



import os
import sys

_lowercase						  =		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,
)


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



@add_start_docstrings(AutoConfig.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       Dict ,       **UpperCamelCase_				:       Tuple	)->  Optional[Any]:
    return AutoConfig.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)



@add_start_docstrings(AutoTokenizer.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       int ,       **UpperCamelCase_				:       Optional[int]	)->  str:
    return AutoTokenizer.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)



@add_start_docstrings(AutoModel.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       List[Any] ,       **UpperCamelCase_				:       List[Any]	)->  List[Any]:
    return AutoModel.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)



@add_start_docstrings(AutoModelForCausalLM.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       int ,       **UpperCamelCase_				:       Dict	)->  Any:
    return AutoModelForCausalLM.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)



@add_start_docstrings(AutoModelForMaskedLM.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       Optional[int] ,       **UpperCamelCase_				:       str	)->  List[Any]:
    return AutoModelForMaskedLM.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)



@add_start_docstrings(AutoModelForSequenceClassification.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       Any ,       **UpperCamelCase_				:       Optional[Any]	)->  Optional[Any]:
    return AutoModelForSequenceClassification.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)



@add_start_docstrings(AutoModelForQuestionAnswering.__doc__	)
def 		lowerCAmelCase__    (					*UpperCamelCase_				:       Any ,       **UpperCamelCase_				:       Any	)->  int:
    return AutoModelForQuestionAnswering.from_pretrained(*UpperCamelCase_ ,       **UpperCamelCase_	)





import numpy as np



def 		lowerCAmelCase__    (					UpperCamelCase_				:       np.array	)->  np.array:
    return 1 / (1 + np.exp(-vector	))



def 		lowerCAmelCase__    (					UpperCamelCase_				:       np.array	)->  np.array:
    return vector * sigmoid(1.702 * vector	)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
