diff --git a/examples/research_projects/diffusion_dpo/train_diffusion_dpo_sdxl.py b/examples/research_projects/diffusion_dpo/train_diffusion_dpo_sdxl.py
index 23e94bc679a6..3fd3fc11ad19 100644
--- a/examples/research_projects/diffusion_dpo/train_diffusion_dpo_sdxl.py
+++ b/examples/research_projects/diffusion_dpo/train_diffusion_dpo_sdxl.py
@@ -740,6 +740,10 @@ def preprocess_train(examples):
             # Resize.
             combined_im = train_resize(combined_im)
 
+            # Flipping.
+            if not args.no_flip and random.random() < 0.5:
+                combined_im = train_flip(combined_im)
+
             # Cropping.
             if not args.random_crop:
                 y1 = max(0, int(round((combined_im.shape[1] - args.resolution) / 2.0)))
@@ -749,11 +753,6 @@ def preprocess_train(examples):
                 y1, x1, h, w = train_crop.get_params(combined_im, (args.resolution, args.resolution))
                 combined_im = crop(combined_im, y1, x1, h, w)
 
-            # Flipping.
-            if random.random() < 0.5:
-                x1 = combined_im.shape[2] - x1
-                combined_im = train_flip(combined_im)
-
             crop_top_left = (y1, x1)
             crop_top_lefts.append(crop_top_left)
             combined_im = normalize(combined_im)