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Fix Wan I2V Quality #11087

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Merged
merged 5 commits into from
Mar 17, 2025
Merged

Fix Wan I2V Quality #11087

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566a915
fix_wan_i2v_quality
chengzeyi Mar 17, 2025
482415c
Update src/diffusers/pipelines/wan/pipeline_wan_i2v.py
chengzeyi Mar 17, 2025
c01d2bf
Update src/diffusers/pipelines/wan/pipeline_wan_i2v.py
chengzeyi Mar 17, 2025
ac15382
Update src/diffusers/pipelines/wan/pipeline_wan_i2v.py
chengzeyi Mar 17, 2025
378e412
Update pipeline_wan_i2v.py
hlky Mar 17, 2025
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6 changes: 4 additions & 2 deletions src/diffusers/pipelines/wan/pipeline_wan_i2v.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,9 +113,11 @@ def retrieve_latents(
latents_mean: torch.Tensor,
latents_std: torch.Tensor,
generator: Optional[torch.Generator] = None,
sample_mode: str = "sample",
sample_mode: str = "none",
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I think this is actually should be same as sample_mode == "argmax" , no?

diffusers/src/diffusers/models/autoencoders/vae.py

Line 743 in 1001425

def mode(self) -> torch.Tensor:

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Yeah, I think it is just without any extra computation cost.

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got it, let's :

  1. still use sample_mode="argmax" so that this is argument is consistent acorss all pipelines
  2. remove the code that's not needed for wan (I think all of the other mode lol

):
if hasattr(encoder_output, "latent_dist") and sample_mode == "sample":
if hasattr(encoder_output, "latent_dist") and sample_mode == "none":
return (encoder_output.latent_dist.mean - latents_mean) * latents_std
elif hasattr(encoder_output, "latent_dist") and sample_mode == "sample":
encoder_output.latent_dist.mean = (encoder_output.latent_dist.mean - latents_mean) * latents_std
encoder_output.latent_dist.logvar = torch.clamp(
(encoder_output.latent_dist.logvar - latents_mean) * latents_std, -30.0, 20.0
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