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fix: refactor huber-loss calculation in multiple training scripts

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Kohya S
2024-12-01 21:20:28 +09:00
parent 0fe6320f09
commit cc11989755
13 changed files with 52 additions and 70 deletions
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5
flux_train.py
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@@ -666,9 +666,8 @@ def train(args):
target = noise - latents
# calculate loss
loss = train_util.conditional_loss(
args, model_pred.float(), target.float(), timesteps, "none", noise_scheduler
)
huber_c = train_util.get_huber_threshold_if_needed(args, timesteps, noise_scheduler)
loss = train_util.conditional_loss(model_pred.float(), target.float(), args.loss_type, "none", huber_c)
if weighting is not None:
loss = loss * weighting
if args.masked_loss or ("alpha_masks" in batch and batch["alpha_masks"] is not None):