPES
|
||||||
|
import nodes
|
||||||
|
import comfy.utils
|
||||||
|
|
||||||
class SetUnionControlNetType:
|
class SetUnionControlNetType:
|
||||||
@classmethod
|
@classmethod
|
||||||
@ -22,6 +24,37 @@ class SetUnionControlNetType:
|
|||||||
|
|
||||||
return (control_net,)
|
return (control_net,)
|
||||||
|
|
||||||
|
class ControlNetInpaintingAliMamaApply(nodes.ControlNetApplyAdvanced):
|
||||||
|
@classmethod
|
||||||
|
def INPUT_TYPES(s):
|
||||||
|
return {"required": {"positive": ("CONDITIONING", ),
|
||||||
|
"negative": ("CONDITIONING", ),
|
||||||
|
"control_net": ("CONTROL_NET", ),
|
||||||
|
"vae": ("VAE", ),
|
||||||
|
"image": ("IMAGE", ),
|
||||||
|
"mask": ("MASK", ),
|
||||||
|
"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
|
||||||
|
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
|
||||||
|
"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001})
|
||||||
|
}}
|
||||||
|
|
||||||
|
FUNCTION = "apply_inpaint_controlnet"
|
||||||
|
|
||||||
|
CATEGORY = "conditioning/controlnet"
|
||||||
|
|
||||||
|
def apply_inpaint_controlnet(self, positive, negative, control_net, vae, image, mask, strength, start_percent, end_percent):
|
||||||
|
extra_concat = []
|
||||||
|
if control_net.concat_mask:
|
||||||
|
mask = 1.0 - mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1]))
|
||||||
|
mask_apply = comfy.utils.common_upscale(mask, image.shape[2], image.shape[1], "bilinear", "center").round()
|
||||||
|
image = image * mask_apply.movedim(1, -1).repeat(1, 1, 1, image.shape[3])
|
||||||
|
extra_concat = [mask]
|
||||||
|
|
||||||
|
return self.apply_controlnet(positive, negative, control_net, image, strength, start_percent, end_percent, vae=vae, extra_concat=extra_concat)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
NODE_CLASS_MAPPINGS = {
|
NODE_CLASS_MAPPINGS = {
|
||||||
"SetUnionControlNetType": SetUnionControlNetType,
|
"SetUnionControlNetType": SetUnionControlNetType,
|
||||||
|
"ControlNetInpaintingAliMamaApply": ControlNetInpaintingAliMamaApply,
|
||||||
}
|
}
|
||||||
|
|||||||
@ -26,6 +26,7 @@ class PerpNeg:
|
|||||||
FUNCTION = "patch"
|
FUNCTION = "patch"
|
||||||
|
|
||||||
CATEGORY = "_for_testing"
|
CATEGORY = "_for_testing"
|
||||||
|
DEPRECATED = True
|
||||||
|
|
||||||
def patch(self, model, empty_conditioning, neg_scale):
|
def patch(self, model, empty_conditioning, neg_scale):
|
||||||
m = model.clone()
|
m = model.clone()
|
||||||
|
|||||||
21
comfy_extras/nodes_torch_compile.py
Normal file
21
comfy_extras/nodes_torch_compile.py
Normal file
@ -0,0 +1,21 @@
|
|||||||
|
import torch
|
||||||
|
|
||||||
|
class TorchCompileModel:
|
||||||
|
@classmethod
|
||||||
|
def INPUT_TYPES(s):
|
||||||
|
return {"required": { "model": ("MODEL",),
|
||||||
|
}}
|
||||||
|
RETURN_TYPES = ("MODEL",)
|
||||||
|
FUNCTION = "patch"
|
||||||
|
|
||||||
|
CATEGORY = "_for_testing"
|
||||||
|
EXPERIMENTAL = True
|
||||||
|
|
||||||
|
def patch(self, model):
|
||||||
|
m = model.clone()
|
||||||
|
m.add_object_patch("diffusion_model", torch.compile(model=m.get_model_object("diffusion_model")))
|
||||||
|
return (m, )
|
||||||
|
|
||||||
|
NODE_CLASS_MAPPINGS = {
|
||||||
|
"TorchCompileModel": TorchCompileModel,
|
||||||
|
}
|
||||||
@ -30,6 +30,9 @@ a111:
|
|||||||
# clip_vision: models/clip_vision/
|
# clip_vision: models/clip_vision/
|
||||||
# configs: models/configs/
|
# configs: models/configs/
|
||||||
# controlnet: models/controlnet/
|
# controlnet: models/controlnet/
|
||||||
|
# diffusion_models: |
|
||||||
|
# models/diffusion_models
|
||||||
|
# models/unet
|
||||||
# embeddings: models/embeddings/
|
# embeddings: models/embeddings/
|
||||||
# loras: models/loras/
|
# loras: models/loras/
|
||||||
# upscale_models: models/upscale_models/
|
# upscale_models: models/upscale_models/
|
||||||
|
|||||||
@ -2,7 +2,9 @@ from __future__ import annotations
|
|||||||
|
|
||||||
import os
|
import os
|
||||||
import time
|
import time
|
||||||
|
import mimetypes
|
||||||
import logging
|
import logging
|
||||||
|
from typing import Set, List, Dict, Tuple, Literal
|
||||||
from collections.abc import Collection
|
from collections.abc import Collection
|
||||||
|
|
||||||
supported_pt_extensions: set[str] = {'.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl', '.sft'}
|
