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add SD_VAE_DEFAULT

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Signed-off-by: vladmandic <mandic00@live.com>
This commit is contained in:
vladmandic
2026-01-04 17:55:01 +01:00
parent 11330c3b32
commit deb59c60fc
2 changed files with 9 additions and 6 deletions
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modules/processing_diffusers.py
+6 -5
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@@ -13,6 +13,7 @@ from modules.lora import lora_common
debug = os.environ.get('SD_DIFFUSERS_DEBUG', None) is not None
output_type = 'np' if os.environ.get('SD_VAE_DEFAULT', None) is not None else 'latent'
last_p = None
orig_pipeline = shared.sd_model
@@ -157,7 +158,7 @@ def process_base(p: processing.StableDiffusionProcessing):
denoising_start=0 if use_refiner_start else p.refiner_start if use_denoise_start else None,
denoising_end=p.refiner_start if use_refiner_start else 1 if use_denoise_start else None,
num_frames=getattr(p, 'frames', 1),
output_type='latent',
output_type=output_type,
clip_skip=p.clip_skip,
desc=desc,
)
@@ -307,7 +308,7 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
eta=shared.opts.scheduler_eta,
guidance_scale=p.image_cfg_scale if p.image_cfg_scale is not None else p.cfg_scale,
guidance_rescale=p.diffusers_guidance_rescale,
output_type='latent',
output_type=output_type,
clip_skip=p.clip_skip,
image=output.images,
strength=strength,
@@ -377,11 +378,11 @@ def process_refine(p: processing.StableDiffusionProcessing, output):
for i in range(len(output.images)):
image = output.images[i]
noise_level = round(350 * p.denoising_strength)
output_type = 'latent'
refiner_output_type = output_type
if 'Upscale' in shared.sd_refiner.__class__.__name__ or 'Flux' in shared.sd_refiner.__class__.__name__ or 'Kandinsky' in shared.sd_refiner.__class__.__name__:
image = processing_vae.vae_decode(latents=image, model=shared.sd_model, vae_type=p.vae_type, output_type='pil', width=p.width, height=p.height)
p.extra_generation_params['Noise level'] = noise_level
output_type = 'np'
refiner_output_type = 'np'
update_sampler(p, shared.sd_refiner, second_pass=True)
shared.opts.prompt_attention = 'fixed'
refiner_args = set_pipeline_args(
@@ -398,7 +399,7 @@ def process_refine(p: processing.StableDiffusionProcessing, output):
denoising_start=p.refiner_start if p.refiner_start > 0 and p.refiner_start < 1 else None,
denoising_end=1 if p.refiner_start > 0 and p.refiner_start < 1 else None,
image=image,
output_type=output_type,
output_type=refiner_output_type,
clip_skip=p.clip_skip,
prompt_attention='fixed',
desc='Refiner',