Update Ruff to latest Version (#10919)

* update

* update

* update

* update

src/diffusers/models/model_loading_utils.py

@@ -205,7 +205,7 @@ def load_state_dict(
                     ) from e
         except (UnicodeDecodeError, ValueError):
             raise OSError(
-                f"Unable to load weights from checkpoint file for '{checkpoint_file}' " f"at '{checkpoint_file}'. "
+                f"Unable to load weights from checkpoint file for '{checkpoint_file}' at '{checkpoint_file}'. "
             )
 
 

src/diffusers/models/transformers/transformer_2d.py

@@ -211,9 +211,9 @@ class Transformer2DModel(LegacyModelMixin, LegacyConfigMixin):
 
     def _init_vectorized_inputs(self, norm_type):
         assert self.config.sample_size is not None, "Transformer2DModel over discrete input must provide sample_size"
-        assert (
-            self.config.num_vector_embeds is not None
-        ), "Transformer2DModel over discrete input must provide num_embed"
+        assert self.config.num_vector_embeds is not None, (
+            "Transformer2DModel over discrete input must provide num_embed"
+        )
 
         self.height = self.config.sample_size
         self.width = self.config.sample_size

src/diffusers/pipelines/audioldm2/pipeline_audioldm2.py

@@ -791,7 +791,7 @@ class AudioLDM2Pipeline(DiffusionPipeline):
 
         if transcription is None:
             if self.text_encoder_2.config.model_type == "vits":
-                raise ValueError("Cannot forward without transcription. Please make sure to" " have transcription")
+                raise ValueError("Cannot forward without transcription. Please make sure to have transcription")
         elif transcription is not None and (
             not isinstance(transcription, str) and not isinstance(transcription, list)
         ):

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py

@@ -657,7 +657,7 @@ class StableDiffusionControlNetInpaintPipeline(
         if padding_mask_crop is not None:
             if not isinstance(image, PIL.Image.Image):
                 raise ValueError(
-                    f"The image should be a PIL image when inpainting mask crop, but is of type" f" {type(image)}."
+                    f"The image should be a PIL image when inpainting mask crop, but is of type {type(image)}."
                 )
             if not isinstance(mask_image, PIL.Image.Image):
                 raise ValueError(
@@ -665,7 +665,7 @@ class StableDiffusionControlNetInpaintPipeline(
                     f" {type(mask_image)}."
                 )
             if output_type != "pil":
-                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is" f" {output_type}.")
+                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is {output_type}.")
 
         # `prompt` needs more sophisticated handling when there are multiple
         # conditionings.

src/diffusers/pipelines/easyanimate/pipeline_easyanimate_inpaint.py

@@ -1130,7 +1130,7 @@ class EasyAnimateInpaintPipeline(DiffusionPipeline):
                     f"Incorrect configuration settings! The config of `pipeline.transformer`: {self.transformer.config} expects"
                     f" {self.transformer.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                     f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                    f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                    f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                     " `pipeline.transformer` or your `mask_image` or `image` input."
                 )
 

src/diffusers/pipelines/flux/pipeline_flux_controlnet_inpainting.py

@@ -507,7 +507,7 @@ class FluxControlNetInpaintPipeline(DiffusionPipeline, FluxLoraLoaderMixin, From
         if padding_mask_crop is not None:
             if not isinstance(image, PIL.Image.Image):
                 raise ValueError(
-                    f"The image should be a PIL image when inpainting mask crop, but is of type" f" {type(image)}."
+                    f"The image should be a PIL image when inpainting mask crop, but is of type {type(image)}."
                 )
             if not isinstance(mask_image, PIL.Image.Image):
                 raise ValueError(
@@ -515,7 +515,7 @@ class FluxControlNetInpaintPipeline(DiffusionPipeline, FluxLoraLoaderMixin, From
                     f" {type(mask_image)}."
                 )
             if output_type != "pil":
-                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is" f" {output_type}.")
+                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is {output_type}.")
 