supported_pt_extensions: set[str] = {'.ckpt', '.pt', '.bin', '.pth', '.safetensors', '.pkl', '.sft'}
|
||||||
@ -44,6 +46,10 @@ user_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), "user
|
|||||||
|
|
||||||
filename_list_cache: dict[str, tuple[list[str], dict[str, float], float]] = {}
|
filename_list_cache: dict[str, tuple[list[str], dict[str, float], float]] = {}
|
||||||
|
|
||||||
|
extension_mimetypes_cache = {
|
||||||
|
"webp" : "image",
|
||||||
|
}
|
||||||
|
|
||||||
def map_legacy(folder_name: str) -> str:
|
def map_legacy(folder_name: str) -> str:
|
||||||
legacy = {"unet": "diffusion_models"}
|
legacy = {"unet": "diffusion_models"}
|
||||||
return legacy.get(folder_name, folder_name)
|
return legacy.get(folder_name, folder_name)
|
||||||
@ -78,6 +84,13 @@ def get_input_directory() -> str:
|
|||||||
global input_directory
|
global input_directory
|
||||||
return input_directory
|
return input_directory
|
||||||
|
|
||||||
|
def get_user_directory() -> str:
|
||||||
|
return user_directory
|
||||||
|
|
||||||
|
def set_user_directory(user_dir: str) -> None:
|
||||||
|
global user_directory
|
||||||
|
user_directory = user_dir
|
||||||
|
|
||||||
|
|
||||||
#NOTE: used in http server so don't put folders that should not be accessed remotely
|
#NOTE: used in http server so don't put folders that should not be accessed remotely
|
||||||
def get_directory_by_type(type_name: str) -> str | None:
|
def get_directory_by_type(type_name: str) -> str | None:
|
||||||
@ -89,6 +102,28 @@ def get_directory_by_type(type_name: str) -> str | None:
|
|||||||
return get_input_directory()
|
return get_input_directory()
|
||||||
return None
|
return None
|
||||||
|
|
||||||
|
def filter_files_content_types(files: List[str], content_types: Literal["image", "video", "audio"]) -> List[str]:
|
||||||
|
"""
|
||||||
|
Example:
|
||||||
|
files = os.listdir(folder_paths.get_input_directory())
|
||||||
|
filter_files_content_types(files, ["image", "audio", "video"])
|
||||||
|
"""
|
||||||
|
global extension_mimetypes_cache
|
||||||
|
result = []
|
||||||
|
for file in files:
|
||||||
|
extension = file.split('.')[-1]
|
||||||
|
if extension not in extension_mimetypes_cache:
|
||||||
|
mime_type, _ = mimetypes.guess_type(file, strict=False)
|
||||||
|
if not mime_type:
|
||||||
|
continue
|
||||||
|
content_type = mime_type.split('/')[0]
|
||||||
|
extension_mimetypes_cache[extension] = content_type
|
||||||
|
else:
|
||||||
|
content_type = extension_mimetypes_cache[extension]
|
||||||
|
|
||||||
|
if content_type in content_types:
|
||||||
|
result.append(file)
|
||||||
|
return result
|
||||||
|
|
||||||
# determine base_dir rely on annotation if name is 'filename.ext [annotation]' format
|
# determine base_dir rely on annotation if name is 'filename.ext [annotation]' format
|
||||||
# otherwise use default_path as base_dir
|
# otherwise use default_path as base_dir
|
||||||
|
|||||||
32
main.py
32
main.py
@ -63,6 +63,7 @@ import threading
|
|||||||
import gc
|
import gc
|
||||||
|
|
||||||
import logging
|
import logging
|
||||||
|
import utils.extra_config
|
||||||
|
|
||||||
if os.name == "nt":
|
if os.name == "nt":
|
||||||
logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
|
logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
|
||||||
@ -85,7 +86,6 @@ if args.windows_standalone_build:
|
|||||||
pass
|
pass
|
||||||
|
|
||||||
import comfy.utils
|
import comfy.utils
|
||||||
import yaml
|
|
||||||
|
|
||||||
import execution
|
import execution
|
||||||
import server
|
import server
|
||||||
@ -180,27 +180,6 @@ def cleanup_temp():
|
|||||||
shutil.rmtree(temp_dir, ignore_errors=True)
|
shutil.rmtree(temp_dir, ignore_errors=True)
|
||||||
|
|
||||||
|
|
||||||
def load_extra_path_config(yaml_path):
|
|
||||||
with open(yaml_path, 'r') as stream:
|
|
||||||
config = yaml.safe_load(stream)
|
|
||||||
for c in config:
|
|
||||||
conf = config[c]
|
|
||||||
if conf is None:
|
|
||||||
continue
|
|
||||||
base_path = None
|
|
||||||
if "base_path" in conf:
|
|
||||||
base_path = conf.pop("base_path")
|
|
||||||
for x in conf:
|
|
||||||
for y in conf[x].split("\n"):
|
|
||||||
if len(y) == 0:
|
|
||||||
continue
|
|
||||||
full_path = y
|
|
||||||
if base_path is not None:
|
|
||||||
full_path = os.path.join(base_path, full_path)
