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fix pipeline args

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This commit is contained in:
霜洁
2026-04-14 10:11:09 +08:00
parent 224060c2a0
commit 9654ec3c65
6 changed files with 102 additions and 102 deletions
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2
diffsynth/pipelines/flux2_image.py
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@@ -83,7 +83,7 @@ class Flux2ImagePipeline(BasePipeline):
input_image: Image.Image = None,
denoising_strength: float = 1.0,
# Edit
edit_image: Union[Image.Image, List[Image.Image]] = None,
edit_image: List[Image.Image] = None,
edit_image_auto_resize: bool = True,
# Shape
height: int = 1024,

6
diffsynth/pipelines/flux_image.py
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@@ -200,9 +200,9 @@ class FluxImagePipeline(BasePipeline):
# Steps
num_inference_steps: int = 30,
# local prompts
multidiffusion_prompts=(),
multidiffusion_masks=(),
multidiffusion_scales=(),
multidiffusion_prompts:tuple[str] =(),
multidiffusion_masks:tuple[str]=(),
multidiffusion_scales:tuple[str]=(),
# Kontext
kontext_images: Union[list[Image.Image], Image.Image] = None,
# ControlNet

56
diffsynth/pipelines/ltx2_audio_video.py
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@@ -170,45 +170,45 @@ class LTX2AudioVideoPipeline(BasePipeline):
self,
# Prompt
prompt: str,
negative_prompt: Optional[str] = "",
negative_prompt: str = "",
denoising_strength: float = 1.0,
# Image-to-video
input_images: Optional[list[Image.Image]] = None,
input_images_indexes: Optional[list[int]] = [0],
input_images_strength: Optional[float] = 1.0,
input_images: list[Image.Image] = None,
input_images_indexes: list[int] = [0],
input_images_strength: float = 1.0,
# In-Context Video Control
in_context_videos: Optional[list[list[Image.Image]]] = None,
in_context_downsample_factor: Optional[int] = 2,
in_context_videos: list[list[Image.Image]] = None,
in_context_downsample_factor: int = 2,
# Video-to-video
retake_video: Optional[list[Image.Image]] = None,
retake_video_regions: Optional[list[tuple[float, float]]] = None,
retake_video: list[Image.Image] = None,
retake_video_regions: list[tuple[float, float]] = None,
# Audio-to-video
retake_audio: Optional[torch.Tensor] = None,
audio_sample_rate: Optional[int] = 48000,
retake_audio_regions: Optional[list[tuple[float, float]]] = None,
retake_audio: torch.Tensor = None,
audio_sample_rate: int = 48000,
retake_audio_regions: list[tuple[float, float]] = None,
# Randomness
seed: Optional[int] = None,
rand_device: Optional[str] = "cpu",
seed: int = None,
rand_device: str = "cpu",
# Shape
height: Optional[int] = 512,
width: Optional[int] = 768,
num_frames: Optional[int] = 121,
frame_rate: Optional[int] = 24,
height: int = 512,
width: int = 768,
num_frames: int = 121,
frame_rate: int = 24,
# Classifier-free guidance
cfg_scale: Optional[float] = 3.0,
cfg_scale: float = 3.0,
# Scheduler
num_inference_steps: Optional[int] = 30,
num_inference_steps: int = 30,
# VAE tiling
tiled: Optional[bool] = True,
tile_size_in_pixels: Optional[int] = 512,
tile_overlap_in_pixels: Optional[int] = 128,
tile_size_in_frames: Optional[int] = 128,
tile_overlap_in_frames: Optional[int] = 24,
tiled: bool = True,
tile_size_in_pixels: int = 512,
tile_overlap_in_pixels: int = 128,
tile_size_in_frames: int = 128,
tile_overlap_in_frames: int = 24,
# Special Pipelines
use_two_stage_pipeline: Optional[bool] = False,
stage2_spatial_upsample_factor: Optional[int] = 2,
clear_lora_before_state_two: Optional[bool] = False,
use_distilled_pipeline: Optional[bool] = False,
use_two_stage_pipeline: bool = False,
stage2_spatial_upsample_factor: int = 2,
clear_lora_before_state_two: bool = False,
use_distilled_pipeline: bool = False,
# progress_bar
progress_bar_cmd=tqdm,
):

