CodeCow/stable-diffusion-webui-forge
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latent

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This commit is contained in:
Haoming 2026-06-08 00:26:39 +08:00
parent 1a369d126e
commit 94b60c876f
1 changed files with 12 additions and 10 deletions
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22
backend/diffusion_engine/pid.py
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@ -22,16 +22,19 @@ class PiD(ForgeDiffusionEngine):
clip = CLIP(model_dict={"gemma2": huggingface_components["text_encoder"]}, tokenizer_dict={"gemma2": huggingface_components["tokenizer"]})
_vae: torch.nn.Module = huggingface_components["vae"]
ae: torch.nn.Module = huggingface_components["vae"]
if _wan := isinstance(_vae, WanVAE):
_vae.latent_format = latent.Wan21()
if _f2 := isinstance(_vae, AutoencoderKLFlux2):
_vae.latent_format = latent.Flux2()
if isinstance(_vae, IntegratedAutoencoderKL):
_vae.latent_format = latent.SDXL() if _vae.embed_dim == 4 else latent.Flux()
if is_wan := type(ae) is WanVAE:
ae.latent_format = latent.Wan21()
if is_flux2 := type(ae) is AutoencoderKLFlux2:
ae.latent_format = latent.Flux2()
if type(ae) is IntegratedAutoencoderKL:
if ae.embed_dim == 4:
ae.latent_format = latent.SDXL()
if ae.embed_dim == 16:
ae.latent_format = latent.Flux()
vae = VAE(model=_vae, is_wan=_wan, is_flux2=_f2)
vae = VAE(model=ae, is_wan=is_wan, is_flux2=is_flux2)
k_predictor = PredictionDiscreteFlow(estimated_config)
@ -67,8 +70,7 @@ class PiD(ForgeDiffusionEngine):
sample = self.forge_objects.vae.encode(x.movedim(1, -1) * 0.5 + 0.5)
sample = self.forge_objects.vae.first_stage_model.process_in(sample)
if sample.ndim == 5:
sample = sample[:, :, 0]
sample = sample.squeeze(2)
dynamic_args.lq_latent = (sample, torch.tensor([float(self.degrade_sigma)], dtype=torch.float32))
return None