diff --git a/examples/research_projects/instructpix2pix_lora/train_instruct_pix2pix_lora.py b/examples/research_projects/instructpix2pix_lora/train_instruct_pix2pix_lora.py
index 06079fe9ed41..0f158131ea40 100644
--- a/examples/research_projects/instructpix2pix_lora/train_instruct_pix2pix_lora.py
+++ b/examples/research_projects/instructpix2pix_lora/train_instruct_pix2pix_lora.py
@@ -788,7 +788,7 @@ def preprocess_images(examples):
         )
         # We need to ensure that the original and the edited images undergo the same
         # augmentation transforms.
-        images = np.concatenate([original_images, edited_images])
+        images = np.stack([original_images, edited_images])
         images = torch.tensor(images)
         images = 2 * (images / 255) - 1
         return train_transforms(images)
@@ -799,7 +799,7 @@ def preprocess_train(examples):
         # Since the original and edited images were concatenated before
         # applying the transformations, we need to separate them and reshape
         # them accordingly.
-        original_images, edited_images = preprocessed_images.chunk(2)
+        original_images, edited_images = preprocessed_images
         original_images = original_images.reshape(-1, 3, args.resolution, args.resolution)
         edited_images = edited_images.reshape(-1, 3, args.resolution, args.resolution)