fix: guard rescale_noise_cfg against zero std_cfg to prevent NaN propagation - #14334
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fix: guard rescale_noise_cfg against zero std_cfg to prevent NaN propagation#14334feiiiiii5 wants to merge 1 commit into
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…gingface#13425) The rescale_noise_cfg function performs an unconditional division by std_cfg: noise_pred_rescaled = noise_cfg * (std_text / std_cfg) When noise_cfg has zero variance (e.g. all-zero tensor), std_cfg becomes 0, causing division by zero that produces NaN/inf values which silently corrupt the diffusion process. Fix: wrap the division in torch.where to fall back to the original noise_cfg when std_cfg is zero. This is mathematically correct: when noise_cfg is constant, there is nothing to rescale. Applied to all 36 copies of the function across pipelines and guiders. Fixes huggingface#13425 Signed-off-by: fei <204683769+feiiiiii5@users.noreply.github.com>
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Fixes #13425
Bug
rescale_noise_cfgperforms unconditional division bystd_cfg. Whennoise_cfghas zero variance,std_cfg=0produces NaN/inf that silently corrupts diffusion output.Fix
Wrap division in
torch.where(std_cfg > 0, ..., noise_cfg)— mathematically correct since constantnoise_cfgneeds no rescaling. Applied to all 36 copies across pipelines and guiders.Tests
6 regression tests in
test_rescale_noise_cfg.pycovering normal inputs, zero-variance, mixed batches, and source guard verification. All passing.AI Disclosure
This PR was developed with assistance from an AI coding agent.