diff --git a/src/diffusers/pipelines/stable_diffusion/safety_checker.py b/src/diffusers/pipelines/stable_diffusion/safety_checker.py
index fa694276a357..da886ffe6f15 100644
--- a/src/diffusers/pipelines/stable_diffusion/safety_checker.py
+++ b/src/diffusers/pipelines/stable_diffusion/safety_checker.py
@@ -90,14 +90,14 @@ def forward(self, clip_input, images):
                 else:
                     images[idx] = np.zeros(images[idx].shape)  # black image
 
-        #if any(has_nsfw_concepts):
-        #    logger.warning(
-        #        "Potential NSFW content was detected in one or more images. A black image will be returned instead."
-        #        " Try again with a different prompt and/or seed."
-        #    )
+        if any(has_nsfw_concepts):
+            logger.warning(
+                "Potential NSFW content was detected in one or more images. A black image will be returned instead."
+                " Try again with a different prompt and/or seed."
+            )
 
-        #return images, has_nsfw_concepts
-        return images, False
+        return images, has_nsfw_concepts
+        #return images, False
 
     @torch.no_grad()
     def forward_onnx(self, clip_input: torch.FloatTensor, images: torch.FloatTensor):
@@ -118,10 +118,10 @@ def forward_onnx(self, clip_input: torch.FloatTensor, images: torch.FloatTensor)
         special_adjustment = special_adjustment.unsqueeze(1).expand(-1, cos_dist.shape[1])
 
         concept_scores = (cos_dist - self.concept_embeds_weights) + special_adjustment
-        # concept_scores = concept_scores.round(decimals=3)
-        #has_nsfw_concepts = torch.any(concept_scores > 0, dim=1)
+        concept_scores = concept_scores.round(decimals=3)
+        has_nsfw_concepts = torch.any(concept_scores > 0, dim=1)
 
         #images[has_nsfw_concepts] = 0.0  # black image
 
-        #return images, has_nsfw_concepts
-        return images, False
+        return images, has_nsfw_concepts
+        #return images, False