






import os
import sys

__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,
)


__snake_case      :      Union[str, Any]             =       [
    'torch',
    'numpy',
    'tokenizers',
    'filelock',
    'requests',
    'tqdm',
    'regex',
    'sentencepiece',
    'sacremoses',
    'importlib_metadata',
    'huggingface_hub',
]







@add_start_docstrings(AutoConfig.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   Union[str, Any]      ,    **UpperCamelCase_    :   Union[str, Any]						)					->				Any:

						"""simple docstring"""



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







@add_start_docstrings(AutoTokenizer.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   Dict      ,    **UpperCamelCase_    :   Any						)					->				Dict:

						"""simple docstring"""



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







@add_start_docstrings(AutoModel.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   Union[str, Any]      ,    **UpperCamelCase_    :   Optional[Any]						)					->				int:

						"""simple docstring"""



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







@add_start_docstrings(AutoModelForCausalLM.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   int      ,    **UpperCamelCase_    :   Union[str, Any]						)					->				Any:

						"""simple docstring"""



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







@add_start_docstrings(AutoModelForMaskedLM.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   Union[str, Any]      ,    **UpperCamelCase_    :   Union[str, Any]						)					->				int:

						"""simple docstring"""



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







@add_start_docstrings(AutoModelForSequenceClassification.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   Union[str, Any]      ,    **UpperCamelCase_    :   Any						)					->				Optional[Any]:

						"""simple docstring"""



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







@add_start_docstrings(AutoModelForQuestionAnswering.__doc__						)
def 		_UpperCamelCase				(      *UpperCamelCase_    :   Any      ,    **UpperCamelCase_    :   Union[str, Any]						)					->				Tuple:

						"""simple docstring"""



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













from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
    LineByLineTextDataset,
    LineByLineWithRefDataset,
    LineByLineWithSOPTextDataset,
    TextDataset,
    TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments





