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Fix issues found in review (pt 2)
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recris committed Nov 30, 2024
1 parent 740ec1d commit 7b61e9e
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Showing 2 changed files with 2 additions and 2 deletions.
2 changes: 1 addition & 1 deletion library/train_util.py
Original file line number Diff line number Diff line change
Expand Up @@ -5875,7 +5875,7 @@ def get_huber_threshold(args, timesteps: torch.Tensor, noise_scheduler) -> torch
alpha = -math.log(args.huber_c) / noise_scheduler.config.num_train_timesteps
result = torch.exp(-alpha * timesteps) * args.huber_scale
elif args.huber_schedule == "snr":
if not hasattr(noise_scheduler, "alphas_cumprod"):
if noise_scheduler is None or not hasattr(noise_scheduler, "alphas_cumprod"):
raise NotImplementedError("Huber schedule 'snr' is not supported with the current model.")
alphas_cumprod = torch.index_select(noise_scheduler.alphas_cumprod, 0, timesteps.cpu())
sigmas = ((1.0 - alphas_cumprod) / alphas_cumprod) ** 0.5
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2 changes: 1 addition & 1 deletion sd3_train.py
Original file line number Diff line number Diff line change
Expand Up @@ -845,7 +845,7 @@ def grad_hook(parameter: torch.Tensor):
# )
# calculate loss
loss = train_util.conditional_loss(
args, model_pred.float(), target.float(), timesteps, "none", noise_scheduler
args, model_pred.float(), target.float(), timesteps, "none", None
)
if args.masked_loss or ("alpha_masks" in batch and batch["alpha_masks"] is not None):
loss = apply_masked_loss(loss, batch)
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