|
|
||||||
logging.info("Adding extra search path {} {}".format(x, full_path))
|
|
||||||
folder_paths.add_model_folder_path(x, full_path)
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
if __name__ == "__main__":
|
||||||
if args.temp_directory:
|
if args.temp_directory:
|
||||||
temp_dir = os.path.join(os.path.abspath(args.temp_directory), "temp")
|
temp_dir = os.path.join(os.path.abspath(args.temp_directory), "temp")
|
||||||
@ -222,11 +201,11 @@ if __name__ == "__main__":
|
|||||||
|
|
||||||
extra_model_paths_config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "extra_model_paths.yaml")
|
extra_model_paths_config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "extra_model_paths.yaml")
|
||||||
if os.path.isfile(extra_model_paths_config_path):
|
if os.path.isfile(extra_model_paths_config_path):
|
||||||
load_extra_path_config(extra_model_paths_config_path)
|
utils.extra_config.load_extra_path_config(extra_model_paths_config_path)
|
||||||
|
|
||||||
if args.extra_model_paths_config:
|
if args.extra_model_paths_config:
|
||||||
for config_path in itertools.chain(*args.extra_model_paths_config):
|
for config_path in itertools.chain(*args.extra_model_paths_config):
|
||||||
load_extra_path_config(config_path)
|
utils.extra_config.load_extra_path_config(config_path)
|
||||||
|
|
||||||
nodes.init_extra_nodes(init_custom_nodes=not args.disable_all_custom_nodes)
|
nodes.init_extra_nodes(init_custom_nodes=not args.disable_all_custom_nodes)
|
||||||
|
|
||||||
@ -254,6 +233,11 @@ if __name__ == "__main__":
|
|||||||
logging.info(f"Setting input directory to: {input_dir}")
|
logging.info(f"Setting input directory to: {input_dir}")
|
||||||
folder_paths.set_input_directory(input_dir)
|
folder_paths.set_input_directory(input_dir)
|
||||||
|
|
||||||
|
if args.user_directory:
|
||||||
|
user_dir = os.path.abspath(args.user_directory)
|
||||||
|
logging.info(f"Setting user directory to: {user_dir}")
|
||||||
|
folder_paths.set_user_directory(user_dir)
|
||||||
|
|
||||||
if args.quick_test_for_ci:
|
if args.quick_test_for_ci:
|
||||||
exit(0)
|
exit(0)
|
||||||
|
|
||||||
|
|||||||
6
nodes.py
6
nodes.py
@ -511,6 +511,7 @@ class CheckpointLoader:
|
|||||||
FUNCTION = "load_checkpoint"
|
FUNCTION = "load_checkpoint"
|
||||||
|
|
||||||
CATEGORY = "advanced/loaders"
|
CATEGORY = "advanced/loaders"
|
||||||
|
DEPRECATED = True
|
||||||
|
|
||||||
def load_checkpoint(self, config_name, ckpt_name):
|
def load_checkpoint(self, config_name, ckpt_name):
|
||||||
config_path = folder_paths.get_full_path("configs", config_name)
|
config_path = folder_paths.get_full_path("configs", config_name)
|
||||||
@ -823,7 +824,7 @@ class ControlNetApplyAdvanced:
|
|||||||
|
|
||||||
CATEGORY = "conditioning/controlnet"
|
CATEGORY = "conditioning/controlnet"
|
||||||
|
|
||||||
def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None):
|
def apply_controlnet(self, positive, negative, control_net, image, strength, start_percent, end_percent, vae=None, extra_concat=[]):
|
||||||
if strength == 0:
|
if strength == 0:
|
||||||
return (positive, negative)
|
return (positive, negative)
|
||||||
|
|
||||||
@ -840,7 +841,7 @@ class ControlNetApplyAdvanced:
|
|||||||
if prev_cnet in cnets:
|
if prev_cnet in cnets:
|
||||||
c_net = cnets[prev_cnet]
|
c_net = cnets[prev_cnet]
|
||||||
else:
|
else:
|
||||||
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae)
|
c_net = control_net.copy().set_cond_hint(control_hint, strength, (start_percent, end_percent), vae=vae, extra_concat=extra_concat)
|
||||||
c_net.set_previous_controlnet(prev_cnet)
|
c_net.set_previous_controlnet(prev_cnet)
|
||||||
cnets[prev_cnet] = c_net
|
cnets[prev_cnet] = c_net
|
||||||
|
|
||||||
@ -2103,6 +2104,7 @@ def init_builtin_extra_nodes():
|
|||||||
"nodes_hunyuan.py",
|
"nodes_hunyuan.py",
|
||||||
"nodes_flux.py",
|
"nodes_flux.py",
|
||||||
"nodes_lora_extract.py",
|
"nodes_lora_extract.py",
|
||||||
|
"nodes_torch_compile.py",
|
||||||
]
|
]
|
||||||
|
|
||||||
import_failed = []
|
import_failed = []
|
||||||
|
|||||||
45
server.py
45
server.py
@ -12,6 +12,8 @@ import json
|
|||||||
import glob
|
import glob
|
||||||
import struct
|
import struct
|
||||||
import ssl
|
import ssl
|
||||||
|
import socket
|
||||||
|
import ipaddress
|
||||||
