
"""simple docstring"""





from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

SCREAMING_SNAKE_CASE_												= [
    '''python''',
    '''tqdm''',
    '''regex''',
    '''requests''',
    '''packaging''',
    '''filelock''',
    '''numpy''',
    '''tokenizers''',
    '''huggingface-hub''',
    '''safetensors''',
    '''accelerate''',
    '''pyyaml''',
]

for pkg in pkgs_to_check_at_runtime:
 if pkg in deps:
  if pkg == "tokenizers":
   # must be loaded here, or else tqdm check may fail
   from .utils import is_tokenizers_available

   if not is_tokenizers_available():
    continue  # not required, check version only if installed
  elif pkg == "accelerate":
   # must be loaded here, or else tqdm check may fail
   from .utils import is_accelerate_available

   # Maybe switch to is_torch_available in the future here so that Accelerate is hard dep of
   # Transformers with PyTorch
   if not is_accelerate_available():
    continue  # not required, check version only if installed

  require_version_core(deps[pkg])
 else:
  raise ValueError(f'''can\'t find {pkg} in {deps.keys()}, check dependency_versions_table.py''')







def   A__ ( A__      ,      A__=None		)		->			Optional[int]:





   '''simple docstring'''




   require_version(deps[pkg]      ,      UpperCAmelCase__		)



import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str      ,					UpperCAmelCase__					:   str      ,					**UpperCAmelCase__					:   List[str]							)	->     Tuple:
							lowerCamelCase_					=       AutoConfig.from_pretrained(UpperCAmelCase__      ,					**UpperCAmelCase__							)
							lowerCamelCase_					=       AutoModelForSeqaSeqLM.from_config(UpperCAmelCase__							)
							model.save_pretrained(UpperCAmelCase__							)
							AutoTokenizer.from_pretrained(UpperCAmelCase__							).save_pretrained(UpperCAmelCase__							)
							return model


if __name__ == "__main__":
		fire.Fire(save_randomly_initialized_version)





