from typing import TYPE_CHECKING

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


UpperCamelCase													=		{
    '''configuration_camembert''': ['''CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CamembertConfig''', '''CamembertOnnxConfig'''],
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase													=		['''CamembertTokenizer''']

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase													=		['''CamembertTokenizerFast''']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase													=		[
          '''CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''CamembertForCausalLM''',
          '''CamembertForMaskedLM''',
          '''CamembertForMultipleChoice''',
          '''CamembertForQuestionAnswering''',
          '''CamembertForSequenceClassification''',
          '''CamembertForTokenClassification''',
          '''CamembertModel''',
          '''CamembertPreTrainedModel''',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase													=		[
          '''TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''TFCamembertForCausalLM''',
          '''TFCamembertForMaskedLM''',
          '''TFCamembertForMultipleChoice''',
          '''TFCamembertForQuestionAnswering''',
          '''TFCamembertForSequenceClassification''',
          '''TFCamembertForTokenClassification''',
          '''TFCamembertModel''',
          '''TFCamembertPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_camembert import CamembertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_camembert_fast import CamembertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_camembert import (
                CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                CamembertForCausalLM,
                CamembertForMaskedLM,
                CamembertForMultipleChoice,
                CamembertForQuestionAnswering,
                CamembertForSequenceClassification,
                CamembertForTokenClassification,
                CamembertModel,
                CamembertPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_camembert import (
                TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFCamembertForCausalLM,
                TFCamembertForMaskedLM,
                TFCamembertForMultipleChoice,
                TFCamembertForQuestionAnswering,
                TFCamembertForSequenceClassification,
                TFCamembertForTokenClassification,
                TFCamembertModel,
                TFCamembertPreTrainedModel,
            )

else:
      import sys

      UpperCamelCase													=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




def     lowercase_       (    _lowerCamelCase							: str	,			_lowerCamelCase							: Optional[int]):
    if len(str(_lowerCamelCase)) == 1 or len(str(_lowerCamelCase)) == 1:
        return a * b

    lowercase__				:     Tuple					      =       max(len(str(_lowerCamelCase))	,			len(str(_lowerCamelCase)))
    lowercase__				:     Union[str, Any]					      =       ma // 2

    lowercase__      ,     lowercase__				:     Union[str, Any]					      =       divmod(_lowerCamelCase	,			10**ma)
    lowercase__      ,     lowercase__				:     Tuple					      =       divmod(_lowerCamelCase	,			10**ma)

    lowercase__				:     int					      =       karatsuba(_lowerCamelCase	,			_lowerCamelCase)
    lowercase__				:     Dict					      =       karatsuba((aa + aa)	,			(ba + ba))
    lowercase__				:     Optional[int]					      =       karatsuba(_lowerCamelCase	,			_lowerCamelCase)

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

def     lowercase_       (    ):
    print(karatsuba(1_5463	,			2_3489))


if __name__ == "__main__":
      main()



