diff --git a/main/README_community_scripts.md b/main/README_community_scripts.md index 3c9ad0d89bb43e66be72fbcfa41500ac4d8c55c6..d790b67a44c5afca337e34651814e2d94727188b 100644 --- a/main/README_community_scripts.md +++ b/main/README_community_scripts.md @@ -260,7 +260,7 @@ class SDPromptSchedulingCallback(PipelineCallback): def callback_fn( self, pipeline, step_index, timestep, callback_kwargs - ) -> Dict[str, Any]: + ) -> dict[str, Any]: cutoff_step_ratio = self.config.cutoff_step_ratio cutoff_step_index = self.config.cutoff_step_index if isinstance(self.config.encoded_prompt, tuple): @@ -343,7 +343,7 @@ class SDXLPromptSchedulingCallback(PipelineCallback): def callback_fn( self, pipeline, step_index, timestep, callback_kwargs - ) -> Dict[str, Any]: + ) -> dict[str, Any]: cutoff_step_ratio = self.config.cutoff_step_ratio cutoff_step_index = self.config.cutoff_step_index if isinstance(self.config.encoded_prompt, tuple): diff --git a/main/adaptive_mask_inpainting.py b/main/adaptive_mask_inpainting.py index da67debe72ec4e1e91fed46acd95025f01e82b1f..0378ffcdf985de3378cc80bbdeb56e24136e86fe 100644 --- a/main/adaptive_mask_inpainting.py +++ b/main/adaptive_mask_inpainting.py @@ -871,7 +871,7 @@ class AdaptiveMaskInpaintPipeline( latents: Optional[torch.FloatTensor] = None, prompt_embeds: Optional[torch.FloatTensor] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None, callback_steps: int = 1, diff --git a/main/bit_diffusion.py b/main/bit_diffusion.py index 67f4cd3fe1996cf5b4428059a335f1f3dab20393..c19bc95eefe0249e1426cc90044f995ea409fc18 100644 --- a/main/bit_diffusion.py +++ b/main/bit_diffusion.py @@ -231,9 +231,9 @@ class BitDiffusion(DiffusionPipeline): height: Optional[int] = 256, width: Optional[int] = 256, num_inference_steps: Optional[int] = 50, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, batch_size: Optional[int] = 1, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, **kwargs, ) -> Union[Tuple, ImagePipelineOutput]: diff --git a/main/clip_guided_images_mixing_stable_diffusion.py b/main/clip_guided_images_mixing_stable_diffusion.py index 2cd3daf68c2425804657f08eb19f5ae4e4eba898..bacf9f0ec8b4a943f436805a160c318f1f7f00ae 100644 --- a/main/clip_guided_images_mixing_stable_diffusion.py +++ b/main/clip_guided_images_mixing_stable_diffusion.py @@ -235,8 +235,8 @@ class CLIPGuidedImagesMixingStableDiffusion(DiffusionPipeline, StableDiffusionMi self, style_image: Union[torch.Tensor, PIL.Image.Image], content_image: Union[torch.Tensor, PIL.Image.Image], - style_prompt: Optional[str] = None, - content_prompt: Optional[str] = None, + style_prompt: str | None = None, + content_prompt: str | None = None, height: Optional[int] = 512, width: Optional[int] = 512, noise_strength: float = 0.6, @@ -245,8 +245,8 @@ class CLIPGuidedImagesMixingStableDiffusion(DiffusionPipeline, StableDiffusionMi batch_size: Optional[int] = 1, eta: float = 0.0, clip_guidance_scale: Optional[float] = 100, - generator: Optional[torch.Generator] = None, - output_type: Optional[str] = "pil", + generator: torch.Generator | None = None, + output_type: str | None = "pil", return_dict: bool = True, slerp_latent_style_strength: float = 0.8, slerp_prompt_style_strength: float = 0.1, diff --git a/main/clip_guided_stable_diffusion.py b/main/clip_guided_stable_diffusion.py index bfd0858d245ea91f3ec805171646054d50108c09..013df7acc7c78bb26823d6bf7b9a85bfb8aa4fd4 100644 --- a/main/clip_guided_stable_diffusion.py +++ b/main/clip_guided_stable_diffusion.py @@ -179,9 +179,9 @@ class CLIPGuidedStableDiffusion(DiffusionPipeline, StableDiffusionMixin): clip_prompt: Optional[Union[str, List[str]]] = None, num_cutouts: Optional[int] = 4, use_cutouts: Optional[bool] = True, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ): if isinstance(prompt, str): diff --git a/main/clip_guided_stable_diffusion_img2img.py b/main/clip_guided_stable_diffusion_img2img.py index f3dd4903f8511c25220feea19117ed88d5809364..739d6dafff73638a6d95ece017f7152c7ad8e3c0 100644 --- a/main/clip_guided_stable_diffusion_img2img.py +++ b/main/clip_guided_stable_diffusion_img2img.py @@ -316,9 +316,9 @@ class CLIPGuidedStableDiffusion(DiffusionPipeline, StableDiffusionMixin): clip_prompt: Optional[Union[str, List[str]]] = None, num_cutouts: Optional[int] = 4, use_cutouts: Optional[bool] = True, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ): if isinstance(prompt, str): diff --git a/main/composable_stable_diffusion.py b/main/composable_stable_diffusion.py index a7c610ad4355829d643688ffe0202f5d6746b31b..466502e8394caf74de096febbd1865a4df3a4689 100644 --- a/main/composable_stable_diffusion.py +++ b/main/composable_stable_diffusion.py @@ -357,13 +357,13 @@ class ComposableStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, - weights: Optional[str] = "", + weights: str | None = "", ): r""" Function invoked when calling the pipeline for generation. diff --git a/main/ddim_noise_comparative_analysis.py b/main/ddim_noise_comparative_analysis.py index 829106c47f65cb70746c031e9d4f9ef698035afa..453f8525a5520cf4ddc65d41bcfb7519f813827d 100644 --- a/main/ddim_noise_comparative_analysis.py +++ b/main/ddim_noise_comparative_analysis.py @@ -110,7 +110,7 @@ class DDIMNoiseComparativeAnalysisPipeline(DiffusionPipeline): eta: float = 0.0, num_inference_steps: int = 50, use_clipped_model_output: Optional[bool] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ) -> Union[ImagePipelineOutput, Tuple]: r""" diff --git a/main/dps_pipeline.py b/main/dps_pipeline.py index b29b06365bf33b60ccd53ddf975a1d3bfe7c8449..6942d8ae608fd632cc36b81d7ea43840043feff0 100644 --- a/main/dps_pipeline.py +++ b/main/dps_pipeline.py @@ -54,7 +54,7 @@ class DPSPipeline(DiffusionPipeline): batch_size: int = 1, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, num_inference_steps: int = 1000, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, zeta: float = 0.3, ) -> Union[ImagePipelineOutput, Tuple]: diff --git a/main/edict_pipeline.py b/main/edict_pipeline.py index a7bc892ddf9353e94cf1cc1f9be2ad53f2e86356..bd96cdd6b2fc4a5f1407badf54a0df4dd86a965f 100644 --- a/main/edict_pipeline.py +++ b/main/edict_pipeline.py @@ -1,5 +1,3 @@ -from typing import Optional - import torch from PIL import Image from tqdm.auto import tqdm @@ -39,7 +37,7 @@ class EDICTPipeline(DiffusionPipeline): self.image_processor = VaeImageProcessor(vae_scale_factor=self.vae_scale_factor) def _encode_prompt( - self, prompt: str, negative_prompt: Optional[str] = None, do_classifier_free_guidance: bool = False + self, prompt: str, negative_prompt: str | None = None, do_classifier_free_guidance: bool = False ): text_inputs = self.tokenizer( prompt, @@ -141,7 +139,7 @@ class EDICTPipeline(DiffusionPipeline): text_embeds: torch.Tensor, timesteps: torch.Tensor, guidance_scale: float, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, ): do_classifier_free_guidance = guidance_scale > 1.0 @@ -194,9 +192,9 @@ class EDICTPipeline(DiffusionPipeline): guidance_scale: float = 3.0, num_inference_steps: int = 50, strength: float = 0.8, - negative_prompt: Optional[str] = None, - generator: Optional[torch.Generator] = None, - output_type: Optional[str] = "pil", + negative_prompt: str | None = None, + generator: torch.Generator | None = None, + output_type: str | None = "pil", ): do_classifier_free_guidance = guidance_scale > 1.0 diff --git a/main/fresco_v2v.py b/main/fresco_v2v.py index b79834db5eed60d189ddca83a46b4212f42a38b7..974f71805baa9a58fdccad5a8a297f9e48ac0445 100644 --- a/main/fresco_v2v.py +++ b/main/fresco_v2v.py @@ -1208,7 +1208,7 @@ def apply_FRESCO_attn(pipe): def retrieve_latents( - encoder_output: torch.Tensor, generator: Optional[torch.Generator] = None, sample_mode: str = "sample" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -2064,7 +2064,7 @@ class FrescoV2VPipeline(StableDiffusionControlNetImg2ImgPipeline): negative_prompt_embeds: Optional[torch.FloatTensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.FloatTensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 0.8, diff --git a/main/gluegen.py b/main/gluegen.py index 86813b63eca57bbd6e91af1251f3145cdcd75cf7..b98e0465561dba74cc449e0e3e5d3893c36b472c 100644 --- a/main/gluegen.py +++ b/main/gluegen.py @@ -597,7 +597,7 @@ class GlueGenStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin, St latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/hd_painter.py b/main/hd_painter.py index 70e5656855ffe0da607368dca68c98d4e566b6ad..f412437b30ffa55ba3b8a41c27999937d909c2f6 100644 --- a/main/hd_painter.py +++ b/main/hd_painter.py @@ -462,7 +462,7 @@ class StableDiffusionHDPainterPipeline(StableDiffusionInpaintPipeline): num_inference_steps: int = 50, timesteps: List[int] = None, guidance_scale: float = 7.5, - positive_prompt: Optional[str] = "", + positive_prompt: str | None = "", negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.01, @@ -471,7 +471,7 @@ class StableDiffusionHDPainterPipeline(StableDiffusionInpaintPipeline): prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, clip_skip: int = None, diff --git a/main/iadb.py b/main/iadb.py index 6262c3cb15fcbd0e2f96fc7c5e3cc63f9c4b0832..d61e2573b55120a019a4712318e256ec6f43c4fd 100644 --- a/main/iadb.py +++ b/main/iadb.py @@ -86,7 +86,7 @@ class IADBPipeline(DiffusionPipeline): batch_size: int = 1, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, num_inference_steps: int = 50, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ) -> Union[ImagePipelineOutput, Tuple]: r""" diff --git a/main/imagic_stable_diffusion.py b/main/imagic_stable_diffusion.py index 091d0fbf8d3ae74e04e1333d7eed044d12e456da..2efea594aff2e8952f413cd3a9e645bddb0a11ba 100644 --- a/main/imagic_stable_diffusion.py +++ b/main/imagic_stable_diffusion.py @@ -113,7 +113,7 @@ class ImagicStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin): image: Union[torch.Tensor, PIL.Image.Image], height: Optional[int] = 512, width: Optional[int] = 512, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, embedding_learning_rate: float = 0.001, diffusion_model_learning_rate: float = 2e-6, text_embedding_optimization_steps: int = 500, @@ -314,8 +314,8 @@ class ImagicStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin): height: Optional[int] = 512, width: Optional[int] = 512, num_inference_steps: Optional[int] = 50, - generator: Optional[torch.Generator] = None, - output_type: Optional[str] = "pil", + generator: torch.Generator | None = None, + output_type: str | None = "pil", return_dict: bool = True, guidance_scale: float = 7.5, eta: float = 0.0, diff --git a/main/img2img_inpainting.py b/main/img2img_inpainting.py index bef682425a2cef1dad64e621842b96c5fe4da668..efc24a339d4f3da76dabf1f94a1e46a382d8f9aa 100644 --- a/main/img2img_inpainting.py +++ b/main/img2img_inpainting.py @@ -143,9 +143,9 @@ class ImageToImageInpaintingPipeline(DiffusionPipeline): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/instaflow_one_step.py b/main/instaflow_one_step.py index 0f16707eadf5a9ae77547f1be8c202730033bec5..d5c304b48d8118aab62a64fbbadb99853671aff1 100644 --- a/main/instaflow_one_step.py +++ b/main/instaflow_one_step.py @@ -512,7 +512,7 @@ class InstaFlowPipeline( latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/interpolate_stable_diffusion.py b/main/interpolate_stable_diffusion.py index 5b96c14d63670bcf46b4a9990baa84a4baadf62a..448cf94216a8a9b272a577a54ca2fc9a2ec12385 100644 --- a/main/interpolate_stable_diffusion.py +++ b/main/interpolate_stable_diffusion.py @@ -131,9 +131,9 @@ class StableDiffusionWalkPipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -401,8 +401,8 @@ class StableDiffusionWalkPipeline(DiffusionPipeline, StableDiffusionMixin): prompts: List[str], seeds: List[int], num_interpolation_steps: Optional[int] = 6, - output_dir: Optional[str] = "./dreams", - name: Optional[str] = None, + output_dir: str | None = "./dreams", + name: str | None = None, batch_size: Optional[int] = 1, height: Optional[int] = 512, width: Optional[int] = 512, diff --git a/main/ip_adapter_face_id.py b/main/ip_adapter_face_id.py index d16aaf5a54c604963bb7ae3f476c1f5bc3bb1eb9..817d31e51af529b247e3c12b0b95521234554895 100644 --- a/main/ip_adapter_face_id.py +++ b/main/ip_adapter_face_id.py @@ -855,7 +855,7 @@ class IPAdapterFaceIDStableDiffusionPipeline( prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, image_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/latent_consistency_img2img.py b/main/latent_consistency_img2img.py index 0f5711f34b627b245ac0a6729c8b4184b5e421a2..a3381dd9bd6fafc142403729eddff9e34652e18e 100644 --- a/main/latent_consistency_img2img.py +++ b/main/latent_consistency_img2img.py @@ -286,7 +286,7 @@ class LatentConsistencyModelImg2ImgPipeline(DiffusionPipeline): num_inference_steps: int = 4, lcm_origin_steps: int = 50, prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, ): diff --git a/main/latent_consistency_interpolate.py b/main/latent_consistency_interpolate.py index e8349ba317e913850b6cd864190944b0346bbbd6..ce87f61b13b09481e5cfdede80fff927fcdd55ce 100644 --- a/main/latent_consistency_interpolate.py +++ b/main/latent_consistency_interpolate.py @@ -669,7 +669,7 @@ class LatentConsistencyModelWalkPipeline( generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, clip_skip: Optional[int] = None, diff --git a/main/latent_consistency_txt2img.py b/main/latent_consistency_txt2img.py index 0ce9820656195bf6b9e5cd197e3f96857846c337..80dc7e2fc2c3d0d2e87dceac08f1338e752a90a9 100644 --- a/main/latent_consistency_txt2img.py +++ b/main/latent_consistency_txt2img.py @@ -212,7 +212,7 @@ class LatentConsistencyModelPipeline(DiffusionPipeline): num_inference_steps: int = 4, lcm_origin_steps: int = 50, prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, ): diff --git a/main/llm_grounded_diffusion.py b/main/llm_grounded_diffusion.py index 5bf6674a43e3b6b1ab81f0a6055e882d919a7bc6..1ec565bac00e2782b6ed8496d1ea490abc066132 100644 --- a/main/llm_grounded_diffusion.py +++ b/main/llm_grounded_diffusion.py @@ -769,7 +769,7 @@ class LLMGroundedDiffusionPipeline( prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/lpw_stable_diffusion.py b/main/lpw_stable_diffusion.py index 58e932bbcf74fafceed8ab9110fd9093eae37d8c..3407c01e1edd20579bdddbf332f163bcbc181c9e 100644 --- a/main/lpw_stable_diffusion.py +++ b/main/lpw_stable_diffusion.py @@ -830,7 +830,7 @@ class StableDiffusionLongPromptWeightingPipeline( prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, is_cancelled_callback: Optional[Callable[[], bool]] = None, @@ -1091,7 +1091,7 @@ class StableDiffusionLongPromptWeightingPipeline( prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, is_cancelled_callback: Optional[Callable[[], bool]] = None, @@ -1209,7 +1209,7 @@ class StableDiffusionLongPromptWeightingPipeline( prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, is_cancelled_callback: Optional[Callable[[], bool]] = None, @@ -1323,7 +1323,7 @@ class StableDiffusionLongPromptWeightingPipeline( prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, is_cancelled_callback: Optional[Callable[[], bool]] = None, diff --git a/main/lpw_stable_diffusion_onnx.py b/main/lpw_stable_diffusion_onnx.py index 92effc1933298f97d7af99e9b551069071cfee91..eb7d86d09d3f67f3db39671609fba7305d3c6bae 100644 --- a/main/lpw_stable_diffusion_onnx.py +++ b/main/lpw_stable_diffusion_onnx.py @@ -664,10 +664,10 @@ class OnnxStableDiffusionLongPromptWeightingPipeline(OnnxStableDiffusionPipeline strength: float = 0.8, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[np.ndarray] = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, np.ndarray], None]] = None, is_cancelled_callback: Optional[Callable[[], bool]] = None, @@ -877,10 +877,10 @@ class OnnxStableDiffusionLongPromptWeightingPipeline(OnnxStableDiffusionPipeline guidance_scale: float = 7.5, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[np.ndarray] = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, np.ndarray], None]] = None, callback_steps: int = 1, @@ -969,9 +969,9 @@ class OnnxStableDiffusionLongPromptWeightingPipeline(OnnxStableDiffusionPipeline guidance_scale: Optional[float] = 7.5, num_images_per_prompt: Optional[int] = 1, eta: Optional[float] = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, np.ndarray], None]] = None, callback_steps: int = 1, @@ -1061,9 +1061,9 @@ class OnnxStableDiffusionLongPromptWeightingPipeline(OnnxStableDiffusionPipeline guidance_scale: Optional[float] = 7.5, num_images_per_prompt: Optional[int] = 1, eta: Optional[float] = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, max_embeddings_multiples: Optional[int] = 3, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, np.ndarray], None]] = None, callback_steps: int = 1, diff --git a/main/lpw_stable_diffusion_xl.py b/main/lpw_stable_diffusion_xl.py index 1aba1f270198ad0dffbeb24d46afbc2c1c09de38..b7a3623bf6ce47c28a7ecaf6fd7390a13160b24e 100644 --- a/main/lpw_stable_diffusion_xl.py +++ b/main/lpw_stable_diffusion_xl.py @@ -519,7 +519,7 @@ def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0): # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -724,12 +724,12 @@ class SDXLLongPromptWeightingPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -1399,7 +1399,7 @@ class SDXLLongPromptWeightingPipeline( def __call__( self, prompt: str = None, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, image: Optional[PipelineImageInput] = None, mask_image: Optional[PipelineImageInput] = None, masked_image_latents: Optional[torch.Tensor] = None, @@ -1411,8 +1411,8 @@ class SDXLLongPromptWeightingPipeline( denoising_start: Optional[float] = None, denoising_end: Optional[float] = None, guidance_scale: float = 5.0, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, @@ -1422,7 +1422,7 @@ class SDXLLongPromptWeightingPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, @@ -1955,7 +1955,7 @@ class SDXLLongPromptWeightingPipeline( def text2img( self, prompt: str = None, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 50, @@ -1963,8 +1963,8 @@ class SDXLLongPromptWeightingPipeline( denoising_start: Optional[float] = None, denoising_end: Optional[float] = None, guidance_scale: float = 5.0, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, @@ -1974,7 +1974,7 @@ class SDXLLongPromptWeightingPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, @@ -2028,7 +2028,7 @@ class SDXLLongPromptWeightingPipeline( def img2img( self, prompt: str = None, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, image: Optional[PipelineImageInput] = None, height: Optional[int] = None, width: Optional[int] = None, @@ -2038,8 +2038,8 @@ class SDXLLongPromptWeightingPipeline( denoising_start: Optional[float] = None, denoising_end: Optional[float] = None, guidance_scale: float = 5.0, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, @@ -2049,7 +2049,7 @@ class SDXLLongPromptWeightingPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, @@ -2105,7 +2105,7 @@ class SDXLLongPromptWeightingPipeline( def inpaint( self, prompt: str = None, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, image: Optional[PipelineImageInput] = None, mask_image: Optional[PipelineImageInput] = None, masked_image_latents: Optional[torch.Tensor] = None, @@ -2117,8 +2117,8 @@ class SDXLLongPromptWeightingPipeline( denoising_start: Optional[float] = None, denoising_end: Optional[float] = None, guidance_scale: float = 5.0, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, @@ -2128,7 +2128,7 @@ class SDXLLongPromptWeightingPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/masked_stable_diffusion_img2img.py b/main/masked_stable_diffusion_img2img.py index 570bd0963e28d36d167886a9996e07d8fbd3c7a7..ac1612527d6a6c3a5f7f0733164f32410755f5ac 100644 --- a/main/masked_stable_diffusion_img2img.py +++ b/main/masked_stable_diffusion_img2img.py @@ -32,7 +32,7 @@ class MaskedStableDiffusionImg2ImgPipeline(StableDiffusionImg2ImgPipeline): generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/masked_stable_diffusion_xl_img2img.py b/main/masked_stable_diffusion_xl_img2img.py index 14d8c7c2da788b9d51ea7ae9ae6da227e4bfc25f..9e47b79e18beb61bd66fa5d2f36df0fef826ffc3 100644 --- a/main/masked_stable_diffusion_xl_img2img.py +++ b/main/masked_stable_diffusion_xl_img2img.py @@ -59,7 +59,7 @@ class MaskedStableDiffusionXLImg2ImgPipeline(StableDiffusionXLImg2ImgPipeline): negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.FloatTensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/matryoshka.py b/main/matryoshka.py index 09b1d1b24465c129de9efc02e81bf98c7e94dece..a4971f94829df72c3c2dd480689d21f47fb5e439 100644 --- a/main/matryoshka.py +++ b/main/matryoshka.py @@ -783,7 +783,7 @@ class CrossAttnDownBlock2D(nn.Module): norm_type: str = "layer_norm", num_attention_heads: int = 1, cross_attention_dim: int = 1280, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, output_scale_factor: float = 1.0, downsample_padding: int = 1, add_downsample: bool = True, @@ -922,7 +922,7 @@ class UNetMidBlock2DCrossAttn(nn.Module): num_attention_heads: int = 1, output_scale_factor: float = 1.0, cross_attention_dim: int = 1280, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, dual_cross_attention: bool = False, use_linear_projection: bool = False, upcast_attention: bool = False, @@ -1055,7 +1055,7 @@ class CrossAttnUpBlock2D(nn.Module): norm_type: str = "layer_norm", num_attention_heads: int = 1, cross_attention_dim: int = 1280, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, output_scale_factor: float = 1.0, add_upsample: bool = True, dual_cross_attention: bool = False, @@ -1617,10 +1617,10 @@ def get_down_block( attention_pre_only: bool = False, resnet_skip_time_act: bool = False, resnet_out_scale_factor: float = 1.0, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, attention_head_dim: Optional[int] = None, use_attention_ffn: bool = True, - downsample_type: Optional[str] = None, + downsample_type: str | None = None, dropout: float = 0.0, ): # If attn head dim is not defined, we default it to the number of heads @@ -1695,7 +1695,7 @@ def get_mid_block( attention_type: str = "default", attention_pre_only: bool = False, resnet_skip_time_act: bool = False, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, attention_head_dim: Optional[int] = 1, dropout: float = 0.0, ): @@ -1747,10 +1747,10 @@ def get_up_block( attention_pre_only: bool = False, resnet_skip_time_act: bool = False, resnet_out_scale_factor: float = 1.0, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, attention_head_dim: Optional[int] = None, use_attention_ffn: bool = True, - upsample_type: Optional[str] = None, + upsample_type: str | None = None, dropout: float = 0.0, ) -> nn.Module: # If attn head dim is not defined, we default it to the number of heads @@ -1972,7 +1972,7 @@ class MatryoshkaUNet2DConditionModel( "CrossAttnDownBlock2D", "DownBlock2D", ), - mid_block_type: Optional[str] = "UNetMidBlock2DCrossAttn", + mid_block_type: str | None = "UNetMidBlock2DCrossAttn", up_block_types: Tuple[str, ...] = ( "UpBlock2D", "CrossAttnUpBlock2D", @@ -1993,14 +1993,14 @@ class MatryoshkaUNet2DConditionModel( transformer_layers_per_block: Union[int, Tuple[int], Tuple[Tuple]] = 1, reverse_transformer_layers_per_block: Optional[Tuple[Tuple[int]]] = None, encoder_hid_dim: Optional[int] = None, - encoder_hid_dim_type: Optional[str] = None, + encoder_hid_dim_type: str | None = None, attention_head_dim: Union[int, Tuple[int]] = 8, num_attention_heads: Optional[Union[int, Tuple[int]]] = None, dual_cross_attention: bool = False, use_attention_ffn: bool = True, use_linear_projection: bool = False, - class_embed_type: Optional[str] = None, - addition_embed_type: Optional[str] = None, + class_embed_type: str | None = None, + addition_embed_type: str | None = None, addition_time_embed_dim: Optional[int] = None, num_class_embeds: Optional[int] = None, upcast_attention: bool = False, @@ -2009,8 +2009,8 @@ class MatryoshkaUNet2DConditionModel( resnet_out_scale_factor: float = 1.0, time_embedding_type: str = "positional", time_embedding_dim: Optional[int] = None, - time_embedding_act_fn: Optional[str] = None, - timestep_post_act: Optional[str] = None, + time_embedding_act_fn: str | None = None, + timestep_post_act: str | None = None, time_cond_proj_dim: Optional[int] = None, conv_in_kernel: int = 3, conv_out_kernel: int = 3, @@ -2021,7 +2021,7 @@ class MatryoshkaUNet2DConditionModel( micro_conditioning_scale: int = None, class_embeddings_concat: bool = False, mid_block_only_cross_attention: Optional[bool] = None, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, addition_embed_type_num_heads: int = 64, temporal_mode: bool = False, temporal_spatial_ds: bool = False, @@ -2384,7 +2384,7 @@ class MatryoshkaUNet2DConditionModel( def _set_encoder_hid_proj( self, - encoder_hid_dim_type: Optional[str], + encoder_hid_dim_type: str | None, cross_attention_dim: Union[int, Tuple[int]], encoder_hid_dim: Optional[int], ): @@ -2424,7 +2424,7 @@ class MatryoshkaUNet2DConditionModel( def _set_class_embedding( self, - class_embed_type: Optional[str], + class_embed_type: str | None, act_fn: str, num_class_embeds: Optional[int], projection_class_embeddings_input_dim: Optional[int], @@ -2524,7 +2524,7 @@ class MatryoshkaUNet2DConditionModel( ) @property - def attn_processors(self) -> Dict[str, AttentionProcessor]: + def attn_processors(self) -> dict[str, AttentionProcessor]: r""" Returns: `dict` of attention processors: A dictionary containing all attention processors used in the model with @@ -4264,7 +4264,7 @@ class MatryoshkaPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/mixture_tiling_sdxl.py b/main/mixture_tiling_sdxl.py index e09f5a25db7312b01010dd90eac0fa1b533d9da9..dee1c3ef055e74720002e881c6b193fad4083508 100644 --- a/main/mixture_tiling_sdxl.py +++ b/main/mixture_tiling_sdxl.py @@ -388,12 +388,12 @@ class StableDiffusionXLTilingPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -780,7 +780,7 @@ class StableDiffusionXLTilingPipeline( num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, original_size: Optional[Tuple[int, int]] = None, diff --git a/main/mod_controlnet_tile_sr_sdxl.py b/main/mod_controlnet_tile_sr_sdxl.py index fe8bd73eabbe1ea1c1289d22e5001fd2b1023311..959ef6453de05aa9299e31a4b3d7a082e10bc55c 100644 --- a/main/mod_controlnet_tile_sr_sdxl.py +++ b/main/mod_controlnet_tile_sr_sdxl.py @@ -243,7 +243,7 @@ def _tile2latent_indices( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -395,12 +395,12 @@ class StableDiffusionXLControlNetTileSRPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -1265,7 +1265,7 @@ class StableDiffusionXLControlNetTileSRPipeline( eta: float = 0.0, generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 1.0, diff --git a/main/multilingual_stable_diffusion.py b/main/multilingual_stable_diffusion.py index 436803f201fe8e399dc106fdec7f5eca2052d935..444012acacec9e6b3f76cf1063be6247301bbbe4 100644 --- a/main/multilingual_stable_diffusion.py +++ b/main/multilingual_stable_diffusion.py @@ -146,9 +146,9 @@ class MultilingualStableDiffusion(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/pipeline_animatediff_controlnet.py b/main/pipeline_animatediff_controlnet.py index 903bfd4fd57b70db4e0369abd1065f4dc5009dc6..b195ba0f8a20160a72ef92a9133e51e90d1dc5c8 100644 --- a/main/pipeline_animatediff_controlnet.py +++ b/main/pipeline_animatediff_controlnet.py @@ -762,7 +762,7 @@ class AnimateDiffControlNetPipeline( ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[PipelineImageInput] = None, conditioning_frames: Optional[List[PipelineImageInput]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 1.0, diff --git a/main/pipeline_animatediff_img2video.py b/main/pipeline_animatediff_img2video.py index feba19f70fc655735afd12176b5aa21108ac84a2..5deadf6784c0ab9af70c4a12e7ec63ff30cbf486 100644 --- a/main/pipeline_animatediff_img2video.py +++ b/main/pipeline_animatediff_img2video.py @@ -182,7 +182,7 @@ def tensor2vid(video: torch.Tensor, processor, output_type="np"): # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -755,7 +755,7 @@ class AnimateDiffImgToVideoPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: Optional[int] = 1, diff --git a/main/pipeline_animatediff_ipex.py b/main/pipeline_animatediff_ipex.py index 409ab9d6ad735008a70a17190a2fb19ced822212..43d93bd3af2a86767fcaa408c22ffed3c486124b 100644 --- a/main/pipeline_animatediff_ipex.py +++ b/main/pipeline_animatediff_ipex.py @@ -588,7 +588,7 @@ class AnimateDiffPipelineIpex( negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, clip_skip: Optional[int] = None, @@ -844,7 +844,7 @@ class AnimateDiffPipelineIpex( negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, clip_skip: Optional[int] = None, diff --git a/main/pipeline_controlnet_xl_kolors.py b/main/pipeline_controlnet_xl_kolors.py index 96c801bab3799ac4ba9acffb95ec4ed3634e408c..d35176ba4f4505a61d0b5fad1d4d9629fc8e6204 100644 --- a/main/pipeline_controlnet_xl_kolors.py +++ b/main/pipeline_controlnet_xl_kolors.py @@ -111,7 +111,7 @@ EXAMPLE_DOC_STRING = """ # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -800,7 +800,7 @@ class KolorsControlNetPipeline( negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 0.8, diff --git a/main/pipeline_controlnet_xl_kolors_img2img.py b/main/pipeline_controlnet_xl_kolors_img2img.py index 41f2550138b3d307fc9e340f7831eaeadbd04e6e..077241d9da220a85b5ee7116b455beade0fcb798 100644 --- a/main/pipeline_controlnet_xl_kolors_img2img.py +++ b/main/pipeline_controlnet_xl_kolors_img2img.py @@ -131,7 +131,7 @@ EXAMPLE_DOC_STRING = """ # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -972,7 +972,7 @@ class KolorsControlNetImg2ImgPipeline( negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 0.8, diff --git a/main/pipeline_controlnet_xl_kolors_inpaint.py b/main/pipeline_controlnet_xl_kolors_inpaint.py index 07bd552a29e737c38f03c3fd059b57b18c1c9593..387a42ba22b3d330dcc51111ee8f5322c8e625ab 100644 --- a/main/pipeline_controlnet_xl_kolors_inpaint.py +++ b/main/pipeline_controlnet_xl_kolors_inpaint.py @@ -118,7 +118,7 @@ EXAMPLE_DOC_STRING = """ # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -1139,7 +1139,7 @@ class KolorsControlNetInpaintPipeline( negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 0.8, diff --git a/main/pipeline_demofusion_sdxl.py b/main/pipeline_demofusion_sdxl.py index b5b68577982b4e112a98e3ce8c844df40734b409..b0a3cab347a049b040be306f6cba26a1348c32f3 100644 --- a/main/pipeline_demofusion_sdxl.py +++ b/main/pipeline_demofusion_sdxl.py @@ -184,12 +184,12 @@ class DemoFusionSDXLPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -637,7 +637,7 @@ class DemoFusionSDXLPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = False, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/pipeline_fabric.py b/main/pipeline_fabric.py index d29e98df5e50228e3b4b44b42992fd950dace314..fe7de1dd94a74757c9e9eb47b85774a5d7255884 100644 --- a/main/pipeline_fabric.py +++ b/main/pipeline_fabric.py @@ -508,7 +508,7 @@ class FabricPipeline(DiffusionPipeline): num_images: int = 4, guidance_scale: float = 7.0, num_inference_steps: int = 20, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", feedback_start_ratio: float = 0.33, feedback_end_ratio: float = 0.66, min_weight: float = 0.05, diff --git a/main/pipeline_faithdiff_stable_diffusion_xl.py b/main/pipeline_faithdiff_stable_diffusion_xl.py index 4b564d5ee5c8abe443b520fe3547f77d9fa595db..796a900b2f753f31d6fcd4d5df8fd21abc8e60f7 100644 --- a/main/pipeline_faithdiff_stable_diffusion_xl.py +++ b/main/pipeline_faithdiff_stable_diffusion_xl.py @@ -437,7 +437,7 @@ class UNet2DConditionModel(OriginalUNet2DConditionModel, ConfigMixin, UNet2DCond "CrossAttnDownBlock2D", "DownBlock2D", ), - mid_block_type: Optional[str] = "UNetMidBlock2DCrossAttn", + mid_block_type: str | None = "UNetMidBlock2DCrossAttn", up_block_types: Tuple[str, ...] = ( "UpBlock2D", "CrossAttnUpBlock2D", @@ -457,13 +457,13 @@ class UNet2DConditionModel(OriginalUNet2DConditionModel, ConfigMixin, UNet2DCond transformer_layers_per_block: Union[int, Tuple[int], Tuple[Tuple]] = 1, reverse_transformer_layers_per_block: Optional[Tuple[Tuple[int]]] = None, encoder_hid_dim: Optional[int] = None, - encoder_hid_dim_type: Optional[str] = None, + encoder_hid_dim_type: str | None = None, attention_head_dim: Union[int, Tuple[int]] = 8, num_attention_heads: Optional[Union[int, Tuple[int]]] = None, dual_cross_attention: bool = False, use_linear_projection: bool = False, - class_embed_type: Optional[str] = None, - addition_embed_type: Optional[str] = None, + class_embed_type: str | None = None, + addition_embed_type: str | None = None, addition_time_embed_dim: Optional[int] = None, num_class_embeds: Optional[int] = None, upcast_attention: bool = False, @@ -472,8 +472,8 @@ class UNet2DConditionModel(OriginalUNet2DConditionModel, ConfigMixin, UNet2DCond resnet_out_scale_factor: float = 1.0, time_embedding_type: str = "positional", time_embedding_dim: Optional[int] = None, - time_embedding_act_fn: Optional[str] = None, - timestep_post_act: Optional[str] = None, + time_embedding_act_fn: str | None = None, + timestep_post_act: str | None = None, time_cond_proj_dim: Optional[int] = None, conv_in_kernel: int = 3, conv_out_kernel: int = 3, @@ -481,7 +481,7 @@ class UNet2DConditionModel(OriginalUNet2DConditionModel, ConfigMixin, UNet2DCond attention_type: str = "default", class_embeddings_concat: bool = False, mid_block_only_cross_attention: Optional[bool] = None, - cross_attention_norm: Optional[str] = None, + cross_attention_norm: str | None = None, addition_embed_type_num_heads: int = 64, ): """Initialize the UnifiedUNet2DConditionModel.""" @@ -565,7 +565,7 @@ class UNet2DConditionModel(OriginalUNet2DConditionModel, ConfigMixin, UNet2DCond self.agg_net = nn.ModuleList() def load_additional_layers( - self, dtype: Optional[torch.dtype] = torch.float16, channel: int = 512, weight_path: Optional[str] = None + self, dtype: Optional[torch.dtype] = torch.float16, channel: int = 512, weight_path: str | None = None ): """Load additional layers and weights from a file. @@ -1096,7 +1096,7 @@ def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0): # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): """Retrieve latents from an encoder output. @@ -1267,12 +1267,12 @@ class FaithDiffStableDiffusionXLPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.FloatTensor] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, @@ -1808,7 +1808,7 @@ class FaithDiffStableDiffusionXLPipeline( height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 50, - start_point: Optional[str] = "noise", + start_point: str | None = "noise", timesteps: List[int] = None, denoising_end: Optional[float] = None, overlap: float = 0.5, @@ -1823,7 +1823,7 @@ class FaithDiffStableDiffusionXLPipeline( negative_prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_flux_differential_img2img.py b/main/pipeline_flux_differential_img2img.py index 3677e73136f79a9539f66ad73774bb5b08669dec..7cfb816d7310f32e3308a31eaaf0020632e85581 100644 --- a/main/pipeline_flux_differential_img2img.py +++ b/main/pipeline_flux_differential_img2img.py @@ -97,7 +97,7 @@ def calculate_shift( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -698,7 +698,7 @@ class FluxDifferentialImg2ImgPipeline(DiffusionPipeline, FluxLoraLoaderMixin): latents: Optional[torch.FloatTensor] = None, prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_flux_kontext_multiple_images.py b/main/pipeline_flux_kontext_multiple_images.py index 9e6ae427dbfa0e09216349e303ffc0dc345131d1..fb344859e99ec0035987064f056be1d078e11a84 100644 --- a/main/pipeline_flux_kontext_multiple_images.py +++ b/main/pipeline_flux_kontext_multiple_images.py @@ -188,7 +188,7 @@ def retrieve_timesteps( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -838,7 +838,7 @@ class FluxKontextPipeline( negative_ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_flux_rf_inversion.py b/main/pipeline_flux_rf_inversion.py index 2cd6eb088cd80d6adaafd2f84342050093aa4a22..16bb83bbcf345385975be131a462b15f411c3563 100644 --- a/main/pipeline_flux_rf_inversion.py +++ b/main/pipeline_flux_rf_inversion.py @@ -685,7 +685,7 @@ class RFInversionFluxPipeline( latents: Optional[torch.FloatTensor] = None, prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_flux_semantic_guidance.py b/main/pipeline_flux_semantic_guidance.py index 74cd5c6981b0f98ef0affacf345178520cfa414f..a8d64b9caca60f789bc030161ee91adeef002b54 100644 --- a/main/pipeline_flux_semantic_guidance.py +++ b/main/pipeline_flux_semantic_guidance.py @@ -802,7 +802,7 @@ class FluxSemanticGuidancePipeline( negative_ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_flux_with_cfg.py b/main/pipeline_flux_with_cfg.py index 5bc13f7e5e1138799fef0a9abf8234a694d57609..107901a76f579763d78952db0cb6b5f320687db1 100644 --- a/main/pipeline_flux_with_cfg.py +++ b/main/pipeline_flux_with_cfg.py @@ -622,7 +622,7 @@ class FluxCFGPipeline(DiffusionPipeline, FluxLoraLoaderMixin, FromSingleFileMixi pooled_prompt_embeds: Optional[torch.FloatTensor] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_hunyuandit_differential_img2img.py b/main/pipeline_hunyuandit_differential_img2img.py index bc6841525b4989cd7e7d486eab2e352384eee45f..123e46e53baef1c714f00ef405fb8188f2cfb17d 100644 --- a/main/pipeline_hunyuandit_differential_img2img.py +++ b/main/pipeline_hunyuandit_differential_img2img.py @@ -164,7 +164,7 @@ def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0): # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img.retrieve_latents def retrieve_latents( encoder_output: torch.Tensor, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, sample_mode: str = "sample", ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": @@ -349,7 +349,7 @@ class HunyuanDiTDifferentialImg2ImgPipeline(DiffusionPipeline): dtype: torch.dtype = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, + negative_prompt: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, prompt_attention_mask: Optional[torch.Tensor] = None, @@ -749,7 +749,7 @@ class HunyuanDiTDifferentialImg2ImgPipeline(DiffusionPipeline): prompt_attention_mask_2: Optional[torch.Tensor] = None, negative_prompt_attention_mask: Optional[torch.Tensor] = None, negative_prompt_attention_mask_2: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback_on_step_end: Optional[ Union[ diff --git a/main/pipeline_kolors_differential_img2img.py b/main/pipeline_kolors_differential_img2img.py index d456af8b3385ced65301dc382ef769fdac562df1..507f71ad61ef3079869e7d2ae95fddcedb765412 100644 --- a/main/pipeline_kolors_differential_img2img.py +++ b/main/pipeline_kolors_differential_img2img.py @@ -67,7 +67,7 @@ EXAMPLE_DOC_STRING = """ # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -800,7 +800,7 @@ class KolorsDifferentialImg2ImgPipeline( negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, original_size: Optional[Tuple[int, int]] = None, diff --git a/main/pipeline_kolors_inpainting.py b/main/pipeline_kolors_inpainting.py index 85a3d698efa1262f7080349ba2d691b6b00834cd..d5cb57580f58dbfdefc1cb943aa08fec8b428377 100644 --- a/main/pipeline_kolors_inpainting.py +++ b/main/pipeline_kolors_inpainting.py @@ -239,7 +239,7 @@ def prepare_mask_and_masked_image(image, mask, height, width, return_image: bool # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -1100,7 +1100,7 @@ class KolorsInpaintPipeline( negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_prompt2prompt.py b/main/pipeline_prompt2prompt.py index eb19667970b01811cc39536643d767f9bd074035..9ca7058892c4409e7b7f3bc4a48c6ef7f6448a44 100644 --- a/main/pipeline_prompt2prompt.py +++ b/main/pipeline_prompt2prompt.py @@ -571,7 +571,7 @@ class Prompt2PromptPipeline( latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: Optional[int] = 1, diff --git a/main/pipeline_sdxl_style_aligned.py b/main/pipeline_sdxl_style_aligned.py index ac7ad33b68c5ff45b1e90b34d3fb32aa8c51def0..75f3cb9ead763f85cfdc178b67f4cad6807468ff 100644 --- a/main/pipeline_sdxl_style_aligned.py +++ b/main/pipeline_sdxl_style_aligned.py @@ -371,7 +371,7 @@ def retrieve_timesteps( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -508,12 +508,12 @@ class StyleAlignedSDXLPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -1394,7 +1394,7 @@ class StyleAlignedSDXLPipeline( pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_stable_diffusion_3_differential_img2img.py b/main/pipeline_stable_diffusion_3_differential_img2img.py index 1803cf60cc4b4cd18a6e909f957ed819aaf6fa27..df5628e55eb67d35616d499d9e83b64e97c497ed 100644 --- a/main/pipeline_stable_diffusion_3_differential_img2img.py +++ b/main/pipeline_stable_diffusion_3_differential_img2img.py @@ -68,7 +68,7 @@ EXAMPLE_DOC_STRING = """ # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -688,7 +688,7 @@ class StableDiffusion3DifferentialImg2ImgPipeline(DiffusionPipeline): negative_prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, clip_skip: Optional[int] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_stable_diffusion_3_instruct_pix2pix.py b/main/pipeline_stable_diffusion_3_instruct_pix2pix.py index d9cee800e8ad47a6ed98ccd021fbf32b38e058db..d4cb2924b9dc9591e87ce1b004aaf777561cb300 100644 --- a/main/pipeline_stable_diffusion_3_instruct_pix2pix.py +++ b/main/pipeline_stable_diffusion_3_instruct_pix2pix.py @@ -102,7 +102,7 @@ def calculate_shift( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -880,7 +880,7 @@ class StableDiffusion3InstructPix2PixPipeline( negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, clip_skip: Optional[int] = None, diff --git a/main/pipeline_stable_diffusion_boxdiff.py b/main/pipeline_stable_diffusion_boxdiff.py index c05a6143132ce20fa0e9aa26cc251426041ac441..69cff867ed6e8b5707163f172f67a9de53bf7f7e 100644 --- a/main/pipeline_stable_diffusion_boxdiff.py +++ b/main/pipeline_stable_diffusion_boxdiff.py @@ -1341,7 +1341,7 @@ class StableDiffusionBoxDiffPipeline( prompt_embeds: Optional[torch.FloatTensor] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_stable_diffusion_pag.py b/main/pipeline_stable_diffusion_pag.py index 3f98dca0b9866b953179cc887f2404d5475c2f47..f8061e11aa9988f94138a60aad1ea050cbed2520 100644 --- a/main/pipeline_stable_diffusion_pag.py +++ b/main/pipeline_stable_diffusion_pag.py @@ -1114,7 +1114,7 @@ class StableDiffusionPAGPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_stable_diffusion_upscale_ldm3d.py b/main/pipeline_stable_diffusion_upscale_ldm3d.py index ba89556a5e4d65cf8e52beba6daeeee6888e4f0f..d537ef8797115cb2d81096c9c163925533075757 100644 --- a/main/pipeline_stable_diffusion_upscale_ldm3d.py +++ b/main/pipeline_stable_diffusion_upscale_ldm3d.py @@ -523,7 +523,7 @@ class StableDiffusionUpscaleLDM3DPipeline( latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/pipeline_stable_diffusion_xl_attentive_eraser.py b/main/pipeline_stable_diffusion_xl_attentive_eraser.py index 822c804ec8a90061f98be7172aa9af7ed1810374..a001e458392cd6eba3d3f9f45ddd50b6d7bf477c 100644 --- a/main/pipeline_stable_diffusion_xl_attentive_eraser.py +++ b/main/pipeline_stable_diffusion_xl_attentive_eraser.py @@ -435,7 +435,7 @@ def prepare_mask_and_masked_image(image, mask, height, width, return_image: bool # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -694,12 +694,12 @@ class