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[fix] fix for prior preservation and mixed precision sampling (#11873)

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Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
This commit is contained in:
Bulat Akhmatov
2025-09-01 14:12:14 +03:00
committed by GitHub
parent 901da9dccc
commit 0ff1aa910c
1 changed files with 7 additions and 1 deletions
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8
examples/dreambooth/train_dreambooth_lora_flux_kontext.py
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@@ -1270,6 +1270,7 @@ def main(args):
subfolder="transformer",
revision=args.revision,
variant=args.variant,
torch_dtype=torch_dtype,
)
pipeline = FluxKontextPipeline.from_pretrained(
args.pretrained_model_name_or_path,
@@ -1292,7 +1293,8 @@ def main(args):
for example in tqdm(
sample_dataloader, desc="Generating class images", disable=not accelerator.is_local_main_process
):
images = pipeline(example["prompt"]).images
with torch.autocast(device_type=accelerator.device.type, dtype=torch_dtype):
images = pipeline(prompt=example["prompt"]).images
for i, image in enumerate(images):
hash_image = insecure_hashlib.sha1(image.tobytes()).hexdigest()
@@ -1899,6 +1901,10 @@ def main(args):
device=accelerator.device,
prompt=args.instance_prompt,
)
else:
prompt_embeds, pooled_prompt_embeds, text_ids = compute_text_embeddings(
prompts, text_encoders, tokenizers
)
# Convert images to latent space
if args.cache_latents: