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update readme, add metadata for network module

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Kohya S
2024-04-07 14:58:17 +09:00
parent 90b18795fc
commit d30ebb205c
3 changed files with 77 additions and 26 deletions
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11
train_network.py
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@@ -476,7 +476,7 @@ class NetworkTrainer:
# pop weights of other models than network to save only network weights
if accelerator.is_main_process:
remove_indices = []
for i,model in enumerate(models):
for i, model in enumerate(models):
if not isinstance(model, type(accelerator.unwrap_model(network))):
remove_indices.append(i)
for i in reversed(remove_indices):
@@ -569,6 +569,11 @@ class NetworkTrainer:
"ss_scale_weight_norms": args.scale_weight_norms,
"ss_ip_noise_gamma": args.ip_noise_gamma,
"ss_debiased_estimation": bool(args.debiased_estimation_loss),
"ss_noise_offset_random_strength": args.noise_offset_random_strength,
"ss_ip_noise_gamma_random_strength": args.ip_noise_gamma_random_strength,
"ss_loss_type": args.loss_type,
"ss_huber_schedule": args.huber_schedule,
"ss_huber_c": args.huber_c,
}
if use_user_config:
@@ -873,7 +878,9 @@ class NetworkTrainer:
else:
target = noise
loss = train_util.conditional_loss(noise_pred.float(), target.float(), reduction="none", loss_type=args.loss_type, huber_c=huber_c)
loss = train_util.conditional_loss(
noise_pred.float(), target.float(), reduction="none", loss_type=args.loss_type, huber_c=huber_c
)
if args.masked_loss:
loss = apply_masked_loss(loss, batch)
loss = loss.mean([1, 2, 3])