[Styling] stylify using ruff (#5841)

* ruff format

* not need to use doc-builder's black styling as the doc is styled in ruff

* make fix-copies

* comment

* use run_ruff

src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py

@@ -49,6 +49,7 @@ class LDMTextToImagePipeline(DiffusionPipeline):
             A scheduler to be used in combination with `unet` to denoise the encoded image latents. Can be one of
             [`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
     """
+
     model_cpu_offload_seq = "bert->unet->vqvae"
 
     def __init__(

src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py

@@ -177,6 +177,7 @@ class PaintByExamplePipeline(DiffusionPipeline):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
 
     """
+
     # TODO: feature_extractor is required to encode initial images (if they are in PIL format),
     # we should give a descriptive message if the pipeline doesn't have one.
 

src/diffusers/pipelines/pipeline_flax_utils.py

@@ -112,6 +112,7 @@ class FlaxDiffusionPipeline(ConfigMixin, PushToHubMixin):
         - **config_name** ([`str`]) -- The configuration filename that stores the class and module names of all the
           diffusion pipeline's components.
     """
+
     config_name = "model_index.json"
 
     def register_modules(self, **kwargs):

src/diffusers/pipelines/pipeline_utils.py

@@ -542,6 +542,7 @@ class DiffusionPipeline(ConfigMixin, PushToHubMixin):
         - **_optional_components** (`List[str]`) -- List of all optional components that don't have to be passed to the
           pipeline to function (should be overridden by subclasses).
     """
+
     config_name = "model_index.json"
     model_cpu_offload_seq = None
     _optional_components = []

src/diffusers/pipelines/pixart_alpha/pipeline_pixart_alpha.py

@@ -120,8 +120,21 @@ class PixArtAlphaPipeline(DiffusionPipeline):
         scheduler ([`SchedulerMixin`]):
             A scheduler to be used in combination with `transformer` to denoise the encoded image latents.
     """
+
     bad_punct_regex = re.compile(
-        r"[" + "#®•©™&@·º½¾¿¡§~" + "\)" + "\(" + "\]" + "\[" + "\}" + "\{" + "\|" + "\\" + "\/" + "\*" + r"]{1,}"
+        r"["
+        + "#®•©™&@·º½¾¿¡§~"
+        + r"\)"
+        + r"\("
+        + r"\]"
+        + r"\["
+        + r"\}"
+        + r"\{"
+        + r"\|"
+        + "\\"
+        + r"\/"
+        + r"\*"
+        + r"]{1,}"
     )  # noqa
 
     _optional_components = ["tokenizer", "text_encoder"]

src/diffusers/pipelines/score_sde_ve/pipeline_score_sde_ve.py

@@ -35,6 +35,7 @@ class ScoreSdeVePipeline(DiffusionPipeline):
         scheduler ([`ScoreSdeVeScheduler`]):
             A `ScoreSdeVeScheduler` to be used in combination with `unet` to denoise the encoded image.
     """
+
     unet: UNet2DModel
     scheduler: ScoreSdeVeScheduler
 

src/diffusers/pipelines/spectrogram_diffusion/pipeline_spectrogram_diffusion.py

@@ -54,6 +54,7 @@ class SpectrogramDiffusionPipeline(DiffusionPipeline):
             A scheduler to be used in combination with `decoder` to denoise the encoded audio latents.
         melgan ([`OnnxRuntimeModel`]):
     """
+
     _optional_components = ["melgan"]
 
     def __init__(

src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py

@@ -148,6 +148,7 @@ class CycleDiffusionPipeline(DiffusionPipeline, TextualInversionLoaderMixin, Lor
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor"]
 

