Fix the configure script crash when no TTY is allocated (e.g. a container) (#2080)

* (config) avoid failure when huggingface token is not set

it is not required for model download, and we are handling the
saving of the token during huggingface authentication phase elsewhere.

* (config) safely print to non-tty terminals where width can not be determined
This commit is contained in:
Eugene Brodsky 2022-12-19 21:52:58 -05:00 committed by GitHub
parent 1ba40db361
commit ab2972f320
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@ -212,7 +212,7 @@ def HfLogin(access_token) -> str:
#-------------------------------Authenticate against Hugging Face
def authenticate(yes_to_all=False):
print('** LICENSE AGREEMENT FOR WEIGHT FILES **')
print("=" * os.get_terminal_size()[0])
print("=" * shutil.get_terminal_size()[0])
print('''
By downloading the Stable Diffusion weight files from the official Hugging Face
repository, you agree to have read and accepted the CreativeML Responsible AI License.
@ -221,7 +221,7 @@ The license terms are located here:
https://huggingface.co/spaces/CompVis/stable-diffusion-license
''')
print("=" * os.get_terminal_size()[0])
print("=" * shutil.get_terminal_size()[0])
if not yes_to_all:
accepted = False
@ -237,7 +237,7 @@ The license terms are located here:
# Authenticate to Huggingface using environment variables.
# If successful, authentication will persist for either interactive or non-interactive use.
# Default env var expected by HuggingFace is HUGGING_FACE_HUB_TOKEN.
print("=" * os.get_terminal_size()[0])
print("=" * shutil.get_terminal_size()[0])
print('Authenticating to Huggingface')
hf_envvars = [ "HUGGING_FACE_HUB_TOKEN", "HUGGINGFACE_TOKEN" ]
if not (access_token := HfFolder.get_token()):
@ -294,7 +294,7 @@ You may re-run the configuration script again in the future if you do not wish t
print()
print(f"Re-run the configuration script without '--yes' to set the HuggingFace token interactively, or use one of the environment variables: {', '.join(hf_envvars)}")
print("=" * os.get_terminal_size()[0])
print("=" * shutil.get_terminal_size()[0])
return access_token
@ -330,13 +330,10 @@ def download_weight_datasets(models:dict, access_token:str):
successful[mod] = True
if len(successful) < len(models):
print(f'\n\n** There were errors downloading one or more files. **')
print('Please double-check your license agreements, and your access token.')
HfFolder.delete_token()
print('Press any key to try again. Type ^C to quit.\n')
input()
return None
HfFolder.save_token(access_token)
keys = ', '.join(successful.keys())
print(f'Successfully installed {keys}')
return successful