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Fix runtime error in dreambooth training script #6282

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Fix runtime error in dreambooth training script #6282

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18 changes: 5 additions & 13 deletions examples/dreambooth/train_dreambooth.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@
from accelerate import Accelerator
from accelerate.logging import get_logger
from accelerate.utils import ProjectConfiguration, set_seed
from huggingface_hub import create_repo, model_info, upload_folder
from huggingface_hub import create_repo, upload_folder
from huggingface_hub.utils import insecure_hashlib
from packaging import version
from PIL import Image
Expand Down Expand Up @@ -756,16 +756,6 @@ def __getitem__(self, index):
return example


def model_has_vae(args):
config_file_name = os.path.join("vae", AutoencoderKL.config_name)
if os.path.isdir(args.pretrained_model_name_or_path):
config_file_name = os.path.join(args.pretrained_model_name_or_path, config_file_name)
return os.path.isfile(config_file_name)
else:
files_in_repo = model_info(args.pretrained_model_name_or_path, revision=args.revision).siblings
return any(file.rfilename == config_file_name for file in files_in_repo)


def tokenize_prompt(tokenizer, prompt, tokenizer_max_length=None):
if tokenizer_max_length is not None:
max_length = tokenizer_max_length
Expand Down Expand Up @@ -920,11 +910,13 @@ def main(args):
args.pretrained_model_name_or_path, subfolder="text_encoder", revision=args.revision, variant=args.variant
)

if model_has_vae(args):
try:
vae = AutoencoderKL.from_pretrained(
args.pretrained_model_name_or_path, subfolder="vae", revision=args.revision, variant=args.variant
)
else:
except OSError:
# IF does not have a VAE so let's just set it to None
# We don't have to error out here
vae = None

unet = UNet2DConditionModel.from_pretrained(
Expand Down