'''simple docstring'''
def 							__UpperCamelCase   (				__UpperCAmelCase     :				Union[str, Any]   ,      __UpperCAmelCase     :				Any   ,      __UpperCAmelCase     :				Optional[int] )       ->  Union[str, Any]:
  assert b != 0, "This cannot accept modulo that is == 0"
  if n == 0:
    return 1

  if n % 2 == 1:
    return (bin_exp_mod(__UpperCAmelCase   ,      n - 1   ,      __UpperCAmelCase ) * a) % b

  lowercase							:       str											=      bin_exp_mod(__UpperCAmelCase   ,      n / 2   ,      __UpperCAmelCase )
  return (r * r) % b


if __name__ == "__main__":
 try:
  _A		:			Any	      =int(input('''Enter Base : ''').strip())
  _A		:			List[Any]	      =int(input('''Enter Power : ''').strip())
  _A		:			Dict	      =int(input('''Enter Modulo : ''').strip())
 except ValueError:
  print('''Invalid literal for integer''')

 print(bin_exp_mod(BASE, POWER, MODULO))
'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_A		:			int	      ={'''configuration_cvt''': ['''CVT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CvtConfig''']}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:			str	      =[
     '''CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''CvtForImageClassification''',
     '''CvtModel''',
     '''CvtPreTrainedModel''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:			Optional[Any]	      =[
     '''TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFCvtForImageClassification''',
     '''TFCvtModel''',
     '''TFCvtPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_cvt import (
      CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
      CvtForImageClassification,
      CvtModel,
      CvtPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_cvt import (
      TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFCvtForImageClassification,
      TFCvtModel,
      TFCvtPreTrainedModel,
  )


else:
 import sys

 _A		:			Tuple	      =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)