



'''simple docstring'''


def 			UpperCAmelCase_							(		lowercase__							,						lowercase__							):


     '''simple docstring'''







     a_									=1.0
     for i in range(1							,						r + 1							):
          ret *= (n + 1 - i) / i
     return round(A_							)






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     return choose(8 + n							,						A_							) + choose(9 + n							,						A_							) - 1_0






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     return sum(non_bouncy_exact(A_							) for i in range(1							,						n + 1							)							)






def 			UpperCAmelCase_							(		lowercase__ = 1_0_0							):


     '''simple docstring'''







     return non_bouncy_upto(A_							)


if __name__ == "__main__":
  print(F"""{solution() = }""")






from typing import TYPE_CHECKING

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


__UpperCAmelCase      			=  {
    """configuration_switch_transformers""": [
        """SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwitchTransformersConfig""",
        """SwitchTransformersOnnxConfig""",
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __UpperCAmelCase      			=  [
         """SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """SwitchTransformersEncoderModel""",
         """SwitchTransformersForConditionalGeneration""",
         """SwitchTransformersModel""",
         """SwitchTransformersPreTrainedModel""",
         """SwitchTransformersTop1Router""",
         """SwitchTransformersSparseMLP""",
     ]


if TYPE_CHECKING:
     from .configuration_switch_transformers import (
         SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SwitchTransformersConfig,
         SwitchTransformersOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_switch_transformers import (
              SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwitchTransformersEncoderModel,
              SwitchTransformersForConditionalGeneration,
              SwitchTransformersModel,
              SwitchTransformersPreTrainedModel,
              SwitchTransformersSparseMLP,
              SwitchTransformersTopaRouter,
          )


else:
     import sys

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

