





'''simple docstring'''







from typing import TYPE_CHECKING

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


_lowercase       						=			{
    '''configuration_longformer''': [
        '''LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''LongformerConfig''',
        '''LongformerOnnxConfig''',
    ],
    '''tokenization_longformer''': ['''LongformerTokenizer'''],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowercase       						=			[
          '''LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''LongformerForMaskedLM''',
          '''LongformerForMultipleChoice''',
          '''LongformerForQuestionAnswering''',
          '''LongformerForSequenceClassification''',
          '''LongformerForTokenClassification''',
          '''LongformerModel''',
          '''LongformerPreTrainedModel''',
          '''LongformerSelfAttention''',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowercase       						=			[
          '''TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''TFLongformerForMaskedLM''',
          '''TFLongformerForMultipleChoice''',
          '''TFLongformerForQuestionAnswering''',
          '''TFLongformerForSequenceClassification''',
          '''TFLongformerForTokenClassification''',
          '''TFLongformerModel''',
          '''TFLongformerPreTrainedModel''',
          '''TFLongformerSelfAttention''',
      ]


if TYPE_CHECKING:
      from .configuration_longformer import (
          LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          LongformerConfig,
          LongformerOnnxConfig,
      )
      from .tokenization_longformer import LongformerTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_longformer_fast import LongformerTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_longformer import (
                LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                LongformerForMaskedLM,
                LongformerForMultipleChoice,
                LongformerForQuestionAnswering,
                LongformerForSequenceClassification,
                LongformerForTokenClassification,
                LongformerModel,
                LongformerPreTrainedModel,
                LongformerSelfAttention,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_longformer import (
                TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFLongformerForMaskedLM,
                TFLongformerForMultipleChoice,
                TFLongformerForQuestionAnswering,
                TFLongformerForSequenceClassification,
                TFLongformerForTokenClassification,
                TFLongformerModel,
                TFLongformerPreTrainedModel,
                TFLongformerSelfAttention,
            )

else:
      import sys

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








'''simple docstring'''







def    __UpperCamelCase	(	a    : int					,   a    : int     ) ->int:
 while b:
  snake_case				,		snake_case				=			b, a % b
 return a

def    __UpperCamelCase	(	a    : int					,   a    : int     ) ->int:
 return a if b == 0 else euclidean_gcd_recursive(a					,   a % b     )

def    __UpperCamelCase	(	) ->Optional[Any]:
 print(f"""euclidean_gcd(3, 5) = {euclidean_gcd(3					,   5     )}"""     )
 print(f"""euclidean_gcd(5, 3) = {euclidean_gcd(5					,   3     )}"""     )
 print(f"""euclidean_gcd(1, 3) = {euclidean_gcd(1					,   3     )}"""     )
 print(f"""euclidean_gcd(3, 6) = {euclidean_gcd(3					,   6     )}"""     )
 print(f"""euclidean_gcd(6, 3) = {euclidean_gcd(6					,   3     )}"""     )

 print(f"""euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3					,   5     )}"""     )
 print(f"""euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5					,   3     )}"""     )
 print(f"""euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1					,   3     )}"""     )
 print(f"""euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3					,   6     )}"""     )
 print(f"""euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6					,   3     )}"""     )


if __name__ == "__main__":
   main()

