


from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE						:List[Any]			=  {
    '''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FunnelConfig'''],
    '''convert_funnel_original_tf_checkpoint_to_pytorch''': [],
    '''tokenization_funnel''': ['''FunnelTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:List[Any]			=  ['''FunnelTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:str			=  [
       '''FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''FunnelBaseModel''',
       '''FunnelForMaskedLM''',
       '''FunnelForMultipleChoice''',
       '''FunnelForPreTraining''',
       '''FunnelForQuestionAnswering''',
       '''FunnelForSequenceClassification''',
       '''FunnelForTokenClassification''',
       '''FunnelModel''',
       '''FunnelPreTrainedModel''',
       '''load_tf_weights_in_funnel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE						:Union[str, Any]			=  [
       '''TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFFunnelBaseModel''',
       '''TFFunnelForMaskedLM''',
       '''TFFunnelForMultipleChoice''',
       '''TFFunnelForPreTraining''',
       '''TFFunnelForQuestionAnswering''',
       '''TFFunnelForSequenceClassification''',
       '''TFFunnelForTokenClassification''',
       '''TFFunnelModel''',
       '''TFFunnelPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
   from .tokenization_funnel import FunnelTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_funnel_fast import FunnelTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_funnel import (
          FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
          FunnelBaseModel,
          FunnelForMaskedLM,
          FunnelForMultipleChoice,
          FunnelForPreTraining,
          FunnelForQuestionAnswering,
          FunnelForSequenceClassification,
          FunnelForTokenClassification,
          FunnelModel,
          FunnelPreTrainedModel,
          load_tf_weights_in_funnel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_funnel import (
          TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFFunnelBaseModel,
          TFFunnelForMaskedLM,
          TFFunnelForMultipleChoice,
          TFFunnelForPreTraining,
          TFFunnelForQuestionAnswering,
          TFFunnelForSequenceClassification,
          TFFunnelForTokenClassification,
          TFFunnelModel,
          TFFunnelPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE						:Union[str, Any]			=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








from math import factorial



def       _lowerCAmelCase    (				lowerCAmelCase_				:int = 20				)->int:
   '''simple docstring'''






   snake_case_            =       2 * n  # middle entry of odd rows starting at row 3 is the solution for n = 1,
   # 2, 3,...
   snake_case_            =       n // 2

   return int(factorial(lowerCAmelCase_				) / (factorial(lowerCAmelCase_				) * factorial(n - k				))				)


if __name__ == "__main__":
   import sys

   if len(sys.argv) == 1:
      print(solution(20))
   else:
      try:
         SCREAMING_SNAKE_CASE						:Any			=  int(sys.argv[1])
         print(solution(n))
      except ValueError:
         print('''Invalid entry - please enter a number.''')