from PIL import Image, ImageOps
|
from PIL import Image, ImageOps
|
||||||
from PIL.PngImagePlugin import PngInfo
|
from PIL.PngImagePlugin import PngInfo
|
||||||
from io import BytesIO
|
from io import BytesIO
|
||||||
@ -80,20 +82,55 @@ def create_cors_middleware(allowed_origin: str):
|
|||||||
|
|
||||||
return cors_middleware
|
return cors_middleware
|
||||||
|
|
||||||
|
def is_loopback(host):
|
||||||
|
if host is None:
|
||||||
|
return False
|
||||||
|
try:
|
||||||
|
if ipaddress.ip_address(host).is_loopback:
|
||||||
|
return True
|
||||||
|
else:
|
||||||
|
return False
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
|
||||||
|
loopback = False
|
||||||
|
for family in (socket.AF_INET, socket.AF_INET6):
|
||||||
|
try:
|
||||||
|
r = socket.getaddrinfo(host, None, family, socket.SOCK_STREAM)
|
||||||
|
for family, _, _, _, sockaddr in r:
|
||||||
|
if not ipaddress.ip_address(sockaddr[0]).is_loopback:
|
||||||
|
return loopback
|
||||||
|
else:
|
||||||
|
loopback = True
|
||||||
|
except socket.gaierror:
|
||||||
|
pass
|
||||||
|
|
||||||
|
return loopback
|
||||||
|
|
||||||
|
|
||||||
def create_origin_only_middleware():
|
def create_origin_only_middleware():
|
||||||
@web.middleware
|
@web.middleware
|
||||||
async def origin_only_middleware(request: web.Request, handler):
|
async def origin_only_middleware(request: web.Request, handler):
|
||||||
|
#this code is used to prevent the case where a random website can queue comfy workflows by making a POST to 127.0.0.1 which browsers don't prevent for some dumb reason.
|
||||||
|
#in that case the Host and Origin hostnames won't match
|
||||||
|
#I know the proper fix would be to add a cookie but this should take care of the problem in the meantime
|
||||||
if 'Host' in request.headers and 'Origin' in request.headers:
|
if 'Host' in request.headers and 'Origin' in request.headers:
|
||||||
host = request.headers['Host']
|
host = request.headers['Host']
|
||||||
origin = request.headers['Origin']
|
origin = request.headers['Origin']
|
||||||
host_domain = host.lower()
|
host_domain = host.lower()
|
||||||
parsed = urllib.parse.urlparse(origin)
|
parsed = urllib.parse.urlparse(origin)
|
||||||
origin_domain = parsed.netloc.lower()
|
origin_domain = parsed.netloc.lower()
|
||||||
if parsed.port is None: #if origin doesn't have a port strip it from the host to handle weird browsers
|
host_domain_parsed = urllib.parse.urlsplit('//' + host_domain)
|
||||||
result = urllib.parse.urlsplit('//' + host_domain)
|
|
||||||
host_domain = result.hostname
|
|
||||||
|
|
||||||
if len(host_domain) > 0 and len(origin_domain) > 0:
|
#limit the check to when the host domain is localhost, this makes it slightly less safe but should still prevent the exploit
|
||||||
|
loopback = is_loopback(host_domain_parsed.hostname)
|
||||||
|
|
||||||
|
if parsed.port is None: #if origin doesn't have a port strip it from the host to handle weird browsers, same for host
|
||||||
|
host_domain = host_domain_parsed.hostname
|
||||||
|
if host_domain_parsed.port is None:
|
||||||
|
origin_domain = parsed.hostname
|
||||||
|
|
||||||
|
if loopback and host_domain is not None and origin_domain is not None and len(host_domain) > 0 and len(origin_domain) > 0:
|
||||||
if host_domain != origin_domain:
|
if host_domain != origin_domain:
|
||||||
logging.warning("WARNING: request with non matching host and origin {} != {}, returning 403".format(host_domain, origin_domain))
|
logging.warning("WARNING: request with non matching host and origin {} != {}, returning 403".format(host_domain, origin_domain))
|
||||||
return web.Response(status=403)
|
return web.Response(status=403)
|
||||||
|
|||||||
@ -2,7 +2,7 @@
|
|||||||
|
|
||||||
## Install test dependencies
|
## Install test dependencies
|
||||||
|
|
||||||
`pip install -r tests-units/requirements.txt`
|
`pip install -r tests-unit/requirements.txt`
|
||||||
|
|
||||||
## Run tests
|
## Run tests
|
||||||
`pytest tests-units/`
|
`pytest tests-unit/`
|
||||||
|
|||||||
66
tests-unit/comfy_test/folder_path_test.py
Normal file
66
tests-unit/comfy_test/folder_path_test.py
Normal file
@ -0,0 +1,66 @@
|
|||||||
|
### 🗻 This file is created through the spirit of Mount Fuji at its peak
|
||||||
|
# TODO(yoland): clean up this after I get back down
|
||||||
|
