comfyanonymous/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2026-03-14 01:29:58 +00:00
Code Issues Packages Projects Releases Wiki Activity

Support the LTXV 2 model. (#11632)

Browse Source
This commit is contained in:
comfyanonymous
2026-01-04 22:58:59 -08:00
committed by GitHub
parent 38d0493825
commit f2b002372b
23 changed files with 4214 additions and 185 deletions
Download Patch File Download Diff File Expand all files Collapse all files

57
comfy/model_base.py
View File

@@ -20,6 +20,7 @@ import comfy.ldm.hunyuan3dv2_1
import comfy.ldm.hunyuan3dv2_1.hunyuandit
import torch
import logging
import comfy.ldm.lightricks.av_model
from comfy.ldm.modules.diffusionmodules.openaimodel import UNetModel, Timestep
from comfy.ldm.cascade.stage_c import StageC
from comfy.ldm.cascade.stage_b import StageB
@@ -946,7 +947,7 @@ class GenmoMochi(BaseModel):
class LTXV(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLUX, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.lightricks.model.LTXVModel) #TODO
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.lightricks.model.LTXVModel)
def extra_conds(self, **kwargs):
out = super().extra_conds(**kwargs)
@@ -977,6 +978,60 @@ class LTXV(BaseModel):
def scale_latent_inpaint(self, sigma, noise, latent_image, **kwargs):
return latent_image
class LTXAV(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLUX, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.lightricks.av_model.LTXAVModel) #TODO
def extra_conds(self, **kwargs):
out = super().extra_conds(**kwargs)
attention_mask = kwargs.get("attention_mask", None)
if attention_mask is not None:
out['attention_mask'] = comfy.conds.CONDRegular(attention_mask)
cross_attn = kwargs.get("cross_attn", None)
if cross_attn is not None:
out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn)
out['frame_rate'] = comfy.conds.CONDConstant(kwargs.get("frame_rate", 25))
denoise_mask = kwargs.get("concat_mask", kwargs.get("denoise_mask", None))
audio_denoise_mask = None
if denoise_mask is not None and "latent_shapes" in kwargs:
denoise_mask = utils.unpack_latents(denoise_mask, kwargs["latent_shapes"])
if len(denoise_mask) > 1:
audio_denoise_mask = denoise_mask[1]
denoise_mask = denoise_mask[0]
if denoise_mask is not None:
out["denoise_mask"] = comfy.conds.CONDRegular(denoise_mask)
if audio_denoise_mask is not None:
out["audio_denoise_mask"] = comfy.conds.CONDRegular(audio_denoise_mask)
keyframe_idxs = kwargs.get("keyframe_idxs", None)
if keyframe_idxs is not None:
out['keyframe_idxs'] = comfy.conds.CONDRegular(keyframe_idxs)
latent_shapes = kwargs.get("latent_shapes", None)
if latent_shapes is not None:
out['latent_shapes'] = comfy.conds.CONDConstant(latent_shapes)
return out
def process_timestep(self, timestep, x, denoise_mask=None, audio_denoise_mask=None, **kwargs):
v_timestep = timestep
a_timestep = timestep
if denoise_mask is not None:
v_timestep = self.diffusion_model.patchifier.patchify(((denoise_mask) * timestep.view([timestep.shape[0]] + [1] * (denoise_mask.ndim - 1)))[:, :1])[0]
if audio_denoise_mask is not None:
a_timestep = self.diffusion_model.a_patchifier.patchify(((audio_denoise_mask) * timestep.view([timestep.shape[0]] + [1] * (audio_denoise_mask.ndim - 1)))[:, :1, :, :1])[0]
return v_timestep, a_timestep
def scale_latent_inpaint(self, sigma, noise, latent_image, **kwargs):
return latent_image
class HunyuanVideo(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLOW, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.hunyuan_video.model.HunyuanVideo)