apply lint

api/onnx_web/chain/tile.py

@@ -115,7 +115,12 @@ def make_tile_mask(
 
     # build gradients
     edge_t, edge_l, edge_b, edge_r = edges
-    grad_x, grad_y = [int(not edge_l), 1, 1, int(not edge_r)], [int(not edge_t), 1, 1, int(not edge_b)]
+    grad_x, grad_y = [int(not edge_l), 1, 1, int(not edge_r)], [
+        int(not edge_t),
+        1,
+        1,
+        int(not edge_b),
+    ]
     logger.debug("tile gradients: %s, %s, %s, %s", points_w, points_h, grad_x, grad_y)
 
     mult_x = [np.interp(i, points_w, grad_x) for i in range(tile_w)]

api/onnx_web/diffusers/pipelines/panorama.py

@@ -660,8 +660,10 @@ class OnnxStableDiffusionPanoramaPipeline(DiffusionPipeline):
                         region_noise_pred_uncond, region_noise_pred_text = np.split(
                             region_noise_pred, 2
                         )
-                        region_noise_pred = region_noise_pred_uncond + guidance_scale * (
-                            region_noise_pred_text - region_noise_pred_uncond
+                        region_noise_pred = (
+                            region_noise_pred_uncond
+                            + guidance_scale
+                            * (region_noise_pred_text - region_noise_pred_uncond)
                         )
 
                     # compute the previous noisy sample x_t -> x_t-1

api/onnx_web/diffusers/pipelines/panorama_xl.py

@@ -502,8 +502,10 @@ class StableDiffusionXLPanoramaPipelineMixin(StableDiffusionXLImg2ImgPipelineMix
                         region_noise_pred_uncond, region_noise_pred_text = np.split(
                             region_noise_pred, 2
                         )
-                        region_noise_pred = region_noise_pred_uncond + guidance_scale * (
-                            region_noise_pred_text - region_noise_pred_uncond
+                        region_noise_pred = (
+                            region_noise_pred_uncond
+                            + guidance_scale
+                            * (region_noise_pred_text - region_noise_pred_uncond)
                         )
                         if guidance_rescale > 0.0:
                             # Based on 3.4. in https://arxiv.org/pdf/2305.08891.pdf

api/onnx_web/diffusers/utils.py

@@ -459,7 +459,9 @@ def slice_prompt(prompt: str, slice: int) -> str:
         return prompt
 
 
-Region = Tuple[int, int, int, int, float, Tuple[float, Tuple[bool, bool, bool, bool]], str]
+Region = Tuple[
+    int, int, int, int, float, Tuple[float, Tuple[bool, bool, bool, bool]], str
+]
 
 
 def parse_region_group(group: Tuple[str, ...]) -> Region:
@@ -478,12 +480,15 @@ def parse_region_group(group: Tuple[str, ...]) -> Region:
         int(bottom),
         int(right),
         float(weight),
-        (float(feather_radius), (
-            "T" in feather_edges,
-            "L" in feather_edges,
-            "B" in feather_edges,
-            "R" in feather_edges,
-        )),
+        (
+            float(feather_radius),
+            (
+                "T" in feather_edges,
+                "L" in feather_edges,
+                "B" in feather_edges,
+                "R" in feather_edges,
+            ),
+        ),
         prompt,
     )
 

api/onnx_web/models/meta.py

@@ -8,7 +8,7 @@ class NetworkModel:
     tokens: List[str]
     type: NetworkType
 
-    def __init__(self, name: str, type: NetworkType, tokens = None) -> None:
+    def __init__(self, name: str, type: NetworkType, tokens=None) -> None:
         self.name = name
         self.tokens = tokens or []
         self.type = type

api/onnx_web/server/load.py

@@ -213,7 +213,11 @@ def load_extras(server: ServerContext):
                                     labels[model_name] = model["label"]
 
                             if "tokens" in model:
-                                logger.debug("collecting tokens for model %s from %s", model_name, file)
+                                logger.debug(
+                                    "collecting tokens for model %s from %s",
+                                    model_name,
+                                    file,
+                                )
                                 extra_tokens[model_name] = model["tokens"]
 
                             if "inversions" in model:
@@ -359,7 +363,10 @@ def load_models(server: ServerContext) -> None:
     )
     logger.debug("loaded Textual Inversion models from disk: %s", inversion_models)
     network_models.extend(
-        [NetworkModel(model, "inversion", tokens=extra_tokens.get(model, [])) for model in inversion_models]
+        [
+            NetworkModel(model, "inversion", tokens=extra_tokens.get(model, []))
+            for model in inversion_models
+        ]
     )
 
     lora_models = list_model_globs(
@@ -370,7 +377,12 @@ def load_models(server: ServerContext) -> None:
         base_path=path.join(server.model_path, "lora"),
     )
     logger.debug("loaded LoRA models from disk: %s", lora_models)
-    network_models.extend([NetworkModel(model, "lora", tokens=extra_tokens.get(model, [])) for model in lora_models])
+    network_models.extend(
+        [
+            NetworkModel(model, "lora", tokens=extra_tokens.get(model, []))
+            for model in lora_models
+        ]
+    )
 
 
 def load_params(server: ServerContext) -> None: