diff --git a/modules/sd_checkpoint.py b/modules/sd_checkpoint.py index c861fcf12..f16909b52 100644 --- a/modules/sd_checkpoint.py +++ b/modules/sd_checkpoint.py @@ -160,7 +160,7 @@ def list_models(): checkpoints_list = dict(sorted(checkpoints_list.items(), key=lambda cp: cp[1].filename)) -def update_model_hashes(model_list: dict = None, model_type: str = 'checkpoint'): +def update_model_hashes(model_list: dict | None = None, model_type: str = 'checkpoint'): def update_model_hashes_table(rows): html = """ diff --git a/pipelines/bria/bria_pipeline.py b/pipelines/bria/bria_pipeline.py index beec4e2dc..6049e3f45 100644 --- a/pipelines/bria/bria_pipeline.py +++ b/pipelines/bria/bria_pipeline.py @@ -237,11 +237,11 @@ class BriaPipeline(FluxPipeline): @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 30, - timesteps: List[int] = None, + timesteps: List[int] | None = None, guidance_scale: float = 5, negative_prompt: Optional[Union[str, List[str]]] = None, num_images_per_prompt: Optional[int] = 1, diff --git a/pipelines/bria/bria_utils.py b/pipelines/bria/bria_utils.py index 3cddeafa1..5aed654c2 100644 --- a/pipelines/bria/bria_utils.py +++ b/pipelines/bria/bria_utils.py @@ -99,7 +99,7 @@ def get_by_t5_prompt_embeds( def get_t5_prompt_embeds( tokenizer: T5TokenizerFast , text_encoder: T5EncoderModel, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, num_images_per_prompt: int = 1, max_sequence_length: int = 128, device: Optional[torch.device] = None, @@ -184,7 +184,7 @@ def get_env_prefix(): def compute_density_for_timestep_sampling( - weighting_scheme: str, batch_size: int, logit_mean: float = None, logit_std: float = None, mode_scale: float = None + weighting_scheme: str, batch_size: int, logit_mean: float | None = None, logit_std: float | None = None, mode_scale: float | None = None ): """Compute the density for sampling the timesteps when doing SD3 training. @@ -236,7 +236,7 @@ def get_clip_prompt_embeds( text_encoder_2: CLIPTextModelWithProjection, tokenizer: CLIPTokenizer, tokenizer_2: CLIPTokenizer, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, num_images_per_prompt: int = 1, max_sequence_length: int = 77, device: Optional[torch.device] = None, diff --git a/pipelines/bria/transformer_bria.py b/pipelines/bria/transformer_bria.py index f75cde912..1378a8e16 100644 --- a/pipelines/bria/transformer_bria.py +++ b/pipelines/bria/transformer_bria.py @@ -82,7 +82,7 @@ class BriaTransformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, FromOrig attention_head_dim: int = 128, num_attention_heads: int = 24, joint_attention_dim: int = 4096, - pooled_projection_dim: int = None, + pooled_projection_dim: int | None = None, guidance_embeds: bool = False, axes_dims_rope: List[int] = [16, 56, 56], rope_theta = 10000, diff --git a/pipelines/flex2/__init__.py b/pipelines/flex2/__init__.py index dbb8e2a0d..1ba0a2eba 100644 --- a/pipelines/flex2/__init__.py +++ b/pipelines/flex2/__init__.py @@ -60,7 +60,7 @@ class Flex2Pipeline(FluxControlPipeline): @torch.no_grad() def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, inpaint_image: Optional[PipelineImageInput] = None, inpaint_mask: Optional[PipelineImageInput] = None, diff --git a/pipelines/hidream/pipeline_hidream_image_editing.py b/pipelines/hidream/pipeline_hidream_image_editing.py index c410ec8ac..09cdc4b26 100644 --- a/pipelines/hidream/pipeline_hidream_image_editing.py +++ b/pipelines/hidream/pipeline_hidream_image_editing.py @@ -210,7 +210,7 @@ class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoaderMixin def _get_t5_prompt_embeds( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, max_sequence_length: int = 128, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, @@ -284,7 +284,7 @@ class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoaderMixin def _get_llama3_prompt_embeds( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, max_sequence_length: int = 128, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, @@ -760,7 +760,7 @@ class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoaderMixin @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, prompt_3: Optional[Union[str, List[str]]] = None, prompt_4: Optional[Union[str, List[str]]] = None, diff --git a/pipelines/model_hyimage.py b/pipelines/model_hyimage.py index 307b31d58..4cf9776ee 100644 --- a/pipelines/model_hyimage.py +++ b/pipelines/model_hyimage.py @@ -81,8 +81,8 @@ class HunyuanImage3Wrapper(torch.nn.Module): def __call__( self, prompt: str, - height: int = None, - width: int = None, + height: int | None = None, + width: int | None = None, num_inference_steps: int = 50, num_images_per_prompt: int = 1, guidance_scale: float = 7.5, diff --git a/pipelines/wan/wan_image.py b/pipelines/wan/wan_image.py index bd9923e5b..254ed2fba 100644 --- a/pipelines/wan/wan_image.py +++ b/pipelines/wan/wan_image.py @@ -10,8 +10,8 @@ from modules import devices class WanImagePipeline(diffusers.WanPipeline): def __call__( self, - prompt: Union[str, List[str]] = None, - negative_prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, + negative_prompt: Union[str, List[str]] | None = None, height: int = 480, width: int = 832, num_frames: int = 81, diff --git a/scripts/ctrlx/__init__.py b/scripts/ctrlx/__init__.py index 07d06aeac..8f464c35a 100644 --- a/scripts/ctrlx/__init__.py +++ b/scripts/ctrlx/__init__.py @@ -136,13 +136,13 @@ class CtrlXStableDiffusionXLPipeline(StableDiffusionXLPipeline): # diffusers==0 @torch.no_grad() def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, structure_prompt: Optional[Union[str, List[str]]] = None, appearance_prompt: Optional[Union[str, List[str]]] = None, structure_image: Optional[PipelineImageInput] = None, appearance_image: Optional[PipelineImageInput] = None, num_inference_steps: int = 50, - timesteps: List[int] = None, + timesteps: List[int] | None = None, negative_prompt: Optional[Union[str, List[str]]] = None, positive_prompt: Optional[Union[str, List[str]]] = None, height: Optional[int] = None, @@ -172,9 +172,9 @@ class CtrlXStableDiffusionXLPipeline(StableDiffusionXLPipeline): # diffusers==0 return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, - original_size: Tuple[int, int] = None, + original_size: Tuple[int, int] | None = None, crops_coords_top_left: Tuple[int, int] = (0, 0), - target_size: Tuple[int, int] = None, + target_size: Tuple[int, int] | None = None, clip_skip: Optional[int] = None, callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None, callback_on_step_end_tensor_inputs: List[str] = ["latents"], diff --git a/scripts/demofusion.py b/scripts/demofusion.py index f27163900..c6bdb046f 100644 --- a/scripts/demofusion.py +++ b/scripts/demofusion.py @@ -498,7 +498,7 @@ class DemoFusionSDXLPipeline(DiffusionPipeline, FromSingleFileMixin, LoraLoaderM @torch.no_grad() def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, height: Optional[int] = None, width: Optional[int] = None, diff --git a/scripts/differential_diffusion.py b/scripts/differential_diffusion.py index acb9ca0b8..24aa844b6 100644 --- a/scripts/differential_diffusion.py +++ b/scripts/differential_diffusion.py @@ -631,7 +631,7 @@ class StableDiffusionXLDiffImg2ImgPipeline(DiffusionPipeline, FromSingleFileMixi @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, image: Union[ torch.FloatTensor, @@ -662,9 +662,9 @@ class StableDiffusionXLDiffImg2ImgPipeline(DiffusionPipeline, FromSingleFileMixi callback_steps: int = 1, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, - original_size: Tuple[int, int] = None, + original_size: Tuple[int, int] | None = None, crops_coords_top_left: Tuple[int, int] = (0, 0), - target_size: Tuple[int, int] = None, + target_size: Tuple[int, int] | None = None, aesthetic_score: float = 6.0, negative_aesthetic_score: float = 2.5, map: torch.FloatTensor = None, # pylint: disable=redefined-builtin @@ -1643,7 +1643,7 @@ class StableDiffusionDiffImg2ImgPipeline(DiffusionPipeline): @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, image: Union[torch.FloatTensor, PIL.Image.Image] = None, strength: float = 1, num_inference_steps: Optional[int] = 50, diff --git a/scripts/infiniteyou/pipeline_flux_infusenet.py b/scripts/infiniteyou/pipeline_flux_infusenet.py index 38fa186f9..aa90cef72 100644 --- a/scripts/infiniteyou/pipeline_flux_infusenet.py +++ b/scripts/infiniteyou/pipeline_flux_infusenet.py @@ -113,12 +113,12 @@ class FluxInfuseNetPipeline(FluxControlNetPipeline): @torch.no_grad() def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 28, - timesteps: List[int] = None, + timesteps: List[int] | None = None, guidance_scale: float = 3.5, id_image: PipelineImageInput = None, controlnet_guidance_scale: float = 1.0, diff --git a/scripts/infiniteyou_ext.py b/scripts/infiniteyou_ext.py index 2ac97fc72..af844f1da 100644 --- a/scripts/infiniteyou_ext.py +++ b/scripts/infiniteyou_ext.py @@ -60,7 +60,7 @@ class Script(scripts_manager.Script): return [model, id_image, control_image, scale, start, end, id_guidance, control_guidance, restore] def run(self, p: processing.StableDiffusionProcessing, - model: str = None, + model: str | None = None, id_image: Image.Image = None, control_image: Image.Image = None, scale: float = 1.0, diff --git a/scripts/mod/__init__.py b/scripts/mod/__init__.py index db9445b8c..e23547dfb 100644 --- a/scripts/mod/__init__.py +++ b/scripts/mod/__init__.py @@ -779,7 +779,7 @@ class StableDiffusionXLTilingPipeline( @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 50, diff --git a/scripts/nudenet/imageguard.py b/scripts/nudenet/imageguard.py index f8747c416..068d21133 100644 --- a/scripts/nudenet/imageguard.py +++ b/scripts/nudenet/imageguard.py @@ -93,7 +93,7 @@ model = None processor = None -def image_guard(image, policy:str=None) -> str: +def image_guard(image, policy:str | None=None) -> str: global model, processor # pylint: disable=global-statement import json from installer import install diff --git a/scripts/pixelsmith/pixelsmith_pipeline.py b/scripts/pixelsmith/pixelsmith_pipeline.py index 474fcd4e8..7f3116510 100644 --- a/scripts/pixelsmith/pixelsmith_pipeline.py +++ b/scripts/pixelsmith/pixelsmith_pipeline.py @@ -1088,12 +1088,12 @@ class PixelSmithXLPipeline( @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, height: Optional[int] = None, width: Optional[int] = None, num_inference_steps: int = 50, - timesteps: List[int] = None, + timesteps: List[int] | None = None, denoising_end: Optional[float] = None, guidance_scale: float = 5.0, #+# @@ -1101,7 +1101,7 @@ class PixelSmithXLPipeline( pag_adaptive_scaling: float = 0.0, pag_drop_rate: float = 0.5, pag_applied_layers: List[str] = ['mid'], #['down', 'mid', 'up'] - pag_applied_layers_index: List[str] = None, #['d4', 'd5', 'm0'] + pag_applied_layers_index: List[str] | None = None, #['d4', 'd5', 'm0'] #+# negative_prompt: Optional[Union[str, List[str]]] = None, negative_prompt_2: Optional[Union[str, List[str]]] = None, diff --git a/scripts/prompt_enhance.py b/scripts/prompt_enhance.py index b15f8ff7d..b702eb3b7 100644 --- a/scripts/prompt_enhance.py +++ b/scripts/prompt_enhance.py @@ -321,7 +321,7 @@ class Script(scripts_manager.Script): from modules.sd_models_compile import compile_torch self.llm = compile_torch(self.llm, apply_to_components=False, op="LLM") - def load(self, name:str=None, model_repo:str=None, model_gguf:str=None, model_type:str=None, model_file:str=None): + def load(self, name:str | None=None, model_repo:str | None=None, model_gguf:str | None=None, model_type:str | None=None, model_file:str | None=None): # Strip symbols from display name if present name = get_model_repo_from_display(name) if name else self.options.default if self.busy: @@ -535,21 +535,21 @@ class Script(scripts_manager.Script): return current_image def enhance(self, - model: str=None, - prompt:str=None, - system:str=None, - prefix:str=None, - suffix:str=None, - sample:bool=None, - tokens:int=None, - temperature:float=None, - penalty:float=None, - top_k:int=None, - top_p:float=None, + model: str | None=None, + prompt:str | None=None, + system:str | None=None, + prefix:str | None=None, + suffix:str | None=None, + sample:bool | None=None, + tokens:int | None=None, + temperature:float | None=None, + penalty:float | None=None, + top_k:int | None=None, + top_p:float | None=None, thinking:bool=False, seed:int=-1, image=None, - nsfw:bool=None, + nsfw:bool | None=None, use_vision:bool=True, prefill:str='', keep_prefill:bool=False, diff --git a/scripts/softfill.py b/scripts/softfill.py index 24cbfbacc..6eb8c0fe2 100644 --- a/scripts/softfill.py +++ b/scripts/softfill.py @@ -928,14 +928,14 @@ class StableDiffusionXLSoftFillPipeline( @replace_example_docstring(EXAMPLE_DOC_STRING) def __call__( self, - prompt: Union[str, List[str]] = None, + prompt: Union[str, List[str]] | None = None, prompt_2: Optional[Union[str, List[str]]] = None, image: Image.Image = None, mask: Image.Image = None, noise_fill_image: bool = True, # Adds noise to the image at the masks >0.8 area. strength: float = 0.3, num_inference_steps: int = 50, - timesteps: List[int] = None, + timesteps: List[int] | None = None, denoising_start: Optional[float] = None, denoising_end: Optional[float] = None, guidance_scale: float = 5.0, @@ -955,9 +955,9 @@ class StableDiffusionXLSoftFillPipeline( return_dict: bool = True, cross_attention_kwargs: Optional[Dict[str, Any]] = None, guidance_rescale: float = 0.0, - original_size: Tuple[int, int] = None, + original_size: Tuple[int, int] | None = None, crops_coords_top_left: Tuple[int, int] = (0, 0), - target_size: Tuple[int, int] = None, + target_size: Tuple[int, int] | None = None, negative_original_size: Optional[Tuple[int, int]] = None, negative_crops_coords_top_left: Tuple[int, int] = (0, 0), negative_target_size: Optional[Tuple[int, int]] = None,