import pytest
|
||||||
|
import os
|
||||||
|
import tempfile
|
||||||
|
from unittest.mock import patch
|
||||||
|
|
||||||
|
import folder_paths
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def temp_dir():
|
||||||
|
with tempfile.TemporaryDirectory() as tmpdirname:
|
||||||
|
yield tmpdirname
|
||||||
|
|
||||||
|
|
||||||
|
def test_get_directory_by_type():
|
||||||
|
test_dir = "/test/dir"
|
||||||
|
folder_paths.set_output_directory(test_dir)
|
||||||
|
assert folder_paths.get_directory_by_type("output") == test_dir
|
||||||
|
assert folder_paths.get_directory_by_type("invalid") is None
|
||||||
|
|
||||||
|
def test_annotated_filepath():
|
||||||
|
assert folder_paths.annotated_filepath("test.txt") == ("test.txt", None)
|
||||||
|
assert folder_paths.annotated_filepath("test.txt [output]") == ("test.txt", folder_paths.get_output_directory())
|
||||||
|
assert folder_paths.annotated_filepath("test.txt [input]") == ("test.txt", folder_paths.get_input_directory())
|
||||||
|
assert folder_paths.annotated_filepath("test.txt [temp]") == ("test.txt", folder_paths.get_temp_directory())
|
||||||
|
|
||||||
|
def test_get_annotated_filepath():
|
||||||
|
default_dir = "/default/dir"
|
||||||
|
assert folder_paths.get_annotated_filepath("test.txt", default_dir) == os.path.join(default_dir, "test.txt")
|
||||||
|
assert folder_paths.get_annotated_filepath("test.txt [output]") == os.path.join(folder_paths.get_output_directory(), "test.txt")
|
||||||
|
|
||||||
|
def test_add_model_folder_path():
|
||||||
|
folder_paths.add_model_folder_path("test_folder", "/test/path")
|
||||||
|
assert "/test/path" in folder_paths.get_folder_paths("test_folder")
|
||||||
|
|
||||||
|
def test_recursive_search(temp_dir):
|
||||||
|
os.makedirs(os.path.join(temp_dir, "subdir"))
|
||||||
|
open(os.path.join(temp_dir, "file1.txt"), "w").close()
|
||||||
|
open(os.path.join(temp_dir, "subdir", "file2.txt"), "w").close()
|
||||||
|
|
||||||
|
files, dirs = folder_paths.recursive_search(temp_dir)
|
||||||
|
assert set(files) == {"file1.txt", os.path.join("subdir", "file2.txt")}
|
||||||
|
assert len(dirs) == 2 # temp_dir and subdir
|
||||||
|
|
||||||
|
def test_filter_files_extensions():
|
||||||
|
files = ["file1.txt", "file2.jpg", "file3.png", "file4.txt"]
|
||||||
|
assert folder_paths.filter_files_extensions(files, [".txt"]) == ["file1.txt", "file4.txt"]
|
||||||
|
assert folder_paths.filter_files_extensions(files, [".jpg", ".png"]) == ["file2.jpg", "file3.png"]
|
||||||
|
assert folder_paths.filter_files_extensions(files, []) == files
|
||||||
|
|
||||||
|
@patch("folder_paths.recursive_search")
|
||||||
|
@patch("folder_paths.folder_names_and_paths")
|
||||||
|
def test_get_filename_list(mock_folder_names_and_paths, mock_recursive_search):
|
||||||
|
mock_folder_names_and_paths.__getitem__.return_value = (["/test/path"], {".txt"})
|
||||||
|
mock_recursive_search.return_value = (["file1.txt", "file2.jpg"], {})
|
||||||
|
assert folder_paths.get_filename_list("test_folder") == ["file1.txt"]
|
||||||
|
|
||||||
|
def test_get_save_image_path(temp_dir):
|
||||||
|
with patch("folder_paths.output_directory", temp_dir):
|
||||||
|
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path("test", temp_dir, 100, 100)
|
||||||
|
assert os.path.samefile(full_output_folder, temp_dir)
|
||||||
|
assert filename == "test"
|
||||||
|
assert counter == 1
|
||||||
|
assert subfolder == ""
|
||||||
|
assert filename_prefix == "test"
|
||||||
0
tests-unit/folder_paths_test/__init__.py
Normal file
0
tests-unit/folder_paths_test/__init__.py
Normal file
52
tests-unit/folder_paths_test/filter_by_content_types_test.py
Normal file
52
tests-unit/folder_paths_test/filter_by_content_types_test.py
Normal file
@ -0,0 +1,52 @@
|
|||||||
|
import pytest
|
||||||
|
import os
|
||||||
|
import tempfile
|
||||||
|
from folder_paths import filter_files_content_types
|
||||||
|
|
||||||
|
@pytest.fixture(scope="module")
|
||||||
|
def file_extensions():
|
||||||
|
return {
|
||||||
|
'image': ['bmp', 'cdr', 'gif', 'heif', 'ico', 'jpeg', 'jpg', 'pcx', 'png', 'pnm', 'ppm', 'psd', 'sgi', 'svg', 'tiff', 'webp', 'xbm', 'xcf', 'xpm'],
|
||||||
|
'audio': ['aif', 'aifc', 'aiff', 'au', 'awb', 'flac', 'm4a', 'mp2', 'mp3', 'ogg', 'sd2', 'smp', 'snd', 'wav'],
|
||||||
|
