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SDNQ fix VAE quant

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Disty0
2025-06-05 13:24:02 +03:00
parent 1c508fbda4
commit c7fb5b1690
1 changed files with 5 additions and 4 deletions
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modules/processing_vae.py
+5 -4
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@@ -125,10 +125,6 @@ def full_vae_decode(latents, model):
model.vae.orig_dtype = model.vae.dtype
model.vae = model.vae.to(dtype=torch.float32)
latents = latents.to(devices.device)
if getattr(model.vae, "post_quant_conv", None) is not None:
latents = latents.to(next(iter(model.vae.post_quant_conv.parameters())).dtype)
else:
latents = latents.to(model.vae.dtype)
# normalize latents
latents_mean = model.vae.config.get("latents_mean", None)
@@ -144,6 +140,11 @@ def full_vae_decode(latents, model):
if shift_factor:
latents = latents + shift_factor
if getattr(model.vae, "post_quant_conv", None) is not None and "VAE" not in shared.opts.sdnq_quantize_weights:
latents = latents.to(next(iter(model.vae.post_quant_conv.parameters())).dtype)
else:
latents = latents.to(model.vae.dtype)
log_debug(f'VAE config: {model.vae.config}')
try:
with devices.inference_context():