From 783f20b5d773d3e7b3b719706cf7fb328e0ee9c0 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Fri, 20 Mar 2026 18:42:00 -0700
Subject: [PATCH 01/25] Remove RUF013 from ignored rules

---
 pyproject.toml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index cd517e67a..57db5b62f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -97,7 +97,6 @@ ignore = [
   "RUF008", # Do not use mutable default values for dataclass
   "RUF010", # Use explicit conversion flag
   "RUF012", # Mutable class attributes
-  "RUF013", # PEP 484 prohibits implicit `Optional`
   "RUF015", # Prefer `next(...)` over single element slice
   "RUF022", # All is not sorted
   "RUF046", # Value being cast to `int` is already an integer

From 8e10ec3fec31bbb516893ebe1a8e594645823378 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Fri, 20 Mar 2026 18:42:44 -0700
Subject: [PATCH 02/25] RUF013 compatibility

---
 cli/api-checkpoint.py | 2 +-
 cli/api-control.py    | 2 +-
 cli/api-detect.py     | 2 +-
 cli/api-enhance.py    | 2 +-
 cli/api-faceid.py     | 2 +-
 cli/api-grid.py       | 2 +-
 cli/api-img2img.py    | 2 +-
 cli/api-info.py       | 4 ++--
 cli/api-json.py       | 2 +-
 cli/api-mask.py       | 4 ++--
 cli/api-preprocess.py | 4 ++--
 cli/api-txt2img.py    | 2 +-
 cli/api-upscale.py    | 4 ++--
 cli/api-vqa.py        | 4 ++--
 cli/api-xyz.py        | 2 +-
 cli/api-xyzenum.py    | 2 +-
 cli/civitai-search.py | 6 +++---
 cli/gen-styles.py     | 2 +-
 cli/image-search.py   | 6 +++---
 cli/process.py        | 4 ++--
 cli/sdapi.py          | 8 ++++----
 21 files changed, 34 insertions(+), 34 deletions(-)

diff --git a/cli/api-checkpoint.py b/cli/api-checkpoint.py
index ff939f64e..61c799d83 100755
--- a/cli/api-checkpoint.py
+++ b/cli/api-checkpoint.py
@@ -24,7 +24,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-control.py b/cli/api-control.py
index 0e73e94be..865e5b54d 100755
--- a/cli/api-control.py
+++ b/cli/api-control.py
@@ -30,7 +30,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-detect.py b/cli/api-detect.py
index ca121b220..8d1ab2b7a 100755
--- a/cli/api-detect.py
+++ b/cli/api-detect.py
@@ -23,7 +23,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-enhance.py b/cli/api-enhance.py
index 520625edd..0acb7d1ab 100755
--- a/cli/api-enhance.py
+++ b/cli/api-enhance.py
@@ -24,7 +24,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-faceid.py b/cli/api-faceid.py
index 18f1d3503..bf9c8a1f0 100755
--- a/cli/api-faceid.py
+++ b/cli/api-faceid.py
@@ -29,7 +29,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-grid.py b/cli/api-grid.py
index e41276bb9..769fbab35 100755
--- a/cli/api-grid.py
+++ b/cli/api-grid.py
@@ -79,7 +79,7 @@ def generate(x: int, y: int): # pylint: disable=redefined-outer-name
     return images
 
 
-def merge(images: list[Image.Image], horizontal: bool, labels: list[str] = None):
+def merge(images: list[Image.Image], horizontal: bool, labels: list[str] | None = None):
     rows = 1 if horizontal else len(images)
     cols = math.ceil(len(images) / rows)
     w = max([i.size[0] for i in images])
diff --git a/cli/api-img2img.py b/cli/api-img2img.py
index 99ab5ac34..49b23b5d7 100755
--- a/cli/api-img2img.py
+++ b/cli/api-img2img.py
@@ -29,7 +29,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-info.py b/cli/api-info.py
index 1056ddf2a..8032a628c 100755
--- a/cli/api-info.py
+++ b/cli/api-info.py
@@ -24,7 +24,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json=dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
@@ -32,7 +32,7 @@ def get(endpoint: str, dct: dict = None):
         return req.json()
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-json.py b/cli/api-json.py
index 61e5ec3ce..d0e657af6 100755
--- a/cli/api-json.py
+++ b/cli/api-json.py
@@ -28,7 +28,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, payload: dict = None):
+def post(endpoint: str, payload: dict | None = None):
     if 'sdapi' not in endpoint:
         endpoint = f'sdapi/v1/{endpoint}'
     if 'http' not in endpoint:
diff --git a/cli/api-mask.py b/cli/api-mask.py
index 38aae3018..f8ee56a10 100755
--- a/cli/api-mask.py
+++ b/cli/api-mask.py
@@ -26,7 +26,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json=dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
@@ -34,7 +34,7 @@ def get(endpoint: str, dct: dict = None):
         return req.json()
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-preprocess.py b/cli/api-preprocess.py
index abb6a9d2f..b51bfbed9 100755
--- a/cli/api-preprocess.py
+++ b/cli/api-preprocess.py
@@ -26,7 +26,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json=dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
@@ -34,7 +34,7 @@ def get(endpoint: str, dct: dict = None):
         return req.json()
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-txt2img.py b/cli/api-txt2img.py
index 19ee6d474..648b72576 100755
--- a/cli/api-txt2img.py
+++ b/cli/api-txt2img.py
@@ -28,7 +28,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-upscale.py b/cli/api-upscale.py
index 488f2db45..2498da964 100755
--- a/cli/api-upscale.py
+++ b/cli/api-upscale.py
@@ -24,7 +24,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json=dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
@@ -32,7 +32,7 @@ def get(endpoint: str, dct: dict = None):
         return req.json()
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-vqa.py b/cli/api-vqa.py
index 87a3ef2b6..b93d8a15f 100755
--- a/cli/api-vqa.py
+++ b/cli/api-vqa.py
@@ -24,7 +24,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json=dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
@@ -32,7 +32,7 @@ def get(endpoint: str, dct: dict = None):
         return req.json()
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-xyz.py b/cli/api-xyz.py
index e82fa23a8..50a0f3ecf 100755
--- a/cli/api-xyz.py
+++ b/cli/api-xyz.py
@@ -30,7 +30,7 @@ def auth():
     return None
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/api-xyzenum.py b/cli/api-xyzenum.py
index e5eb12f83..0decd02f3 100755
--- a/cli/api-xyzenum.py
+++ b/cli/api-xyzenum.py
@@ -24,7 +24,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json = dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/civitai-search.py b/cli/civitai-search.py
index cdb29c7ab..b8fbc68b3 100755
--- a/cli/civitai-search.py
+++ b/cli/civitai-search.py
@@ -99,10 +99,10 @@ def search_civitai(
         types:str = '', # (Checkpoint, TextualInversion, Hypernetwork, AestheticGradient, LORA, Controlnet, Poses)
         sort:str = '', # (Highest Rated, Most Downloaded, Newest)
         period:str = '', # (AllTime, Year, Month, Week, Day)
-        nsfw:bool = None, # optional:bool
+        nsfw:bool | None = None, # optional:bool
         limit:int = 0,
         base:list[str] = [], # list
-        token:str = None,
+        token:str | None = None,
         exact:bool = True,
 ):
     import requests
@@ -169,7 +169,7 @@ def search_civitai(
     return exact_models if len(exact_models) > 0 else models
 
 
-def models_to_dct(all_models:list, model_id:int=None):
+def models_to_dct(all_models:list, model_id:int | None=None):
     dct = []
     for model in all_models:
         if model_id is not None and model.id != model_id:
diff --git a/cli/gen-styles.py b/cli/gen-styles.py
index ec1f1089f..1171265a5 100755
--- a/cli/gen-styles.py
+++ b/cli/gen-styles.py
@@ -33,7 +33,7 @@ def pil_to_b64(img: Image, size: int, quality: int):
     return f'data:image/jpeg;base64,{b64encoded}'
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(endpoint, json = dct, timeout=300, verify=False)
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/cli/image-search.py b/cli/image-search.py
index 8b740a82e..5be923e6e 100755
--- a/cli/image-search.py
+++ b/cli/image-search.py
@@ -19,7 +19,7 @@ class ImageDB:
     def __init__(self,
                  name:str='db',
                  fmt:str='json',
-                 cache_dir:str=None,
+                 cache_dir:str | None=None,
                  dtype:torch.dtype=torch.float16,
                  device:torch.device=torch.device('cpu'),
                  model:str='openai/clip-vit-large-patch14', # 'facebook/dinov2-small'
@@ -123,8 +123,8 @@ class ImageDB:
             self.df = rec
         self.index.add(embed)
 
-    def search(self, filename: str = None, metadata: str = None, embed: np.ndarray = None, k=10, d=1.0): # search by filename/metadata/prompt-embed/image-embed
-        def dct(record: pd.DataFrame, mode: str, distance: float = None):
+    def search(self, filename: str | None = None, metadata: str | None = None, embed: np.ndarray = None, k=10, d=1.0): # search by filename/metadata/prompt-embed/image-embed
+        def dct(record: pd.DataFrame, mode: str, distance: float | None = None):
             if distance is not None:
                 return {'type': mode, 'filename': record[1]['filename'], 'metadata': record[1]['metadata'], 'distance': round(distance, 2)}
             else:
diff --git a/cli/process.py b/cli/process.py
index 3461e8f04..dcb4278d9 100644
--- a/cli/process.py
+++ b/cli/process.py
@@ -21,7 +21,7 @@ all_images_by_type = {}
 
 
 class Result():
-    def __init__(self, typ: str, fn: str, tag: str = None, requested: list = []):
+    def __init__(self, typ: str, fn: str, tag: str | None = None, requested: list = []):
         self.type = typ
         self.input = fn
         self.output = ''
@@ -144,7 +144,7 @@ def upscale_restore_image(res: Result, upscale: bool = False):
     return res
 
 
-def caption_image(res: Result, tag: str = None):
+def caption_image(res: Result, tag: str | None = None):
     caption = ''
     tags = []
     for model in options.process.caption_model:
diff --git a/cli/sdapi.py b/cli/sdapi.py
index a91910b1b..6c01d7de3 100755
--- a/cli/sdapi.py
+++ b/cli/sdapi.py
@@ -93,7 +93,7 @@ def resultsync(req: requests.Response):
         return res
 
 
-async def get(endpoint: str, json: dict = None):
+async def get(endpoint: str, json: dict | None = None):
     global sess # pylint: disable=global-statement
     sess = sess if sess is not None else await session()
     try:
@@ -105,7 +105,7 @@ async def get(endpoint: str, json: dict = None):
         return {}
 
 
-def getsync(endpoint: str, json: dict = None):
+def getsync(endpoint: str, json: dict | None = None):
     try:
         req = requests.get(f'{sd_url}{endpoint}', json=json, verify=False, auth=authsync()) # pylint: disable=missing-timeout
         res = resultsync(req)
@@ -115,7 +115,7 @@ def getsync(endpoint: str, json: dict = None):
         return {}
 
 
-async def post(endpoint: str, json: dict = None):
+async def post(endpoint: str, json: dict | None = None):
     global sess # pylint: disable=global-statement
     # sess = sess if sess is not None else await session()
     if sess and not sess.closed:
@@ -130,7 +130,7 @@ async def post(endpoint: str, json: dict = None):
         return {}
 
 
-def postsync(endpoint: str, json: dict = None):
+def postsync(endpoint: str, json: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json=json, verify=False, auth=authsync()) # pylint: disable=missing-timeout
     res = resultsync(req)
     return res

From d474f28cb372e883d3da38e769add4c20aed5695 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Mon, 23 Mar 2026 22:53:34 -0700
Subject: [PATCH 03/25] RUF013 update

---
 modules/api/docs.py      |  8 ++++----
 modules/api/endpoints.py |  2 +-
 modules/api/models.py    | 12 ++++++------
 3 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/modules/api/docs.py b/modules/api/docs.py
index 1eac8226e..2d5ff6e4a 100644
--- a/modules/api/docs.py
+++ b/modules/api/docs.py
@@ -10,11 +10,11 @@ def get_swagger_ui_html(*,
                         title: str,
                         swagger_js_url: str = "https://cdn.jsdelivr.net/npm/swagger-ui-dist@5/swagger-ui-bundle.js",
                         swagger_css_url: str = "https://cdn.jsdelivr.net/npm/swagger-ui-dist@5/swagger-ui.css",
-                        swagger_extra_css_url: str = None,
+                        swagger_extra_css_url: str | None = None,
                         swagger_favicon_url: str = "https://fastapi.tiangolo.com/img/favicon.png",
-                        oauth2_redirect_url: str = None,
-                        init_oauth: dict = None,
-                        swagger_ui_parameters: dict = None,
+                        oauth2_redirect_url: str | None = None,
+                        init_oauth: dict | None = None,
+                        swagger_ui_parameters: dict | None = None,
                        ) -> HTMLResponse:
     current_swagger_ui_parameters = swagger_ui_default_parameters.copy()
     if swagger_ui_parameters:
diff --git a/modules/api/endpoints.py b/modules/api/endpoints.py
index 775fa1bc9..f950db601 100644
--- a/modules/api/endpoints.py
+++ b/modules/api/endpoints.py
@@ -242,7 +242,7 @@ def get_checkpoint():
             checkpoint['hash'] = shared.sd_model.sd_checkpoint_info.shorthash
     return checkpoint
 
-def set_checkpoint(sd_model_checkpoint: str, dtype:str=None, force:bool=False):
+def set_checkpoint(sd_model_checkpoint: str, dtype: str | None = None, force: bool = False):
     """Load a checkpoint by name. Optionally set dtype and force a clean reload."""
     from modules import sd_models, devices
     if force:
diff --git a/modules/api/models.py b/modules/api/models.py
index f51bd3ad9..f32152027 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -57,10 +57,10 @@ def underscore(name: str) -> str: # Convert CamelCase or PascalCase string to un
 class PydanticModelGenerator:
     def __init__(
         self,
-        model_name: str = None,
-        class_instance = None,
-        additional_fields = None,
-        exclude_fields: list = None,
+        model_name: str,
+        class_instance,
+        additional_fields: list,
+        exclude_fields: list | None = None,
     ):
         if exclude_fields is None:
             exclude_fields = []
@@ -100,7 +100,7 @@ class PydanticModelGenerator:
             self._model_def = [x for x in self._model_def if x.field != fld]
 
     def generate_model(self):
-        model_fields = { d.field: (d.field_type, Field(default=d.field_value, alias=d.field_alias, exclude=d.field_exclude)) for d in self._model_def }
+        model_fields: dict[str, Any] = { d.field: (d.field_type, Field(default=d.field_value, alias=d.field_alias, exclude=d.field_exclude)) for d in self._model_def }
         if PYDANTIC_V2:
             config = ConfigDict(arbitrary_types_allowed=True, from_attributes=True, populate_by_name=True)
         else:
@@ -507,7 +507,7 @@ class ItemLoadedModel(BaseModel):
 
 # helper function
 
-def create_model_from_signature(func: Callable, model_name: str, base_model: type[BaseModel] = BaseModel, additional_fields: list = None, exclude_fields: list[str] = None) -> type[BaseModel]:
+def create_model_from_signature(func: Callable, model_name: str, base_model: type[BaseModel] = BaseModel, additional_fields: list | None = None, exclude_fields: list[str] | None = None) -> type[BaseModel]:
     from PIL import Image
 
     if exclude_fields is None:

From de86927c1b5b734d3aa5abd00039780c1c440de5 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Mon, 23 Mar 2026 22:54:40 -0700
Subject: [PATCH 04/25] Remove unneeded type and default

---
 modules/attention.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/attention.py b/modules/attention.py
index 8224f59df..24c30582d 100644
--- a/modules/attention.py
+++ b/modules/attention.py
@@ -186,11 +186,11 @@ def set_sage_attention(backend: str, device: torch.device):
         log.error(f'Torch attention: type="Sage attention" {err}')
 
 
-def set_diffusers_attention(pipe, quiet:bool=False):
+def set_diffusers_attention(pipe, quiet = False):
     from modules import shared
     import diffusers.models.attention_processor as p
 
-    def set_attn(pipe, attention, name:str=None):
+    def set_attn(pipe, attention, name: str):
         if attention is None:
             return
         # other models uses their own attention processor

From 3e228afa7827acebd9e6251a4f7ae06028d9c8af Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Mon, 23 Mar 2026 22:57:35 -0700
Subject: [PATCH 05/25] RUF013 update

---
 modules/caption/deepbooru.py      | 16 +++++-----
 modules/caption/joycaption.py     |  8 ++---
 modules/caption/moondream3.py     | 10 +++----
 modules/caption/tagger.py         |  2 +-
 modules/caption/vqa.py            | 49 +++++++++++++++++++------------
 modules/caption/vqa_detection.py  |  6 ++--
 modules/caption/waifudiffusion.py | 24 +++++++--------
 7 files changed, 63 insertions(+), 52 deletions(-)

diff --git a/modules/caption/deepbooru.py b/modules/caption/deepbooru.py
index 6ccb848b1..878b3852a 100644
--- a/modules/caption/deepbooru.py
+++ b/modules/caption/deepbooru.py
@@ -53,13 +53,13 @@ class DeepDanbooru:
     def tag_multi(
         self,
         pil_image,
-        general_threshold: float = None,
-        include_rating: bool = None,
-        exclude_tags: str = None,
-        max_tags: int = None,
-        sort_alpha: bool = None,
-        use_spaces: bool = None,
-        escape_brackets: bool = None,
+        general_threshold: float | None = None,
+        include_rating: bool | None = None,
+        exclude_tags: str | None = None,
+        max_tags: int | None = None,
+        sort_alpha: bool | None = None,
+        use_spaces: bool | None = None,
+        escape_brackets: bool | None = None,
     ):
         """Run inference and return formatted tag string.
 
@@ -134,7 +134,7 @@ def get_models() -> list:
     return ["DeepBooru"]
 
 
-def load_model(model_name: str = None) -> bool: # pylint: disable=unused-argument
+def load_model(model_name: str = "") -> bool: # pylint: disable=unused-argument
     """Load the DeepBooru model."""
     try:
         model.load()
diff --git a/modules/caption/joycaption.py b/modules/caption/joycaption.py
index dbee83eba..a18b46800 100644
--- a/modules/caption/joycaption.py
+++ b/modules/caption/joycaption.py
@@ -53,12 +53,12 @@ class JoyOptions:
         return f'repo="{self.repo}" temp={self.temp} top_k={self.top_k} top_p={self.top_p} sample={self.sample} tokens={self.max_new_tokens}'
 
 
-processor: AutoProcessor = None
-llava_model: LlavaForConditionalGeneration = None
+processor: AutoProcessor | None = None
+llava_model: LlavaForConditionalGeneration | None = None
 opts = JoyOptions()
 
 
-def load(repo: str = None):
+def load(repo: str | None = None):
     """Load JoyCaption model."""
     global llava_model, processor  # pylint: disable=global-statement
     repo = repo or opts.repo
@@ -93,7 +93,7 @@ def unload():
         log.debug('JoyCaption unload: no model loaded')
 
 
-def predict(question: str, image, vqa_model: str = None) -> str:
+def predict(question: str, image, vqa_model: str | None = None) -> str:
     opts.max_new_tokens = shared.opts.caption_vlm_max_length
     load(vqa_model)
 
diff --git a/modules/caption/moondream3.py b/modules/caption/moondream3.py
index 20418134c..7859f0f06 100644
--- a/modules/caption/moondream3.py
+++ b/modules/caption/moondream3.py
@@ -87,7 +87,7 @@ def _image_hash(image: Image.Image) -> str:
     return h.hexdigest()
 
 
-def encode_image(image: Image.Image, cache_key: str = None):
+def encode_image(image: Image.Image, cache_key: str | None = None):
     """
     Encode image for reuse across multiple queries.
 