34
diffsynth/pipelines/mova_audio_video.py
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@@ -116,32 +116,32 @@ class MovaAudioVideoPipeline(BasePipeline):
self,
# Prompt
prompt: str,
negative_prompt: Optional[str] = "",
negative_prompt: str = "",
# Image-to-video
input_image: Optional[Image.Image] = None,
input_image: Image.Image = None,
# First-last-frame-to-video
end_image: Optional[Image.Image] = None,
end_image: Image.Image = None,
# Video-to-video
denoising_strength: Optional[float] = 1.0,
denoising_strength: float = 1.0,
# Randomness
seed: Optional[int] = None,
rand_device: Optional[str] = "cpu",
seed: int = None,
rand_device: str = "cpu",
# Shape
height: Optional[int] = 352,
width: Optional[int] = 640,
num_frames: Optional[int] = 81,
frame_rate: Optional[int] = 24,
height: int = 352,
width: int = 640,
num_frames: int = 81,
frame_rate: int = 24,
# Classifier-free guidance
cfg_scale: Optional[float] = 5.0,
cfg_scale: float = 5.0,
# Boundary
switch_DiT_boundary: Optional[float] = 0.9,
switch_DiT_boundary: float = 0.9,
# Scheduler
num_inference_steps: Optional[int] = 50,
sigma_shift: Optional[float] = 5.0,
num_inference_steps: int = 50,
sigma_shift: float = 5.0,
# VAE tiling
tiled: Optional[bool] = True,
tile_size: Optional[tuple[int, int]] = (30, 52),
tile_stride: Optional[tuple[int, int]] = (15, 26),
tiled: bool = True,
tile_size: tuple[int, int] = (30, 52),
tile_stride: tuple[int, int] = (15, 26),
# progress_bar
progress_bar_cmd=tqdm,
):