'video': ['avi', 'flv', 'm2v', 'm4v', 'mj2', 'mkv', 'mov', 'mp4', 'mpeg', 'mpg', 'ogv', 'qt', 'webm', 'wmv']
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture(scope="module")
|
||||||
|
def mock_dir(file_extensions):
|
||||||
|
with tempfile.TemporaryDirectory() as directory:
|
||||||
|
for content_type, extensions in file_extensions.items():
|
||||||
|
for extension in extensions:
|
||||||
|
with open(f"{directory}/sample_{content_type}.{extension}", "w") as f:
|
||||||
|
f.write(f"Sample {content_type} file in {extension} format")
|
||||||
|
yield directory
|
||||||
|
|
||||||
|
|
||||||
|
def test_categorizes_all_correctly(mock_dir, file_extensions):
|
||||||
|
files = os.listdir(mock_dir)
|
||||||
|
for content_type, extensions in file_extensions.items():
|
||||||
|
filtered_files = filter_files_content_types(files, [content_type])
|
||||||
|
for extension in extensions:
|
||||||
|
assert f"sample_{content_type}.{extension}" in filtered_files
|
||||||
|
|
||||||
|
|
||||||
|
def test_categorizes_all_uniquely(mock_dir, file_extensions):
|
||||||
|
files = os.listdir(mock_dir)
|
||||||
|
for content_type, extensions in file_extensions.items():
|
||||||
|
filtered_files = filter_files_content_types(files, [content_type])
|
||||||
|
assert len(filtered_files) == len(extensions)
|
||||||
|
|
||||||
|
|
||||||
|
def test_handles_bad_extensions():
|
||||||
|
files = ["file1.txt", "file2.py", "file3.example", "file4.pdf", "file5.ini", "file6.doc", "file7.md"]
|
||||||
|
assert filter_files_content_types(files, ["image", "audio", "video"]) == []
|
||||||
|
|
||||||
|
|
||||||
|
def test_handles_no_extension():
|
||||||
|
files = ["file1", "file2", "file3", "file4", "file5", "file6", "file7"]
|
||||||
|
assert filter_files_content_types(files, ["image", "audio", "video"]) == []
|
||||||
|
|
||||||
|
|
||||||
|
def test_handles_no_files():
|
||||||
|
files = []
|
||||||
|
assert filter_files_content_types(files, ["image", "audio", "video"]) == []
|
||||||
120
tests-unit/prompt_server_test/user_manager_test.py
Normal file
120
tests-unit/prompt_server_test/user_manager_test.py
Normal file
@ -0,0 +1,120 @@
|
|||||||
|
import pytest
|
||||||
|
import os
|
||||||
|
from aiohttp import web
|
||||||
|
from app.user_manager import UserManager
|
||||||
|
from unittest.mock import patch
|
||||||
|
|
||||||
|
pytestmark = (
|
||||||
|
pytest.mark.asyncio
|
||||||
|
) # This applies the asyncio mark to all test functions in the module
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def user_manager(tmp_path):
|
||||||
|
um = UserManager()
|
||||||
|
um.get_request_user_filepath = lambda req, file, **kwargs: os.path.join(
|
||||||
|
tmp_path, file
|
||||||
|
)
|
||||||
|
return um
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def app(user_manager):
|
||||||
|
app = web.Application()
|
||||||
|
routes = web.RouteTableDef()
|
||||||
|
user_manager.add_routes(routes)
|
||||||
|
app.add_routes(routes)
|
||||||
|
return app
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_empty_directory(aiohttp_client, app, tmp_path):
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=test_dir")
|
||||||
|
assert resp.status == 404
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_with_files(aiohttp_client, app, tmp_path):
|
||||||
|
os.makedirs(tmp_path / "test_dir")
|
||||||
|
with open(tmp_path / "test_dir" / "file1.txt", "w") as f:
|
||||||
|
f.write("test content")
|
||||||
|
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=test_dir")
|
||||||
|
assert resp.status == 200
|
||||||
|
assert await resp.json() == ["file1.txt"]
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_recursive(aiohttp_client, app, tmp_path):
|
||||||
|
os.makedirs(tmp_path / "test_dir" / "subdir")
|
||||||
|
with open(tmp_path / "test_dir" / "file1.txt", "w") as f:
|
||||||
|
f.write("test content")
|
||||||
|
with open(tmp_path / "test_dir" / "subdir" / "file2.txt", "w") as f:
|
||||||
|
f.write("test content")
|
||||||
|
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=test_dir&recurse=true")
|
||||||
|
assert resp.status == 200
|
||||||
|
assert set(await resp.json()) == {"file1.txt", "subdir/file2.txt"}
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_full_info(aiohttp_client, app, tmp_path):
|
||||||
|
os.makedirs(tmp_path / "test_dir")
