
'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A							     = {
    "configuration_deberta_v2": ["DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaV2Config", "DebertaV2OnnxConfig"],
    "tokenization_deberta_v2": ["DebertaV2Tokenizer"],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = ["DebertaV2TokenizerFast"]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = [
         "TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFDebertaV2ForMaskedLM",
         "TFDebertaV2ForQuestionAnswering",
         "TFDebertaV2ForSequenceClassification",
         "TFDebertaV2ForTokenClassification",
         "TFDebertaV2Model",
         "TFDebertaV2PreTrainedModel",
     ]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A							     = [
         "DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
         "DebertaV2ForMaskedLM",
         "DebertaV2ForMultipleChoice",
         "DebertaV2ForQuestionAnswering",
         "DebertaV2ForSequenceClassification",
         "DebertaV2ForTokenClassification",
         "DebertaV2Model",
         "DebertaV2PreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_deberta_va import (
         DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
         DebertaVaConfig,
         DebertaVaOnnxConfig,
     )
     from .tokenization_deberta_va import DebertaVaTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_deberta_va import (
              TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFDebertaVaForMaskedLM,
              TFDebertaVaForQuestionAnswering,
              TFDebertaVaForSequenceClassification,
              TFDebertaVaForTokenClassification,
              TFDebertaVaModel,
              TFDebertaVaPreTrainedModel,
          )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_deberta_va import (
              DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
              DebertaVaForMaskedLM,
              DebertaVaForMultipleChoice,
              DebertaVaForQuestionAnswering,
              DebertaVaForSequenceClassification,
              DebertaVaForTokenClassification,
              DebertaVaModel,
              DebertaVaPreTrainedModel,
          )

else:
     import sys

     A							     = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ):
	if len(str(__a ) ) == 1 or len(str(__a ) ) == 1:
		return a * b

	snake_case_		:      Dict           =						max(len(str(__a ) ) ,			len(str(__a ) ) )
	snake_case_		:      Tuple           =						ma // 2

	snake_case_    ,snake_case_		:      Tuple           =						divmod(__a ,			10**ma )
	snake_case_    ,snake_case_		:      int           =						divmod(__a ,			10**ma )

	snake_case_		:      str           =						karatsuba(__a ,			__a )
	snake_case_		:      List[str]           =						karatsuba((aa + aa) ,			(ba + ba) )
	snake_case_		:      Optional[Any]           =						karatsuba(__a ,			__a )

	return (z * 10 ** (2 * ma)) + ((y - z - x) * 10 ** (ma)) + (x)


def 				SCREAMING_SNAKE_CASE__    (     ):
	print(karatsuba(1_54_63 ,			2_34_89 ) )


if __name__ == "__main__":
						main()

