(style) fix ruff and typegen errors

invokeai/app/invocations/seed_variance_enhancer.py

@@ -99,9 +99,7 @@ class SeedVarianceEnhancerInvocation(BaseInvocation):
         # Early return if strength is zero
         if self.strength == 0:
             if self.log_statistics:
-                context.logger.info(
-                    "Seed Variance Enhancer strength is zero. Passing conditioning through unchanged."
-                )
+                context.logger.info("Seed Variance Enhancer strength is zero. Passing conditioning through unchanged.")
                 self._log_statistics(context, conditioning_data)
             return ZImageConditioningOutput(conditioning=self.conditioning)
 
@@ -141,7 +139,7 @@ class SeedVarianceEnhancerInvocation(BaseInvocation):
 
     def _apply_noise(self, context: InvocationContext, prompt_embeds: torch.Tensor) -> torch.Tensor:
         """Apply random noise to prompt embeddings.
-        
+
         Z-Image uses 2D tensors: [seq_len, hidden_size]
         """
         # Normalize parameters
@@ -191,9 +189,7 @@ class SeedVarianceEnhancerInvocation(BaseInvocation):
 
                 # Convert is_null_list to tensor: True where sequences should be protected (null sequences)
                 null_mask_tensor = torch.tensor(is_null_list, device=prompt_embeds.device, dtype=torch.bool)
-                null_mask_tensor = null_mask_tensor.unsqueeze(1).expand(
-                    prompt_embeds.size(0), prompt_embeds.size(1)
-                )
+                null_mask_tensor = null_mask_tensor.unsqueeze(1).expand(prompt_embeds.size(0), prompt_embeds.size(1))
                 prompt_mask = prompt_mask | null_mask_tensor
 
             # Combine with noise mask
@@ -207,7 +203,7 @@ class SeedVarianceEnhancerInvocation(BaseInvocation):
 
     def _find_null_sequences(self, tensor: torch.Tensor) -> tuple[int, int, list[int]]:
         """Find sequences in tensor that contain all zeros (padding).
-        
+
         Z-Image uses 2D tensors: [seq_len, hidden_size]
 
         Returns:
@@ -216,7 +212,7 @@ class SeedVarianceEnhancerInvocation(BaseInvocation):
         """
         first_null = -1
         last_nonnull = -1
-        
+
         # For 2D tensor: dimension 0 = seq_len, dimension 1 = hidden_size
         is_null_list = [0] * tensor.size(0)
 
@@ -240,7 +236,7 @@ class SeedVarianceEnhancerInvocation(BaseInvocation):
 
     def _log_statistics(self, context: InvocationContext, conditioning_data: ConditioningFieldData) -> None:
         """Log statistics about the conditioning tensor.
-        
+
         Z-Image uses 2D tensors: [seq_len, hidden_size]
         """
         if not conditioning_data.conditionings: