


"""simple docstring"""



import os
import sys

__snake_case         =					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,
)


__snake_case         =					[
    """torch""",
    """numpy""",
    """tokenizers""",
    """filelock""",
    """requests""",
    """tqdm""",
    """regex""",
    """sentencepiece""",
    """sacremoses""",
    """importlib_metadata""",
    """huggingface_hub""",
]







@add_start_docstrings(AutoConfig.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						Optional[Any]		,							**lowercase						:						Optional[Any]				)			->		List[str]:


    """simple docstring"""





    return AutoConfig.from_pretrained(*lowercase		,							**lowercase				)







@add_start_docstrings(AutoTokenizer.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						Tuple		,							**lowercase						:						str				)			->		List[Any]:


    """simple docstring"""





    return AutoTokenizer.from_pretrained(*lowercase		,							**lowercase				)







@add_start_docstrings(AutoModel.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						str		,							**lowercase						:						Optional[Any]				)			->		Tuple:


    """simple docstring"""





    return AutoModel.from_pretrained(*lowercase		,							**lowercase				)







@add_start_docstrings(AutoModelForCausalLM.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						Optional[Any]		,							**lowercase						:						int				)			->		int:


    """simple docstring"""





    return AutoModelForCausalLM.from_pretrained(*lowercase		,							**lowercase				)







@add_start_docstrings(AutoModelForMaskedLM.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						Optional[int]		,							**lowercase						:						str				)			->		Dict:


    """simple docstring"""





    return AutoModelForMaskedLM.from_pretrained(*lowercase		,							**lowercase				)







@add_start_docstrings(AutoModelForSequenceClassification.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						Dict		,							**lowercase						:						Optional[Any]				)			->		Union[str, Any]:


    """simple docstring"""





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







@add_start_docstrings(AutoModelForQuestionAnswering.__doc__				)
def 						__lowerCAmelCase		(		*lowercase						:						Optional[Any]		,							**lowercase						:						Tuple				)			->		List[str]:


    """simple docstring"""





    return AutoModelForQuestionAnswering.from_pretrained(*lowercase		,							**lowercase				)









"""simple docstring"""



from __future__ import annotations

from cmath import sqrt







def 						__lowerCAmelCase		(		lowercase						:						int		,							lowercase						:						int		,							lowercase						:						int				)			->		tuple[complex, complex]:


    """simple docstring"""





    if a == 0:
        raise ValueError("Coefficient 'a' must not be zero."				)
    snake_case					:   Dict         =					b * b - 4 * a * c

    snake_case					:   Tuple         =					(-b + sqrt(lowercase				)) / (2 * a)
    snake_case					:   Optional[int]         =					(-b - sqrt(lowercase				)) / (2 * a)

    return (
        root_a.real if not root_a.imag else root_a,
        root_a.real if not root_a.imag else root_a,
    )







def 						__lowerCAmelCase		(		)			->		List[Any]:


    """simple docstring"""





    snake_case      ,snake_case					:   Optional[Any]         =					quadratic_roots(a=5		,							b=6		,							c=1				)
    print(F'The solutions are: {solutiona} and {solutiona}'				)


if __name__ == "__main__":
  main()