         if max_sequence_length is not None and max_sequence_length > 512:
             raise ValueError(f"`max_sequence_length` cannot be greater than 512 but is {max_sequence_length}")

src/diffusers/pipelines/flux/pipeline_flux_inpaint.py

@@ -574,7 +574,7 @@ class FluxInpaintPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FluxIPAdapterM
         if padding_mask_crop is not None:
             if not isinstance(image, PIL.Image.Image):
                 raise ValueError(
-                    f"The image should be a PIL image when inpainting mask crop, but is of type" f" {type(image)}."
+                    f"The image should be a PIL image when inpainting mask crop, but is of type {type(image)}."
                 )
             if not isinstance(mask_image, PIL.Image.Image):
                 raise ValueError(
@@ -582,7 +582,7 @@ class FluxInpaintPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FluxIPAdapterM
                     f" {type(mask_image)}."
                 )
             if output_type != "pil":
-                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is" f" {output_type}.")
+                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is {output_type}.")
 
         if max_sequence_length is not None and max_sequence_length > 512:
             raise ValueError(f"`max_sequence_length` cannot be greater than 512 but is {max_sequence_length}")

src/diffusers/pipelines/free_noise_utils.py

@@ -341,9 +341,9 @@ class AnimateDiffFreeNoiseMixin:
                 start_tensor = negative_prompt_embeds[i].unsqueeze(0)
                 end_tensor = negative_prompt_embeds[i + 1].unsqueeze(0)
 
-                negative_prompt_interpolation_embeds[
-                    start_frame : end_frame + 1
-                ] = self._free_noise_prompt_interpolation_callback(start_frame, end_frame, start_tensor, end_tensor)
+                negative_prompt_interpolation_embeds[start_frame : end_frame + 1] = (
+                    self._free_noise_prompt_interpolation_callback(start_frame, end_frame, start_tensor, end_tensor)
+                )
 
         prompt_embeds = prompt_interpolation_embeds
         negative_prompt_embeds = negative_prompt_interpolation_embeds

src/diffusers/pipelines/kandinsky/pipeline_kandinsky_combined.py

@@ -360,7 +360,7 @@ class KandinskyImg2ImgCombinedPipeline(DiffusionPipeline):
     """
 
     _load_connected_pipes = True
-    model_cpu_offload_seq = "prior_text_encoder->prior_image_encoder->prior_prior->" "text_encoder->unet->movq"
+    model_cpu_offload_seq = "prior_text_encoder->prior_image_encoder->prior_prior->text_encoder->unet->movq"
     _exclude_from_cpu_offload = ["prior_prior"]
 
     def __init__(

src/diffusers/pipelines/kandinsky/pipeline_kandinsky_inpaint.py

@@ -579,7 +579,7 @@ class KandinskyInpaintPipeline(DiffusionPipeline):
                 f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
                 f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                 f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                 " `pipeline.unet` or your `mask_image` or `image` input."
             )
 

src/diffusers/pipelines/omnigen/processor_omnigen.py

@@ -95,13 +95,13 @@ class OmniGenMultiModalProcessor:
         image_ids = [int(s.split("|")[1].split("_")[-1]) for s in image_tags]
 
         unique_image_ids = sorted(set(image_ids))
-        assert unique_image_ids == list(
-            range(1, len(unique_image_ids) + 1)
-        ), f"image_ids must start from 1, and must be continuous int, e.g. [1, 2, 3], cannot be {unique_image_ids}"
+        assert unique_image_ids == list(range(1, len(unique_image_ids) + 1)), (
+            f"image_ids must start from 1, and must be continuous int, e.g. [1, 2, 3], cannot be {unique_image_ids}"
+        )
         # total images must be the same as the number of image tags
-        assert (
-            len(unique_image_ids) == len(input_images)
-        ), f"total images must be the same as the number of image tags, got {len(unique_image_ids)} image tags and {len(input_images)} images"
+        assert len(unique_image_ids) == len(input_images), (
+            f"total images must be the same as the number of image tags, got {len(unique_image_ids)} image tags and {len(input_images)} images"
+        )
 
         input_images = [input_images[x - 1] for x in image_ids]
 

src/diffusers/pipelines/pag/pipeline_pag_controlnet_sd_inpaint.py

@@ -604,7 +604,7 @@ class StableDiffusionControlNetPAGInpaintPipeline(
         if padding_mask_crop is not None:
             if not isinstance(image, PIL.Image.Image):
                 raise ValueError(
-                    f"The image should be a PIL image when inpainting mask crop, but is of type" f" {type(image)}."
+                    f"The image should be a PIL image when inpainting mask crop, but is of type {type(image)}."
                 )
             if not isinstance(mask_image, PIL.Image.Image):
                 raise ValueError(
@@ -612,7 +612,7 @@ class StableDiffusionControlNetPAGInpaintPipeline(
                     f" {type(mask_image)}."
                 )
             if output_type != "pil":
-                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is" f" {output_type}.")
+                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is {output_type}.")
 
         # `prompt` needs more sophisticated handling when there are multiple
         # conditionings.
@@ -1340,7 +1340,7 @@ class StableDiffusionControlNetPAGInpaintPipeline(
                     f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
                     f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                     f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                    f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                    f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                     " `pipeline.unet` or your `mask_image` or `image` input."
                 )
         elif num_channels_unet != 4:

src/diffusers/pipelines/pag/pipeline_pag_sd_inpaint.py

@@ -683,7 +683,7 @@ class StableDiffusionPAGInpaintPipeline(
         if padding_mask_crop is not None:
             if not isinstance(image, PIL.Image.Image):
                 raise ValueError(
-                    f"The image should be a PIL image when inpainting mask crop, but is of type" f" {type(image)}."
+                    f"The image should be a PIL image when inpainting mask crop, but is of type {type(image)}."
                 )
             if not isinstance(mask_image, PIL.Image.Image):
                 raise ValueError(
@@ -691,7 +691,7 @@ class StableDiffusionPAGInpaintPipeline(
                     f" {type(mask_image)}."
                 )
             if output_type != "pil":
-                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is" f" {output_type}.")
+                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is {output_type}.")
 
         if ip_adapter_image is not None and ip_adapter_image_embeds is not None:
             raise ValueError(
@@ -1191,7 +1191,7 @@ class StableDiffusionPAGInpaintPipeline(
                     f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
                     f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                     f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                    f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                    f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                     " `pipeline.unet` or your `mask_image` or `image` input."
                 )
         elif num_channels_unet != 4:

src/diffusers/pipelines/pag/pipeline_pag_sd_xl_inpaint.py

@@ -737,7 +737,7 @@ class StableDiffusionXLPAGInpaintPipeline(
         if padding_mask_crop is not None:
             if not isinstance(image, PIL.Image.Image):
                 raise ValueError(
-                    f"The image should be a PIL image when inpainting mask crop, but is of type" f" {type(image)}."
+                    f"The image should be a PIL image when inpainting mask crop, but is of type {type(image)}."
                 )
             if not isinstance(mask_image, PIL.Image.Image):
                 raise ValueError(
@@ -745,7 +745,7 @@ class StableDiffusionXLPAGInpaintPipeline(
                     f" {type(mask_image)}."
                 )
             if output_type != "pil":
-                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is" f" {output_type}.")
+                raise ValueError(f"The output type should be PIL when inpainting mask crop, but is {output_type}.")
 
         if ip_adapter_image is not None and ip_adapter_image_embeds is not None:
             raise ValueError(
@@ -1509,7 +1509,7 @@ class StableDiffusionXLPAGInpaintPipeline(
                     f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
                     f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                     f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                    f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                    f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                     " `pipeline.unet` or your `mask_image` or `image` input."
                 )
         elif num_channels_unet != 4:

src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py

@@ -575,7 +575,7 @@ class PaintByExamplePipeline(DiffusionPipeline, StableDiffusionMixin):
                 f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
                 f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                 f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                 " `pipeline.unet` or your `mask_image` or `image` input."
             )
 

