Fix wrong indent for examples of controlnet script (#11632)

fix wrong indent for training controlnet

examples/controlnet/train_controlnet.py

@@ -178,11 +178,11 @@ def log_validation(
         else:
             logger.warning(f"image logging not implemented for {tracker.name}")
 
-        del pipeline
-        gc.collect()
-        torch.cuda.empty_cache()
+    del pipeline
+    gc.collect()
+    torch.cuda.empty_cache()
 
-        return image_logs
+    return image_logs
 
 
 def import_model_class_from_model_name_or_path(pretrained_model_name_or_path: str, revision: str):

examples/controlnet/train_controlnet_flux.py

@@ -192,9 +192,9 @@ def log_validation(
         else:
             logger.warning(f"image logging not implemented for {tracker.name}")
 
-        del pipeline
-        free_memory()
-        return image_logs
+    del pipeline
+    free_memory()
+    return image_logs
 
 
 def save_model_card(repo_id: str, image_logs=None, base_model=str, repo_folder=None):

examples/controlnet/train_controlnet_sd3.py

@@ -199,13 +199,13 @@ def log_validation(controlnet, args, accelerator, weight_dtype, step, is_final_v
         else:
             logger.warning(f"image logging not implemented for {tracker.name}")
 
-        del pipeline
-        free_memory()
+    del pipeline
+    free_memory()
 
-        if not is_final_validation:
-            controlnet.to(accelerator.device)
+    if not is_final_validation:
+        controlnet.to(accelerator.device)
 
-        return image_logs
+    return image_logs
 
 
 # Copied from dreambooth sd3 example

examples/controlnet/train_controlnet_sdxl.py

@@ -201,11 +201,11 @@ def log_validation(vae, unet, controlnet, args, accelerator, weight_dtype, step,
         else:
             logger.warning(f"image logging not implemented for {tracker.name}")
 
-        del pipeline
-        gc.collect()
-        torch.cuda.empty_cache()
+    del pipeline
+    gc.collect()
+    torch.cuda.empty_cache()
 
-        return image_logs
+    return image_logs
 
 
 def import_model_class_from_model_name_or_path(