Correct path to schedlure (#1322)

* [Examples] Correct path

* uP
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Patrick von Platen 2022-11-18 12:32:49 +01:00 committed by GitHub
parent fcfdd95f0b
commit 195e437ac5
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3 changed files with 5 additions and 5 deletions

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@ -472,7 +472,7 @@ def main(args):
eps=args.adam_epsilon,
)
noise_scheduler = DDPMScheduler.from_config("CompVis/stable-diffusion-v1-4", subfolder="scheduler")
noise_scheduler = DDPMScheduler.from_config(args.pretrained_model_name_or_path, subfolder="scheduler")
train_dataset = DreamBoothDataset(
instance_data_root=args.instance_data_dir,

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@ -372,7 +372,7 @@ def main():
weight_decay=args.adam_weight_decay,
eps=args.adam_epsilon,
)
noise_scheduler = DDPMScheduler.from_config("CompVis/stable-diffusion-v1-4", subfolder="scheduler")
noise_scheduler = DDPMScheduler.from_config(args.pretrained_model_name_or_path, subfolder="scheduler")
# Get the datasets: you can either provide your own training and evaluation files (see below)
# or specify a Dataset from the hub (the dataset will be downloaded automatically from the datasets Hub).
@ -605,7 +605,7 @@ def main():
vae=vae,
unet=unet,
tokenizer=tokenizer,
scheduler=PNDMScheduler.from_config("CompVis/stable-diffusion-v1-4", subfolder="scheduler"),
scheduler=PNDMScheduler.from_config(args.pretrained_model_name_or_path, subfolder="scheduler"),
safety_checker=StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker"),
feature_extractor=CLIPFeatureExtractor.from_pretrained("openai/clip-vit-base-patch32"),
)

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@ -441,7 +441,7 @@ def main():
eps=args.adam_epsilon,
)
noise_scheduler = DDPMScheduler.from_config("CompVis/stable-diffusion-v1-4", subfolder="scheduler")
noise_scheduler = DDPMScheduler.from_config(args.pretrained_model_name_or_path, subfolder="scheduler")
train_dataset = TextualInversionDataset(
data_root=args.train_data_dir,
@ -574,7 +574,7 @@ def main():
vae=vae,
unet=unet,
tokenizer=tokenizer,
scheduler=PNDMScheduler.from_config("CompVis/stable-diffusion-v1-4", subfolder="scheduler"),
scheduler=PNDMScheduler.from_config(args.pretrained_model_name_or_path, subfolder="scheduler"),
safety_checker=StableDiffusionSafetyChecker.from_pretrained("CompVis/stable-diffusion-safety-checker"),
feature_extractor=CLIPFeatureExtractor.from_pretrained("openai/clip-vit-base-patch32"),
)