diff --git a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
index b017454a78..5fe1483ebc 100644
--- a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
+++ b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
@@ -3,7 +3,7 @@ from __future__ import annotations
 import math
 from dataclasses import dataclass
 from enum import Enum
-from typing import TYPE_CHECKING, List, Optional, Union
+from typing import TYPE_CHECKING, List, Optional, Tuple, Union
 
 import torch
 
@@ -231,7 +231,7 @@ class TextConditioningData:
         conditionings: List[torch.Tensor],
     ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
         """Concatenate provided conditioning tensors to one batched tensor.
-        If tensors have different sizes then pad them by zeros and creates 
+        If tensors have different sizes then pad them by zeros and creates
         encoder_attention_mask to exclude padding from attention.
 
         Args:
@@ -242,9 +242,7 @@ class TextConditioningData:
         if any(c.shape[1] != max_len for c in conditionings):
             encoder_attention_masks = [None] * len(conditionings)
             for i in range(len(conditionings)):
-                conditionings[i], encoder_attention_masks[i] = cls._pad_conditioning(
-                    conditionings[i], max_len
-                )
+                conditionings[i], encoder_attention_masks[i] = cls._pad_conditioning(conditionings[i], max_len)
             encoder_attention_mask = torch.cat(encoder_attention_masks)
 
         return torch.cat(conditionings), encoder_attention_mask