StableDiffusionXL_AE_Pipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.FloatTensor] = None, negative_prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, @@ -1640,7 +1640,7 @@ class StableDiffusionXL_AE_Pipeline( negative_pooled_prompt_embeds: Optional[torch.FloatTensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.FloatTensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_stable_diffusion_xl_controlnet_adapter.py b/main/pipeline_stable_diffusion_xl_controlnet_adapter.py index d435a6e146b235cb11cab7274c7dc11318d8179e..e38801cd7647293d4a0cb8e03104edc5322c3533 100644 --- a/main/pipeline_stable_diffusion_xl_controlnet_adapter.py +++ b/main/pipeline_stable_diffusion_xl_controlnet_adapter.py @@ -241,12 +241,12 @@ class StableDiffusionXLControlNetAdapterPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -878,7 +878,7 @@ class StableDiffusionXLControlNetAdapterPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py b/main/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py index 8d70e8f3c2a1b653e822a503229638a823a5344b..2e05e338031670d3c42c27748a9ef8ffd45e191b 100644 --- a/main/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py +++ b/main/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py @@ -388,12 +388,12 @@ class StableDiffusionXLControlNetAdapterInpaintPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -1219,7 +1219,7 @@ class StableDiffusionXLControlNetAdapterInpaintPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/pipeline_stable_diffusion_xl_differential_img2img.py b/main/pipeline_stable_diffusion_xl_differential_img2img.py index 99657facddf68f162b0981978acca367c4f51e40..16144671d89200213e04e48f342472f150785255 100644 --- a/main/pipeline_stable_diffusion_xl_differential_img2img.py +++ b/main/pipeline_stable_diffusion_xl_differential_img2img.py @@ -101,7 +101,7 @@ def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0): # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -268,12 +268,12 @@ class StableDiffusionXLDifferentialImg2ImgPipeline( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -949,7 +949,7 @@ class StableDiffusionXLDifferentialImg2ImgPipeline( negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_stable_diffusion_xl_instandid_img2img.py b/main/pipeline_stable_diffusion_xl_instandid_img2img.py index 33bf5ad346f458716db721e7520ea33c5da0c17f..1710f682d0ed510516016250a2cd4727f9f9ddf5 100644 --- a/main/pipeline_stable_diffusion_xl_instandid_img2img.py +++ b/main/pipeline_stable_diffusion_xl_instandid_img2img.py @@ -567,7 +567,7 @@ class StableDiffusionXLInstantIDImg2ImgPipeline(StableDiffusionXLControlNetImg2I pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, image_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 1.0, diff --git a/main/pipeline_stable_diffusion_xl_instantid.py b/main/pipeline_stable_diffusion_xl_instantid.py index 45876b91f7d878656d027306a00dbe0ebb472497..4dfbcc194dd8636353dfbc062b241822dabd85f9 100644 --- a/main/pipeline_stable_diffusion_xl_instantid.py +++ b/main/pipeline_stable_diffusion_xl_instantid.py @@ -565,7 +565,7 @@ class StableDiffusionXLInstantIDPipeline(StableDiffusionXLControlNetPipeline): pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, image_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 1.0, diff --git a/main/pipeline_stable_diffusion_xl_ipex.py b/main/pipeline_stable_diffusion_xl_ipex.py index 8e8357db3c7a9a7091b30888ec459b2cd2d79458..a0c07ccaeefb07b50fe5103f5cddc5948f7564ac 100644 --- a/main/pipeline_stable_diffusion_xl_ipex.py +++ b/main/pipeline_stable_diffusion_xl_ipex.py @@ -268,12 +268,12 @@ class StableDiffusionXLPipelineIpex( def encode_prompt( self, prompt: str, - prompt_2: Optional[str] = None, + prompt_2: str | None = None, device: Optional[torch.device] = None, num_images_per_prompt: int = 1, do_classifier_free_guidance: bool = True, - negative_prompt: Optional[str] = None, - negative_prompt_2: Optional[str] = None, + negative_prompt: str | None = None, + negative_prompt_2: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, @@ -741,7 +741,7 @@ class StableDiffusionXLPipelineIpex( pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, @@ -1181,7 +1181,7 @@ class StableDiffusionXLPipelineIpex( pooled_prompt_embeds: Optional[torch.Tensor] = None, negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/pipeline_stg_hunyuan_video.py b/main/pipeline_stg_hunyuan_video.py index 028d54d047e49c4b03bd21611e46c15f944e9673..489125ff6a62eeefb35ed889608cd2cb9def5fed 100644 --- a/main/pipeline_stg_hunyuan_video.py +++ b/main/pipeline_stg_hunyuan_video.py @@ -571,7 +571,7 @@ class HunyuanVideoSTGPipeline(DiffusionPipeline, HunyuanVideoLoraLoaderMixin): prompt_embeds: Optional[torch.Tensor] = None, pooled_prompt_embeds: Optional[torch.Tensor] = None, prompt_attention_mask: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[ diff --git a/main/pipeline_stg_ltx.py b/main/pipeline_stg_ltx.py index 70069a33f5d9c94aad535b8faa783f7e84fded75..5bf98f97fa7db94d849afd488aeee3e267498dd8 100644 --- a/main/pipeline_stg_ltx.py +++ b/main/pipeline_stg_ltx.py @@ -506,7 +506,7 @@ class LTXSTGPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVideoLoraLoaderM num_frames: int = 161, dtype: Optional[torch.dtype] = None, device: Optional[torch.device] = None, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, ) -> torch.Tensor: if latents is not None: @@ -576,7 +576,7 @@ class LTXSTGPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVideoLoraLoaderM negative_prompt_attention_mask: Optional[torch.Tensor] = None, decode_timestep: Union[float, List[float]] = 0.0, decode_noise_scale: Optional[Union[float, List[float]]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_stg_ltx_image2video.py b/main/pipeline_stg_ltx_image2video.py index c32805e1419ff7cdec492ecc363bacfbcc3293f2..4eec632d7853f8fa9afc42c3d0ba4bc1e9efc78f 100644 --- a/main/pipeline_stg_ltx_image2video.py +++ b/main/pipeline_stg_ltx_image2video.py @@ -200,7 +200,7 @@ def retrieve_timesteps( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -535,7 +535,7 @@ class LTXImageToVideoSTGPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVide num_frames: int = 161, dtype: Optional[torch.dtype] = None, device: Optional[torch.device] = None, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, ) -> torch.Tensor: height = height // self.vae_spatial_compression_ratio @@ -636,7 +636,7 @@ class LTXImageToVideoSTGPipeline(DiffusionPipeline, FromSingleFileMixin, LTXVide negative_prompt_attention_mask: Optional[torch.Tensor] = None, decode_timestep: Union[float, List[float]] = 0.0, decode_noise_scale: Optional[Union[float, List[float]]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_stg_mochi.py b/main/pipeline_stg_mochi.py index ad9317f6bc9da2b899a9ea4a0eb021449ad4390d..350fba3bcf8056bf07d41ebde00857112a87deb5 100644 --- a/main/pipeline_stg_mochi.py +++ b/main/pipeline_stg_mochi.py @@ -579,7 +579,7 @@ class MochiSTGPipeline(DiffusionPipeline, Mochi1LoraLoaderMixin): prompt_attention_mask: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_attention_mask: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_stg_wan.py b/main/pipeline_stg_wan.py index 39f208bad7c560f1f5c7034e9d4db849dc504814..0833869bd35ca9015b06bfff7ed51383864f0b6c 100644 --- a/main/pipeline_stg_wan.py +++ b/main/pipeline_stg_wan.py @@ -423,7 +423,7 @@ class WanSTGPipeline(DiffusionPipeline, WanLoraLoaderMixin): latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "np", + output_type: str | None = "np", return_dict: bool = True, attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[ diff --git a/main/pipeline_z_image_differential_img2img.py b/main/pipeline_z_image_differential_img2img.py index 8bde065c4013a9588425dfea1858478c57e8baf7..6309e91abbdd51f58d9e055f7e899e9158108a14 100644 --- a/main/pipeline_z_image_differential_img2img.py +++ b/main/pipeline_z_image_differential_img2img.py @@ -81,7 +81,7 @@ def calculate_shift( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -467,7 +467,7 @@ class ZImageDifferentialImg2ImgPipeline(DiffusionPipeline, ZImageLoraLoaderMixin latents: Optional[torch.FloatTensor] = None, prompt_embeds: Optional[List[torch.FloatTensor]] = None, negative_prompt_embeds: Optional[List[torch.FloatTensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/pipeline_zero1to3.py b/main/pipeline_zero1to3.py index 1be59fd8323e1e8543b55ebae83067e18bff46b5..125566d7cf2d42727188e4a332e871cf3ebd673e 100644 --- a/main/pipeline_zero1to3.py +++ b/main/pipeline_zero1to3.py @@ -614,7 +614,7 @@ class Zero1to3StableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin): latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/pipline_flux_fill_controlnet_Inpaint.py