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Fix sample norms in batches

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rockerBOO
2025-02-27 00:00:20 -05:00
parent 70403f6977
commit 542f980443
1 changed files with 6 additions and 4 deletions
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10
library/lumina_train_util.py
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@@ -680,12 +680,14 @@ def denoise(
dim=tuple(range(1, len(noise_pred_cond.shape))), dim=tuple(range(1, len(noise_pred_cond.shape))),
keepdim=True, keepdim=True,
) )
max_new_norm = cond_norm * float(renorm_cfg) max_new_norms = cond_norm * float(renorm_cfg)
noise_norm = torch.linalg.vector_norm( noise_norms = torch.linalg.vector_norm(
noise_pred, dim=tuple(range(1, len(noise_pred.shape))), keepdim=True noise_pred, dim=tuple(range(1, len(noise_pred.shape))), keepdim=True
) )
if noise_norm >= max_new_norm: # Iterate through batch
noise_pred = noise_pred * (max_new_norm / noise_norm) for noise_norm, max_new_norm, noise in zip(noise_norms, max_new_norms, noise_pred):
if noise_norm >= max_new_norm:
noise = noise * (max_new_norm / noise_norm)
else: else:
noise_pred = noise_pred_cond noise_pred = noise_pred_cond