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

@@ -33,10 +33,7 @@ logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img.preprocess with 8->64
 def preprocess(image):
-    deprecation_message = (
-        "The preprocess method is deprecated and will be removed in diffusers 1.0.0. Please use"
-        " VaeImageProcessor.preprocess(...) instead"
-    )
+    deprecation_message = "The preprocess method is deprecated and will be removed in diffusers 1.0.0. Please use VaeImageProcessor.preprocess(...) instead"
     deprecate("preprocess", "1.0.0", deprecation_message, standard_warn=False)
     if isinstance(image, torch.Tensor):
         return image
@@ -85,6 +82,7 @@ class OnnxStableDiffusionImg2ImgPipeline(DiffusionPipeline):
         feature_extractor ([`CLIPImageProcessor`]):
             Model that extracts features from generated images to be used as inputs for the `safety_checker`.
     """
+
     vae_encoder: OnnxRuntimeModel
     vae_decoder: OnnxRuntimeModel
     text_encoder: OnnxRuntimeModel

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint.py

@@ -80,6 +80,7 @@ class OnnxStableDiffusionInpaintPipeline(DiffusionPipeline):
         feature_extractor ([`CLIPImageProcessor`]):
             Model that extracts features from generated images to be used as inputs for the `safety_checker`.
     """
+
     vae_encoder: OnnxRuntimeModel
     vae_decoder: OnnxRuntimeModel
     text_encoder: OnnxRuntimeModel

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint_legacy.py

@@ -66,6 +66,7 @@ class OnnxStableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
         feature_extractor ([`CLIPImageProcessor`]):
             Model that extracts features from generated images to be used as inputs for the `safety_checker`.
     """
+
     _optional_components = ["safety_checker", "feature_extractor"]
     _is_onnx = True
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -102,6 +102,7 @@ class StableDiffusionPipeline(DiffusionPipeline, TextualInversionLoaderMixin, Lo
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor"]
     _exclude_from_cpu_offload = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py

@@ -196,6 +196,7 @@ class StableDiffusionAttendAndExcitePipeline(DiffusionPipeline, TextualInversion
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor"]
     _exclude_from_cpu_offload = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py

@@ -95,6 +95,7 @@ class StableDiffusionDepth2ImgPipeline(DiffusionPipeline, TextualInversionLoader
             A scheduler to be used in combination with `unet` to denoise the encoded image latents. Can be one of
             [`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _callback_tensor_inputs = ["latents", "prompt_embeds", "negative_prompt_embeds", "depth_mask"]
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_diffedit.py

@@ -273,6 +273,7 @@ class StableDiffusionDiffEditPipeline(DiffusionPipeline, TextualInversionLoaderM
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor", "inverse_scheduler"]
     _exclude_from_cpu_offload = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_gligen.py

@@ -125,6 +125,7 @@ class StableDiffusionGLIGENPipeline(DiffusionPipeline):
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     _optional_components = ["safety_checker", "feature_extractor"]
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _exclude_from_cpu_offload = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_gligen_text_image.py

@@ -177,6 +177,7 @@ class StableDiffusionGLIGENTextImagePipeline(DiffusionPipeline):
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor"]
     _exclude_from_cpu_offload = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_image_variation.py

@@ -62,6 +62,7 @@ class StableDiffusionImageVariationPipeline(DiffusionPipeline):
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     # TODO: feature_extractor is required to encode images (if they are in PIL format),
     # we should give a descriptive message if the pipeline doesn't have one.
     _optional_components = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

@@ -139,6 +139,7 @@ class StableDiffusionImg2ImgPipeline(
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor"]
     _exclude_from_cpu_offload = ["safety_checker"]

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py

@@ -202,6 +202,7 @@ class StableDiffusionInpaintPipeline(
         feature_extractor ([`~transformers.CLIPImageProcessor`]):
             A `CLIPImageProcessor` to extract features from generated images; used as inputs to the `safety_checker`.
     """
+
     model_cpu_offload_seq = "text_encoder->unet->vae"
     _optional_components = ["safety_checker", "feature_extractor"]
     _exclude_from_cpu_offload = ["safety_checker"]