style changes as suggested

Author: painebenjamin

src/diffusers/pipelines/pag/pipeline_pag_sd_3_img2img.py

@@ -74,6 +74,7 @@
         ```
 """
 
+
 # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img.retrieve_latents
 def retrieve_latents(
     encoder_output: torch.Tensor, generator: Optional[torch.Generator] = None, sample_mode: str = "sample"
@@ -87,6 +88,7 @@ def retrieve_latents(
     else:
         raise AttributeError("Could not access latents of provided encoder_output")
 
+
 # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.retrieve_timesteps
 def retrieve_timesteps(
     scheduler,
@@ -149,7 +151,8 @@ def retrieve_timesteps(
 
 class StableDiffusion3PAGImg2ImgPipeline(DiffusionPipeline, SD3LoraLoaderMixin, FromSingleFileMixin, PAGMixin):
     r"""
-    [PAG pipeline](https://huggingface.co/docs/diffusers/main/en/using-diffusers/pag) for image-to-image generation using Stable Diffusion 3.
+    [PAG pipeline](https://huggingface.co/docs/diffusers/main/en/using-diffusers/pag) for image-to-image generation
+    using Stable Diffusion 3.
 
     Args:
         transformer ([`SD3Transformer2DModel`]):
@@ -643,16 +646,7 @@ def get_timesteps(self, num_inference_steps, strength, device):
         return timesteps, num_inference_steps - t_start
 
     # Copied from diffusers.pipelines.stable_diffusion_3.pipeline_stable_diffusion_3_img2img.StableDiffusion3Img2ImgPipeline.prepare_latents
-    def prepare_latents(
-        self,
-        image,
-        timestep,
-        batch_size,
-        num_images_per_prompt,
-        dtype,
-        device,
-        generator=None
-    ):
+    def prepare_latents(self, image, timestep, batch_size, num_images_per_prompt, dtype, device, generator=None):
         if not isinstance(image, (torch.Tensor, PIL.Image.Image, list)):
             raise ValueError(
                 f"`image` has to be of type `torch.Tensor`, `PIL.Image.Image` or list but is {type(image)}"

tests/pipelines/pag/test_pag_sd3_img2img.py

@@ -37,6 +37,7 @@
 
 enable_full_determinism()
 
+
 class StableDiffusion3PAGImg2ImgPipelineFastTests(unittest.TestCase, PipelineTesterMixin):
     pipeline_class = StableDiffusion3PAGImg2ImgPipeline
     params = TEXT_GUIDED_IMAGE_VARIATION_PARAMS.union({"pag_scale", "pag_adaptive_scale"}) - {"height", "width"}
@@ -176,7 +177,6 @@ def test_pag_inference(self):
         inputs = self.get_dummy_inputs(device)
         image = pipe_pag(**inputs).images
         image_slice = image[0, -3:, -3:, -1]
-        print(f"{image_slice=}")
 
         assert image.shape == (
             1,
@@ -185,12 +185,10 @@ def test_pag_inference(self):
             3,
         ), f"the shape of the output image should be (1, 32, 32, 3) but got {image.shape}"
 
-        expected_slice = np.array([
-            [0.7251651, 0.52043426, 0.5527822],
-            [0.7089102, 0.62233330, 0.5923926],
-            [0.4929751, 0.52322210, 0.5529656]
-        ])
-        max_diff = np.abs(image_slice.flatten() - expected_slice.flatten()).max()
+        expected_slice = np.array(
+            [0.7251651, 0.52043426, 0.5527822, 0.7089102, 0.62233330, 0.5923926, 0.4929751, 0.52322210, 0.5529656]
+        )
+        max_diff = np.abs(image_slice.flatten() - expected_slice).max()
         self.assertLessEqual(max_diff, 1e-3)
 
 
@@ -210,7 +208,9 @@ def tearDown(self):
         gc.collect()
         torch.cuda.empty_cache()
 
-    def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0, guidance_scale=7.0, pag_scale=0.7):
+    def get_inputs(
+        self, device, generator_device="cpu", dtype=torch.float32, seed=0, guidance_scale=7.0, pag_scale=0.7
+    ):
         img_url = (
             "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/sdxl-text2img.png"
         )
@@ -230,7 +230,9 @@ def get_inputs(self, device, generator_device="cpu", dtype=torch.float32, seed=0
         return inputs
 
     def test_pag_cfg(self):
-        pipeline = AutoPipelineForImage2Image.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16, pag_applied_layers=["blocks.17"])
+        pipeline = AutoPipelineForImage2Image.from_pretrained(
+            self.repo_id, enable_pag=True, torch_dtype=torch.float16, pag_applied_layers=["blocks.17"]
+        )
         pipeline.enable_model_cpu_offload()
         pipeline.set_progress_bar_config(disable=None)
 
@@ -246,7 +248,9 @@ def test_pag_cfg(self):
         ), f"output is different from expected, {image_slice.flatten()}"
 
     def test_pag_uncond(self):
-        pipeline = AutoPipelineForImage2Image.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16, pag_applied_layers=["blocks.(4|17)"])
+        pipeline = AutoPipelineForImage2Image.from_pretrained(
+            self.repo_id, enable_pag=True, torch_dtype=torch.float16, pag_applied_layers=["blocks.(4|17)"]
+        )
         pipeline.enable_model_cpu_offload()
         pipeline.set_progress_bar_config(disable=None)