|
||||||
|
with open(tmp_path / "test_dir" / "file1.txt", "w") as f:
|
||||||
|
f.write("test content")
|
||||||
|
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=test_dir&full_info=true")
|
||||||
|
assert resp.status == 200
|
||||||
|
result = await resp.json()
|
||||||
|
assert len(result) == 1
|
||||||
|
assert result[0]["path"] == "file1.txt"
|
||||||
|
assert "size" in result[0]
|
||||||
|
assert "modified" in result[0]
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_split_path(aiohttp_client, app, tmp_path):
|
||||||
|
os.makedirs(tmp_path / "test_dir" / "subdir")
|
||||||
|
with open(tmp_path / "test_dir" / "subdir" / "file1.txt", "w") as f:
|
||||||
|
f.write("test content")
|
||||||
|
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=test_dir&recurse=true&split=true")
|
||||||
|
assert resp.status == 200
|
||||||
|
assert await resp.json() == [
|
||||||
|
["subdir/file1.txt", "subdir", "file1.txt"]
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_invalid_directory(aiohttp_client, app):
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=")
|
||||||
|
assert resp.status == 400
|
||||||
|
|
||||||
|
|
||||||
|
async def test_listuserdata_normalized_separator(aiohttp_client, app, tmp_path):
|
||||||
|
os_sep = "\\"
|
||||||
|
with patch("os.sep", os_sep):
|
||||||
|
with patch("os.path.sep", os_sep):
|
||||||
|
os.makedirs(tmp_path / "test_dir" / "subdir")
|
||||||
|
with open(tmp_path / "test_dir" / "subdir" / "file1.txt", "w") as f:
|
||||||
|
f.write("test content")
|
||||||
|
|
||||||
|
client = await aiohttp_client(app)
|
||||||
|
resp = await client.get("/userdata?dir=test_dir&recurse=true")
|
||||||
|
assert resp.status == 200
|
||||||
|
result = await resp.json()
|
||||||
|
assert len(result) == 1
|
||||||
|
assert "/" in result[0] # Ensure forward slash is used
|
||||||
|
assert "\\" not in result[0] # Ensure backslash is not present
|
||||||
|
assert result[0] == "subdir/file1.txt"
|
||||||
|
|
||||||
|
# Test with full_info
|
||||||
|
resp = await client.get(
|
||||||
|
"/userdata?dir=test_dir&recurse=true&full_info=true"
|
||||||
|
)
|
||||||
|
assert resp.status == 200
|
||||||
|
result = await resp.json()
|
||||||
|
assert len(result) == 1
|
||||||
|
assert "/" in result[0]["path"] # Ensure forward slash is used
|
||||||
|
assert "\\" not in result[0]["path"] # Ensure backslash is not present
|
||||||
|
assert result[0]["path"] == "subdir/file1.txt"
|
||||||
124
tests-unit/utils/extra_config_test.py
Normal file
124
tests-unit/utils/extra_config_test.py
Normal file
@ -0,0 +1,124 @@
|
|||||||
|
import pytest
|
||||||
|
import yaml
|
||||||
|
import os
|
||||||
|
from unittest.mock import Mock, patch, mock_open
|
||||||
|
|
||||||
|
from utils.extra_config import load_extra_path_config
|
||||||
|
import folder_paths
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_yaml_content():
|
||||||
|
return {
|
||||||
|
'test_config': {
|
||||||
|
'base_path': '~/App/',
|
||||||
|
'checkpoints': 'subfolder1',
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_expanded_home():
|
||||||
|
return '/home/user'
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def yaml_config_with_appdata():
|
||||||
|
return """
|
||||||
|
test_config:
|
||||||
|
base_path: '%APPDATA%/ComfyUI'
|
||||||
|
checkpoints: 'models/checkpoints'
|
||||||
|
"""
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_yaml_content_appdata(yaml_config_with_appdata):
|
||||||
|
return yaml.safe_load(yaml_config_with_appdata)
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_expandvars_appdata():
|
||||||
|
mock = Mock()
|
||||||
|
mock.side_effect = lambda path: path.replace('%APPDATA%', 'C:/Users/TestUser/AppData/Roaming')
|
||||||
|
return mock
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_add_model_folder_path():
|
||||||
|
return Mock()
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_expanduser(mock_expanded_home):
|
||||||
|
def _expanduser(path):
|
||||||
|
if path.startswith('~/'):
|
||||||
|
return os.path.join(mock_expanded_home, path[2:])
|
||||||
|
return path
|
||||||
|
return _expanduser
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_yaml_safe_load(mock_yaml_content):
|
||||||
|
return Mock(return_value=mock_yaml_content)
|
||||||
|
|
||||||
|
