mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
attempt to make batch install more reliable
1. added nvidia channel to environment.yml 2. updated pytorch-cuda requirement 3. let conda figure out what version of pytorch to install 4. add conda install status checking to .bat and .sh install files 5. in preload_models.py catch and handle download/access token errors
This commit is contained in:
Lincoln Stein
parent
d7107d931a
commit
ce298d32b5
@ -1,14 +1,14 @@
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name: invokeai
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channels:
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- pytorch
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- nvidia
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- defaults
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dependencies:
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- python>=3.9
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- pip=20.3
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- cudatoolkit=11.3
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- pytorch=1.11.0
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- torchvision=0.12.0
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- numpy=1.19.2
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- pip=22.2.2
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- numpy=1.23.3
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- torchvision=0.14.0
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- pytorch-cuda=11.7
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- pip:
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- albumentations==0.4.3
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- opencv-python==4.5.5.64
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@ -80,14 +80,35 @@ if not exist ".git" (
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call conda activate
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@rem create the environment
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call conda env remove -n invokeai
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call conda env create
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call conda activate invokeai
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if "%ERRORLEVEL%" NE "0" (
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echo ""
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echo "Something went wrong while installing Python libraries and cannot continue.
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echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
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echo "installation methods."
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echo "Press any key to continue"
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pause
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exit /b
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)
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call conda activate invokeai
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@rem preload the models
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call python scripts\preload_models.py
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if "%ERRORLEVEL%" NE "0" (
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echo ""
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echo "The preload_models.py script crashed or was cancelled."
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echo "InvokeAI is not ready to run. To run preload_models.py again,"
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echo "run the command 'python scripts/preload_models.py'"
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echo "Press any key to continue"
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pause
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exit /b
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)
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@rem tell the user their next steps
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echo.
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echo ""
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echo "You can now start generating images by double-clicking the 'invoke.bat' file (inside this folder)
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echo "Press any key to continue"
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pause
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exit 0
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@ -99,13 +99,29 @@ conda activate
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if [ "$OS_NAME" == "mac" ]; then
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PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-${OS_ARCH} conda env create -f environment-mac.yml
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else
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conda env remove -n invokeai
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conda env create -f environment.yml
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fi
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conda activate invokeai
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status = $?
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# preload the models
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python scripts/preload_models.py
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if test $status -ne 0
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then
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echo "Something went wrong while installing Python libraries and cannot continue.
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echo "Please visit https://invoke-ai.github.io/InvokeAI/#installation for alternative"
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echo "installation methods"
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else
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conda activate invokeai
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# tell the user their next steps
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echo "You can now start generating images by running invoke.sh (inside this folder), using ./invoke.sh"
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# preload the models
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echo "Calling the preload_models.py script"
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python scripts/preload_models.py
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if test $? -ne 0
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then
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echo "The preload_models.py script crashed or was cancelled."
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echo "InvokeAI is not ready to run. To run preload_models.py again,"
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echo "give the command 'python scripts/preload_models.py'"
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else
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# tell the user their next steps
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echo "You can now start generating images by running invoke.sh (inside this folder), using ./invoke.sh"
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fi
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@ -18,6 +18,12 @@ import traceback
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import getpass
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import requests
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import warnings
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warnings.filterwarnings('ignore')
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#warnings.simplefilter('ignore')
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#warnings.filterwarnings('ignore',category=DeprecationWarning)
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#warnings.filterwarnings('ignore',category=UserWarning)
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# deferred loading so that help message can be printed quickly
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def load_libs():
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print('Loading Python libraries...\n')
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@ -238,7 +244,6 @@ This involves a few easy steps.
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Now copy the token to your clipboard and paste it here: '''
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)
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access_token = getpass.getpass()
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HfFolder.save_token(access_token)
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return access_token
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#---------------------------------------------
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@ -256,6 +261,7 @@ def migrate_models_ckpt():
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#---------------------------------------------
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def download_weight_datasets(models:dict, access_token:str):
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from huggingface_hub import HfFolder
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migrate_models_ckpt()
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successful = dict()
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for mod in models.keys():
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@ -268,6 +274,12 @@ def download_weight_datasets(models:dict, access_token:str):
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)
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if success:
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successful[mod] = True
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if len(successful) < len(models):
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print(f'\n* There were errors downloading one or more files.')
