import os
import sys

__SCREAMING_SNAKE_CASE						:   int         =			os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


__SCREAMING_SNAKE_CASE						:   Dict         =			[
    'torch',
    'numpy',
    'tokenizers',
    'filelock',
    'requests',
    'tqdm',
    'regex',
    'sentencepiece',
    'sacremoses',
    'importlib_metadata',
    'huggingface_hub',
]
@add_start_docstrings(AutoConfig.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	Dict:

						'''simple docstring'''



						return AutoConfig.from_pretrained(*__lowercase ,      **__lowercase						)
@add_start_docstrings(AutoTokenizer.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	int:

						'''simple docstring'''



						return AutoTokenizer.from_pretrained(*__lowercase ,      **__lowercase						)
@add_start_docstrings(AutoModel.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	int:

						'''simple docstring'''



						return AutoModel.from_pretrained(*__lowercase ,      **__lowercase						)
@add_start_docstrings(AutoModelForCausalLM.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	List[Any]:

						'''simple docstring'''



						return AutoModelForCausalLM.from_pretrained(*__lowercase ,      **__lowercase						)
@add_start_docstrings(AutoModelForMaskedLM.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	Optional[int]:

						'''simple docstring'''



						return AutoModelForMaskedLM.from_pretrained(*__lowercase ,      **__lowercase						)
@add_start_docstrings(AutoModelForSequenceClassification.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	Tuple:

						'''simple docstring'''



						return AutoModelForSequenceClassification.from_pretrained(*__lowercase ,      **__lowercase						)

@add_start_docstrings(AutoModelForQuestionAnswering.__doc__						)
def  snake_case						(*__lowercase ,      **__lowercase						)	->	Tuple:

						'''simple docstring'''



						return AutoModelForQuestionAnswering.from_pretrained(*__lowercase ,      **__lowercase						)
def  snake_case						(__lowercase						)	->	list:

						'''simple docstring'''



						return [
						    txt[:a] + txt[a].upper() + txt[a + 1 :]
						    for a in range(len(__lowercase						)						)
						    if txt[a].isalpha()
						]


if __name__ == "__main__":
				__import__('doctest').testmod()