src/diffusers/pipelines/pipeline_loading_utils.py

@@ -323,9 +323,7 @@ def maybe_raise_or_warn(
         model_cls = unwrapped_sub_model.__class__
 
         if not issubclass(model_cls, expected_class_obj):
-            raise ValueError(
-                f"{passed_class_obj[name]} is of type: {model_cls}, but should be" f" {expected_class_obj}"
-            )
+            raise ValueError(f"{passed_class_obj[name]} is of type: {model_cls}, but should be {expected_class_obj}")
     else:
         logger.warning(
             f"You have passed a non-standard module {passed_class_obj[name]}. We cannot verify whether it"

src/diffusers/pipelines/shap_e/renderer.py

@@ -983,9 +983,9 @@ class ShapERenderer(ModelMixin, ConfigMixin):
         fields = torch.cat(fields, dim=1)
         fields = fields.float()
 
-        assert (
-            len(fields.shape) == 3 and fields.shape[-1] == 1
-        ), f"expected [meta_batch x inner_batch] SDF results, but got {fields.shape}"
+        assert len(fields.shape) == 3 and fields.shape[-1] == 1, (
+            f"expected [meta_batch x inner_batch] SDF results, but got {fields.shape}"
+        )
 
         fields = fields.reshape(1, *([grid_size] * 3))
 
@@ -1039,9 +1039,9 @@ class ShapERenderer(ModelMixin, ConfigMixin):
         textures = textures.float()
 
         # 3.3 augument the mesh with texture data
-        assert len(textures.shape) == 3 and textures.shape[-1] == len(
-            texture_channels
-        ), f"expected [meta_batch x inner_batch x texture_channels] field results, but got {textures.shape}"
+        assert len(textures.shape) == 3 and textures.shape[-1] == len(texture_channels), (
+            f"expected [meta_batch x inner_batch x texture_channels] field results, but got {textures.shape}"
+        )
 
         for m, texture in zip(raw_meshes, textures):
             texture = texture[: len(m.verts)]

src/diffusers/pipelines/stable_audio/pipeline_stable_audio.py

@@ -584,7 +584,7 @@ class StableAudioPipeline(DiffusionPipeline):
 
         if audio_end_in_s - audio_start_in_s > max_audio_length_in_s:
             raise ValueError(
-                f"The total audio length requested ({audio_end_in_s-audio_start_in_s}s) is longer than the model maximum possible length ({max_audio_length_in_s}). Make sure that 'audio_end_in_s-audio_start_in_s<={max_audio_length_in_s}'."
+                f"The total audio length requested ({audio_end_in_s - audio_start_in_s}s) is longer than the model maximum possible length ({max_audio_length_in_s}). Make sure that 'audio_end_in_s-audio_start_in_s<={max_audio_length_in_s}'."
             )
 
         waveform_start = int(audio_start_in_s * self.vae.config.sampling_rate)

src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_inpaint.py

@@ -335,7 +335,7 @@ class FlaxStableDiffusionInpaintPipeline(FlaxDiffusionPipeline):
                 f"Incorrect configuration settings! The config of `pipeline.unet`: {self.unet.config} expects"
                 f" {self.unet.config.in_channels} but received `num_channels_latents`: {num_channels_latents} +"
                 f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                 " `pipeline.unet` or your `mask_image` or `image` input."
             )
 

src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint.py

@@ -475,7 +475,7 @@ class OnnxStableDiffusionInpaintPipeline(DiffusionPipeline):
                 "Incorrect configuration settings! The config of `pipeline.unet` expects"
                 f" {unet_input_channels} but received `num_channels_latents`: {num_channels_latents} +"
                 f" `num_channels_mask`: {num_channels_mask} + `num_channels_masked_image`: {num_channels_masked_image}"
-                f" = {num_channels_latents+num_channels_masked_image+num_channels_mask}. Please verify the config of"
+                f" = {num_channels_latents + num_channels_masked_image + num_channels_mask}. Please verify the config of"
                 " `pipeline.unet` or your `mask_image` or `image` input."
             )