VictorMylle/Kohya-ss-sd-scripts
1
0
Fork 1
mirror of https://github.com/kohya-ss/sd-scripts.git synced 2026-04-09 06:45:09 +00:00
Code Issues Packages Projects Releases Wiki Activity

Change val latent loss compare

Browse Source
This commit is contained in:
Hina Chen
2024-12-28 11:57:04 +08:00
parent 64bd5317dc
commit cb89e0284e
1 changed files with 10 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
train_network.py
View File

@@ -1350,6 +1350,8 @@ class NetworkTrainer:
validation_steps = min(args.max_validation_steps, len(val_dataloader)) if args.max_validation_steps is not None else len(val_dataloader)
for val_step in tqdm(range(validation_steps), desc="Validation Steps バリデーションテップ"):
val_latents = None
while True:
val_batch = next(cyclic_val_dataloader)
@@ -1371,19 +1373,22 @@ class NetworkTrainer:
if val_latents.shape == latents.shape:
break
if val_latents is not None:
del val_latents
timesteps_list = [10, 350, 500, 650, 990]
val_loss = 0.0
for fixed_timesteps in timesteps_list:
with torch.set_grad_enabled(False), accelerator.autocast():
noise = torch.randn_like(val_latents, device=val_latents.device)
b_size = val_latents.shape[0]
noise = torch.randn_like(latents, device=latents.device)
b_size = latents.shape[0]
timesteps = torch.full((b_size,), fixed_timesteps, dtype=torch.long, device="cpu")
timesteps = timesteps.long().to(val_latents.device)
timesteps = timesteps.long().to(latents.device)
noisy_latents = noise_scheduler.add_noise(val_latents, noise, timesteps)
noisy_latents = noise_scheduler.add_noise(latents, noise, timesteps)
with accelerator.autocast():
noise_pred = self.call_unet(
@@ -1399,7 +1404,7 @@ class NetworkTrainer:
if args.v_parameterization:
# v-parameterization training
target = noise_scheduler.get_velocity(val_latents, noise, timesteps)
target = noise_scheduler.get_velocity(latents, noise, timesteps)
else:
target = noise