104
diffsynth/pipelines/wan_video.py
View File

@@ -191,81 +191,81 @@ class WanVideoPipeline(BasePipeline):
self,
# Prompt
prompt: str,
negative_prompt: Optional[str] = "",
negative_prompt: str = "",
# Image-to-video
input_image: Optional[Image.Image] = None,
input_image: Image.Image = None,
# First-last-frame-to-video
end_image: Optional[Image.Image] = None,
end_image: Image.Image = None,
# Video-to-video
input_video: Optional[list[Image.Image]] = None,
denoising_strength: Optional[float] = 1.0,
input_video: list[Image.Image] = None,
denoising_strength: float = 1.0,
# Speech-to-video
input_audio: Optional[np.array] = None,
audio_embeds: Optional[torch.Tensor] = None,
audio_sample_rate: Optional[int] = 16000,
s2v_pose_video: Optional[list[Image.Image]] = None,
s2v_pose_latents: Optional[torch.Tensor] = None,
motion_video: Optional[list[Image.Image]] = None,
input_audio: np.array = None,
audio_embeds: torch.Tensor = None,
audio_sample_rate: int = 16000,
s2v_pose_video: list[Image.Image] = None,
s2v_pose_latents: torch.Tensor = None,
motion_video: list[Image.Image] = None,
# ControlNet
control_video: Optional[list[Image.Image]] = None,
reference_image: Optional[Image.Image] = None,
control_video: list[Image.Image] = None,
reference_image: Image.Image = None,
# Camera control
camera_control_direction: Optional[Literal["Left", "Right", "Up", "Down", "LeftUp", "LeftDown", "RightUp", "RightDown"]] = None,
camera_control_speed: Optional[float] = 1/54,
camera_control_origin: Optional[tuple] = (0, 0.532139961, 0.946026558, 0.5, 0.5, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0),
camera_control_direction: Literal["Left", "Right", "Up", "Down", "LeftUp", "LeftDown", "RightUp", "RightDown"] = None,
camera_control_speed: float = 1/54,
camera_control_origin: tuple = (0, 0.532139961, 0.946026558, 0.5, 0.5, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0),
# VACE
vace_video: Optional[list[Image.Image]] = None,
vace_video_mask: Optional[Image.Image] = None,
vace_reference_image: Optional[Image.Image] = None,
vace_scale: Optional[float] = 1.0,
vace_video: list[Image.Image] = None,
vace_video_mask: Image.Image = None,
vace_reference_image: Image.Image = None,
vace_scale: float = 1.0,
# Animate
animate_pose_video: Optional[list[Image.Image]] = None,
animate_face_video: Optional[list[Image.Image]] = None,
animate_inpaint_video: Optional[list[Image.Image]] = None,
animate_mask_video: Optional[list[Image.Image]] = None,
animate_pose_video: list[Image.Image] = None,
animate_face_video: list[Image.Image] = None,
animate_inpaint_video: list[Image.Image] = None,
animate_mask_video: list[Image.Image] = None,
# VAP
vap_video: Optional[list[Image.Image]] = None,
vap_prompt: Optional[str] = " ",
negative_vap_prompt: Optional[str] = " ",
vap_video: list[Image.Image] = None,
vap_prompt: str = " ",
negative_vap_prompt: str = " ",
# Randomness
seed: Optional[int] = None,
rand_device: Optional[str] = "cpu",
seed: int = None,
rand_device: str = "cpu",
# Shape
height: Optional[int] = 480,
width: Optional[int] = 832,
num_frames=81,
height: int = 480,
width: int = 832,
num_frames: int = 81,
# Classifier-free guidance
cfg_scale: Optional[float] = 5.0,
cfg_merge: Optional[bool] = False,
cfg_scale: float = 5.0,
cfg_merge: bool = False,
# Boundary
switch_DiT_boundary: Optional[float] = 0.875,
switch_DiT_boundary: float = 0.875,
# Scheduler
num_inference_steps: Optional[int] = 50,
sigma_shift: Optional[float] = 5.0,
num_inference_steps: int = 50,
sigma_shift: float = 5.0,
# Speed control
motion_bucket_id: Optional[int] = None,
motion_bucket_id: int = None,
# LongCat-Video
longcat_video: Optional[list[Image.Image]] = None,
longcat_video: list[Image.Image] = None,
# VAE tiling
tiled: Optional[bool] = True,
tile_size: Optional[tuple[int, int]] = (30, 52),
tile_stride: Optional[tuple[int, int]] = (15, 26),
tiled: bool = True,
tile_size: tuple[int, int] = (30, 52),
tile_stride: tuple[int, int] = (15, 26),
# Sliding window
sliding_window_size: Optional[int] = None,
sliding_window_stride: Optional[int] = None,
sliding_window_size: int = None,
sliding_window_stride: int = None,
# Teacache
tea_cache_l1_thresh: Optional[float] = None,
tea_cache_model_id: Optional[str] = "",
tea_cache_l1_thresh: float = None,
tea_cache_model_id: str = "",
# WanToDance
wantodance_music_path: Optional[str] = None,
wantodance_reference_image: Optional[Image.Image] = None,
wantodance_fps: Optional[float] = 30,
wantodance_keyframes: Optional[list[Image.Image]] = None,
wantodance_keyframes_mask: Optional[list[int]] = None,
wantodance_music_path: str = None,
wantodance_reference_image: Image.Image = None,
wantodance_fps: float = 30,
wantodance_keyframes: list[Image.Image] = None,
wantodance_keyframes_mask: list[int] = None,
framewise_decoding: bool = False,
# progress_bar
progress_bar_cmd=tqdm,
output_type: Optional[Literal["quantized", "floatpoint"]] = "quantized",
output_type: Literal["quantized", "floatpoint"] = "quantized",
):
# Scheduler
self.scheduler.set_timesteps(num_inference_steps, denoising_strength=denoising_strength, shift=sigma_shift)