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





def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  str  ,      lowerCAmelCase:  str )   ->       int:
				if len(lowerCAmelCase ) != len(lowerCAmelCase ):
								raise ValueError("String lengths must match!" )

				_UpperCAmelCase       :		List[Any] 		=    0

				for chara, chara in zip(lowerCAmelCase  ,      lowerCAmelCase ):
								if chara != chara:
												count += 1

				return count


if __name__ == "__main__":
					import doctest

					doctest.testmod()


