ran the ruff formatter

inference.py

@@ -240,10 +240,14 @@ def main():
     assert height % 32 == 0, f"Height ({height}) should be divisible by 32."
     assert width % 32 == 0, f"Width ({width}) should be divisible by 32."
     assert (
-        height,
-        width,
-        args.num_frames,
-    ) in RECOMMENDED_RESOLUTIONS or args.custom_resolution, f"The selected resolution + num frames combination is not supported, results would be suboptimal. Supported (h,w,f) are: {RECOMMENDED_RESOLUTIONS}. Use --custom_resolution to enable working with this resolution."
+        (
+            height,
+            width,
+            args.num_frames,
+        )
+        in RECOMMENDED_RESOLUTIONS
+        or args.custom_resolution
+    ), f"The selected resolution + num frames combination is not supported, results would be suboptimal. Supported (h,w,f) are: {RECOMMENDED_RESOLUTIONS}. Use --custom_resolution to enable working with this resolution."
 
     # Paths for the separate mode directories
     ckpt_dir = Path(args.ckpt_dir)
@@ -296,8 +300,10 @@ def main():
     torch.manual_seed(args.seed)
     if torch.cuda.is_available():
         torch.cuda.manual_seed(args.seed)
-        
-    generator = torch.Generator(device="cuda" if torch.cuda.is_available() else 'cpu').manual_seed(args.seed)
+
+    generator = torch.Generator(
+        device="cuda" if torch.cuda.is_available() else "cpu"
+    ).manual_seed(args.seed)
 
     images = pipeline(
         num_inference_steps=args.num_inference_steps,

xora/pipelines/pipeline_xora_video.py

@@ -1010,9 +1010,11 @@ class XoraVideoPipeline(DiffusionPipeline):
                     current_timestep = current_timestep * (1 - conditioning_mask)
                 # Choose the appropriate context manager based on `mixed_precision`
                 if mixed_precision:
-                    if 'xla' in device.type:
-                        raise NotImplementedError("Mixed precision is not supported yet on XLA devices.")
-                        
+                    if "xla" in device.type:
+                        raise NotImplementedError(
+                            "Mixed precision is not supported yet on XLA devices."
+                        )
+
                     context_manager = torch.autocast(device, dtype=torch.bfloat16)
                 else:
                     context_manager = nullcontext()  # Dummy context manager