@@ -119,7 +119,7 @@ def encode_image(image: Image.Image, cache_key: str = None):
 
 
 def query(image: Image.Image, question: str, repo: str, stream: bool = False,
-          temperature: float = None, top_p: float = None, max_tokens: int = None,
+          temperature: float | None = None, top_p: float | None = None, max_tokens: int | None = None,
           use_cache: bool = False, reasoning: bool = True):
     """
     Visual question answering with optional streaming.
@@ -180,7 +180,7 @@ def query(image: Image.Image, question: str, repo: str, stream: bool = False,
 
 
 def caption(image: Image.Image, repo: str, length: str = 'normal', stream: bool = False,
-            temperature: float = None, top_p: float = None, max_tokens: int = None):
+            temperature: float | None = None, top_p: float | None = None, max_tokens: int | None = None):
     """
     Generate image captions at different lengths.
 
@@ -290,8 +290,8 @@ def detect(image: Image.Image, object_name: str, repo: str, max_objects: int = 1
     return detections
 
 
-def predict(question: str, image: Image.Image, repo: str, model_name: str = None, thinking_mode: bool = False,
-            mode: str = None, stream: bool = False, use_cache: bool = False, **kwargs):
+def predict(question: str, image: Image.Image, repo: str, model_name: str | None = None, thinking_mode: bool = False,
+            mode: str | None = None, stream: bool = False, use_cache: bool = False, **kwargs):
     """
     Main entry point for Moondream 3 VQA - auto-detects mode from question.
 
diff --git a/modules/caption/tagger.py b/modules/caption/tagger.py
index e73e7df4d..6f2436b38 100644
--- a/modules/caption/tagger.py
+++ b/modules/caption/tagger.py
@@ -65,7 +65,7 @@ def unload_model():
     waifudiffusion.unload_model()
 
 
-def tag(image, model_name: str = None, **kwargs) -> str:
+def tag(image, model_name: str | None = None, **kwargs) -> str:
     """Unified tagging - dispatch to correct backend.
 
     Args:
diff --git a/modules/caption/vqa.py b/modules/caption/vqa.py
index a10818624..807479144 100644
--- a/modules/caption/vqa.py
+++ b/modules/caption/vqa.py
@@ -50,7 +50,7 @@ def get_prompts_for_model(model_name: str) -> list:
     return vlm_prompts_common
 
 
-def get_internal_prompt(friendly_name: str, user_prompt: str = None) -> str:
+def get_internal_prompt(friendly_name: str, user_prompt: str | None = None) -> str:
     """Convert friendly prompt name to internal token/command."""
     internal = vlm_prompt_mapping.get(friendly_name, friendly_name)
 
@@ -350,7 +350,7 @@ class VQA:
             self.processor = None
             devices.torch_gc(force=True, reason='vqa model switch')
 
-    def load(self, model_name: str = None):
+    def load(self, model_name: str | None = None):
         """Load VLM model into memory for the specified model name."""
         model_name = model_name or shared.opts.caption_vlm_model
         if not model_name:
@@ -444,7 +444,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _fastvlm(self, question: str, image: Image.Image, repo: str, model_name: str = None):
+    def _fastvlm(self, question: str, image: Image.Image, repo: str, model_name: str | None = None):
         debug(f'VQA caption: handler=fastvlm model_name="{model_name}" repo="{repo}" question="{question}" image_size={image.size if image else None}')
         self._load_fastvlm(repo)
         move_aux_to_gpu('vqa')
@@ -521,7 +521,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _qwen(self, question: str, image: Image.Image, repo: str, system_prompt: str = None, model_name: str = None, prefill: str = None, thinking_mode: bool = False):
+    def _qwen(self, question: str, image: Image.Image, repo: str, system_prompt: str | None = None, model_name: str | None = None, prefill: str | None = None, thinking_mode: bool = False):
         self._load_qwen(repo)
         move_aux_to_gpu('vqa')
         # Get model class name for logging
@@ -644,7 +644,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _gemma(self, question: str, image: Image.Image, repo: str, system_prompt: str = None, model_name: str = None, prefill: str = None, thinking_mode: bool = False):
+    def _gemma(self, question: str, image: Image.Image, repo: str, system_prompt: str | None = None, model_name: str | None = None, prefill: str | None = None, thinking_mode: bool = False):
         self._load_gemma(repo)
         move_aux_to_gpu('vqa')
         # Get model class name for logging
@@ -757,7 +757,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _mistral(self, question: str, image: Image.Image, repo: str, system_prompt: str = None, model_name: str = None, prefill: str = None, thinking_mode: bool = False):
+    def _mistral(self, question: str, image: Image.Image, repo: str, system_prompt: str | None = None, model_name: str | None = None, prefill: str | None = None, thinking_mode: bool = False):
         self._load_mistral(repo)
         move_aux_to_gpu('vqa')
         cls_name = self.model.__class__.__name__
@@ -828,7 +828,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _paligemma(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _paligemma(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_paligemma(repo)
         move_aux_to_gpu('vqa')
         question = question.replace('<', '').replace('>', '').replace('_', ' ')
@@ -870,7 +870,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _ovis(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _ovis(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         try:
             pass  # pylint: disable=unused-import
         except Exception:
@@ -925,7 +925,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _smol(self, question: str, image: Image.Image, repo: str, system_prompt: str = None, model_name: str = None, prefill: str = None, thinking_mode: bool = False):
+    def _smol(self, question: str, image: Image.Image, repo: str, system_prompt: str | None = None, model_name: str | None = None, prefill: str | None = None, thinking_mode: bool = False):
         self._load_smol(repo)
         move_aux_to_gpu('vqa')
         # Get model class name for logging
@@ -1019,7 +1019,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _git(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _git(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_git(repo)
         move_aux_to_gpu('vqa')
         pixel_values = self.processor(images=image, return_tensors="pt").pixel_values
@@ -1053,7 +1053,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _blip(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _blip(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_blip(repo)
         move_aux_to_gpu('vqa')
         inputs = self.processor(image, question, return_tensors="pt")
@@ -1081,7 +1081,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _vilt(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _vilt(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_vilt(repo)
         move_aux_to_gpu('vqa')
         inputs = self.processor(image, question, return_tensors="pt")
@@ -1111,7 +1111,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _pix(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _pix(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_pix(repo)
         move_aux_to_gpu('vqa')
         if len(question) > 0:
@@ -1144,7 +1144,7 @@ class VQA:
             register_aux('vqa', self.model)
             devices.torch_gc()
 
-    def _moondream(self, question: str, image: Image.Image, repo: str, model_name: str = None, thinking_mode: bool = False):
+    def _moondream(self, question: str, image: Image.Image, repo: str, model_name: str | None = None, thinking_mode: bool = False):
         debug(f'VQA caption: handler=moondream model_name="{model_name}" repo="{repo}" question="{question}" thinking_mode={thinking_mode}')
         self._load_moondream(repo)
         move_aux_to_gpu('vqa')
@@ -1207,7 +1207,7 @@ class VQA:
                     # When keep_thinking is False, just use the answer (reasoning is discarded)
         return response
 
-    def _load_florence(self, repo: str, revision: str = None):
+    def _load_florence(self, repo: str, revision: str | None = None):
         """Load Florence-2 model and processor."""
         _get_imports = transformers.dynamic_module_utils.get_imports
 
@@ -1247,7 +1247,7 @@ class VQA:
             self.loaded = cache_key
             devices.torch_gc()
 
-    def _florence(self, question: str, image: Image.Image, repo: str, revision: str = None, model_name: str = None): # pylint: disable=unused-argument
+    def _florence(self, question: str, image: Image.Image, repo: str, revision: str | None = None, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_florence(repo, revision)
         move_aux_to_gpu('vqa')
         if question.startswith('<'):
@@ -1306,7 +1306,7 @@ class VQA:
             self.loaded = repo
             devices.torch_gc()
 
-    def _sa2(self, question: str, image: Image.Image, repo: str, model_name: str = None): # pylint: disable=unused-argument
+    def _sa2(self, question: str, image: Image.Image, repo: str, model_name: str | None = None): # pylint: disable=unused-argument
         self._load_sa2(repo)
         move_aux_to_gpu('vqa')
         if question.startswith('<'):
@@ -1325,7 +1325,18 @@ class VQA:
         response = return_dict["prediction"]  # the text format answer
         return response
 
-    def caption(self, question: str = '', system_prompt: str = None, prompt: str = None, image: Image.Image = None, model_name: str = None, prefill: str = None, thinking_mode: bool = None, quiet: bool = False, generation_kwargs: dict = None) -> str:
+    def caption(
+        self,
+        question: str = "",
+        system_prompt: str | None = None,
+        prompt: str | None = None,
+        image: list[Image.Image] | Image.Image | dict | None = None,
+        model_name: str | None = None,
+        prefill: str | None = None,
+        thinking_mode: bool | None = None,
+        quiet: bool = False,
+        generation_kwargs: dict | None = None,
+    ) -> str:
         """
         Main entry point for VQA captioning. Returns string answer.
         Detection data stored in self.last_detection_data for annotated image creation.
@@ -1596,7 +1607,7 @@ def unload_model():
     return get_instance().unload()
 
 
-def load_model(model_name: str = None):
+def load_model(model_name: str | None = None):
     return get_instance().load(model_name)
 
 
diff --git a/modules/caption/vqa_detection.py b/modules/caption/vqa_detection.py
index d0aadf970..683067250 100644
--- a/modules/caption/vqa_detection.py
+++ b/modules/caption/vqa_detection.py
@@ -38,7 +38,7 @@ def parse_points(result) -> list:
     return points
 
 
-def parse_detections(result, label: str, max_objects: int = None) -> list:
+def parse_detections(result, label: str, max_objects: int | None = None) -> list:
     """Parse and validate detection bboxes from model result.
 
     Args:
@@ -74,7 +74,7 @@ def parse_detections(result, label: str, max_objects: int = None) -> list:
     return detections
 
 
-def parse_florence_detections(response, image_size: tuple = None) -> list:
+def parse_florence_detections(response, image_size: tuple | None = None) -> list:
     """Parse Florence-style detection response into standard detection format.
 
     Florence returns detection data in two possible formats:
@@ -286,7 +286,7 @@ def calculate_eye_position(face_bbox: dict) -> tuple:
     return (eye_x, eye_y)
 
 
-def draw_bounding_boxes(image: Image.Image, detections: list, points: list = None) -> Image.Image:
+def draw_bounding_boxes(image: Image.Image, detections: list, points: list | None = None) -> Image.Image:
     """
     Draw bounding boxes and/or points on an image.
 
diff --git a/modules/caption/waifudiffusion.py b/modules/caption/waifudiffusion.py
index 3e284db75..4fe455553 100644
--- a/modules/caption/waifudiffusion.py
+++ b/modules/caption/waifudiffusion.py
@@ -50,7 +50,7 @@ class WaifuDiffusionTagger:
         self.model_path = None
         self.image_size = 448  # Standard for WD models
 
-    def load(self, model_name: str = None):
+    def load(self, model_name: str | None = None):
         """Load the ONNX model and tags from HuggingFace."""
         import huggingface_hub
 
@@ -195,15 +195,15 @@ class WaifuDiffusionTagger:
 
     def predict(
         self,
-        image: Image.Image,
-        general_threshold: float = None,
-        character_threshold: float = None,
-        include_rating: bool = None,
-        exclude_tags: str = None,
-        max_tags: int = None,
-        sort_alpha: bool = None,
-        use_spaces: bool = None,
-        escape_brackets: bool = None,
+        image: Image.Image | list[Image.Image] | dict | None,
+        general_threshold: float | None = None,
+        character_threshold: float | None = None,
+        include_rating: bool | None = None,
+        exclude_tags: str | None = None,
+        max_tags: int | None = None,
+        sort_alpha: bool | None = None,
+        use_spaces: bool | None = None,
+        escape_brackets: bool | None = None,
     ) -> str:
         """Run inference and return formatted tag string.
 
@@ -352,7 +352,7 @@ def refresh_models() -> list:
     return get_models()
 
 
-def load_model(model_name: str = None) -> bool:
+def load_model(model_name: str | None = None) -> bool:
     """Load the specified WaifuDiffusion model."""
     return tagger.load(model_name)
 
@@ -362,7 +362,7 @@ def unload_model():
     tagger.unload()
 
 
-def tag(image: Image.Image, model_name: str = None, **kwargs) -> str:
+def tag(image: Image.Image, model_name: str | None = None, **kwargs) -> str:
     """Tag an image using WaifuDiffusion tagger.
 
     Args:

From 53598d40ab52c1e31aa043aa5abf0007337d02e1 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Mon, 23 Mar 2026 22:59:32 -0700
Subject: [PATCH 06/25] RUF013 update

---
 modules/civitai/api_civitai.py      | 28 ++++++++++++++--------------
 modules/civitai/download_civitai.py |  2 +-
 modules/civitai/metadata_civitai.py |  2 +-
 modules/civitai/search_civitai.py   |  4 ++--
 modules/civitai/userdata_civitai.py |  2 +-
 5 files changed, 19 insertions(+), 19 deletions(-)

diff --git a/modules/civitai/api_civitai.py b/modules/civitai/api_civitai.py
index de07186fd..37ba28bf0 100644
--- a/modules/civitai/api_civitai.py
+++ b/modules/civitai/api_civitai.py
@@ -87,12 +87,12 @@ def get_search(
     sort: str = '',
     period: str = '',
     base_models: str = '',
-    nsfw: bool = None,
+    nsfw: bool | None = None,
     limit: int = 20,
-    cursor: str = None,
+    cursor: str | None = None,
     username: str = '',
     favorites: bool = False,
-    token: str = None,
+    token: str | None = None,
 ):
     """Search CivitAI models with pagination."""
     from modules.civitai.client_civitai import client
@@ -110,7 +110,7 @@ def get_search(
     return response.dict(by_alias=True)
 
 
-def get_model(model_id: int, token: str = None):
+def get_model(model_id: int, token: str | None = None):
     """Get a single model by ID (fresh fetch)."""
     from modules.civitai.client_civitai import client
     model = client.get_model(model_id, token=token)
@@ -119,7 +119,7 @@ def get_model(model_id: int, token: str = None):
     return model_to_dict(model)
 
 
-def get_version(version_id: int, token: str = None):
+def get_version(version_id: int, token: str | None = None):
     """Get a single version by ID."""
     from modules.civitai.client_civitai import client
     version = client.get_version(version_id, token=token)
@@ -128,7 +128,7 @@ def get_version(version_id: int, token: str = None):
     return version_to_dict(version)
 
 
-def get_version_by_hash(hash_str: str, token: str = None):
+def get_version_by_hash(hash_str: str, token: str | None = None):
     """Look up a version by file hash."""
     from modules.civitai.client_civitai import client
     version = client.get_version_by_hash(hash_str, token=token)
@@ -155,13 +155,13 @@ def get_creators(query: str = '', limit: int = 20, page: int = 1):
     return client.get_creators(query=query, limit=limit, page=page).dict(by_alias=True)
 
 
-def get_images(model_id: int = None, model_version_id: int = None, limit: int = 20):
+def get_images(model_id: int | None = None, model_version_id: int | None = None, limit: int = 20):
     """Get images with generation metadata from CivitAI."""
     from modules.civitai.client_civitai import client
     return {"items": client.get_images_raw(model_id=model_id, model_version_id=model_version_id, limit=limit)}
 
 
-def get_me(token: str = None):
+def get_me(token: str | None = None):
     """Get authenticated CivitAI user profile."""
     from modules.civitai.client_civitai import client
     profile = client.get_me(token=token)
@@ -300,7 +300,7 @@ def get_resolve_path(
 # Metadata
 # ---------------------------------------------------------------------------
 
-def post_metadata_scan(request: dict = None):
+def post_metadata_scan(request: dict | None = None):
     """Scan local models for CivitAI metadata. Optional ``page`` filters by network type (e.g. 'lora', 'model')."""
     from modules.civitai import metadata_civitai
     page = (request or {}).get('page', None)
@@ -388,7 +388,7 @@ def delete_banned(name: str):
 # User Data — Search History
 # ---------------------------------------------------------------------------
 
-def get_history(search_type: str = None):
+def get_history(search_type: str | None = None):
     from modules.civitai.userdata_civitai import search_history
     return {"history": search_history.list(search_type)}
 
@@ -529,16 +529,16 @@ def post_check_local(request: dict):
 # ---------------------------------------------------------------------------
 
 def legacy_get_civitai(
-    model_id: int = None,
+    model_id: int | None = None,
     query: str = '',
     tag: str = '',
     types: str = '',
     sort: str = '',
     period: str = '',
-    nsfw: bool = None,
+    nsfw: bool | None = None,
     limit: int = 0,
     base: str = '',
-    token: str = None,
+    token: str | None = None,
     exact: bool = True,
 ):
     """Legacy GET /sdapi/v1/civitai — delegates to search or model lookup."""
@@ -559,7 +559,7 @@ def legacy_get_civitai(
     return JSONResponse(content=[], status_code=200)
 
 
-def legacy_post_civitai(page: str = None):
+def legacy_post_civitai(page: str | None = None):
     """Legacy POST /sdapi/v1/civitai — scan metadata."""
     from modules.civitai import metadata_civitai
     result = []
diff --git a/modules/civitai/download_civitai.py b/modules/civitai/download_civitai.py
index da5378b41..402f2ac28 100644
--- a/modules/civitai/download_civitai.py
+++ b/modules/civitai/download_civitai.py
@@ -406,7 +406,7 @@ def download_civit_preview(model_path: str, preview_url: str):
     return 200, str(total_size), ''
 
 
-def download_civit_model(model_url: str, model_name: str = '', model_path: str = '', model_type: str = '', token: str = None,
+def download_civit_model(model_url: str, model_name: str = '', model_path: str = '', model_type: str = '', token: str | None = None,
                          base_model: str = '', model_id: int = 0, version_id: int = 0):
     """Legacy function — delegates to DownloadManager for non-blocking downloads."""
     if not model_url:
diff --git a/modules/civitai/metadata_civitai.py b/modules/civitai/metadata_civitai.py
index 57c4e082e..c5c7b89e6 100644
--- a/modules/civitai/metadata_civitai.py
+++ b/modules/civitai/metadata_civitai.py
@@ -169,7 +169,7 @@ def atomic_civit_search_metadata(item, results):
             results.append(dict(result))
 
 
-def civit_search_metadata(title: str = None, raw: bool = False):
+def civit_search_metadata(title: str | None = None, raw: bool = False):
     def create_search_metadata_table(rows):
         html = """
             <table class="simple-table">
diff --git a/modules/civitai/search_civitai.py b/modules/civitai/search_civitai.py
index e3b116dc2..947bcbc51 100644
--- a/modules/civitai/search_civitai.py
+++ b/modules/civitai/search_civitai.py
@@ -15,10 +15,10 @@ def search_civitai(
         types: str = '',
         sort: str = '',
         period: str = '',
-        nsfw: bool = None,
+        nsfw: bool | None = None,
         limit: int = 0,
         base: str = '',
-        token: str = None,
+        token: str | None = None,
         exact: bool = True,
 ) -> list[CivitModel]:
     if not query and not tag and not sort:
diff --git a/modules/civitai/userdata_civitai.py b/modules/civitai/userdata_civitai.py
index d990699a2..64c7efae5 100644
--- a/modules/civitai/userdata_civitai.py
+++ b/modules/civitai/userdata_civitai.py
@@ -111,7 +111,7 @@ class SearchHistory:
                 self._entries = self._entries[:self._max_entries]
             self._save()
 
-    def list(self, search_type: str = None) -> list[dict]:
+    def list(self, search_type: str | None = None) -> list[dict]:
         with self._lock:
             if search_type:
                 return [e for e in self._entries if e.get('type') == search_type]

From b75a1f971fa0716b40fe0adc371ee98fd7e79be4 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 03:39:02 -0700
Subject: [PATCH 07/25] RUF013 update + minor typing fixes

---
 modules/control/processor.py  | 26 +++++-----
 modules/control/processors.py | 13 ++---
 modules/control/run.py        | 92 +++++++++++++++++------------------
 modules/control/unit.py       | 31 +++++++-----
 4 files changed, 86 insertions(+), 76 deletions(-)

diff --git a/modules/control/processor.py b/modules/control/processor.py
index ee9189b97..56fa66f66 100644
--- a/modules/control/processor.py
+++ b/modules/control/processor.py
@@ -61,19 +61,19 @@ processors = [
 
 
 def preprocess_image(
-        p:StableDiffusionProcessingControl,
-        pipe,
-        input_image:Image.Image = None,
-        init_image:Image.Image = None,
-        input_mask:Image.Image = None,
-        input_type:str = 0,
-        unit_type:str = 'controlnet',
-        active_process:list = None,
-        active_model:list = None,
-        selected_models:list = None,
-        has_models:bool = False,
-        active_units:list = None,
-    ):
+    p: StableDiffusionProcessingControl,
+    pipe,
+    input_image: Image.Image | None= None,
+    init_image: Image.Image | None = None,
+    input_mask: Image.Image | None = None,
+    input_type = 0,
+    unit_type = "controlnet",
+    active_process: list | None = None,
+    active_model: list | None = None,
+    selected_models: list | None = None,
+    has_models = False,
+    active_units: list | None = None,
+):
     if selected_models is None:
         selected_models = []
     if active_model is None:
diff --git a/modules/control/processors.py b/modules/control/processors.py
index 6be1f570b..accdc1f67 100644
--- a/modules/control/processors.py
+++ b/modules/control/processors.py
@@ -195,20 +195,21 @@ def update_settings(*settings):
 
 
 class Processor:
-    def __init__(self, processor_id: str = None, resize = True):
+    def __init__(self, processor_id: str | None = None, resize = True):
         self.model = None
-        self.processor_id = None
-        self.override = None
+        self.processor_id: str | None = None
+        self.override: Image.Image | None = None
         self.resize = resize
         self.reset()
         self.config(processor_id)
+        self.load_config: dict = {}
         if processor_id is not None:
             self.load()
 
     def __str__(self):
         return f' Processor(id={self.processor_id} model={self.model.__class__.__name__})' if self.processor_id and self.model else ''
 
-    def reset(self, processor_id: str = None):
+    def reset(self, processor_id: str | None = None):
         if self.model is not None:
             debug(f'Control Processor unloaded: id="{self.processor_id}"')
             self.model = None
@@ -237,7 +238,7 @@ class Processor:
             for k, v in from_config.items():
                 self.load_config[k] = v
 
-    def load(self, processor_id: str = None, force: bool = True) -> str:
+    def load(self, processor_id: str | None = None, force: bool = True) -> str:
         from modules.shared import state
         try:
             t0 = time.time()
@@ -304,7 +305,7 @@ class Processor:
             display(e, 'Control Processor load')
             return f'Processor load filed: {processor_id}'
 
-    def __call__(self, image_input: Image, mode: str = 'RGB', width: int = 0, height: int = 0, resize_mode: int = 0, resize_name: str = 'None', scale_tab: int = 1, scale_by: float = 1.0, local_config: dict = None):
+    def __call__(self, image_input: Image, mode: str = 'RGB', width: int = 0, height: int = 0, resize_mode: int = 0, resize_name: str = 'None', scale_tab: int = 1, scale_by: float = 1.0, local_config: dict | None = None):
         """Run the preprocessor on an input image and return the processed control map.
 
         Args:
diff --git a/modules/control/run.py b/modules/control/run.py
index 007833374..94bcc73b8 100644
--- a/modules/control/run.py
+++ b/modules/control/run.py
@@ -140,7 +140,7 @@ def set_pipe(p, has_models, unit_type, selected_models, active_model, active_str
     return pipe
 
 
-def check_active(p, unit_type, units):
+def check_active(p, unit_type: str, units: list[unit.Unit]):
     active_process: list[processors.Processor] = [] # all active preprocessors
     active_model: list[controlnet.ControlNet | xs.ControlNetXS | t2iadapter.Adapter] = [] # all active models
     active_strength: list[float] = [] # strength factors for all active models
@@ -216,9 +216,9 @@ def check_active(p, unit_type, units):
     return active_process, active_model, active_strength, active_start, active_end, active_units
 
 
-def check_enabled(p, unit_type, units, active_model, active_strength, active_start, active_end):
+def check_enabled(p, unit_type: str, units: list[unit.Unit], active_model: list[controlnet.ControlNet | xs.ControlNetXS | t2iadapter.Adapter], active_strength: list[float], active_start: list[float], active_end: list[float]):
     has_models = False
-    selected_models: list[controlnet.ControlNetModel | xs.ControlNetXSModel | t2iadapter.AdapterModel] = None
+    selected_models: list[controlnet.ControlNetModel | xs.ControlNetXSModel | t2iadapter.AdapterModel] | None = None
     control_conditioning = None
     control_guidance_start = None
     control_guidance_end = None
@@ -271,17 +271,17 @@ def init_units(units: list[unit.Unit]):
 
 
 def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
-                units: list[unit.Unit] = None, inputs: list[Image.Image] = None, inits: list[Image.Image] = None, mask: Image.Image = None, unit_type: str = None, is_generator: bool = True,
+                units: list[unit.Unit] | None = None, inputs: list[Image.Image] | None = None, inits: list[Image.Image] | None = None, mask: Image.Image = None, unit_type: str | None = None, is_generator: bool = True,
                 input_type: int = 0,
-                prompt: str = '', negative_prompt: str = '', styles: list[str] = None,
-                steps: int = 20, sampler_index: int = None,
+                prompt: str = '', negative_prompt: str = '', styles: list[str] | None = None,
+                steps: int = 20, sampler_index: int | None = None,
                 seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1,
                 guidance_name: str = 'Default', guidance_scale: float = 6.0, guidance_rescale: float = 0.0, guidance_start: float = 0.0, guidance_stop: float = 1.0,
                 cfg_scale: float = 6.0, clip_skip: float = 1.0, image_cfg_scale: float = 6.0, diffusers_guidance_rescale: float = 0.7, pag_scale: float = 0.0, pag_adaptive: float = 0.5, cfg_end: float = 1.0,
                 vae_type: str = 'Full', tiling: bool = False, hidiffusion: bool = False,
                 detailer_enabled: bool = False, detailer_prompt: str = '', detailer_negative: str = '', detailer_steps: int = 10, detailer_strength: float = 0.3, detailer_resolution: int = 1024,
                 hdr_mode: int = 0, hdr_brightness: float = 0, hdr_color: float = 0, hdr_sharpen: float = 0, hdr_clamp: bool = False, hdr_boundary: float = 4.0, hdr_threshold: float = 0.95,
-                hdr_maximize: bool = False, hdr_max_center: float = 0.6, hdr_max_boundary: float = 1.0, hdr_color_picker: str = None, hdr_tint_ratio: float = 0, hdr_apply_hires: bool = True,
+                hdr_maximize: bool = False, hdr_max_center: float = 0.6, hdr_max_boundary: float = 1.0, hdr_color_picker: str | None = None, hdr_tint_ratio: float = 0, hdr_apply_hires: bool = True,
                 grading_brightness: float = 0.0, grading_contrast: float = 0.0, grading_saturation: float = 0.0, grading_hue: float = 0.0,
                 grading_gamma: float = 1.0, grading_sharpness: float = 0.0, grading_color_temp: float = 6500,
                 grading_shadows: float = 0.0, grading_midtones: float = 0.0, grading_highlights: float = 0.0,
@@ -293,54 +293,54 @@ def control_run(state: str = '', # pylint: disable=keyword-arg-before-vararg
                 resize_mode_after: int = 0, resize_name_after: str = 'None', resize_context_after: str = 'None', width_after: int = 0, height_after: int = 0, scale_by_after: float = 1.0, selected_scale_tab_after: int = 0,
                 resize_mode_mask: int = 0, resize_name_mask: str = 'None', resize_context_mask: str = 'None', width_mask: int = 0, height_mask: int = 0, scale_by_mask: float = 1.0, selected_scale_tab_mask: int = 0,
                 denoising_strength: float = 0.3, batch_count: int = 1, batch_size: int = 1,
-                enable_hr: bool = False, hr_sampler_index: int = None, hr_denoising_strength: float = 0.0, hr_resize_mode: int = 0, hr_resize_context: str = 'None', hr_upscaler: str = None, hr_force: bool = False, hr_second_pass_steps: int = 20,
+                enable_hr: bool = False, hr_sampler_index: int | None = None, hr_denoising_strength: float = 0.0, hr_resize_mode: int = 0, hr_resize_context: str = 'None', hr_upscaler: str | None = None, hr_force: bool = False, hr_second_pass_steps: int = 20,
                 hr_scale: float = 1.0, hr_resize_x: int = 0, hr_resize_y: int = 0, refiner_steps: int = 5, refiner_start: float = 0.0, refiner_prompt: str = '', refiner_negative: str = '',
                 video_skip_frames: int = 0, video_type: str = 'None', video_duration: float = 2.0, video_loop: bool = False, video_pad: int = 0, video_interpolate: int = 0,
-                override_script_name: str = None, override_script_args = None, extra: dict = None,
+                override_script_name: str | None = None, override_script_args = None, extra: dict | None = None,
                 *input_script_args,
                 # API-only params (keyword-only, not wired to Gradio)
-                detailer_segmentation: bool = None, detailer_include_detections: bool = None, detailer_merge: bool = None, detailer_sort: bool = None, detailer_classes: str = None,
-                detailer_conf: float = None, detailer_iou: float = None, detailer_max: int = None,
-                detailer_min_size: float = None, detailer_max_size: float = None,
-                detailer_blur: int = None, detailer_padding: int = None,
-                detailer_sigma_adjust: float = None, detailer_sigma_adjust_max: float = None,
-                detailer_models: list = None, detailer_augment: bool = None,
-                img2img_color_correction: bool = None, color_correction_method: str = None, img2img_background_color: str = None,
-                img2img_fix_steps: bool = None, mask_apply_overlay: bool = None,
-                include_mask: bool = None, inpainting_mask_weight: float = None,
+                detailer_segmentation: bool | None = None, detailer_include_detections: bool | None = None, detailer_merge: bool | None = None, detailer_sort: bool | None = None, detailer_classes: str | None = None,
+                detailer_conf: float | None = None, detailer_iou: float | None = None, detailer_max: int | None = None,
+                detailer_min_size: float | None = None, detailer_max_size: float | None = None,
+                detailer_blur: int | None = None, detailer_padding: int | None = None,
+                detailer_sigma_adjust: float | None = None, detailer_sigma_adjust_max: float | None = None,
+                detailer_models: list | None = None, detailer_augment: bool | None = None,
+                img2img_color_correction: bool | None = None, color_correction_method: str | None = None, img2img_background_color: str | None = None,
+                img2img_fix_steps: bool | None = None, mask_apply_overlay: bool | None = None,
+                include_mask: bool | None = None, inpainting_mask_weight: float | None = None,
                 # output and saving
-                samples_save: bool = None, samples_format: str = None,
-                save_images_before_highres_fix: bool = None, save_images_before_refiner: bool = None,
-                save_images_before_detailer: bool = None, save_images_before_color_correction: bool = None,
-                grid_save: bool = None, grid_format: str = None, return_grid: bool = None,
-                save_mask: bool = None, save_mask_composite: bool = None,
-                return_mask: bool = None, return_mask_composite: bool = None,
-                keep_incomplete: bool = None, image_metadata: bool = None, jpeg_quality: int = None,
+                samples_save: bool | None = None, samples_format: str | None = None,
+                save_images_before_highres_fix: bool | None = None, save_images_before_refiner: bool | None = None,
+                save_images_before_detailer: bool | None = None, save_images_before_color_correction: bool | None = None,
+                grid_save: bool | None = None, grid_format: str | None = None, return_grid: bool | None = None,
+                save_mask: bool | None = None, save_mask_composite: bool | None = None,
+                return_mask: bool | None = None, return_mask_composite: bool | None = None,
+                keep_incomplete: bool | None = None, image_metadata: bool | None = None, jpeg_quality: int | None = None,
                 # scheduler/noise overrides
-                schedulers_prediction_type: str = None, schedulers_beta_schedule: str = None, schedulers_timesteps: str = None,
-                schedulers_sigma: str = None, schedulers_use_thresholding: bool = None, schedulers_use_loworder: bool = None,
-                schedulers_solver_order: int = None, uni_pc_variant: str = None, schedulers_beta_start: float = None,
-                schedulers_beta_end: float = None, schedulers_shift: float = None, schedulers_dynamic_shift: bool = None,
-                schedulers_base_shift: float = None, schedulers_max_shift: float = None, schedulers_rescale_betas: bool = None,
-                schedulers_timestep_spacing: str = None, schedulers_timesteps_range: int = None,
-                schedulers_sigma_adjust: float = None, schedulers_sigma_adjust_min: float = None, schedulers_sigma_adjust_max: float = None,
-                scheduler_eta: float = None, eta_noise_seed_delta: int = None, enable_batch_seeds: bool = None,
-                diffusers_generator_device: str = None, nan_skip: bool = None,
-                sequential_seed: bool = None,
+                schedulers_prediction_type: str | None = None, schedulers_beta_schedule: str | None = None, schedulers_timesteps: str | None = None,
+                schedulers_sigma: str | None = None, schedulers_use_thresholding: bool | None = None, schedulers_use_loworder: bool | None = None,
+                schedulers_solver_order: int | None = None, uni_pc_variant: str | None = None, schedulers_beta_start: float | None = None,
+                schedulers_beta_end: float | None = None, schedulers_shift: float | None = None, schedulers_dynamic_shift: bool | None = None,
+                schedulers_base_shift: float | None = None, schedulers_max_shift: float | None = None, schedulers_rescale_betas: bool | None = None,
+                schedulers_timestep_spacing: str | None = None, schedulers_timesteps_range: int | None = None,
+                schedulers_sigma_adjust: float | None = None, schedulers_sigma_adjust_min: float | None = None, schedulers_sigma_adjust_max: float | None = None,
+                scheduler_eta: float | None = None, eta_noise_seed_delta: int | None = None, enable_batch_seeds: bool | None = None,
+                diffusers_generator_device: str | None = None, nan_skip: bool | None = None,
+                sequential_seed: bool | None = None,
                 # prompt/attention overrides
-                prompt_attention: str = None, prompt_mean_norm: bool = None, diffusers_zeros_prompt_pad: bool = None,
-                te_pooled_embeds: bool = None, lora_apply_te: bool = None, te_complex_human_instruction: str = None, te_use_mask: bool = None,
+                prompt_attention: str | None = None, prompt_mean_norm: bool | None = None, diffusers_zeros_prompt_pad: bool | None = None,
+                te_pooled_embeds: bool | None = None, lora_apply_te: bool | None = None, te_complex_human_instruction: str | None = None, te_use_mask: bool | None = None,
                 # generation modifier overrides (hijack)
-                freeu_enabled: bool = None, freeu_b1: float = None, freeu_b2: float = None, freeu_s1: float = None, freeu_s2: float = None,
-                hypertile_unet_enabled: bool = None, hypertile_hires_only: bool = None, hypertile_unet_tile: int = None, hypertile_unet_min_tile: int = None,
-                hypertile_unet_swap_size: int = None, hypertile_unet_depth: int = None,
-                hypertile_vae_enabled: bool = None, hypertile_vae_tile: int = None, hypertile_vae_swap_size: int = None,
-                teacache_enabled: bool = None, teacache_thresh: float = None,
-                token_merging_method: str = None, tome_ratio: float = None, todo_ratio: float = None,
+                freeu_enabled: bool | None = None, freeu_b1: float | None = None, freeu_b2: float | None = None, freeu_s1: float | None = None, freeu_s2: float | None = None,
+                hypertile_unet_enabled: bool | None = None, hypertile_hires_only: bool | None = None, hypertile_unet_tile: int | None = None, hypertile_unet_min_tile: int | None = None,
+                hypertile_unet_swap_size: int | None = None, hypertile_unet_depth: int | None = None,
+                hypertile_vae_enabled: bool | None = None, hypertile_vae_tile: int | None = None, hypertile_vae_swap_size: int | None = None,
+                teacache_enabled: bool | None = None, teacache_thresh: float | None = None,
+                token_merging_method: str | None = None, tome_ratio: float | None = None, todo_ratio: float | None = None,
                 # lora behavior
-                lora_fuse_native: bool = None, lora_fuse_diffusers: bool = None,
-                lora_force_reload: bool = None, extra_networks_default_multiplier: float = None,
-                lora_apply_tags: int = None,
+                lora_fuse_native: bool | None = None, lora_fuse_diffusers: bool | None = None,
+                lora_force_reload: bool | None = None, extra_networks_default_multiplier: float | None = None,
+                lora_apply_tags: int | None = None,
         ):
     if override_script_args is None:
         override_script_args = []
diff --git a/modules/control/unit.py b/modules/control/unit.py
index fc33eb349..e66aed02b 100644
--- a/modules/control/unit.py
+++ b/modules/control/unit.py
@@ -1,3 +1,4 @@
+from typing import TYPE_CHECKING
 from PIL import Image
 import gradio as gr
 from modules.logger import log
@@ -33,10 +34,10 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
 
     def __init__(self,
                  # values
-                 index: int = None,
-                 enabled: bool = None,
-                 strength: float = None,
-                 unit_type: str = None,
+                 index: int | None = None,
+                 enabled: bool | None = None,
+                 strength: float | None = None,
+                 unit_type: str | None = None,
                  start: float = 0,
                  end: float = 1,
                  # ui bindings
@@ -55,7 +56,7 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
                  control_mode = None,
                  control_tile = None,
                  result_txt = None,
-                 extra_controls: list = None,
+                 extra_controls: list | None = None,
         ):
         if extra_controls is None:
             extra_controls = []
@@ -71,15 +72,15 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
         self.end = end or 1
         self.start = min(self.start, self.end)
         self.end = max(self.start, self.end)
-        self.mode = None
+        self.mode: int | None = None
         # processor always exists, adapter and controlnet are optional
-        self.model_name = None
-        self.process_name = None
+        self.model_name: str | None = None
+        self.process_name: str | None = None
         self.process: processors.Processor = processors.Processor()
-        self.adapter: t2iadapter.Adapter = None
-        self.controlnet: controlnet.ControlNet | xs.ControlNetXS = None
+        self.adapter: t2iadapter.Adapter | None = None
+        self.controlnet: controlnet.ControlNet | xs.ControlNetXS | lite.ControlLLLite | None = None
         # map to input image
-        self.override: Image = None
+        self.override: Image.Image | None = None
         # global settings but passed per-unit
         self.factor = 1.0
         self.guess = False
@@ -177,6 +178,8 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
 
         # bind ui controls to properties if present
         if self.type == 't2i adapter':
+            if TYPE_CHECKING:
+                assert isinstance(self.adapter, t2iadapter.Adapter)
             if model_id is not None:
                 if isinstance(model_id, str):
                     self.adapter.load(model_id)
@@ -186,6 +189,8 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
             if extra_controls is not None and len(extra_controls) > 0:
                 extra_controls[0].change(fn=adapter_extra, inputs=extra_controls)
         elif self.type == 'controlnet':
+            if TYPE_CHECKING:
+                assert isinstance(self.controlnet, controlnet.ControlNet)
             if model_id is not None:
                 if isinstance(model_id, str):
                     self.controlnet.load(model_id)
@@ -196,6 +201,8 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
             if extra_controls is not None and len(extra_controls) > 0:
                 extra_controls[0].change(fn=controlnet_extra, inputs=extra_controls)
         elif self.type == 'xs':
+            if TYPE_CHECKING:
+                assert isinstance(self.controlnet, xs.ControlNetXS)
             if model_id is not None:
                 if isinstance(model_id, str):
                     self.controlnet.load(model_id)
@@ -205,6 +212,8 @@ class Unit: # mashup of gradio controls and mapping to actual implementation cla
             if extra_controls is not None and len(extra_controls) > 0:
                 extra_controls[0].change(fn=controlnetxs_extra, inputs=extra_controls)
         elif self.type == 'lite':
+            if TYPE_CHECKING:
+                assert isinstance(self.controlnet, lite.ControlLLLite)
             if model_id is not None:
                 if isinstance(model_id, str):
                     self.controlnet.load(model_id)

From 481d974b91983e58026052be36d3d634457dc262 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 03:40:15 -0700
Subject: [PATCH 08/25] RUF013 update

---
 modules/devices.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/devices.py b/modules/devices.py
index 4e0d63722..fbcf0146a 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -197,7 +197,7 @@ def get_optimal_device():
     return torch.device(get_optimal_device_name())
 
 
-def torch_gc(force:bool=False, fast:bool=False, reason:str=None):
+def torch_gc(force: bool = False, fast: bool = False, reason: str | None = None):
     def get_stats():
         mem_dict = memstats.memory_stats()
         gpu_dict = mem_dict.get('gpu', {})

From d3f925e8e5df4dba5bacf334efc8d81fb364aa88 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 03:46:26 -0700
Subject: [PATCH 09/25] RUF013 update

---
 modules/face/instantid_model.py     | 10 +++++-----
 modules/face/photomaker_pipeline.py |  8 ++++----
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/modules/face/instantid_model.py b/modules/face/instantid_model.py
index 2511ec27a..be17b709a 100644
--- a/modules/face/instantid_model.py
+++ b/modules/face/instantid_model.py
@@ -545,9 +545,9 @@ class StableDiffusionXLInstantIDPipeline(StableDiffusionXLControlNetPipeline):
     @replace_example_docstring(EXAMPLE_DOC_STRING)
     def __call__(
         self,
-        prompt: str | list[str] = None,
+        prompt: str | list[str] | None = None,
         prompt_2: str | list[str] | None = None,
-        image: PipelineImageInput = None,
+        image: PipelineImageInput | None = None,
         height: int | None = None,
         width: int | None = None,
         num_inference_steps: int = 50,
@@ -570,15 +570,15 @@ class StableDiffusionXLInstantIDPipeline(StableDiffusionXLControlNetPipeline):
         guess_mode: bool = False,
         control_guidance_start: float | list[float] = 0.0,
         control_guidance_end: float | list[float] = 1.0,
-        original_size: tuple[int, int] = None,
+        original_size: tuple[int, int] | None = None,
         crops_coords_top_left: tuple[int, int] = (0, 0),
-        target_size: tuple[int, int] = None,
+        target_size: tuple[int, int] | None = None,
         negative_original_size: tuple[int, int] | None = None,
         negative_crops_coords_top_left: tuple[int, int] = (0, 0),
         negative_target_size: tuple[int, int] | None = None,
         clip_skip: int | None = None,
         callback_on_step_end: Callable[[int, int, dict], None] | None = None,
-        callback_on_step_end_tensor_inputs: list[str] = None,
+        callback_on_step_end_tensor_inputs: list[str] | None = None,
         **kwargs,
     ):
         r"""
diff --git a/modules/face/photomaker_pipeline.py b/modules/face/photomaker_pipeline.py
index 191c4f352..82daefbd7 100644
--- a/modules/face/photomaker_pipeline.py
+++ b/modules/face/photomaker_pipeline.py
@@ -445,13 +445,13 @@ class PhotoMakerStableDiffusionXLPipeline(StableDiffusionXLPipeline):
     @torch.no_grad()
     def __call__(
         self,
-        prompt: str | list[str] = None,
+        prompt: str | list[str] | None = None,
         prompt_2: str | list[str] | None = None,
         height: int | None = None,
         width: int | None = None,
         num_inference_steps: int = 50,
-        timesteps: list[int] = None,
-        sigmas: list[float] = None,
+        timesteps: list[int] | None = None,
+        sigmas: list[float] | None = None,
         denoising_end: float | None = None,
         guidance_scale: float = 5.0,
         negative_prompt: str | list[str] | None = None,
@@ -478,7 +478,7 @@ class PhotoMakerStableDiffusionXLPipeline(StableDiffusionXLPipeline):
         negative_target_size: tuple[int, int] | None = None,
         clip_skip: int | None = None,
         callback_on_step_end: Callable[[int, int, dict], None] | PipelineCallback | MultiPipelineCallbacks | None = None,
-        callback_on_step_end_tensor_inputs: list[str] = None,
+        callback_on_step_end_tensor_inputs: list[str] | None = None,
         # Added parameters (for PhotoMaker)
         input_id_images: PipelineImageInput = None,
         start_merge_step: int = 10,

From abe25e7b079e79e75ae6653e364d9285e45976b0 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 03:46:44 -0700
Subject: [PATCH 10/25] RUF013 update

---
 modules/framepack/create-video.py     | 4 ++--
 modules/framepack/framepack_hijack.py | 2 +-
 modules/framepack/framepack_load.py   | 4 ++--
 modules/framepack/framepack_worker.py | 4 ++--
 4 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/modules/framepack/create-video.py b/modules/framepack/create-video.py
index f1b334d3a..1863a2e72 100755
--- a/modules/framepack/create-video.py
+++ b/modules/framepack/create-video.py
@@ -26,7 +26,7 @@ def auth():
     return None
 
 
-def get(endpoint: str, dct: dict = None):
+def get(endpoint: str, dct: dict | None = None):
     req = requests.get(f'{sd_url}{endpoint}', json=dct, timeout=300, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
@@ -34,7 +34,7 @@ def get(endpoint: str, dct: dict = None):
         return req.json()
 
 
-def post(endpoint: str, dct: dict = None):
+def post(endpoint: str, dct: dict | None = None):
     req = requests.post(f'{sd_url}{endpoint}', json = dct, timeout=None, verify=False, auth=auth())
     if req.status_code != 200:
         return { 'error': req.status_code, 'reason': req.reason, 'url': req.url }
diff --git a/modules/framepack/framepack_hijack.py b/modules/framepack/framepack_hijack.py
index 4ce623827..63f4b24f0 100644
--- a/modules/framepack/framepack_hijack.py
+++ b/modules/framepack/framepack_hijack.py
@@ -30,7 +30,7 @@ def set_progress_bar_config():
     uni_pc_fm.sample_unipc = sample_unipc
 
 
-def set_prompt_template(prompt, system_prompt:str=None, optimized_prompt:bool=True, unmodified_prompt:bool=False):
+def set_prompt_template(prompt, system_prompt: str | None = None, optimized_prompt: bool = True, unmodified_prompt: bool = False):
     from modules import shared
     from modules.framepack.pipeline import hunyuan
     mode = 'unknown'
diff --git a/modules/framepack/framepack_load.py b/modules/framepack/framepack_load.py
index 21f0819ce..74e853a52 100644
--- a/modules/framepack/framepack_load.py
+++ b/modules/framepack/framepack_load.py
@@ -35,7 +35,7 @@ def split_url(url):
     return { 'repo': f'{url[0]}/{url[1]}', 'subfolder': url[2] }
 
 
-def set_model(receipe: str=None):
+def set_model(receipe: str | None = None):
     if receipe is None or receipe == '':
         return
     lines = [line.strip() for line in receipe.split('\n') if line.strip() != '' and ':' in line]
@@ -62,7 +62,7 @@ def reset_model():
     return ''
 
 
-def load_model(variant:str=None, pipeline:str=None, text_encoder:str=None, text_encoder_2:str=None, feature_extractor:str=None, image_encoder:str=None, transformer:str=None):
+def load_model(variant: str | None = None, pipeline: str | None = None, text_encoder: str | None = None, text_encoder_2: str | None = None, feature_extractor: str | None = None, image_encoder: str | None = None, transformer: str | None = None):
     shared.state.begin('Load FramePack')
     if variant is not None:
         if variant not in models.keys():
diff --git a/modules/framepack/framepack_worker.py b/modules/framepack/framepack_worker.py
index 85f87a624..fdd9637c9 100644
--- a/modules/framepack/framepack_worker.py
+++ b/modules/framepack/framepack_worker.py
@@ -44,7 +44,7 @@ def worker(
         mp4_fps, mp4_codec, mp4_sf, mp4_video, mp4_frames, mp4_opt, mp4_ext, mp4_interpolate,
         vae_type,
         variant,
-        metadata:dict=None,
+        metadata: dict | None = None,
     ):
     if metadata is None:
         metadata = {}
@@ -85,7 +85,7 @@ def worker(
     if not is_f1:
         prompts = list(reversed(prompts))
 
-    def text_encode(prompt, i:int=None):
+    def text_encode(prompt, i: int | None = None):
         jobid = shared.state.begin('TE Encode')
         pbar.update(task, description=f'text encode section={i}')
         t0 = time.time()

From 2d81bcdc697d04b48c13e3932b97d976c3cac123 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 04:12:14 -0700
Subject: [PATCH 11/25] RUF013 updates + type fixes

---
 modules/image/grid.py   | 17 +++++++++++++----
 modules/image/resize.py |  4 ++--
 2 files changed, 15 insertions(+), 6 deletions(-)

diff --git a/modules/image/grid.py b/modules/image/grid.py
index 0a411b500..9ba8801fe 100644
--- a/modules/image/grid.py
+++ b/modules/image/grid.py
@@ -1,5 +1,6 @@
 import math
 from collections import namedtuple
+from typing import TYPE_CHECKING
 import numpy as np
 from PIL import Image, ImageFont, ImageDraw
 from modules import shared, script_callbacks
@@ -26,7 +27,7 @@ def check_grid_size(imgs):
     return ok
 
 
-def get_grid_size(imgs, batch_size=1, rows=None, cols=None):
+def get_grid_size(imgs, batch_size=1, rows: int | None = None, cols: int | None = None):
     if rows and rows > len(imgs):
         rows = len(imgs)
     if cols and cols > len(imgs):
@@ -34,12 +35,16 @@ def get_grid_size(imgs, batch_size=1, rows=None, cols=None):
     if rows is None and cols is None:
         if shared.opts.n_rows > 0:
             rows = shared.opts.n_rows
+            if TYPE_CHECKING:
+                assert isinstance(rows, int)
             cols = math.ceil(len(imgs) / rows)
         elif shared.opts.n_rows == 0:
             rows = batch_size
             cols = math.ceil(len(imgs) / rows)
         elif shared.opts.n_cols > 0:
             cols = shared.opts.n_cols
+            if TYPE_CHECKING:
+                assert isinstance(cols, int)
             rows = math.ceil(len(imgs) / cols)
         elif shared.opts.n_cols == 0:
             cols = batch_size
@@ -49,16 +54,20 @@ def get_grid_size(imgs, batch_size=1, rows=None, cols=None):
             while len(imgs) % rows != 0:
                 rows -= 1
             cols = math.ceil(len(imgs) / rows)
-    elif cols is None:
+        return rows, cols
+    elif rows is not None and cols is None:
         cols = math.ceil(len(imgs) / rows)
-    elif rows is None:
+    elif rows is None and cols is not None:
         rows = math.ceil(len(imgs) / cols)
     else:
+        if TYPE_CHECKING:
+            assert isinstance(rows, int)
+            assert isinstance(cols, int)
         pass
     return rows, cols
 
 
-def image_grid(imgs, batch_size:int=1, rows:int=None, cols:int=None):
+def image_grid(imgs, batch_size=1, rows=1, cols=1):
     rows, cols = get_grid_size(imgs, batch_size, rows=rows, cols=cols)
     params = script_callbacks.ImageGridLoopParams(imgs, cols, rows)
     script_callbacks.image_grid_callback(params)
diff --git a/modules/image/resize.py b/modules/image/resize.py
index 1ff04b610..22841e6e5 100644
--- a/modules/image/resize.py
+++ b/modules/image/resize.py
@@ -8,7 +8,7 @@ from modules.logger import log
 from modules.image import sharpfin
 
 
-def resize_image(resize_mode: int, im: Image.Image | torch.Tensor, width: int, height: int, upscaler_name: str=None, output_type: str='image', context: str=None):
+def resize_image(resize_mode: int, im: Image.Image | torch.Tensor, width: int, height: int, upscaler_name: str | None = None, output_type: str = 'image', context: str | None = None):
     upscaler_name = upscaler_name or shared.opts.upscaler_for_img2img
 
     def verify_image(image):
@@ -95,7 +95,7 @@ def resize_image(resize_mode: int, im: Image.Image | torch.Tensor, width: int, h
         res.paste(im, box=((width - im.width)//2, (height - im.height)//2))
         return res
 
-    def context_aware(im: Image.Image, width, height, context):
+    def context_aware(im: Image.Image, width: int, height: int, context: str):
         from installer import install
         install('seam-carving')
         width, height = int(width), int(height)

From 6ab9b7bc6250b053eb1589b6016bf9827ca329e6 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 04:19:53 -0700
Subject: [PATCH 12/25] RUF013 updates

---
 modules/intel/openvino/__init__.py | 6 +++---
 modules/logger.py                  | 4 ++--
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/modules/intel/openvino/__init__.py b/modules/intel/openvino/__init__.py
index 661b1f393..31405f1f7 100644
--- a/modules/intel/openvino/__init__.py
+++ b/modules/intel/openvino/__init__.py
@@ -83,7 +83,7 @@ def warn_once(msg):
         warned = True
 
 class OpenVINOGraphModule(torch.nn.Module):
-    def __init__(self, gm, partition_id, use_python_fusion_cache, model_hash_str: str = None, file_name="", int_inputs=None):
+    def __init__(self, gm, partition_id, use_python_fusion_cache, model_hash_str: str | None = None, file_name="", int_inputs: list | None = None):
         if int_inputs is None:
             int_inputs = []
         super().__init__()
@@ -211,7 +211,7 @@ def execute_cached(compiled_model, *args):
     result = [torch.from_numpy(res[out]) for out in compiled_model.outputs]
     return result
 
-def openvino_compile(gm: GraphModule, *example_inputs, model_hash_str: str = None, file_name=""):
+def openvino_compile(gm: GraphModule, *example_inputs, model_hash_str: str | None = None, file_name=""):
     core = Core()
 
     device = get_device()
@@ -427,7 +427,7 @@ def openvino_execute_partitioned(gm: GraphModule, *args, executor_parameters=Non
     return shared.compiled_model_state.partitioned_modules[signature][0](*ov_inputs)
 
 
-def partition_graph(gm: GraphModule, use_python_fusion_cache: bool, model_hash_str: str = None, file_name="", int_inputs=None):
+def partition_graph(gm: GraphModule, use_python_fusion_cache: bool, model_hash_str: str | None = None, file_name="", int_inputs=None):
     if int_inputs is None:
         int_inputs = []
     for node in gm.graph.nodes:
diff --git a/modules/logger.py b/modules/logger.py
index d451df0c5..89f5a2277 100644
--- a/modules/logger.py
+++ b/modules/logger.py
@@ -40,7 +40,7 @@ def get_log():
     return log
 
 
-def install_traceback(suppress: list = None):
+def install_traceback(suppress: list | None = None):
     if suppress is None:
         suppress = []
     width = os.environ.get("SD_TRACEWIDTH", console.width if console else None)
@@ -143,7 +143,7 @@ def setup_logging(debug=None, trace=None, filename=None):
     logging.Logger.trace = partialmethod(logging.Logger.log, logging.TRACE)
     logging.trace = partial(logging.log, logging.TRACE)
 
-    def exception_hook(e: Exception, suppress=None):
+    def exception_hook(e: Exception, suppress: list | None = None):
         from rich.traceback import Traceback
         if suppress is None:
             suppress = []

From 92960de8d6a2778954cfb7d2d6482cd765bf6130 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 04:27:30 -0700
Subject: [PATCH 13/25] RUF013 updates

---
 modules/lora/extra_networks_lora.py |  2 +-
 modules/masking.py                  |  2 +-
 modules/merging/convert_sdxl.py     |  2 +-
 modules/merging/modules_sdxl.py     | 14 +++++++-------
 4 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/modules/lora/extra_networks_lora.py b/modules/lora/extra_networks_lora.py
index 9ca2b3b9f..4e82e79f7 100644
--- a/modules/lora/extra_networks_lora.py
+++ b/modules/lora/extra_networks_lora.py
@@ -173,7 +173,7 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
     def signature(self, names: list[str], te_multipliers: list, unet_multipliers: list):
         return [f'{name}:{te}:{unet}' for name, te, unet in zip(names, te_multipliers, unet_multipliers, strict=False)]
 
-    def changed(self, requested: list[str], include: list[str] = None, exclude: list[str] = None) -> bool:
+    def changed(self, requested: list[str], include: list[str] | None = None, exclude: list[str] | None = None) -> bool:
         if shared.opts.lora_force_reload:
             debug_log(f'Network check: type=LoRA requested={requested} status=forced')
             return True
diff --git a/modules/masking.py b/modules/masking.py
index 82c24a3e2..600ec87f2 100644
--- a/modules/masking.py
+++ b/modules/masking.py
@@ -378,7 +378,7 @@ def outpaint(input_image: Image.Image, outpaint_type: str = 'Edge'):
     return image, mask
 
 
-def run_mask(input_image: Image.Image, input_mask: Image.Image = None, return_type: str = None, mask_blur: int = None, mask_padding: int = None, invert=None):
+def run_mask(input_image: Image.Image, input_mask: Image.Image | None = None, return_type: str | None = None, mask_blur: int | None = None, mask_padding: int | None = None, invert=None):
     if isinstance(input_image, list) and len(input_image) > 0:
         input_image = input_image[0]
     elif isinstance(input_image, dict):
diff --git a/modules/merging/convert_sdxl.py b/modules/merging/convert_sdxl.py
index 3238cfd35..969816ae1 100644
--- a/modules/merging/convert_sdxl.py
+++ b/modules/merging/convert_sdxl.py
@@ -260,7 +260,7 @@ def calculate_model_hash(state_dict):
     return func.hexdigest()
 
 
-def convert(model_path:str, checkpoint_path:str, metadata:dict=None):
+def convert(model_path: str, checkpoint_path: str, metadata: dict | None = None):
     if metadata is None:
         metadata = {}
     unet_path = os.path.join(model_path, "unet", "diffusion_pytorch_model.safetensors")
diff --git a/modules/merging/modules_sdxl.py b/modules/merging/modules_sdxl.py
index d4fb799c5..b803e90d3 100644
--- a/modules/merging/modules_sdxl.py
+++ b/modules/merging/modules_sdxl.py
@@ -65,7 +65,7 @@ def msg(text, err:bool=False):
     return status
 
