

import math



def 				snake_case_(_UpperCamelCase					)							->     int:



  """simple docstring"""






  if not isinstance(_UpperCamelCase			,	_UpperCamelCase					):
    _snake_case						=							F"""Input value of [number={number}] must be an integer"""
    raise TypeError(_UpperCamelCase					)

  if number < 1:
    _snake_case						=							F"""Input value of [number={number}] must be > 0"""
    raise ValueError(_UpperCamelCase					)
  elif number == 1:
    return 3
  elif number == 2:
    return 5
  else:
    _snake_case						=							int(math.log(number // 3			,	2					)					) + 2

    _snake_case						=							[3, 5]
    _snake_case						=							2
    _snake_case						=							3
    for block in range(1			,	_UpperCamelCase					):
      for _ in range(_UpperCamelCase					):
        proth_list.append(2 ** (block + 1) + proth_list[proth_index - 1]					)
        proth_index += 1
      increment *= 2

  return proth_list[number - 1]


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 for number in range(11):
  __A      		=     0
  try:
   __A      		=     proth(number)
  except ValueError:
   print(f'''ValueError: there is no {number}th Proth number''')
   continue

  print(f'''The {number}th Proth number: {value}''')




from typing import TYPE_CHECKING

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


__A      		=     {
    '''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A      		=     [
     '''FALCON_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''FalconForCausalLM''',
     '''FalconModel''',
     '''FalconPreTrainedModel''',
     '''FalconForSequenceClassification''',
     '''FalconForTokenClassification''',
     '''FalconForQuestionAnswering''',
 ]


if TYPE_CHECKING:
 from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_falcon import (
      FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
      FalconForCausalLM,
      FalconForQuestionAnswering,
      FalconForSequenceClassification,
      FalconForTokenClassification,
      FalconModel,
      FalconPreTrainedModel,
  )


else:
 import sys

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

