VictorMylle/Kohya-ss-sd-scripts
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Merge branch 'dev' into sd3

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Kohya S
2025-04-07 21:55:17 +09:00
parent 4589262f8f 572cc3efb8
commit 5a18a03ffc
1 changed files with 12 additions and 1 deletions
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13
train_network.py
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@@ -389,7 +389,18 @@ class NetworkTrainer:
latents = typing.cast(torch.FloatTensor, batch["latents"].to(accelerator.device)) latents = typing.cast(torch.FloatTensor, batch["latents"].to(accelerator.device))
else: else:
# latentに変換 # latentに変換
latents = self.encode_images_to_latents(args, vae, batch["images"].to(accelerator.device, dtype=vae_dtype)) if args.vae_batch_size is None or len(batch["images"]) <= args.vae_batch_size:
latents = self.encode_images_to_latents(args, vae, batch["images"].to(accelerator.device, dtype=vae_dtype))
else:
chunks = [
batch["images"][i : i + args.vae_batch_size] for i in range(0, len(batch["images"]), args.vae_batch_size)
]
list_latents = []
for chunk in chunks:
with torch.no_grad():
chunk = self.encode_images_to_latents(args, vae, chunk.to(accelerator.device, dtype=vae_dtype))
list_latents.append(chunk)
latents = torch.cat(list_latents, dim=0)
# NaNが含まれていれば警告を表示し0に置き換える # NaNが含まれていれば警告を表示し0に置き換える
if torch.any(torch.isnan(latents)): if torch.any(torch.isnan(latents)):