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Update train_network.py

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DKnight54
2025-03-29 01:58:52 +08:00
committed by GitHub
parent 9dcdd163fb
commit 5647f12bc3
1 changed files with 3 additions and 8 deletions
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11
train_network.py
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@@ -913,12 +913,12 @@ class NetworkTrainer:
if "latents" in batch and batch["latents"] is not None:
latents = batch["latents"].to(accelerator.device).to(dtype=weight_dtype)
else:
if args.train_vae_batch is None or len(batch["images"]) <= args.train_vae_batch:
if args.vae_batch_size is None or len(batch["images"]) <= args.vae_batch_size:
with torch.no_grad():
# latentに変換
latents = vae.encode(batch["images"].to(dtype=vae_dtype)).latent_dist.sample().to(dtype=weight_dtype)
else:
chunks = [batch["images"][i:i + args.train_vae_batch] for i in range(0, len(batch["images"]), args.train_vae_batch)]
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():
@@ -1240,12 +1240,7 @@ def setup_parser() -> argparse.ArgumentParser:
help="initial step number including all epochs, 0 means first step (same as not specifying). overwrites initial_epoch."
+ " / 初期ステップ数、全エポックを含むステップ数、0で最初のステップ（未指定時と同じ）。initial_epochを上書きする",
)
parser.add_argument(
"--train_vae_batch",
type=int,
default=None,
help="Sets batch size of VAE when not using cached latents",
)
# parser.add_argument("--loraplus_lr_ratio", default=None, type=float, help="LoRA+ learning rate ratio")
# parser.add_argument("--loraplus_unet_lr_ratio", default=None, type=float, help="LoRA+ UNet learning rate ratio")
# parser.add_argument("--loraplus_text_encoder_lr_ratio", default=None, type=float, help="LoRA+ text encoder learning rate ratio")