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quick taesd vae decode

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Vladimir Mandic
2023-08-09 09:34:59 +00:00
parent a77fa4c12e
commit e2b0d981ac
7 changed files with 24 additions and 15 deletions
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modules/processing_diffusers.py
+3 -6
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@@ -49,8 +49,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
decoded = torch.zeros((len(latents), 3, p.height, p.width), dtype=devices.dtype_vae, device=devices.device)
for i in range(len(output.images)):
decoded[i] = (sd_vae_taesd.decode(latents[i]) * 2.0) - 1.0
images = model.image_processor.postprocess(decoded, output_type=output_type)
return images
imgs = model.image_processor.postprocess(decoded, output_type=output_type)
return imgs
def set_pipeline_args(model, prompt: str, negative_prompt: str, prompt_2: typing.Optional[str] =None, negative_prompt_2: typing.Optional[str] = None, is_refiner: bool = False, **kwargs):
@@ -177,10 +177,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
return results
if shared.sd_refiner is None or not p.enable_hr:
if shared.opts.diffusers_taesd_vae_output:
output.images = taesd_vae_decode(output.images, shared.sd_model)
else:
output.images = vae_decode(output.images, shared.sd_model)
output.images = vae_decode(output.images, shared.sd_model) if p.full_quality else taesd_vae_decode(output.images, shared.sd_model)
if lora_state['active']:
unload_diffusers_lora()