b/main/pipline_flux_fill_controlnet_Inpaint.py index cc642a767f879371d0e20349fc92c06fc17203bd..88dcbecf8de0c09a44c83b5e9f5fac721ede3924 100644 --- a/main/pipline_flux_fill_controlnet_Inpaint.py +++ b/main/pipline_flux_fill_controlnet_Inpaint.py @@ -99,7 +99,7 @@ def calculate_shift( # 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" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -112,7 +112,7 @@ def retrieve_latents( def retrieve_latents_fill( - encoder_output: torch.Tensor, generator: Optional[torch.Generator] = None, sample_mode: str = "sample" + encoder_output: torch.Tensor, generator: torch.Generator | None = None, sample_mode: str = "sample" ): if hasattr(encoder_output, "latent_dist") and sample_mode == "sample": return encoder_output.latent_dist.sample(generator) @@ -855,7 +855,7 @@ class FluxControlNetFillInpaintPipeline(DiffusionPipeline, FluxLoraLoaderMixin, latents: Optional[torch.FloatTensor] = None, prompt_embeds: Optional[torch.FloatTensor] = None, pooled_prompt_embeds: Optional[torch.FloatTensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, joint_attention_kwargs: Optional[Dict[str, Any]] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, diff --git a/main/regional_prompting_stable_diffusion.py b/main/regional_prompting_stable_diffusion.py index 3bc780cfcf7ae1cf0f3b13b16c7bf384897fecb5..daea47b3c3ddceb1a4cc93aebf28cd6d07f0ae0b 100644 --- a/main/regional_prompting_stable_diffusion.py +++ b/main/regional_prompting_stable_diffusion.py @@ -148,9 +148,9 @@ class RegionalPromptingStableDiffusionPipeline( negative_prompt: str = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, rp_args: Dict[str, str] = None, ): @@ -800,7 +800,7 @@ class RegionalPromptingStableDiffusionPipeline( negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/rerender_a_video.py b/main/rerender_a_video.py index 840f9e206d4d15e194560f93eef1f8813e6f85bb..b2680ebb2d4f03b5f41af8b74ae01ef520c33c40 100644 --- a/main/rerender_a_video.py +++ b/main/rerender_a_video.py @@ -607,7 +607,7 @@ class RerenderAVideoPipeline(StableDiffusionControlNetImg2ImgPipeline): latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/run_onnx_controlnet.py b/main/run_onnx_controlnet.py index 2b56e8a1e51b9437a048cb24e8ce728d5f1c3e92..2c631ae37ed78ba60300e094fe059712b738c69e 100644 --- a/main/run_onnx_controlnet.py +++ b/main/run_onnx_controlnet.py @@ -136,7 +136,7 @@ class OnnxStableDiffusionControlNetImg2ImgPipeline(DiffusionPipeline): prompt: Union[str, List[str]], num_images_per_prompt: Optional[int], do_classifier_free_guidance: bool, - negative_prompt: Optional[str], + negative_prompt: str | None, prompt_embeds: Optional[np.ndarray] = None, negative_prompt_embeds: Optional[np.ndarray] = None, ): @@ -534,7 +534,7 @@ class OnnxStableDiffusionControlNetImg2ImgPipeline(DiffusionPipeline): latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/run_tensorrt_controlnet.py b/main/run_tensorrt_controlnet.py index b62eb4f58e8f68c4f944e09773a07e571593dedf..23c13e6a501c93ec3d672b76b0e6d454a70a6a14 100644 --- a/main/run_tensorrt_controlnet.py +++ b/main/run_tensorrt_controlnet.py @@ -240,7 +240,7 @@ class TensorRTStableDiffusionControlNetImg2ImgPipeline(DiffusionPipeline): prompt: Union[str, List[str]], num_images_per_prompt: Optional[int], do_classifier_free_guidance: bool, - negative_prompt: Optional[str], + negative_prompt: str | None, prompt_embeds: Optional[np.ndarray] = None, negative_prompt_embeds: Optional[np.ndarray] = None, ): @@ -638,7 +638,7 @@ class TensorRTStableDiffusionControlNetImg2ImgPipeline(DiffusionPipeline): latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/scheduling_ufogen.py b/main/scheduling_ufogen.py index fada2636e98d64177e91fa52d4fbe35910811691..2d109ef36909b5cc6b7d9b973563bc64e4baecc8 100644 --- a/main/scheduling_ufogen.py +++ b/main/scheduling_ufogen.py @@ -377,7 +377,7 @@ class UFOGenScheduler(SchedulerMixin, ConfigMixin): model_output: torch.Tensor, timestep: int, sample: torch.Tensor, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, return_dict: bool = True, ) -> Union[UFOGenSchedulerOutput, Tuple]: """ diff --git a/main/sd_text2img_k_diffusion.py b/main/sd_text2img_k_diffusion.py index e351420f786a98b3a7e4183832bd4f657643406f..690182714cdee6838bc29524a0ba00454fafb7aa 100644 --- a/main/sd_text2img_k_diffusion.py +++ b/main/sd_text2img_k_diffusion.py @@ -285,9 +285,9 @@ class StableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/sde_drag.py b/main/sde_drag.py index 63899ce738bb614aaf5bcf127acbd8f56e4f6b74..0b654730fcc4acc6aac568b12d026272c79487d4 100644 --- a/main/sde_drag.py +++ b/main/sde_drag.py @@ -73,7 +73,7 @@ class SdeDragPipeline(DiffusionPipeline): image_scale: Optional[float] = 0.3, adapt_radius: Optional[int] = 5, min_lora_scale: Optional[float] = 0.5, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, ): r""" Function invoked when calling the pipeline for image editing. diff --git a/main/seed_resize_stable_diffusion.py b/main/seed_resize_stable_diffusion.py index eafe7572aab51278c1dafc4cce49280f6b91e905..373095fa2ca2f5a1ac0582f12a107f02a35d7b0f 100644 --- a/main/seed_resize_stable_diffusion.py +++ b/main/seed_resize_stable_diffusion.py @@ -80,9 +80,9 @@ class SeedResizeStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/speech_to_image_diffusion.py b/main/speech_to_image_diffusion.py index a8ec1620a2eb997e37cb6b0701ff9dc85650850b..695dca2465b4aef93555db9e88254524242922c7 100644 --- a/main/speech_to_image_diffusion.py +++ b/main/speech_to_image_diffusion.py @@ -75,9 +75,9 @@ class SpeechToImagePipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_comparison.py b/main/stable_diffusion_comparison.py index ce6e77c87ff07f74dccd9299c2c52b7eaa055384..8ce9c39227e72b9dc70d43672ec3d4cf030db09c 100644 --- a/main/stable_diffusion_comparison.py +++ b/main/stable_diffusion_comparison.py @@ -1,4 +1,4 @@ -from typing import Any, Callable, Dict, List, Optional, Union +from typing import Any, Callable, List, Optional, Union import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer @@ -81,7 +81,7 @@ class StableDiffusionComparisonPipeline(DiffusionPipeline, StableDiffusionMixin) self.register_modules(pipeline1=self.pipe1, pipeline2=self.pipe2, pipeline3=self.pipe3, pipeline4=self.pipe4) @property - def layers(self) -> Dict[str, Any]: + def layers(self) -> dict[str, Any]: return {k: getattr(self, k) for k in self.config.keys() if not k.startswith("_")} @torch.no_grad() @@ -95,9 +95,9 @@ class StableDiffusionComparisonPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -132,9 +132,9 @@ class StableDiffusionComparisonPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -169,9 +169,9 @@ class StableDiffusionComparisonPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -206,9 +206,9 @@ class StableDiffusionComparisonPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -243,9 +243,9 @@ class StableDiffusionComparisonPipeline(DiffusionPipeline, StableDiffusionMixin) negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_controlnet_img2img.py b/main/stable_diffusion_controlnet_img2img.py index aa116112be1cdcf66237b457bdd8c70e184c62cd..03c6fe7f6466608f9559ca998a78ea433db33710 100644 --- a/main/stable_diffusion_controlnet_img2img.py +++ b/main/stable_diffusion_controlnet_img2img.py @@ -614,7 +614,7 @@ class StableDiffusionControlNetImg2ImgPipeline(DiffusionPipeline, StableDiffusio latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_controlnet_inpaint.py b/main/stable_diffusion_controlnet_inpaint.py index 6d710e0d73c7f946b4519127d037a318274e686c..9b76faf56a8ae8e992608c6c5c29d4bdb445eedb 100644 --- a/main/stable_diffusion_controlnet_inpaint.py +++ b/main/stable_diffusion_controlnet_inpaint.py @@ -757,7 +757,7 @@ class StableDiffusionControlNetInpaintPipeline(DiffusionPipeline, StableDiffusio latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_controlnet_inpaint_img2img.py b/main/stable_diffusion_controlnet_inpaint_img2img.py index fcb5ed059bb4b5c404bba3432fdecc097e2162b3..299dad58707d7109709679b3968072c953398547 100644 --- a/main/stable_diffusion_controlnet_inpaint_img2img.py +++ b/main/stable_diffusion_controlnet_inpaint_img2img.py @@ -745,7 +745,7 @@ class StableDiffusionControlNetInpaintImg2ImgPipeline(DiffusionPipeline, StableD latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_controlnet_reference.py b/main/stable_diffusion_controlnet_reference.py index 74c81b63626df768e59c99ca23ddb11f7b14c5aa..18c79a0853f955f0435918557ab8b7602e34f4ec 100644 --- a/main/stable_diffusion_controlnet_reference.py +++ b/main/stable_diffusion_controlnet_reference.py @@ -119,7 +119,7 @@ class StableDiffusionControlNetReferencePipeline(StableDiffusionControlNetPipeli latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_ipex.py b/main/stable_diffusion_ipex.py index 4f545aa09dedf3584acfe51685ccdae8c0429902..ddc39b5b7b1a3c6ab74fca58ce7ea3c7d11c0b35 100644 --- a/main/stable_diffusion_ipex.py +++ b/main/stable_diffusion_ipex.py @@ -574,7 +574,7 @@ class StableDiffusionIPEXPipeline( latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_mega.py b/main/stable_diffusion_mega.py index c67ebc80b0061673b8eeb2026c28eb50d9c56aa9..a22ecb209ada116032e353e6b7c52d68008f7088 100644 --- a/main/stable_diffusion_mega.py +++ b/main/stable_diffusion_mega.py @@ -1,4 +1,4 @@ -from typing import Any, Callable, Dict, List, Optional, Union +from typing import Any, Callable, List, Optional, Union import PIL.Image import torch @@ -92,7 +92,7 @@ class StableDiffusionMegaPipeline(DiffusionPipeline, StableDiffusionMixin): self.register_to_config(requires_safety_checker=requires_safety_checker) @property - def components(self) -> Dict[str, Any]: + def components(self) -> dict[str, Any]: return {k: getattr(self, k) for k in self.config.keys() if not k.startswith("_")} @torch.no_grad() @@ -107,8 +107,8 @@ class StableDiffusionMegaPipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: Optional[float] = 0.0, - generator: Optional[torch.Generator] = None, - output_type: Optional[str] = "pil", + generator: torch.Generator | None = None, + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -141,8 +141,8 @@ class StableDiffusionMegaPipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: Optional[float] = 0.0, - generator: Optional[torch.Generator] = None, - output_type: Optional[str] = "pil", + generator: torch.Generator | None = None, + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, @@ -176,9 +176,9 @@ class StableDiffusionMegaPipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_reference.py b/main/stable_diffusion_reference.py index d0372bbeba656e6bbc1092c9d83bb5078d7723d9..7a32827a935024d846f6f07ae2e3ad2e8782f55d 100644 --- a/main/stable_diffusion_reference.py +++ b/main/stable_diffusion_reference.py @@ -276,7 +276,7 @@ class StableDiffusionReferencePipeline( height: int, width: int, callback_steps: Optional[int], - negative_prompt: Optional[str] = None, + negative_prompt: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[torch.Tensor] = None, @@ -291,7 +291,7 @@ class StableDiffusionReferencePipeline( height (int): The height of the input image. width (int): The width of the input image. callback_steps (Optional[int]): The number of steps to perform the callback on. - negative_prompt (Optional[str]): The negative prompt text. + negative_prompt (str | None): The negative prompt text. prompt_embeds (Optional[torch.Tensor]): The prompt embeddings. negative_prompt_embeds (Optional[torch.Tensor]): The negative prompt embeddings. ip_adapter_image (Optional[torch.Tensor]): The input adapter image. @@ -411,11 +411,11 @@ class StableDiffusionReferencePipeline( # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.encode_prompt def encode_prompt( self, - prompt: Optional[str], + prompt: str | None, device: torch.device, num_images_per_prompt: int, do_classifier_free_guidance: bool, - negative_prompt: Optional[str] = None, + negative_prompt: str | None = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, lora_scale: Optional[float] = None, @@ -642,7 +642,7 @@ class StableDiffusionReferencePipeline( # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.prepare_extra_step_kwargs def prepare_extra_step_kwargs( self, generator: Union[torch.Generator, List[torch.Generator]], eta: float - ) -> Dict[str, Any]: + ) -> dict[str, Any]: r""" Prepare extra keyword arguments for the scheduler step. @@ -834,7 +834,7 @@ class StableDiffusionReferencePipeline( latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_repaint.py b/main/stable_diffusion_repaint.py index b974e3c7ae744dc48c543186c16bd58e75c55462..7248e410120631fd8f06cbbc8e4e2d4d90e6be25 100644 --- a/main/stable_diffusion_repaint.py +++ b/main/stable_diffusion_repaint.py @@ -625,7 +625,7 @@ class StableDiffusionRepaintPipeline( latents: Optional[torch.Tensor] = None, prompt_embeds: Optional[torch.Tensor] = None, negative_prompt_embeds: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/stable_diffusion_xl_controlnet_reference.py b/main/stable_diffusion_xl_controlnet_reference.py index 421e67f5bba669423200f67f6c956b7758998e4c..a458ee7c65069ad04fca2e9fe47a00b64313648b 100644 --- a/main/stable_diffusion_xl_controlnet_reference.py +++ b/main/stable_diffusion_xl_controlnet_reference.py @@ -345,7 +345,7 @@ class StableDiffusionXLControlNetReferencePipeline(StableDiffusionXLControlNetPi negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, controlnet_conditioning_scale: Union[float, List[float]] = 1.0, diff --git a/main/stable_diffusion_xl_reference.py b/main/stable_diffusion_xl_reference.py index eb055574966d0ebc02332e8b3fbbaaa741d86046..c6be397144c530210ec0c1124c3c4725a6ea077e 100644 --- a/main/stable_diffusion_xl_reference.py +++ b/main/stable_diffusion_xl_reference.py @@ -290,7 +290,7 @@ class StableDiffusionXLReferencePipeline(StableDiffusionXLPipeline): negative_pooled_prompt_embeds: Optional[torch.Tensor] = None, ip_adapter_image: Optional[PipelineImageInput] = None, ip_adapter_image_embeds: Optional[List[torch.Tensor]] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, diff --git a/main/stable_unclip.py b/main/stable_unclip.py index f13c4e0a490bdc114eb2dbc3cb5ed9253912f965..22c3b8c6fe9c9eb36fa67e8bee8e80777c929a9c 100644 --- a/main/stable_unclip.py +++ b/main/stable_unclip.py @@ -190,7 +190,7 @@ class StableUnCLIPPipeline(DiffusionPipeline): width: Optional[int] = None, num_images_per_prompt: int = 1, prior_num_inference_steps: int = 25, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, prior_latents: Optional[torch.Tensor] = None, text_model_output: Optional[Union[CLIPTextModelOutput, Tuple]] = None, text_attention_mask: Optional[torch.Tensor] = None, @@ -199,7 +199,7 @@ class StableUnCLIPPipeline(DiffusionPipeline): decoder_num_inference_steps: int = 50, decoder_num_images_per_prompt: Optional[int] = 1, decoder_eta: float = 0.0, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ): if prompt is not None: diff --git a/main/text_inpainting.py b/main/text_inpainting.py index bdf9eca498e7f5167d9b2a6cfda40ae87c7cdc95..6df9570898830aa055be48459cfffba7c3cc1473 100644 --- a/main/text_inpainting.py +++ b/main/text_inpainting.py @@ -134,9 +134,9 @@ class TextInpainting(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/tiled_upscaling.py b/main/tiled_upscaling.py index 7a5e77155cd0b82363fcbb89c5c72fb0250b29d5..5fe67dce43d82d8b1204dafcd5f8788be1bd9c5a 100644 --- a/main/tiled_upscaling.py +++ b/main/tiled_upscaling.py @@ -192,7 +192,7 @@ class StableDiffusionTiledUpscalePipeline(StableDiffusionUpscalePipeline): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1, diff --git a/main/unclip_image_interpolation.py b/main/unclip_image_interpolation.py index 65b52578601e6310bc68e7a2a4146bf96eadcf7a..54e3a98139086e716d3c85cb7433bf8249d6e31b 100644 --- a/main/unclip_image_interpolation.py +++ b/main/unclip_image_interpolation.py @@ -216,7 +216,7 @@ class UnCLIPImageInterpolationPipeline(DiffusionPipeline): decoder_latents: Optional[torch.Tensor] = None, super_res_latents: Optional[torch.Tensor] = None, decoder_guidance_scale: float = 8.0, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ): """ diff --git a/main/unclip_text_interpolation.py b/main/unclip_text_interpolation.py index 6fd4f348f48de688c8c95d9c6137d7de47b22a79..e2478811a059219857f7b1280244e3cf39ccb5b4 100644 --- a/main/unclip_text_interpolation.py +++ b/main/unclip_text_interpolation.py @@ -225,7 +225,7 @@ class UnCLIPTextInterpolationPipeline(DiffusionPipeline): decoder_guidance_scale: float = 8.0, enable_sequential_cpu_offload=True, gpu_id=0, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, ): """ diff --git a/main/wildcard_stable_diffusion.py b/main/wildcard_stable_diffusion.py index d40221e5b1cffd7d5b14e8963df82f94139f100d..342913b1508e517a41e9334b6239e97111d3ea03 100644 --- a/main/wildcard_stable_diffusion.py +++ b/main/wildcard_stable_diffusion.py @@ -165,9 +165,9 @@ class WildcardStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin): negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, eta: float = 0.0, - generator: Optional[torch.Generator] = None, + generator: torch.Generator | None = None, latents: Optional[torch.Tensor] = None, - output_type: Optional[str] = "pil", + output_type: str | None = "pil", return_dict: bool = True, callback: Optional[Callable[[int, int, torch.Tensor], None]] = None, callback_steps: int = 1,