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print('Please double-check your license agreements, and your access token. Type ^C to quit.\n')
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return None
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HfFolder.save_token(access_token)
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keys = ', '.join(successful.keys())
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print(f'Successfully installed {keys}')
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return successful
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@ -295,6 +307,8 @@ def download_with_resume(repo_id:str, model_name:str, access_token:str)->bool:
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if resp.status_code==416: # "range not satisfiable", which means nothing to return
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print(f'* {model_name}: complete file found. Skipping.')
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return True
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elif resp.status_code != 200:
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print(f'** An error occurred during downloading {model_name}: {resp.reason}')
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elif exist_size > 0:
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print(f'* {model_name}: partial file found. Resuming...')
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else:
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@ -302,7 +316,7 @@ def download_with_resume(repo_id:str, model_name:str, access_token:str)->bool:
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try:
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if total < 2000:
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print(f'* {model_name}: {resp.text}')
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print(f'*** ERROR DOWNLOADING {model_name}: {resp.text}')
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return False
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with open(model_dest, open_mode) as file, tqdm(
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@ -329,7 +343,7 @@ def update_config_file(successfully_downloaded:dict,opt:dict):
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try:
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if os.path.exists(Config_file):
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print(f'** {Config_file} exists. Renaming to {Config_file}.orig')
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print(f'* {Config_file} exists. Renaming to {Config_file}.orig')
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os.rename(Config_file,f'{Config_file}.orig')
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tmpfile = os.path.join(os.path.dirname(Config_file),'new_config.tmp')
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with open(tmpfile, 'w') as outfile:
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@ -383,26 +397,27 @@ def new_config_file_contents(successfully_downloaded:dict, Config_file:str)->str
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# this will preload the Bert tokenizer fles
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def download_bert():
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print('Installing bert tokenizer (ignore deprecation errors)...', end='')
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from transformers import BertTokenizerFast, AutoFeatureExtractor
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sys.stdout.flush()
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with warnings.catch_warnings():
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warnings.filterwarnings('ignore', category=DeprecationWarning)
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from transformers import BertTokenizerFast, AutoFeatureExtractor
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tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')
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print('...success')
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sys.stdout.flush()
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#---------------------------------------------
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# this will download requirements for Kornia
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def download_kornia():
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print('Installing Kornia requirements...', end='')
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with warnings.catch_warnings():
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warnings.filterwarnings('ignore', category=DeprecationWarning)
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import kornia
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print('Installing Kornia requirements (ignore deprecation errors)...', end='')
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sys.stdout.flush()
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import kornia
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print('...success')
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#---------------------------------------------
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def download_clip():
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print('Loading CLIP model...',end='')
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from transformers import CLIPTokenizer, CLIPTextModel
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with warnings.catch_warnings():
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warnings.filterwarnings('ignore', category=DeprecationWarning)
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from transformers import CLIPTokenizer, CLIPTextModel
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sys.stdout.flush()
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version = 'openai/clip-vit-large-patch14'
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tokenizer = CLIPTokenizer.from_pretrained(version)
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@ -541,11 +556,16 @@ if __name__ == '__main__':
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if models is None:
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if yes_or_no('Quit?',default_yes=False):
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sys.exit(0)
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print('** LICENSE AGREEMENT FOR WEIGHT FILES **')
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access_token = authenticate()
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print('\n** DOWNLOADING WEIGHTS **')
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successfully_downloaded = download_weight_datasets(models, access_token)
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done = False
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while not done:
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print('** LICENSE AGREEMENT FOR WEIGHT FILES **')
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access_token = authenticate()
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print('\n** DOWNLOADING WEIGHTS **')
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successfully_downloaded = download_weight_datasets(models, access_token)
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done = successfully_downloaded is not None
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update_config_file(successfully_downloaded,opt)
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print('\n** DOWNLOADING SUPPORT MODELS **')
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download_bert()
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download_kornia()
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