 
-def load_base(override:str=None):
+def load_base(override: str | None = None):
     global pipeline # pylint: disable=global-statement
     fn = override or recipe.base
     yield msg(f'base={fn}')
@@ -79,7 +79,7 @@ def load_base(override:str=None):
     pipeline.vae.register_to_config(force_upcast = False)
 
 
-def load_unet(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
+def load_unet(pipe: diffusers.StableDiffusionXLPipeline, override: str | None = None):
     if (recipe.unet is None or len(recipe.unet) == 0) and override is None:
         return
     fn = override or recipe.unet
@@ -99,7 +99,7 @@ def load_unet(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
         yield msg(f'unet: {e}')
 
 
-def load_scheduler(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
+def load_scheduler(pipe: diffusers.StableDiffusionXLPipeline, override: str | None = None):
     if recipe.scheduler is None and override is None:
         return
     config = pipe.scheduler.config.__dict__
@@ -114,7 +114,7 @@ def load_scheduler(pipe: diffusers.StableDiffusionXLPipeline, override:str=None)
 
 
 
-def load_vae(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
+def load_vae(pipe: diffusers.StableDiffusionXLPipeline, override: str | None = None):
     if (recipe.vae is None or len(recipe.vae) == 0)and override is None:
         return
     fn = override or recipe.vae
@@ -135,7 +135,7 @@ def load_vae(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
         yield msg(f'vae: {e}')
 
 
-def load_te1(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
+def load_te1(pipe: diffusers.StableDiffusionXLPipeline, override: str | None = None):
     if (recipe.te1 is None or len(recipe.te1) == 0) and override is None:
         return
     config = pipe.text_encoder.config.__dict__
@@ -156,7 +156,7 @@ def load_te1(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
         yield msg(f'te1: {e}')
 
 
-def load_te2(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
+def load_te2(pipe: diffusers.StableDiffusionXLPipeline, override: str | None = None):
     if (recipe.te2 is None or len(recipe.te2) == 0) and override is None:
         return
     config = pipe.text_encoder_2.config.__dict__
@@ -177,7 +177,7 @@ def load_te2(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
         yield msg(f'te2: {e}')
 
 
-def load_lora(pipe: diffusers.StableDiffusionXLPipeline, override: dict=None, fuse: float=None):
+def load_lora(pipe: diffusers.StableDiffusionXLPipeline, override: dict | None = None, fuse: float | None = None):
     if recipe.lora is None and override is None:
         return
     names = []

From 641321d7d22d1d6b6001861f37658b47f2b6857b Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 04:34:38 -0700
Subject: [PATCH 14/25] RUF013 updates

---
 modules/model_quant.py | 16 ++++++++--------
 modules/modelloader.py |  8 ++++----
 2 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/modules/model_quant.py b/modules/model_quant.py
index b57c29582..a963dc3cc 100644
--- a/modules/model_quant.py
+++ b/modules/model_quant.py
@@ -51,7 +51,7 @@ def dont_quant():
     return False
 
 
-def create_bnb_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list = None):
+def create_bnb_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list | None = None):
     from modules import shared, devices
     if allow and (module == 'any' or module in shared.opts.bnb_quantization):
         load_bnb()
@@ -74,7 +74,7 @@ def create_bnb_config(kwargs = None, allow: bool = True, module: str = 'Model',
     return kwargs
 
 
-def create_ao_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list = None):
+def create_ao_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list | None = None):
     from modules import shared
     if allow and (shared.opts.torchao_quantization_mode in {'pre', 'auto'}) and (module == 'any' or module in shared.opts.torchao_quantization):
         torchao = load_torchao()
@@ -93,7 +93,7 @@ def create_ao_config(kwargs = None, allow: bool = True, module: str = 'Model', m
     return kwargs
 
 
-def create_quanto_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list = None):
+def create_quanto_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list | None = None):
     from modules import shared
     if allow and (module == 'any' or module in shared.opts.quanto_quantization):
         load_quanto(silent=True)
@@ -115,7 +115,7 @@ def create_quanto_config(kwargs = None, allow: bool = True, module: str = 'Model
     return kwargs
 
 
-def create_trt_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list = None):
+def create_trt_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list | None = None):
     from modules import shared
     if allow and (module == 'any' or module in shared.opts.trt_quantization):
         load_trt()
@@ -163,7 +163,7 @@ def get_sdnq_devices(mode="pre"):
     return quantization_device, return_device
 
 
-def create_sdnq_config(kwargs = None, allow: bool = True, module: str = 'Model', weights_dtype: str = None, quantized_matmul_dtype: str = None, modules_to_not_convert: list = None, modules_dtype_dict: dict = None):
+def create_sdnq_config(kwargs = None, allow: bool = True, module: str = 'Model', weights_dtype: str | None = None, quantized_matmul_dtype: str | None = None, modules_to_not_convert: list | None = None, modules_dtype_dict: dict | None = None):
     from modules import shared
     if allow and (shared.opts.sdnq_quantize_mode in {'pre', 'auto'}) and (module == 'any' or module in shared.opts.sdnq_quantize_weights):
         from modules.sdnq import SDNQConfig
@@ -276,7 +276,7 @@ def check_nunchaku(module: str = ''):
     return False
 
 
-def create_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list = None, modules_dtype_dict: dict = None):
+def create_config(kwargs = None, allow: bool = True, module: str = 'Model', modules_to_not_convert: list | None = None, modules_dtype_dict: dict | None = None):
     if kwargs is None:
         kwargs = {}
     if module == 'Model' and dont_quant():
@@ -508,7 +508,7 @@ def apply_layerwise(sd_model, quiet:bool=False):
                 log.error(f'Quantization: type=layerwise {e}')
 
 
-def sdnq_quantize_model(model, op=None, sd_model=None, do_gc: bool = True, weights_dtype: str = None, quantized_matmul_dtype: str = None, modules_to_not_convert: list = None, modules_dtype_dict: dict = None):
+def sdnq_quantize_model(model, op=None, sd_model=None, do_gc: bool = True, weights_dtype: str | None = None, quantized_matmul_dtype: str | None = None, modules_to_not_convert: list | None = None, modules_dtype_dict: dict | None = None):
     global quant_last_model_name, quant_last_model_device # pylint: disable=global-statement
     from modules import devices, shared, timer
     from modules.sdnq import sdnq_post_load_quant
@@ -774,7 +774,7 @@ def torchao_quantization(sd_model):
     return sd_model
 
 
-def get_dit_args(load_config:dict=None, module:str=None, device_map:bool=False, allow_quant:bool=True, modules_to_not_convert: list = None, modules_dtype_dict: dict = None):
+def get_dit_args(load_config: dict | None = None, module: str | None = None, device_map: bool = False, allow_quant: bool = True, modules_to_not_convert: list | None = None, modules_dtype_dict: dict | None = None):
     from modules import shared, devices
     config = {} if load_config is None else load_config.copy()
     if 'torch_dtype' not in config:
diff --git a/modules/modelloader.py b/modules/modelloader.py
index 6d6a776f7..974a4b1a5 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -56,7 +56,7 @@ def hf_login(token=None):
     return True
 
 
-def download_diffusers_model(hub_id: str, cache_dir: str = None, download_config: dict[str, str] = None, token = None, variant = None, revision = None, mirror = None, custom_pipeline = None):
+def download_diffusers_model(hub_id: str, cache_dir: str | None = None, download_config: dict[str, str | bool] | None = None, token = None, variant = None, revision = None, mirror = None, custom_pipeline = None):
     if hub_id is None or len(hub_id) == 0:
         return None
     from diffusers import DiffusionPipeline
@@ -219,7 +219,7 @@ def get_reference_opts(name: str, quiet=False):
     return model_opts
 
 
-def load_reference(name: str, variant: str = None, revision: str = None, mirror: str = None, custom_pipeline: str = None):
+def load_reference(name: str, variant: str | None = None, revision: str | None = None, mirror: str | None = None, custom_pipeline: str | None = None):
     if '+' in name:
         name = name.split('+')[0]
     found = [r for r in diffuser_repos if name == r['name'] or name == r['friendly'] or name == r['path']]
@@ -337,7 +337,7 @@ def load_file_from_url(url: str, *, model_dir: str, progress: bool = True, file_
         return None
 
 
-def load_models(model_path: str, model_url: str = None, command_path: str = None, ext_filter=None, download_name=None, ext_blacklist=None) -> list:
+def load_models(model_path: str, model_url: str | None = None, command_path: str | None = None, ext_filter=None, download_name=None, ext_blacklist=None) -> list:
     """
     A one-and done loader to try finding the desired models in specified directories.
     @param download_name: Specify to download from model_url immediately.
@@ -404,7 +404,7 @@ def cleanup_models():
     move_files(src_path, dest_path)
 
 
-def move_files(src_path: str, dest_path: str, ext_filter: str = None):
+def move_files(src_path: str, dest_path: str, ext_filter: str | None = None):
     try:
         if not os.path.exists(dest_path):
             os.makedirs(dest_path)

From fb853af4b0d5b20ce679fcd8444a77301121e0e7 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 04:58:19 -0700
Subject: [PATCH 15/25] RUF013 updates

---
 .../onnx_stable_diffusion_pipeline.py         |   2 +-
 modules/options_handler.py                    |   2 +-
 modules/postprocess/pixelart.py               |   4 +-
 modules/postprocess/yolo.py                   |   6 +-
 modules/processing_callbacks.py               |   2 +-
 modules/processing_class.py                   | 216 +++++++++---------
 modules/processing_helpers.py                 |   2 +-
 7 files changed, 117 insertions(+), 117 deletions(-)

diff --git a/modules/onnx_impl/pipelines/onnx_stable_diffusion_pipeline.py b/modules/onnx_impl/pipelines/onnx_stable_diffusion_pipeline.py
index 2b583e8f5..dc2aa9e75 100644
--- a/modules/onnx_impl/pipelines/onnx_stable_diffusion_pipeline.py
+++ b/modules/onnx_impl/pipelines/onnx_stable_diffusion_pipeline.py
@@ -30,7 +30,7 @@ class OnnxStableDiffusionPipeline(diffusers.OnnxStableDiffusionPipeline, Callabl
 
     def __call__(
         self,
-        prompt: str | list[str] = None,
+        prompt: str | list[str] | None = None,
         height: int | None = 512,
         width: int | None = 512,
         num_inference_steps: int | None = 50,
diff --git a/modules/options_handler.py b/modules/options_handler.py
index 5041eb86c..c14fadfb4 100644
--- a/modules/options_handler.py
+++ b/modules/options_handler.py
@@ -28,7 +28,7 @@ class Options:
     debug = os.environ.get('SD_CONFIG_DEBUG', None) is not None
     secrets_debug = os.environ.get("SD_SECRETS_DEBUG", None) is not None
 
-    def __init__(self, options_templates: dict[str, OptionInfo | LegacyOption] = None, restricted: set[str] | None = None, *, filename = '', secrets = ''):
+    def __init__(self, options_templates: dict[str, OptionInfo | LegacyOption] | None = None, restricted: set[str] | None = None, *, filename = '', secrets = ''):
         if options_templates is None:
             options_templates = {}
         if restricted is None:
diff --git a/modules/postprocess/pixelart.py b/modules/postprocess/pixelart.py
index 00b9b9636..57768b1b4 100644
--- a/modules/postprocess/pixelart.py
+++ b/modules/postprocess/pixelart.py
@@ -224,8 +224,8 @@ class JPEGEncoder(ImageProcessingMixin, ConfigMixin):
         block_size: int = 16,
         cbcr_downscale: int = 2,
         norm: str = "ortho",
-        latents_std: list[float] = None,
-        latents_mean: list[float] = None,
+        latents_std: list[float] | None = None,
+        latents_mean: list[float] | None = None,
     ):
         self.block_size = block_size
         self.cbcr_downscale = cbcr_downscale
diff --git a/modules/postprocess/yolo.py b/modules/postprocess/yolo.py
index 89802050d..e70df763f 100644
--- a/modules/postprocess/yolo.py
+++ b/modules/postprocess/yolo.py
@@ -96,11 +96,11 @@ class YoloRestorer(Detailer):
             imgsz: int = 640,
             half: bool = True,
             device = devices.device,
-            augment: bool = None,
             agnostic: bool = False,
             retina: bool = False,
             mask: bool = True,
-            offload: bool = None,
+            augment: bool | None = None,
+            offload: bool | None = None,
             p = None,
         ) -> list[YoloResult]:
         if augment is None:
@@ -201,7 +201,7 @@ class YoloRestorer(Detailer):
                     break
         return result
 
-    def load(self, model_name: str = None):
+    def load(self, model_name: str | None = None):
         with load_lock:
             from modules import modelloader
             model = None
diff --git a/modules/processing_callbacks.py b/modules/processing_callbacks.py
index 0f6fdb533..e1c2c19ba 100644
--- a/modules/processing_callbacks.py
+++ b/modules/processing_callbacks.py
@@ -51,7 +51,7 @@ def diffusers_callback_legacy(step: int, timestep: int, latents: torch.FloatTens
             time.sleep(0.1)
 
 
-def diffusers_callback(pipe, step: int = 0, timestep: int = 0, kwargs: dict = None):
+def diffusers_callback(pipe, step: int = 0, timestep: int = 0, kwargs: dict | None = None):
     if kwargs is None:
         kwargs = {}
     t0 = time.time()
diff --git a/modules/processing_class.py b/modules/processing_class.py
index 75ab9cb71..287a2b17a 100644
--- a/modules/processing_class.py
+++ b/modules/processing_class.py
@@ -35,10 +35,10 @@ class StableDiffusionProcessing:
                  width: int = 1024,
                  height: int = 1024,
                  # samplers
-                 sampler_index: int = None, # pylint: disable=unused-argument # used only to set sampler_name
-                 sampler_name: str = None,
-                 hr_sampler_name: str = None,
-                 eta: float = None,
+                 sampler_index: int | None = None, # pylint: disable=unused-argument # used only to set sampler_name
+                 sampler_name: str | None = None,
+                 hr_sampler_name: str | None = None,
+                 eta: float | None = None,
                  # modular guidance
                  guidance_name: str = 'Default',
                  guidance_scale: float = 6.0,
@@ -52,7 +52,7 @@ class StableDiffusionProcessing:
                  pag_scale: float = 0.0,
                  pag_adaptive: float = 0.5,
                  # styles
-                 styles: list[str] = None,
+                 styles: list[str] | None = None,
                  # vae
                  tiling: bool = False,
                  vae_type: str = 'Full',
@@ -66,53 +66,53 @@ class StableDiffusionProcessing:
                  detailer_steps: int = 10,
                  detailer_strength: float = 0.3,
                  detailer_resolution: int = 1024,
-                 detailer_segmentation: bool = None,
-                 detailer_include_detections: bool = None,
-                 detailer_merge: bool = None,
-                 detailer_sort: bool = None,
-                 detailer_classes: str = None,
-                 detailer_conf: float = None,
-                 detailer_iou: float = None,
-                 detailer_max: int = None,
-                 detailer_min_size: float = None,
-                 detailer_max_size: float = None,
-                 detailer_blur: int = None,
-                 detailer_padding: int = None,
-                 detailer_sigma_adjust: float = None,
-                 detailer_sigma_adjust_max: float = None,
-                 detailer_models: list = None,
-                 detailer_augment: bool = None,
+                 detailer_segmentation: bool | None = None,
+                 detailer_include_detections: bool | None = None,
+                 detailer_merge: bool | None = None,
+                 detailer_sort: bool | None = None,
+                 detailer_classes: str | None = None,
+                 detailer_conf: float | None = None,
+                 detailer_iou: float | None = None,
+                 detailer_max: int | None = None,
+                 detailer_min_size: float | None = None,
+                 detailer_max_size: float | None = None,
+                 detailer_blur: int | None = None,
+                 detailer_padding: int | None = None,
+                 detailer_sigma_adjust: float | None = None,
+                 detailer_sigma_adjust_max: float | None = None,
+                 detailer_models: list | None = None,
+                 detailer_augment: bool | None = None,
                  # img2img and mask
-                 img2img_color_correction: bool = None,
-                 color_correction_method: str = None,
-                 img2img_background_color: str = None,
-                 img2img_fix_steps: bool = None,
-                 mask_apply_overlay: bool = None,
-                 include_mask: bool = None,
-                 inpainting_mask_weight: float = None,
+                 img2img_color_correction: bool | None = None,
+                 color_correction_method: str | None = None,
+                 img2img_background_color: str | None = None,
+                 img2img_fix_steps: bool | None = None,
+                 mask_apply_overlay: bool | None = None,
+                 include_mask: bool | None = None,
+                 inpainting_mask_weight: float | None = None,
                  # output and saving
-                 samples_save: bool = None,
-                 samples_format: str = None,
-                 save_images_before_highres_fix: bool = None,
-                 save_images_before_refiner: bool = None,
-                 save_images_before_detailer: bool = None,
-                 save_images_before_color_correction: bool = None,
-                 grid_save: bool = None,
-                 grid_format: str = None,
-                 return_grid: bool = None,
-                 save_mask: bool = None,
-                 save_mask_composite: bool = None,
-                 return_mask: bool = None,
-                 return_mask_composite: bool = None,
-                 keep_incomplete: bool = None,
-                 image_metadata: bool = None,
-                 jpeg_quality: int = None,
+                 samples_save: bool | None = None,
+                 samples_format: str | None = None,
+                 save_images_before_highres_fix: bool | None = None,
+                 save_images_before_refiner: bool | None = None,
+                 save_images_before_detailer: bool | None = None,
+                 save_images_before_color_correction: bool | None = None,
+                 grid_save: bool | None = None,
+                 grid_format: str | None = None,
+                 return_grid: bool | None = None,
+                 save_mask: bool | None = None,
+                 save_mask_composite: bool | None = None,
+                 return_mask: bool | None = None,
+                 return_mask_composite: bool | None = None,
+                 keep_incomplete: bool | None = None,
+                 image_metadata: bool | None = None,
+                 jpeg_quality: int | None = None,
                  # lora behavior
-                 lora_fuse_native: bool = None,
-                 lora_fuse_diffusers: bool = None,
-                 lora_force_reload: bool = None,
-                 extra_networks_default_multiplier: float = None,
-                 lora_apply_tags: int = None,
+                 lora_fuse_native: bool | None = None,
+                 lora_fuse_diffusers: bool | None = None,
+                 lora_force_reload: bool | None = None,
+                 extra_networks_default_multiplier: float | None = None,
+                 lora_apply_tags: int | None = None,
                  # hdr corrections
                  hdr_mode: int = 0,
                  hdr_brightness: float = 0,
@@ -148,11 +148,11 @@ class StableDiffusionProcessing:
                  grading_lut_file: str = "",
                  grading_lut_strength: float = 1.0,
                  # img2img
-                 init_images: list = None,
-                 init_control: list = None,
                  denoising_strength: float = 0.3,
-                 image_cfg_scale: float = None,
-                 initial_noise_multiplier: float = None, # pylint: disable=unused-argument # a1111 compatibility
+                 init_images: list | None = None,
+                 init_control: list | None = None,
+                 image_cfg_scale: float | None = None,
+                 initial_noise_multiplier: float | None = None, # pylint: disable=unused-argument # a1111 compatibility
                  # resize
                  scale_by: float = 1,
                  selected_scale_tab: int = 0, # pylint: disable=unused-argument # a1111 compatibility
@@ -199,12 +199,12 @@ class StableDiffusionProcessing:
                  hr_force: bool = False,
                  hr_resize_mode: int = 0,
                  hr_resize_context: str = 'None',
-                 hr_upscaler: str = None,
                  hr_second_pass_steps: int = 0,
                  hr_resize_x: int = 0,
                  hr_resize_y: int = 0,
                  hr_denoising_strength: float = 0.0,
                  refiner_steps: int = 5,
+                 hr_upscaler: str | None = None,
                  refiner_start: float = 0,
                  refiner_prompt: str = '',
                  refiner_negative: str = '',
@@ -219,65 +219,65 @@ class StableDiffusionProcessing:
                  # xyz flag
                  xyz: bool = False,
                  # scripts
-                 script_args: list = [],
+                 script_args: list | None = None,
                  # scheduler/noise overrides
-                 schedulers_prediction_type: str = None,
-                 schedulers_beta_schedule: str = None,
-                 schedulers_timesteps: str = None,
-                 schedulers_sigma: str = None,
-                 schedulers_use_thresholding: bool = None,
-                 schedulers_use_loworder: bool = None,
-                 schedulers_solver_order: int = None,
-                 uni_pc_variant: str = None,
-                 schedulers_beta_start: float = None,
-                 schedulers_beta_end: float = None,
-                 schedulers_shift: float = None,
-                 schedulers_dynamic_shift: bool = None,
-                 schedulers_base_shift: float = None,
-                 schedulers_max_shift: float = None,
-                 schedulers_rescale_betas: bool = None,
-                 schedulers_timestep_spacing: str = None,
-                 schedulers_timesteps_range: int = None,
-                 schedulers_sigma_adjust: float = None,
-                 schedulers_sigma_adjust_min: float = None,
-                 schedulers_sigma_adjust_max: float = None,
-                 scheduler_eta: float = None,
-                 eta_noise_seed_delta: int = None,
-                 enable_batch_seeds: bool = None,
-                 diffusers_generator_device: str = None,
-                 nan_skip: bool = None,
-                 sequential_seed: bool = None,
+                 schedulers_prediction_type: str | None = None,
+                 schedulers_beta_schedule: str | None = None,
+                 schedulers_timesteps: str | None = None,
+                 schedulers_sigma: str | None = None,
+                 schedulers_use_thresholding: bool | None = None,
+                 schedulers_use_loworder: bool | None = None,
+                 schedulers_solver_order: int | None = None,
+                 uni_pc_variant: str | None = None,
+                 schedulers_beta_start: float | None = None,
+                 schedulers_beta_end: float | None = None,
+                 schedulers_shift: float | None = None,
+                 schedulers_dynamic_shift: bool | None = None,
+                 schedulers_base_shift: float | None = None,
+                 schedulers_max_shift: float | None = None,
+                 schedulers_rescale_betas: bool | None = None,
+                 schedulers_timestep_spacing: str | None = None,
+                 schedulers_timesteps_range: int | None = None,
+                 schedulers_sigma_adjust: float | None = None,
+                 schedulers_sigma_adjust_min: float | None = None,
+                 schedulers_sigma_adjust_max: float | None = None,
+                 scheduler_eta: float | None = None,
+                 eta_noise_seed_delta: int | None = None,
+                 enable_batch_seeds: bool | None = None,
+                 diffusers_generator_device: str | None = None,
+                 nan_skip: bool | None = None,
+                 sequential_seed: bool | None = None,
                  # prompt/attention overrides
-                 prompt_attention: str = None,
-                 prompt_mean_norm: bool = None,
-                 diffusers_zeros_prompt_pad: bool = None,
-                 te_pooled_embeds: bool = None,
-                 lora_apply_te: bool = None,
-                 te_complex_human_instruction: str = None,
-                 te_use_mask: bool = None,
+                 prompt_attention: str | None = None,
+                 prompt_mean_norm: bool | None = None,
+                 diffusers_zeros_prompt_pad: bool | None = None,
+                 te_pooled_embeds: bool | None = None,
+                 lora_apply_te: bool | None = None,
+                 te_complex_human_instruction: str | None = None,
+                 te_use_mask: bool | None = None,
                  # generation modifier overrides (hijack)
-                 freeu_enabled: bool = None,
-                 freeu_b1: float = None,
-                 freeu_b2: float = None,
-                 freeu_s1: float = None,
-                 freeu_s2: float = None,
-                 hypertile_unet_enabled: bool = None,
-                 hypertile_hires_only: bool = None,
-                 hypertile_unet_tile: int = None,
-                 hypertile_unet_min_tile: int = None,
-                 hypertile_unet_swap_size: int = None,
-                 hypertile_unet_depth: int = None,
-                 hypertile_vae_enabled: bool = None,
-                 hypertile_vae_tile: int = None,
-                 hypertile_vae_swap_size: int = None,
-                 teacache_enabled: bool = None,
-                 teacache_thresh: float = None,
-                 token_merging_method: str = None,
-                 tome_ratio: float = None,
-                 todo_ratio: float = None,
+                 freeu_enabled: bool | None = None,
+                 freeu_b1: float | None = None,
+                 freeu_b2: float | None = None,
+                 freeu_s1: float | None = None,
+                 freeu_s2: float | None = None,
+                 hypertile_unet_enabled: bool | None = None,
+                 hypertile_hires_only: bool | None = None,
+                 hypertile_unet_tile: int | None = None,
+                 hypertile_unet_min_tile: int | None = None,
+                 hypertile_unet_swap_size: int | None = None,
+                 hypertile_unet_depth: int | None = None,
+                 hypertile_vae_enabled: bool | None = None,
+                 hypertile_vae_tile: int | None = None,
+                 hypertile_vae_swap_size: int | None = None,
+                 teacache_enabled: bool | None = None,
+                 teacache_thresh: float | None = None,
+                 token_merging_method: str | None = None,
+                 tome_ratio: float | None = None,
+                 todo_ratio: float | None = None,
                  # overrides
-                 override_settings: dict[str, Any] = None,
                  override_settings_restore_afterwards: bool = True,
+                 override_settings: dict[str, Any] | None = None,
                  # metadata
                  # extra_generation_params: Dict[Any, Any] = {},
                  # task_args: Dict[str, Any] = {},
diff --git a/modules/processing_helpers.py b/modules/processing_helpers.py
index ed3e546a0..f93bcea89 100644
--- a/modules/processing_helpers.py
+++ b/modules/processing_helpers.py
@@ -155,7 +155,7 @@ def images_tensor_to_samples(image, approximation=None, model=None): # pylint: d
     return x_latent
 
 
-def get_sampler_name(sampler_index: int, img: bool = False) -> str:
+def get_sampler_name(sampler_index: int | None = None, img: bool = False) -> str:
     sampler_index = sampler_index or 0
     if len(sd_samplers.samplers) > sampler_index:
         sampler_name = sd_samplers.samplers[sampler_index].name

From 4f0fb7cc29415fd12cf03097dedd2d331b954848 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 05:00:41 -0700
Subject: [PATCH 16/25] More RUF013 updates for processing_class

---
 modules/processing_class.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/processing_class.py b/modules/processing_class.py
index 287a2b17a..b0e3df0ec 100644
--- a/modules/processing_class.py
+++ b/modules/processing_class.py
@@ -18,7 +18,7 @@ debug = log.trace if os.environ.get('SD_PROCESS_DEBUG', None) is not None else l
 @dataclass(repr=False)
 class StableDiffusionProcessing:
     def __init__(self,
-                 sd_model_checkpoint: str = None, # # used only to set sd_model
+                 sd_model_checkpoint: str | None = None, # # used only to set sd_model
                  sd_model=None, # pylint: disable=unused-argument # local instance of sd_model
                  # base params
                  prompt: str = "",
@@ -834,7 +834,7 @@ class StableDiffusionProcessingControl(StableDiffusionProcessingImg2Img):
         debug(f'Process init: mode={self.__class__.__name__} kwargs={kwargs}') # pylint: disable=protected-access
         super().__init__(**kwargs)
 
-    def init_hr(self, scale:float=None, upscaler:str=None, force:bool=False):
+    def init_hr(self, scale: float | None = None, upscaler: str | None = None, force = False):
         scale = scale or self.scale_by or self.scale_by_before
         upscaler = upscaler or self.hr_upscaler or self.resize_name or self.resize_name_before
         if upscaler is None:
@@ -852,7 +852,7 @@ class StableDiffusionProcessingControl(StableDiffusionProcessingImg2Img):
             self.hr_upscale_to_x, self.hr_upscale_to_y = int(self.hr_resize_x), int(self.hr_resize_y)
 
 
-def switch_class(p: StableDiffusionProcessing, new_class: type, dct: dict = None):
+def switch_class(p: StableDiffusionProcessing, new_class: type, dct: dict | None = None):
     kwargs = {}
     signature = inspect.signature(StableDiffusionProcessing.__init__, follow_wrapped=True) # base class
     possible = list(signature.parameters)

From 62d22295200c566cfa0e0301d75cd49d4b63d844 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 05:12:18 -0700
Subject: [PATCH 17/25] RUIF013 updates and formatting

---
 modules/prompt_parser_diffusers.py |  2 +-
 modules/prompt_parser_xhinker.py   | 20 +++-----------------
 modules/ras/ras_forward.py         |  8 ++++----
 3 files changed, 8 insertions(+), 22 deletions(-)

diff --git a/modules/prompt_parser_diffusers.py b/modules/prompt_parser_diffusers.py
index 0391bdc4a..93bfcbdab 100644
--- a/modules/prompt_parser_diffusers.py
+++ b/modules/prompt_parser_diffusers.py
@@ -753,7 +753,7 @@ def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", c
     return prompt_embeds, pooled_prompt_embeds, None, negative_prompt_embeds, negative_pooled_prompt_embeds, None
 
 
-def get_xhinker_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int = None):
+def get_xhinker_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int | None = None):
     is_sd3 = hasattr(pipe, 'text_encoder_3')
     prompt, prompt_2, _prompt_3, _ = split_prompts(pipe, prompt, is_sd3)
     neg_prompt, neg_prompt_2, _neg_prompt_3, _ = split_prompts(pipe, neg_prompt, is_sd3)
diff --git a/modules/prompt_parser_xhinker.py b/modules/prompt_parser_xhinker.py
index 7b4d32d56..cce59d262 100644
--- a/modules/prompt_parser_xhinker.py
+++ b/modules/prompt_parser_xhinker.py
@@ -27,10 +27,7 @@ from diffusers import ChromaPipeline
 from modules.prompt_parser import parse_prompt_attention  # use built-in A1111 parser
 
 
-def get_prompts_tokens_with_weights(
-        clip_tokenizer: CLIPTokenizer
-        , prompt: str = None
-):
+def get_prompts_tokens_with_weights(clip_tokenizer: CLIPTokenizer, prompt: str | None = None):
     """
     Get prompt token ids and weights, this function works for both prompt and negative prompt
 
@@ -754,13 +751,7 @@ def get_weighted_text_embeddings_sdxl_refiner(
     return prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
 
 
-def get_weighted_text_embeddings_sdxl_2p(
-        pipe: StableDiffusionXLPipeline
-        , prompt: str = ""
-        , prompt_2: str = None
-        , neg_prompt: str = ""
-        , neg_prompt_2: str = None
-):
+def get_weighted_text_embeddings_sdxl_2p(pipe: StableDiffusionXLPipeline, prompt: str = "", prompt_2: str | None = None, neg_prompt: str = "", neg_prompt_2: str | None = None):
     """
     This function can process long prompt with weights, no length limitation
     for Stable Diffusion XL, support two prompt sets.
@@ -1345,12 +1336,7 @@ def get_weighted_text_embeddings_sd3(
     return sd3_prompt_embeds, sd3_neg_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
 
 
-def get_weighted_text_embeddings_flux1(
-        pipe: FluxPipeline
-        , prompt: str = ""
-        , prompt2: str = None
-        , device=None
-):
+def get_weighted_text_embeddings_flux1(pipe: FluxPipeline, prompt: str = "", prompt2: str | None = None, device=None):
     """
     This function can process long prompt with weights for flux1 model
 
diff --git a/modules/ras/ras_forward.py b/modules/ras/ras_forward.py
index ef0f245ea..14a2080b7 100644
--- a/modules/ras/ras_forward.py
+++ b/modules/ras/ras_forward.py
@@ -22,10 +22,10 @@ from . import ras_manager
 def ras_forward(
         self,
         hidden_states: torch.FloatTensor,
-        encoder_hidden_states: torch.FloatTensor = None,
-        pooled_projections: torch.FloatTensor = None,
-        timestep: torch.LongTensor = None,
-        block_controlnet_hidden_states: list = None,
+        encoder_hidden_states: torch.FloatTensor | None = None,
+        pooled_projections: torch.FloatTensor | None = None,
+        timestep: torch.LongTensor | None = None,
+        block_controlnet_hidden_states: list | None = None,
         joint_attention_kwargs: dict[str, Any] | None = None,
         return_dict: bool = True,
         skip_layers: list[int] | None = None,

From f0bb0a921a8d0727489437615d063858bd3e5db6 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 05:13:11 -0700
Subject: [PATCH 18/25] RUF013 updates and value handling fix

---
 modules/sd_models.py | 4 +++-
 modules/ui_models.py | 2 +-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/modules/sd_models.py b/modules/sd_models.py
index b2f7f3c55..57fd85ff8 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -1418,7 +1418,7 @@ def hf_auth_check(checkpoint_info, force:bool=False):
         return False
 
 
-def save_model(name: str, path: str = None, shard: str = None, overwrite: bool = False):
+def save_model(name: str, path: str | None = None, shard: str = "5GB", overwrite = False):
     if (name is None) or len(name.strip()) == 0:
         log.error('Save model: invalid model name')
         return 'Invalid model name'
@@ -1432,6 +1432,8 @@ def save_model(name: str, path: str = None, shard: str = None, overwrite: bool =
     if os.path.exists(model_name) and not overwrite:
         log.error(f'Save model: path="{model_name}" exists')
         return f'Path exists: {model_name}'
+    if not shard.strip():
+        shard = "5GB"  # Guard against empty input
     try:
         t0 = time.time()
         save_sdnq_model(
diff --git a/modules/ui_models.py b/modules/ui_models.py
index 2856448e6..881c11649 100644
--- a/modules/ui_models.py
+++ b/modules/ui_models.py
@@ -75,7 +75,7 @@ def create_ui():
                     with gr.Row():
                         save_path = gr.Textbox(label="Model base path", placeholder="Path to save model to", value=opts.diffusers_dir)
                     with gr.Row():
-                        save_shard = gr.Textbox(label="Max shard size", placeholder="Maximum shard size", value="10GB")
+                        save_shard = gr.Textbox(label="Max shard size", placeholder="Maximum shard size", value="5GB")
                         save_overwrite = gr.Checkbox(label="Overwrite existing", value=False)
                     with gr.Row():
                         save_result = gr.HTML(value="", elem_id="model_save_outcome")

From 3f830589d122b792997935da2a92346514c5cc3c Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 05:19:51 -0700
Subject: [PATCH 19/25] RUF013 updates and typing update

---
 modules/sd_offload.py     | 2 +-
 modules/sd_offload_aux.py | 2 +-
 modules/sd_te_remote.py   | 2 +-
 modules/sd_unet.py        | 8 ++++----
 4 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/modules/sd_offload.py b/modules/sd_offload.py
index e2568f1f5..da478b883 100644
--- a/modules/sd_offload.py
+++ b/modules/sd_offload.py
@@ -467,7 +467,7 @@ def report_model_stats(module_name, module):
         log.error(f'Module stats: name={module_name} {e}')
 
 
-def apply_balanced_offload(sd_model=None, exclude:list[str]=None, force:bool=False, silent:bool=False):
+def apply_balanced_offload(sd_model=None, exclude: list[str] | None = None, force: bool = False, silent: bool = False):
     global offload_hook_instance # pylint: disable=global-statement
     if shared.opts.diffusers_offload_mode != "balanced":
         return sd_model
diff --git a/modules/sd_offload_aux.py b/modules/sd_offload_aux.py
index 8578b8184..26c8c9fa7 100644
--- a/modules/sd_offload_aux.py
+++ b/modules/sd_offload_aux.py
@@ -33,7 +33,7 @@ def deregister_aux(name: str) -> None:
         debug_move(f'Offload: type=aux op=deregister name={name}')
 
 
-def evict_aux(exclude: str = None, reason: str = 'evict') -> None:
+def evict_aux(exclude: str | None = None, reason: str = 'evict') -> None:
     for name, entry in aux_models.items():
         if name == exclude:
             continue
diff --git a/modules/sd_te_remote.py b/modules/sd_te_remote.py
index 36c920762..6a87df927 100644
--- a/modules/sd_te_remote.py
+++ b/modules/sd_te_remote.py
@@ -8,7 +8,7 @@ from modules.logger import log
 
 
 def get_t5_prompt_embeds(
-    prompt: str | list[str] = None,
+    prompt: str | list[str] | None = None,
     num_images_per_prompt: int = 1, # pylint: disable=unused-argument
     max_sequence_length: int = 512, # pylint: disable=unused-argument
     device: torch.device | None = None,
diff --git a/modules/sd_unet.py b/modules/sd_unet.py
index a3ac1c633..6b5d94545 100644
--- a/modules/sd_unet.py
+++ b/modules/sd_unet.py
@@ -35,11 +35,11 @@ def load_unet_sdxl_nunchaku(repo_id):
     return unet
 
 
-def load_unet(model, repo_id:str=None):
-    global loaded_unet # pylint: disable=global-statement
+def load_unet(model, repo_id: str | None = None):
+    global loaded_unet  # pylint: disable=global-statement
 
-    if ("StableDiffusionXLPipeline" in model.__class__.__name__) and (('stable-diffusion-xl-base' in repo_id) or ('sdxl-turbo' in repo_id)):
-        if model_quant.check_nunchaku('Model'):
+    if ("StableDiffusionXLPipeline" in model.__class__.__name__) and repo_id is not None and (("stable-diffusion-xl-base" in repo_id) or ("sdxl-turbo" in repo_id)):
+        if model_quant.check_nunchaku("Model"):
             unet = load_unet_sdxl_nunchaku(repo_id)
             if unet is not None:
                 model.unet = unet

From c4ebef29a9dd70148af3229da1cdd63e5bce4be2 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 05:48:19 -0700
Subject: [PATCH 20/25] RUF013 updates

---
 modules/prompt_parser_diffusers.py            |  2 +-
 modules/sdnq/file_loader.py                   |  8 ++--
 modules/sdnq/layers/conv/conv_fp16.py         | 10 ++---
 modules/sdnq/layers/conv/conv_fp8.py          | 10 ++---
 .../sdnq/layers/conv/conv_fp8_tensorwise.py   | 10 ++---
 modules/sdnq/layers/conv/conv_int8.py         | 10 ++---
 modules/sdnq/layers/conv/forward.py           |  6 +--
 modules/sdnq/layers/linear/linear_fp16.py     | 10 ++---
 modules/sdnq/layers/linear/linear_fp8.py      | 10 ++---
 .../layers/linear/linear_fp8_tensorwise.py    | 10 ++---
 modules/sdnq/layers/linear/linear_int8.py     | 10 ++---
 modules/sdnq/loader.py                        |  8 ++--
 modules/sdnq/quantizer.py                     | 42 +++++++++----------
 13 files changed, 73 insertions(+), 73 deletions(-)

diff --git a/modules/prompt_parser_diffusers.py b/modules/prompt_parser_diffusers.py
index 93bfcbdab..8c7dd13ba 100644
--- a/modules/prompt_parser_diffusers.py
+++ b/modules/prompt_parser_diffusers.py
@@ -600,7 +600,7 @@ def split_prompts(pipe, prompt, SD3 = False):
     return prompt, prompt2, prompt3, prompt4
 
 
-def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int = None, prompt_mean_norm=None, diffusers_zeros_prompt_pad=None, te_pooled_embeds=None):
+def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int | None = None, prompt_mean_norm=None, diffusers_zeros_prompt_pad=None, te_pooled_embeds=None):
     device = devices.device
     if prompt is None:
         prompt = ''
diff --git a/modules/sdnq/file_loader.py b/modules/sdnq/file_loader.py
index 8028627b8..4390745b7 100644
--- a/modules/sdnq/file_loader.py
+++ b/modules/sdnq/file_loader.py
@@ -13,7 +13,7 @@ def map_keys(key: str, key_mapping: dict) -> str:
     return new_key
 
 
-def load_safetensors(files: list[str], state_dict: dict = None, key_mapping: dict = None, device: torch.device = "cpu") -> dict:
+def load_safetensors(files: list[str], state_dict: dict | None = None, key_mapping: dict | None = None, device: torch.device = "cpu") -> dict:
     from safetensors.torch import safe_open
     if state_dict is None:
         state_dict = {}
@@ -23,7 +23,7 @@ def load_safetensors(files: list[str], state_dict: dict = None, key_mapping: dic
                 state_dict[map_keys(key, key_mapping)] = f.get_tensor(key)
 
 
-def load_threaded(files: list[str], state_dict: dict = None, key_mapping: dict = None, device: torch.device = "cpu") -> dict:
+def load_threaded(files: list[str], state_dict: dict | None = None, key_mapping: dict | None = None, device: torch.device = "cpu") -> dict:
     future_items = {}
     if state_dict is None:
         state_dict = {}
@@ -34,7 +34,7 @@ def load_threaded(files: list[str], state_dict: dict = None, key_mapping: dict =
             future.result()
 
 
-def load_streamer(files: list[str], state_dict: dict = None, key_mapping: dict = None, device: torch.device = "cpu") -> dict:
+def load_streamer(files: list[str], state_dict: dict | None = None, key_mapping: dict | None = None, device: torch.device = "cpu") -> dict:
     # requires pip install runai_model_streamer
     from runai_model_streamer import SafetensorsStreamer
     if state_dict is None:
@@ -45,7 +45,7 @@ def load_streamer(files: list[str], state_dict: dict = None, key_mapping: dict =
             state_dict[map_keys(key, key_mapping)] = tensor.to(device)
 
 
-def load_files(files: list[str], state_dict: dict = None, key_mapping: dict = None, device: torch.device = "cpu", method: str = None) -> dict:
+def load_files(files: list[str], state_dict: dict | None = None, key_mapping: dict | None = None, device: torch.device = "cpu", method: str | None = None) -> dict:
     # note: files is list-of-files within a module for chunked loading, not accross model
     if isinstance(files, str):
         files = [files]
diff --git a/modules/sdnq/layers/conv/conv_fp16.py b/modules/sdnq/layers/conv/conv_fp16.py
index 31beb017e..4f6cdecef 100644
--- a/modules/sdnq/layers/conv/conv_fp16.py
+++ b/modules/sdnq/layers/conv/conv_fp16.py
@@ -20,11 +20,11 @@ def conv_fp16_matmul(
     padding_mode: str, conv_type: int,
     groups: int, stride: list[int],
     padding: list[int], dilation: list[int],
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     return_dtype = input.dtype
     input, mm_output_shape = process_conv_input(conv_type, input, reversed_padding_repeated_twice, padding_mode, result_shape, stride, padding, dilation)
diff --git a/modules/sdnq/layers/conv/conv_fp8.py b/modules/sdnq/layers/conv/conv_fp8.py
index 3595a5366..2099dfd18 100644
--- a/modules/sdnq/layers/conv/conv_fp8.py
+++ b/modules/sdnq/layers/conv/conv_fp8.py
@@ -19,11 +19,11 @@ def conv_fp8_matmul(
     padding_mode: str, conv_type: int,
     groups: int, stride: list[int],
     padding: list[int], dilation: list[int],
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     return_dtype = input.dtype
     input, mm_output_shape = process_conv_input(conv_type, input, reversed_padding_repeated_twice, padding_mode, result_shape, stride, padding, dilation)
diff --git a/modules/sdnq/layers/conv/conv_fp8_tensorwise.py b/modules/sdnq/layers/conv/conv_fp8_tensorwise.py
index 38258bff7..2ad268eb8 100644
--- a/modules/sdnq/layers/conv/conv_fp8_tensorwise.py
+++ b/modules/sdnq/layers/conv/conv_fp8_tensorwise.py
@@ -20,11 +20,11 @@ def conv_fp8_matmul_tensorwise(
     padding_mode: str, conv_type: int,
     groups: int, stride: list[int],
     padding: list[int], dilation: list[int],
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     return_dtype = input.dtype
     input, mm_output_shape = process_conv_input(conv_type, input, reversed_padding_repeated_twice, padding_mode, result_shape, stride, padding, dilation)
diff --git a/modules/sdnq/layers/conv/conv_int8.py b/modules/sdnq/layers/conv/conv_int8.py
index df54830ef..b5b2dcebf 100644
--- a/modules/sdnq/layers/conv/conv_int8.py
+++ b/modules/sdnq/layers/conv/conv_int8.py
@@ -20,11 +20,11 @@ def conv_int8_matmul(
     padding_mode: str, conv_type: int,
     groups: int, stride: list[int],
     padding: list[int], dilation: list[int],
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     return_dtype = input.dtype
     input, mm_output_shape = process_conv_input(conv_type, input, reversed_padding_repeated_twice, padding_mode, result_shape, stride, padding, dilation)
diff --git a/modules/sdnq/layers/conv/forward.py b/modules/sdnq/layers/conv/forward.py
index 9f6336173..2504b9090 100644
--- a/modules/sdnq/layers/conv/forward.py
+++ b/modules/sdnq/layers/conv/forward.py
@@ -76,16 +76,16 @@ def quantized_conv_forward(self, input) -> torch.FloatTensor:
     return self._conv_forward(input, self.sdnq_dequantizer(self.weight, self.scale, self.zero_point, self.svd_up, self.svd_down), self.bias)
 
 
-def quantized_conv_transpose_1d_forward(self, input: torch.FloatTensor, output_size: list[int] = None) -> torch.FloatTensor:
+def quantized_conv_transpose_1d_forward(self, input: torch.FloatTensor, output_size: list[int] | None = None) -> torch.FloatTensor:
     output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size, 1, self.dilation)
     return torch.nn.functional.conv_transpose1d(input, self.sdnq_dequantizer(self.weight, self.scale, self.zero_point, self.svd_up, self.svd_down), self.bias, self.stride, self.padding, output_padding, self.groups, self.dilation)
 
 
-def quantized_conv_transpose_2d_forward(self, input: torch.FloatTensor, output_size: list[int] = None) -> torch.FloatTensor:
+def quantized_conv_transpose_2d_forward(self, input: torch.FloatTensor, output_size: list[int] | None = None) -> torch.FloatTensor:
     output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size, 2, self.dilation)
     return torch.nn.functional.conv_transpose2d(input, self.sdnq_dequantizer(self.weight, self.scale, self.zero_point, self.svd_up, self.svd_down), self.bias, self.stride, self.padding, output_padding, self.groups, self.dilation)
 
 
-def quantized_conv_transpose_3d_forward(self, input: torch.FloatTensor, output_size: list[int] = None) -> torch.FloatTensor:
+def quantized_conv_transpose_3d_forward(self, input: torch.FloatTensor, output_size: list[int] | None = None) -> torch.FloatTensor:
     output_padding = self._output_padding(input, output_size, self.stride, self.padding, self.kernel_size, 3, self.dilation)
     return torch.nn.functional.conv_transpose3d(input, self.sdnq_dequantizer(self.weight, self.scale, self.zero_point, self.svd_up, self.svd_down), self.bias, self.stride, self.padding, output_padding, self.groups, self.dilation)
diff --git a/modules/sdnq/layers/linear/linear_fp16.py b/modules/sdnq/layers/linear/linear_fp16.py
index 2999d09cb..705aaeb6f 100644
--- a/modules/sdnq/layers/linear/linear_fp16.py
+++ b/modules/sdnq/layers/linear/linear_fp16.py
@@ -14,11 +14,11 @@ def fp16_matmul(
     input: torch.FloatTensor,
     weight: torch.Tensor,
     scale: torch.FloatTensor,
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     if quantized_weight_shape is not None:
         weight = unpack_float(weight, weights_dtype, quantized_weight_shape).to(dtype=torch.float16).t_()
diff --git a/modules/sdnq/layers/linear/linear_fp8.py b/modules/sdnq/layers/linear/linear_fp8.py
index c0b005b75..132dcb647 100644
--- a/modules/sdnq/layers/linear/linear_fp8.py
+++ b/modules/sdnq/layers/linear/linear_fp8.py
@@ -19,11 +19,11 @@ def fp8_matmul(
     input: torch.FloatTensor,
     weight: torch.Tensor,
     scale: torch.FloatTensor,
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     if quantized_weight_shape is not None:
         weight = unpack_float(weight, weights_dtype, quantized_weight_shape).to(dtype=torch.float8_e4m3fn).t_()
diff --git a/modules/sdnq/layers/linear/linear_fp8_tensorwise.py b/modules/sdnq/layers/linear/linear_fp8_tensorwise.py
index 9977fbe7c..235dde48d 100644
--- a/modules/sdnq/layers/linear/linear_fp8_tensorwise.py
+++ b/modules/sdnq/layers/linear/linear_fp8_tensorwise.py
@@ -22,11 +22,11 @@ def fp8_matmul_tensorwise(
     input: torch.FloatTensor,
     weight: torch.Tensor,
     scale: torch.FloatTensor,
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     if quantized_weight_shape is not None:
         weight = unpack_float(weight, weights_dtype, quantized_weight_shape).to(dtype=torch.float8_e4m3fn).t_()
diff --git a/modules/sdnq/layers/linear/linear_int8.py b/modules/sdnq/layers/linear/linear_int8.py
index 21eed8e10..e34222c5f 100644
--- a/modules/sdnq/layers/linear/linear_int8.py
+++ b/modules/sdnq/layers/linear/linear_int8.py
@@ -22,11 +22,11 @@ def int8_matmul(
     input: torch.FloatTensor,
     weight: torch.Tensor,
     scale: torch.FloatTensor,
-    bias: torch.FloatTensor = None,
-    svd_up: torch.FloatTensor = None,
-    svd_down: torch.FloatTensor = None,
-    quantized_weight_shape: torch.Size = None,
-    weights_dtype: str = None,
+    bias: torch.FloatTensor | None = None,
+    svd_up: torch.FloatTensor | None = None,
+    svd_down: torch.FloatTensor | None = None,
+    quantized_weight_shape: torch.Size | None = None,
+    weights_dtype: str | None = None,
 ) -> torch.FloatTensor:
     if quantized_weight_shape is not None:
         weight = unpack_int(weight, weights_dtype, quantized_weight_shape, dtype=torch.int8).t_()
diff --git a/modules/sdnq/loader.py b/modules/sdnq/loader.py
index 0edda40c0..1b3c5ae3e 100644
--- a/modules/sdnq/loader.py
+++ b/modules/sdnq/loader.py
@@ -25,7 +25,7 @@ def unset_config_on_save(quantization_config: SDNQConfig) -> SDNQConfig:
     return quantization_config
 
 
-def save_sdnq_model(model: ModelMixin, model_path: str, max_shard_size: str = "5GB", is_pipeline: bool = False, sdnq_config: SDNQConfig = None) -> None:
+def save_sdnq_model(model: ModelMixin, model_path: str, max_shard_size: str = "5GB", is_pipeline: bool = False, sdnq_config: SDNQConfig | None = None) -> None:
     if is_pipeline:
         for module_name in get_module_names(model):
             module = getattr(model, module_name, None)
@@ -63,7 +63,7 @@ def save_sdnq_model(model: ModelMixin, model_path: str, max_shard_size: str = "5
             model.config.quantization_config.to_json_file(quantization_config_path)
 
 
-def load_sdnq_model(model_path: str, model_cls: ModelMixin = None, file_name: str = None, dtype: torch.dtype = None, device: torch.device = "cpu", dequantize_fp32: bool = None, use_quantized_matmul: bool = None, model_config: dict = None, quantization_config: dict = None, load_method: str = "safetensors") -> ModelMixin:
+def load_sdnq_model(model_path: str, model_cls: ModelMixin | None = None, file_name: str | None = None, dtype: torch.dtype | None = None, device: torch.device = "cpu", dequantize_fp32: bool | None = None, use_quantized_matmul: bool | None = None, model_config: dict | None = None, quantization_config: dict | None = None, load_method: str = "safetensors") -> ModelMixin:
     from accelerate import init_empty_weights
 
     with init_empty_weights():
@@ -162,7 +162,7 @@ def post_process_model(model):
     return model
 
 
-def apply_sdnq_options_to_module(model, dtype: torch.dtype = None, dequantize_fp32: bool = None, use_quantized_matmul: bool = None):
+def apply_sdnq_options_to_module(model, dtype: torch.dtype | None = None, dequantize_fp32: bool | None = None, use_quantized_matmul: bool | None = None):
     has_children = list(model.children())
     if not has_children:
         if dtype is not None and getattr(model, "dtype", torch.float32) not in {torch.float32, torch.float64}:
@@ -231,7 +231,7 @@ def apply_sdnq_options_to_module(model, dtype: torch.dtype = None, dequantize_fp
     return model
 
 
-def apply_sdnq_options_to_model(model, dtype: torch.dtype = None, dequantize_fp32: bool = None, use_quantized_matmul: bool = None):
+def apply_sdnq_options_to_model(model, dtype: torch.dtype | None = None, dequantize_fp32: bool | None = None, use_quantized_matmul: bool | None = None):
     if use_quantized_matmul and not check_torch_compile():
         raise RuntimeError("SDNQ Quantized MatMul requires a working Triton install.")
     model = apply_sdnq_options_to_module(model, dtype=dtype, dequantize_fp32=dequantize_fp32, use_quantized_matmul=use_quantized_matmul)
diff --git a/modules/sdnq/quantizer.py b/modules/sdnq/quantizer.py
index e4b462ad0..13c89d77a 100644
--- a/modules/sdnq/quantizer.py
+++ b/modules/sdnq/quantizer.py
@@ -189,7 +189,7 @@ def get_quant_kwargs(quant_kwargs: dict, modules_quant_config: dict[str, dict])
     return quant_kwargs
 
 
-def add_module_skip_keys(model, modules_to_not_convert: list[str] = None, modules_dtype_dict: dict[str, list[str]] = None):
+def add_module_skip_keys(model, modules_to_not_convert: list[str] | None = None, modules_dtype_dict: dict[str, list[str]] | None = None):
     if modules_to_not_convert is None:
         modules_to_not_convert = []
     if modules_dtype_dict is None:
@@ -547,7 +547,7 @@ def sdnq_quantize_layer(layer, weights_dtype="int8", quantized_matmul_dtype=None
 
 
 @devices.inference_context()
-def apply_sdnq_to_module(model, weights_dtype="int8", quantized_matmul_dtype=None, torch_dtype=None, group_size=0, svd_rank=32, svd_steps=8, dynamic_loss_threshold=1e-2, use_svd=False, quant_conv=False, use_quantized_matmul=False, use_quantized_matmul_conv=False, use_dynamic_quantization=False, use_stochastic_rounding=False, dequantize_fp32=True, non_blocking=False, modules_to_not_convert: list[str] = None, modules_dtype_dict: dict[str, list[str]] = None, modules_quant_config: dict[str, dict] = None, quantization_device=None, return_device=None, full_param_name=""): # pylint: disable=unused-argument
+def apply_sdnq_to_module(model, weights_dtype="int8", quantized_matmul_dtype=None, torch_dtype=None, group_size=0, svd_rank=32, svd_steps=8, dynamic_loss_threshold=1e-2, use_svd=False, quant_conv=False, use_quantized_matmul=False, use_quantized_matmul_conv=False, use_dynamic_quantization=False, use_stochastic_rounding=False, dequantize_fp32=True, non_blocking=False, modules_to_not_convert: list[str] | None = None, modules_dtype_dict: dict[str, list[str]] | None = None, modules_quant_config: dict[str, dict] | None = None, quantization_device=None, return_device=None, full_param_name=""): # pylint: disable=unused-argument
     has_children = list(model.children())
     if not has_children:
         return model, modules_to_not_convert, modules_dtype_dict
@@ -628,8 +628,8 @@ def apply_sdnq_to_module(model, weights_dtype="int8", quantized_matmul_dtype=Non
 def sdnq_post_load_quant(
     model: torch.nn.Module,
     weights_dtype: str = "int8",
-    quantized_matmul_dtype: str = None,
-    torch_dtype: torch.dtype = None,
+    quantized_matmul_dtype: str | None = None,
+    torch_dtype: torch.dtype | None = None,
     group_size: int = 0,
     svd_rank: int = 32,
     svd_steps: int = 8,
@@ -643,11 +643,11 @@ def sdnq_post_load_quant(
     dequantize_fp32: bool = True,
     non_blocking: bool = False,
     add_skip_keys:bool = True,
-    quantization_device: torch.device = None,
-    return_device: torch.device = None,
-    modules_to_not_convert: list[str] = None,
-    modules_dtype_dict: dict[str, list[str]] = None,
-    modules_quant_config: dict[str, dict] = None,
+    quantization_device: torch.device | None = None,
+    return_device: torch.device | None = None,
+    modules_to_not_convert: list[str] | None = None,
+    modules_dtype_dict: dict[str, list[str]] | None = None,
+    modules_quant_config: dict[str, dict] | None = None,
 ):
     if modules_to_not_convert is None:
         modules_to_not_convert = []
@@ -735,9 +735,9 @@ class SDNQQuantize:
     def convert(
         self,
         input_dict: dict[str, list[torch.Tensor]],
-        model: torch.nn.Module = None,
-        full_layer_name: str = None,
-        missing_keys: list[str] = None, # pylint: disable=unused-argument
+        model: torch.nn.Module | None = None,
+        full_layer_name: str | None = None,
+        missing_keys: list[str] | None = None, # pylint: disable=unused-argument
         **kwargs, # pylint: disable=unused-argument
     ) -> dict[str, torch.FloatTensor]:
         _module_name, value = tuple(input_dict.items())[0]
@@ -898,11 +898,11 @@ class SDNQQuantizer(DiffusersQuantizer, HfQuantizer):
     def adjust_target_dtype(self, target_dtype: torch.dtype) -> torch.dtype: # pylint: disable=unused-argument,arguments-renamed
         return dtype_dict[self.quantization_config.weights_dtype]["target_dtype"]
 
-    def update_torch_dtype(self, torch_dtype: torch.dtype = None) -> torch.dtype:
+    def update_torch_dtype(self, torch_dtype: torch.dtype | None = None) -> torch.dtype:
         self.torch_dtype = torch_dtype
         return torch_dtype
 
