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5 changes: 4 additions & 1 deletion src/diffusers/pipelines/stable_diffusion/safety_checker.py
Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,10 @@ def forward(self, clip_input, images):

for idx, has_nsfw_concept in enumerate(has_nsfw_concepts):
if has_nsfw_concept:
images[idx] = np.zeros(images[idx].shape) # black image
if torch.is_tensor(images) or torch.is_tensor(images[0]):
images[idx] = torch.zeros_like(images[idx]) # black image
else:
images[idx] = np.zeros(images[idx].shape) # black image

if any(has_nsfw_concepts):
logger.warning(
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14 changes: 14 additions & 0 deletions tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py
Original file line number Diff line number Diff line change
Expand Up @@ -453,6 +453,20 @@ def test_stable_diffusion_img2img_pipeline_multiple_of_8(self):

assert np.abs(image_slice.flatten() - expected_slice).max() < 5e-3

def test_img2img_safety_checker_works(self):
sd_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
sd_pipe.to(torch_device)
sd_pipe.set_progress_bar_config(disable=None)

inputs = self.get_inputs(torch_device)
inputs["num_inference_steps"] = 20
# make sure the safety checker is activated
inputs["prompt"] = "naked, sex, porn"
out = sd_pipe(**inputs)

assert out.nsfw_content_detected[0], f"Safety checker should work for prompt: {inputs['prompt']}"
assert np.abs(out.images[0]).sum() < 1e-5 # should be all zeros


@nightly
@require_torch_gpu
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