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https://github.com/invoke-ai/InvokeAI
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Merge branch 'main' into lstein-import-safetensors
This commit is contained in:
Lincoln Stein
GitHub
commit
b9ab9ffb4a
@ -1,18 +1,32 @@
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stable-diffusion-2.1-768:
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description: Stable Diffusion version 2.1 diffusers model, trained on 768x768 images (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1
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format: diffusers
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recommended: True
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stable-diffusion-2.1-base:
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description: Stable Diffusion version 2.1 diffusers base model, trained on 512x512 images (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1-base
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format: diffusers
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recommended: False
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stable-diffusion-1.5:
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description: Stable Diffusion version 1.5 weight file (4.27 GB)
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repo_id: runwayml/stable-diffusion-v1-5
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format: diffusers
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recommended: True
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default: True
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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default: True
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stable-diffusion-2.1:
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description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
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repo_id: stabilityai/stable-diffusion-2-1
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stable-diffusion-1.4:
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description: The original Stable Diffusion version 1.4 weight file (4.27 GB)
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repo_id: CompVis/stable-diffusion-v1-4
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recommended: False
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format: diffusers
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recommended: True
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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width: 512
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height: 512
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inpainting-1.5:
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description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
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description: RunwayML SD 1.5 model optimized for inpainting (ckpt version) (4.27 GB)
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repo_id: runwayml/stable-diffusion-inpainting
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config: v1-inpainting-inference.yaml
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file: sd-v1-5-inpainting.ckpt
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@ -23,19 +37,13 @@ inpainting-1.5:
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recommended: True
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width: 512
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height: 512
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stable-diffusion-1.4:
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description: The original Stable Diffusion version 1.4 weight file (4.27 GB)
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repo_id: CompVis/stable-diffusion-v1-4
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recommended: False
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format: diffusers
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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waifu-diffusion-1.4:
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description: Waifu diffusion 1.4
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description: Latest waifu diffusion 1.4 (diffusers version)
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format: diffusers
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repo_id: hakurei/waifu-diffusion
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recommended: True
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waifu-diffusion-1.3:
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description: Stable Diffusion 1.4 fine tuned on anime-styled images (4.27 GB)
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description: Stable Diffusion 1.4 fine tuned on anime-styled images (ckpt version) (4.27 GB)
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repo_id: hakurei/waifu-diffusion-v1-3
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config: v1-inference.yaml
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file: model-epoch09-float32.ckpt
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@ -53,8 +61,8 @@ trinart-2.0:
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recommended: False
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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trinart_characters-2.0:
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description: An SD model finetuned with 19.2M anime/manga style images (4.27 GB)
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trinart_characters-2_0:
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description: An SD model finetuned with 19.2M anime/manga style images (ckpt version) (4.27 GB)
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repo_id: naclbit/trinart_derrida_characters_v2_stable_diffusion
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config: v1-inference.yaml
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file: derrida_final.ckpt
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@ -65,6 +73,11 @@ trinart_characters-2.0:
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recommended: False
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width: 512
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height: 512
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anything-4.0:
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description: High-quality, highly detailed anime style images with just a few prompts
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format: diffusers
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repo_id: andite/anything-v4.0
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recommended: False
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papercut-1.0:
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description: SD 1.5 fine-tuned for papercut art (use "PaperCut" in your prompts) (2.13 GB)
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repo_id: Fictiverse/Stable_Diffusion_PaperCut_Model
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@ -72,8 +85,6 @@ papercut-1.0:
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vae:
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repo_id: stabilityai/sd-vae-ft-mse
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recommended: False
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width: 512
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height: 512
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voxel_art-1.0:
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description: Stable Diffusion trained on voxel art (use "VoxelArt" in your prompts) (4.27 GB)
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repo_id: Fictiverse/Stable_Diffusion_VoxelArt_Model
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@ -52,7 +52,7 @@ version of InvokeAI with the option to upgrade to experimental versions later.
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find python, then open the Python installer again and choose
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"Modify" existing installation.
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- Installation requires an up to date version of the Microsoft Visual C libraries. Please install the 2015-2022 libraries available here: https://learn.microsoft.com/en-us/cpp/windows/deploying-native-desktop-applications-visual-cpp?view=msvc-170
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- Installation requires an up to date version of the Microsoft Visual C libraries. Please install the 2015-2022 libraries available here: https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist?view=msvc-170
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=== "Mac users"
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@ -613,8 +613,6 @@ def import_diffuser_model(path_or_repo:str, gen, opt, completer)->str:
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description = model_description):
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print('** model failed to import')
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return None
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if input('Make this the default model? [n] ').startswith(('y','Y')):
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manager.set_default_model(model_name)
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return model_name
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def import_ckpt_model(path_or_url:str, gen, opt, completer)->str:
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@ -647,8 +645,6 @@ def import_ckpt_model(path_or_url:str, gen, opt, completer)->str:
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print('** model failed to import')
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return None
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if input('Make this the default model? [n] ').startswith(('y','Y')):
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manager.set_model_default(model_name)
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return model_name
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def _verify_load(model_name:str, gen)->bool:
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@ -726,6 +722,9 @@ def del_config(model_name:str, gen, opt, completer):
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if model_name == current_model:
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print("** Can't delete active model. !switch to another model first. **")
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return
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if model_name not in gen.model_manager.config:
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print(f"** Unknown model {model_name}")
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return
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gen.model_manager.del_model(model_name)
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gen.model_manager.commit(opt.conf)
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print(f'** {model_name} deleted')
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@ -230,6 +230,9 @@ class ModelManager(object):
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Delete the named model.
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'''
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omega = self.config
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if model_name not in omega:
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print(f'** Unknown model {model_name}')
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return
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del omega[model_name]
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if model_name in self.stack:
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self.stack.remove(model_name)
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@ -253,9 +256,8 @@ class ModelManager(object):
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assert (clobber or model_name not in omega), f'attempt to overwrite existing model definition "{model_name}"'
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if model_name not in omega:
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omega[model_name] = dict()
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OmegaConf.update(omega,model_name,model_attributes,merge=False)
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omega[model_name] = model_attributes
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if 'weights' in omega[model_name]:
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omega[model_name]['weights'].replace('\\','/')
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@ -755,16 +757,20 @@ class ModelManager(object):
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print('** Legacy version <= 2.2.5 model directory layout detected. Reorganizing.')
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print('** This is a quick one-time operation.')
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from shutil import move
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from shutil import move, rmtree
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# transformer files get moved into the hub directory
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hub = models_dir / 'hub'
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os.makedirs(hub, exist_ok=True)
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for model in legacy_locations:
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source = models_dir /model
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source = models_dir / model
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dest = hub / model.stem
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print(f'** {source} => {dest}')
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if source.exists():
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print(f'** Moving {models_dir / model} into hub')
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move(models_dir / model, hub)
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if dest.exists():
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rmtree(source)
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else:
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move(source, dest)
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# anything else gets moved into the diffusers directory
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diffusers = models_dir / 'diffusers'
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@ -775,7 +781,12 @@ class ModelManager(object):
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if full_path.is_relative_to(hub) or full_path.is_relative_to(diffusers):
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continue
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if Path(dir).match('models--*--*'):
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move(full_path,diffusers)
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dest = diffusers / dir
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print(f'** {full_path} => {dest}')
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if dest.exists():
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rmtree(full_path)
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else:
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move(full_path,dest)
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# now clean up by removing any empty directories
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empty = [root for root, dirs, files, in os.walk(models_dir) if not len(dirs) and not len(files)]
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