@patch('builtins.open', new_callable=mock_open, read_data="dummy file content")
|
||||||
|
def test_load_extra_model_paths_expands_userpath(
|
||||||
|
mock_file,
|
||||||
|
monkeypatch,
|
||||||
|
mock_add_model_folder_path,
|
||||||
|
mock_expanduser,
|
||||||
|
mock_yaml_safe_load,
|
||||||
|
mock_expanded_home
|
||||||
|
):
|
||||||
|
# Attach mocks used by load_extra_path_config
|
||||||
|
monkeypatch.setattr(folder_paths, 'add_model_folder_path', mock_add_model_folder_path)
|
||||||
|
monkeypatch.setattr(os.path, 'expanduser', mock_expanduser)
|
||||||
|
monkeypatch.setattr(yaml, 'safe_load', mock_yaml_safe_load)
|
||||||
|
|
||||||
|
dummy_yaml_file_name = 'dummy_path.yaml'
|
||||||
|
load_extra_path_config(dummy_yaml_file_name)
|
||||||
|
|
||||||
|
expected_calls = [
|
||||||
|
('checkpoints', os.path.join(mock_expanded_home, 'App', 'subfolder1')),
|
||||||
|
]
|
||||||
|
|
||||||
|
assert mock_add_model_folder_path.call_count == len(expected_calls)
|
||||||
|
|
||||||
|
# Check if add_model_folder_path was called with the correct arguments
|
||||||
|
for actual_call, expected_call in zip(mock_add_model_folder_path.call_args_list, expected_calls):
|
||||||
|
assert actual_call.args == expected_call
|
||||||
|
|
||||||
|
# Check if yaml.safe_load was called
|
||||||
|
mock_yaml_safe_load.assert_called_once()
|
||||||
|
|
||||||
|
# Check if open was called with the correct file path
|
||||||
|
mock_file.assert_called_once_with(dummy_yaml_file_name, 'r')
|
||||||
|
|
||||||
|
@patch('builtins.open', new_callable=mock_open)
|
||||||
|
def test_load_extra_model_paths_expands_appdata(
|
||||||
|
mock_file,
|
||||||
|
monkeypatch,
|
||||||
|
mock_add_model_folder_path,
|
||||||
|
mock_expandvars_appdata,
|
||||||
|
yaml_config_with_appdata,
|
||||||
|
mock_yaml_content_appdata
|
||||||
|
):
|
||||||
|
# Set the mock_file to return yaml with appdata as a variable
|
||||||
|
mock_file.return_value.read.return_value = yaml_config_with_appdata
|
||||||
|
|
||||||
|
# Attach mocks
|
||||||
|
monkeypatch.setattr(folder_paths, 'add_model_folder_path', mock_add_model_folder_path)
|
||||||
|
monkeypatch.setattr(os.path, 'expandvars', mock_expandvars_appdata)
|
||||||
|
monkeypatch.setattr(yaml, 'safe_load', Mock(return_value=mock_yaml_content_appdata))
|
||||||
|
|
||||||
|
# Mock expanduser to do nothing (since we're not testing it here)
|
||||||
|
monkeypatch.setattr(os.path, 'expanduser', lambda x: x)
|
||||||
|
|
||||||
|
dummy_yaml_file_name = 'dummy_path.yaml'
|
||||||
|
load_extra_path_config(dummy_yaml_file_name)
|
||||||
|
|
||||||
|
expected_base_path = 'C:/Users/TestUser/AppData/Roaming/ComfyUI'
|
||||||
|
expected_calls = [
|
||||||
|
('checkpoints', os.path.join(expected_base_path, 'models/checkpoints')),
|
||||||
|
]
|
||||||
|
|
||||||
|
assert mock_add_model_folder_path.call_count == len(expected_calls)
|
||||||
|
|
||||||
|
# Check the base path variable was expanded
|
||||||
|
for actual_call, expected_call in zip(mock_add_model_folder_path.call_args_list, expected_calls):
|
||||||
|
assert actual_call.args == expected_call
|
||||||
|
|
||||||
|
# Verify that expandvars was called
|
||||||
|
assert mock_expandvars_appdata.called
|
||||||
0
utils/__init__.py
Normal file
0
utils/__init__.py
Normal file
25
utils/extra_config.py
Normal file
25
utils/extra_config.py
Normal file
@ -0,0 +1,25 @@
|
|||||||
|
import os
|
||||||
|
import yaml
|
||||||
|
import folder_paths
|
||||||
|
import logging
|
||||||
|
|
||||||
|
def load_extra_path_config(yaml_path):
|
||||||
|
with open(yaml_path, 'r') as stream:
|
||||||
|
config = yaml.safe_load(stream)
|
||||||
|
for c in config:
|
||||||
|
conf = config[c]
|
||||||
|
if conf is None:
|
||||||
|
continue
|
||||||
|
base_path = None
|
||||||
|
if "base_path" in conf:
|
||||||
|
base_path = conf.pop("base_path")
|
||||||
|
base_path = os.path.expandvars(os.path.expanduser(base_path))
|
||||||
|
for x in conf:
|
||||||
|
for y in conf[x].split("\n"):
|
||||||
|
if len(y) == 0:
|
||||||
|
continue
|
||||||
|
full_path = y
|
||||||
|
if base_path is not None:
|
||||||
|
full_path = os.path.join(base_path, full_path)
|
||||||
|
logging.info("Adding extra search path {} {}".format(x, full_path))
|
||||||
|
folder_paths.add_model_folder_path(x, full_path)
|
||||||
Loading…
x
Reference in New Issue
Block a user