-    def update_dtype(self, dtype: torch.dtype = None) -> torch.dtype:
+    def update_dtype(self, dtype: torch.dtype | None = None) -> torch.dtype:
         """
         needed for transformers compatibilty, returns self.update_torch_dtype
         """
@@ -912,7 +912,7 @@ class SDNQQuantizer(DiffusersQuantizer, HfQuantizer):
         self,
         model,
         device_map, # pylint: disable=unused-argument
-        keep_in_fp32_modules: list[str] = None,
+        keep_in_fp32_modules: list[str] | None = None,
         **kwargs, # pylint: disable=unused-argument
     ):
         if self.pre_quantized:
@@ -1055,7 +1055,7 @@ class SDNQConfig(QuantizationConfigMixin):
     def __init__( # pylint: disable=super-init-not-called
         self,
         weights_dtype: str = "int8",
-        quantized_matmul_dtype: str = None,
+        quantized_matmul_dtype: str | None = None,
         group_size: int = 0,
         svd_rank: int = 32,
         svd_steps: int = 8,
@@ -1071,11 +1071,11 @@ class SDNQConfig(QuantizationConfigMixin):
         dequantize_fp32: bool = True,
         non_blocking: bool = False,
         add_skip_keys: bool = True,
-        quantization_device: torch.device = None,
-        return_device: torch.device = None,
-        modules_to_not_convert: list[str] = None,
-        modules_dtype_dict: dict[str, list[str]] = None,
-        modules_quant_config: dict[str, dict] = None,
+        quantization_device: torch.device | None = None,
+        return_device: torch.device | None = None,
+        modules_to_not_convert: list[str] | None = None,
+        modules_dtype_dict: dict[str, list[str]] | None = None,
+        modules_quant_config: dict[str, dict] | None = None,
         is_training: bool = False,
         **kwargs, # pylint: disable=unused-argument
     ):

From 09ab19c43883765b6a487853bb2c889619278add Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 06:07:34 -0700
Subject: [PATCH 21/25] RUF013 updates and formatting

---
 modules/shared_state.py            |  4 +-
 modules/taesd/hybrid_small.py      |  4 +-
 modules/textual_inversion.py       |  2 +-
 modules/todo/todo_merge.py         |  2 +-
 modules/ui_control.py              |  4 +-
 modules/ui_sections.py             |  4 +-
 modules/ui_video_vlm.py            |  2 +-
 modules/vae/sd_vae_fal.py          |  8 ++--
 modules/video_models/video_save.py | 59 +++++++++++++++---------------
 9 files changed, 45 insertions(+), 44 deletions(-)

diff --git a/modules/shared_state.py b/modules/shared_state.py
index f1ac2b975..8357cea4d 100644
--- a/modules/shared_state.py
+++ b/modules/shared_state.py
@@ -148,7 +148,7 @@ class State:
                 return job
         return None
 
-    def history(self, op:str, task_id:str=None, results:list=None):
+    def history(self, op: str, task_id: str | None = None, results: list | None = None):
         if results is None:
             results = []
         job = {
@@ -174,7 +174,7 @@ class State:
         if len(self.results) > 0:
             self.history('output', self.id, results=self.results)
 
-    def get_id(self, task_id:str=None):
+    def get_id(self, task_id: str | None = None):
         if task_id is None or task_id == 0:
             task_id = uuid.uuid4().hex[:15]
         if not isinstance(task_id, str):
diff --git a/modules/taesd/hybrid_small.py b/modules/taesd/hybrid_small.py
index 8ca1135ab..964541d2c 100644
--- a/modules/taesd/hybrid_small.py
+++ b/modules/taesd/hybrid_small.py
@@ -76,8 +76,8 @@ class AutoencoderSmall(ModelMixin, ConfigMixin, FromOriginalModelMixin):
         down_block_types: tuple[str] = ("DownEncoderBlock2D",),
         up_block_types: tuple[str] = ("UpDecoderBlock2D",),
         block_out_channels: tuple[int] = (64,),
-        encoder_block_out_channels: tuple[int] = None,
-        decoder_block_out_channels: tuple[int] = None,
+        encoder_block_out_channels: tuple[int] | None = None,
+        decoder_block_out_channels: tuple[int] | None = None,
         layers_per_block: int = 1,
         act_fn: str = "silu",
         latent_channels: int = 4,
diff --git a/modules/textual_inversion.py b/modules/textual_inversion.py
index 32ca1a54e..de2d22278 100644
--- a/modules/textual_inversion.py
+++ b/modules/textual_inversion.py
@@ -254,7 +254,7 @@ class EmbeddingDatabase:
         self.ids_lookup[first_id] = sorted(self.ids_lookup[first_id] + [(ids, embedding)], key=lambda x: len(x[0]), reverse=True)
         return embedding
 
-    def load_diffusers_embedding(self, filename: str | list[str] = None, data: dict = None):
+    def load_diffusers_embedding(self, filename: str | list[str] | None = None, data: dict | None = None):
         """
         File names take precidence over bundled embeddings passed as a dict.
         Bundled embeddings are automatically set to overwrite previous embeddings.
diff --git a/modules/todo/todo_merge.py b/modules/todo/todo_merge.py
index cde8381fe..bc03b96c7 100644
--- a/modules/todo/todo_merge.py
+++ b/modules/todo/todo_merge.py
@@ -38,7 +38,7 @@ def init_generator(device: torch.device, fallback: torch.Generator = None):
             return fallback
 
 
-def do_nothing(x: torch.Tensor, mode: str = None): # pylint: disable=unused-argument
+def do_nothing(x: torch.Tensor, mode: str | None = None): # pylint: disable=unused-argument
     return x
 
 
diff --git a/modules/ui_control.py b/modules/ui_control.py
index 9be9bc3b3..da4784403 100644
--- a/modules/ui_control.py
+++ b/modules/ui_control.py
@@ -19,7 +19,7 @@ debug('Trace: CONTROL')
 use_generator = os.environ.get('SD_USE_GENERATOR', None) is not None
 
 
-def return_stats(t: float = None):
+def return_stats(t: float | None = None):
     if t is None:
         elapsed_text = ''
     else:
@@ -48,7 +48,7 @@ def return_stats(t: float = None):
     return f"<div class='performance'><p>{elapsed_text} {summary} {gpu} {cpu}</p></div>"
 
 
-def return_controls(res, t: float = None):
+def return_controls(res, t: float | None = None):
     # return preview, image, video, gallery, text
     debug(f'Control received: type={type(res)} {res}')
     if t is None:
diff --git a/modules/ui_sections.py b/modules/ui_sections.py
index 886e392a2..32b71b193 100644
--- a/modules/ui_sections.py
+++ b/modules/ui_sections.py
@@ -5,7 +5,7 @@ from modules.ui_components import ToolButton
 from modules.caption import caption
 
 
-def create_toprow(is_img2img: bool = False, id_part: str = None, generate_visible: bool = True, negative_visible: bool = True, reprocess_visible: bool = True):
+def create_toprow(is_img2img: bool = False, id_part: str | None = None, generate_visible: bool = True, negative_visible: bool = True, reprocess_visible: bool = True):
     def apply_styles(prompt, prompt_neg, styles):
         prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles, wildcards=not shared.opts.extra_networks_apply_unparsed)
         prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles, wildcards=not shared.opts.extra_networks_apply_unparsed)
@@ -92,7 +92,7 @@ def create_resolution_inputs(tab, default_width=1024, default_height=1024):
     return width, height
 
 
-def create_caption_button(tab: str, inputs: list = None, outputs: str = None, what: str = ''):
+def create_caption_button(tab: str, inputs: list | None = None, outputs: str | None = None, what: str = ''):
     button_caption = gr.Button(ui_symbols.caption, elem_id=f"{tab}_caption_{what}", elem_classes=['caption'])
     if inputs is not None and outputs is not None:
         button_caption.click(fn=caption.caption, inputs=inputs, outputs=[outputs])
diff --git a/modules/ui_video_vlm.py b/modules/ui_video_vlm.py
index 4e702c771..da3ed1ec7 100644
--- a/modules/ui_video_vlm.py
+++ b/modules/ui_video_vlm.py
@@ -21,7 +21,7 @@ system_prompts = {
 }
 
 
-def enhance_prompt(enable:bool, model:str=None, image=None, prompt:str='', system_prompt:str='', nsfw:bool=True):
+def enhance_prompt(enable: bool, model: str | None = None, image=None, prompt: str = "", system_prompt: str = "", nsfw: bool = True):
     from modules.caption import vqa
     if not enable:
         return prompt
diff --git a/modules/vae/sd_vae_fal.py b/modules/vae/sd_vae_fal.py
index d132fa77e..dc8042d1b 100644
--- a/modules/vae/sd_vae_fal.py
+++ b/modules/vae/sd_vae_fal.py
@@ -50,12 +50,12 @@ class Flux2TinyAutoEncoder(ModelMixin, ConfigMixin):
         in_channels: int = 3,
         out_channels: int = 3,
         latent_channels: int = 128,
-        encoder_block_out_channels: list[int] = None,
-        decoder_block_out_channels: list[int] = None,
+        encoder_block_out_channels: list[int] | None = None,
+        decoder_block_out_channels: list[int] | None = None,
         act_fn: str = "silu",
         upsampling_scaling_factor: int = 2,
-        num_encoder_blocks: list[int] = None,
-        num_decoder_blocks: list[int] = None,
+        num_encoder_blocks: list[int] | None = None,
+        num_decoder_blocks: list[int] | None = None,
         latent_magnitude: float = 3.0,
         latent_shift: float = 0.5,
         force_upcast: bool = False,
diff --git a/modules/video_models/video_save.py b/modules/video_models/video_save.py
index 175bc3433..bd67c321f 100644
--- a/modules/video_models/video_save.py
+++ b/modules/video_models/video_save.py
@@ -29,7 +29,7 @@ def get_video_filename(p:processing.StableDiffusionProcessingVideo):
     return filename
 
 
-def save_params(p, filename: str = None):
+def save_params(p, filename: str | None = None):
     from modules.paths import params_path
     if p is None:
         dct = {}
@@ -129,17 +129,18 @@ def write_audio(
         container.mux(packet)
 
 
-def atomic_save_video(filename: str,
-                      tensor:torch.Tensor,
-                      audio:torch.Tensor=None,
-                      fps:float=24,
-                      codec:str='libx264',
-                      pix_fmt:str='yuv420p',
-                      options:str='',
-                      aac:int=24000,
-                      metadata:dict=None,
-                      pbar=None,
-                    ):
+def atomic_save_video(
+    filename: str,
+    tensor: torch.Tensor,
+    audio: torch.Tensor | None = None,
+    fps: float = 24,
+    codec: str = "libx264",
+    pix_fmt: str = "yuv420p",
+    options: str = "",
+    aac: int = 24000,
+    metadata: dict | None = None,
+    pbar=None,
+):
     if metadata is None:
         metadata = {}
     av = check_av()
@@ -212,23 +213,23 @@ def save_thumbnail(video_path, tensor=None):
 
 
 def save_video(
-        p:processing.StableDiffusionProcessingVideo,
-        pixels:torch.Tensor=None,
-        audio:torch.Tensor=None,
-        binary:bytes=None,
-        mp4_fps:int=24,
-        mp4_codec:str='libx264',
-        mp4_opt:str='',
-        mp4_ext:str='mp4',
-        mp4_sf:bool=False, # save safetensors
-        mp4_video:bool=True, # save video
-        mp4_frames:bool=False, # save frames
-        mp4_interpolate:int=0, # rife interpolation
-        aac_sample_rate:int=24000, # audio sample rate
-        stream=None, # async progress reporting stream
-        metadata:dict=None, # metadata for video
-        pbar=None, # progress bar for video
-    ):
+    p: processing.StableDiffusionProcessingVideo,
+    pixels: torch.Tensor | None = None,
+    audio: torch.Tensor | None = None,
+    binary: bytes | None = None,
+    mp4_fps: int = 24,
+    mp4_codec: str = "libx264",
+    mp4_opt: str = "",
+    mp4_ext: str = "mp4",
+    mp4_sf: bool = False,  # save safetensors
+    mp4_video: bool = True,  # save video
+    mp4_frames: bool = False,  # save frames
+    mp4_interpolate: int = 0,  # rife interpolation
+    aac_sample_rate: int = 24000,  # audio sample rate
+    stream=None,  # async progress reporting stream
+    metadata: dict | None = None,  # metadata for video
+    pbar=None,  # progress bar for video
+):
     if metadata is None:
         metadata = {}
     output_video = None

From 1003926646a1b3a8c39d3fb3924334a89b7ab24f Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 06:08:15 -0700
Subject: [PATCH 22/25] RUF013 updates and import updates

---
 modules/upscaler.py | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/modules/upscaler.py b/modules/upscaler.py
index 44dfad48d..6bafa3db0 100644
--- a/modules/upscaler.py
+++ b/modules/upscaler.py
@@ -1,10 +1,16 @@
+from __future__ import annotations
+
 import os
 from abc import abstractmethod
+from typing import TYPE_CHECKING
 from PIL import Image
 from modules import modelloader, shared, paths
 from modules.logger import log
 
 
+if TYPE_CHECKING:
+    from torch import Tensor
+
 models = None
 
 
@@ -92,10 +98,10 @@ class Upscaler:
         return scalers
 
     @abstractmethod
-    def do_upscale(self, img: Image, selected_model: str):
+    def do_upscale(self, img: Image.Image | Tensor, selected_model: str):
         return img
 
-    def upscale(self, img: Image, scale, selected_model: str = None):
+    def upscale(self, img: Image.Image | Tensor, scale, selected_model: str | None = None):
         jobid = shared.state.begin('Upscale')
         self.scale = scale
         if isinstance(img, Image.Image):
@@ -153,10 +159,10 @@ class UpscalerData:
     name = None
     data_path = None
     scale: int = 4
-    scaler: Upscaler = None
+    scaler: Upscaler | None = None
     model: None
 
-    def __init__(self, name: str, path: str = None, upscaler: Upscaler = None, scale: int = 4, model=None):
+    def __init__(self, name: str, path: str | None = None, upscaler: Upscaler | None = None, scale: int = 4, model=None):
         self.name = name
         self.data_path = path
         self.local_data_path = path

From 876e3b9897f959dfb0fd98190f485c8376f1ff8e Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 06:15:26 -0700
Subject: [PATCH 23/25] RUF013 updates

---
 modules/apg/pipeline_stable_cascade_prior_apg.py | 4 ++--
 modules/apg/pipeline_stable_diffision_xl_apg.py  | 8 ++++----
 modules/apg/pipeline_stable_diffusion_apg.py     | 8 ++++----
 3 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/modules/apg/pipeline_stable_cascade_prior_apg.py b/modules/apg/pipeline_stable_cascade_prior_apg.py
index 6ffaf8089..c4747612d 100644
--- a/modules/apg/pipeline_stable_cascade_prior_apg.py
+++ b/modules/apg/pipeline_stable_cascade_prior_apg.py
@@ -372,7 +372,7 @@ class StableCascadePriorPipelineAPG(DiffusionPipeline):
         height: int = 1024,
         width: int = 1024,
         num_inference_steps: int = 20,
-        timesteps: list[float] = None,
+        timesteps: list[float] | None = None,
         guidance_scale: float = 4.0,
         negative_prompt: str | list[str] | None = None,
         prompt_embeds: torch.Tensor | None = None,
@@ -386,7 +386,7 @@ class StableCascadePriorPipelineAPG(DiffusionPipeline):
         output_type: str | None = "pt",
         return_dict: bool = True,
         callback_on_step_end: Callable[[int, int, dict], None] | None = None,
-        callback_on_step_end_tensor_inputs: list[str] = None,
+        callback_on_step_end_tensor_inputs: list[str] | None = None,
     ):
         """
         Function invoked when calling the pipeline for generation.
diff --git a/modules/apg/pipeline_stable_diffision_xl_apg.py b/modules/apg/pipeline_stable_diffision_xl_apg.py
index b09ae242f..5da74c299 100644
--- a/modules/apg/pipeline_stable_diffision_xl_apg.py
+++ b/modules/apg/pipeline_stable_diffision_xl_apg.py
@@ -793,13 +793,13 @@ class StableDiffusionXLPipelineAPG(
     @replace_example_docstring(EXAMPLE_DOC_STRING)
     def __call__(
         self,
-        prompt: str | list[str] = None,
+        prompt: str | list[str] | None = None,
         prompt_2: str | list[str] | None = None,
         height: int | None = None,
         width: int | None = None,
         num_inference_steps: int = 50,
-        timesteps: list[int] = None,
-        sigmas: list[float] = None,
+        timesteps: list[int] | None = None,
+        sigmas: list[float] | None = None,
         denoising_end: float | None = None,
         guidance_scale: float = 5.0,
         negative_prompt: str | list[str] | None = None,
@@ -826,7 +826,7 @@ class StableDiffusionXLPipelineAPG(
         negative_target_size: tuple[int, int] | None = None,
         clip_skip: int | None = None,
         callback_on_step_end: Callable[[int, int, dict], None] | PipelineCallback | MultiPipelineCallbacks | None = None,
-        callback_on_step_end_tensor_inputs: list[str] = None,
+        callback_on_step_end_tensor_inputs: list[str] | None = None,
         **kwargs,
     ):
         r"""
diff --git a/modules/apg/pipeline_stable_diffusion_apg.py b/modules/apg/pipeline_stable_diffusion_apg.py
index ae1eb26e0..57aebafca 100644
--- a/modules/apg/pipeline_stable_diffusion_apg.py
+++ b/modules/apg/pipeline_stable_diffusion_apg.py
@@ -749,12 +749,12 @@ class StableDiffusionPipelineAPG(
     @replace_example_docstring(EXAMPLE_DOC_STRING)
     def __call__(
         self,
-        prompt: str | list[str] = None,
+        prompt: str | list[str] | None = None,
         height: int | None = None,
         width: int | None = None,
         num_inference_steps: int = 50,
-        timesteps: list[int] = None,
-        sigmas: list[float] = None,
+        timesteps: list[int] | None = None,
+        sigmas: list[float] | None = None,
         guidance_scale: float = 7.5,
         negative_prompt: str | list[str] | None = None,
         num_images_per_prompt: int | None = 1,
@@ -771,7 +771,7 @@ class StableDiffusionPipelineAPG(
         guidance_rescale: float = 0.0,
         clip_skip: int | None = None,
         callback_on_step_end: Callable[[int, int, dict], None] | PipelineCallback | MultiPipelineCallbacks | None = None,
-        callback_on_step_end_tensor_inputs: list[str] = None,
+        callback_on_step_end_tensor_inputs: list[str] | None = None,
         **kwargs,
     ):
         r"""

From a6f6a37dea8a2ac9d0e936e7f830b7564ae25ca4 Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 06:16:13 -0700
Subject: [PATCH 24/25] Add Ruff per-file-ignores

---
 pyproject.toml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 57db5b62f..b339015a1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -107,6 +107,9 @@ fixable = ["ALL"]
 unfixable = []
 dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
 
+[tool.ruff.lint.per-file-ignores]
+"modules/caption/joytag.py" = ["RUF013"] # Per header comment: "Do not modify directly — sync from upstream"
+
 [tool.ruff.format]
 quote-style = "double"
 indent-style = "space"

From fd1646cc37f66773a8f2eda9c56736e4f737b4ea Mon Sep 17 00:00:00 2001
From: awsr <43862868+awsr@users.noreply.github.com>
Date: Tue, 24 Mar 2026 06:28:39 -0700
Subject: [PATCH 25/25] Revert extra return statement

---
 modules/image/grid.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/modules/image/grid.py b/modules/image/grid.py
index 9ba8801fe..0c8745dbd 100644
--- a/modules/image/grid.py
+++ b/modules/image/grid.py
@@ -54,7 +54,6 @@ def get_grid_size(imgs, batch_size=1, rows: int | None = None, cols: int | None
             while len(imgs) % rows != 0:
                 rows -= 1
             cols = math.ceil(len(imgs) / rows)
-        return rows, cols
     elif rows is not None and cols is None:
         cols = math.ceil(len(imgs) / rows)
     elif rows is None and cols is not None: