code: 
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowerCAmelCase__	:  Dict 		={
      '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
      '''tokenization_dpr''': [
          '''DPRContextEncoderTokenizer''',
          '''DPRQuestionEncoderTokenizer''',
          '''DPRReaderOutput''',
          '''DPRReaderTokenizer''',
      ],
  }
  
  
  try:
  			if not is_tokenizers_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			lowerCAmelCase__	:  Optional[Any] 		=[
  			    '''DPRContextEncoderTokenizerFast''',
  			    '''DPRQuestionEncoderTokenizerFast''',
  			    '''DPRReaderTokenizerFast''',
  			]
  
  try:
  			if not is_torch_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			lowerCAmelCase__	:  List[str] 		=[
  			    '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
  			    '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
  			    '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
  			    '''DPRContextEncoder''',
  			    '''DPRPretrainedContextEncoder''',
  			    '''DPRPreTrainedModel''',
  			    '''DPRPretrainedQuestionEncoder''',
  			    '''DPRPretrainedReader''',
  			    '''DPRQuestionEncoder''',
  			    '''DPRReader''',
  			]
  
  try:
  			if not is_tf_available():
  						raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  			pass
  else:
  			lowerCAmelCase__	:  Tuple 		=[
  			    '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
  			    '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
  			    '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
  			    '''TFDPRContextEncoder''',
  			    '''TFDPRPretrainedContextEncoder''',
  			    '''TFDPRPretrainedQuestionEncoder''',
  			    '''TFDPRPretrainedReader''',
  			    '''TFDPRQuestionEncoder''',
  			    '''TFDPRReader''',
  			]
  
  
  if TYPE_CHECKING:
  			from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
  			from .tokenization_dpr import (
  			    DPRContextEncoderTokenizer,
  			    DPRQuestionEncoderTokenizer,
  			    DPRReaderOutput,
  			    DPRReaderTokenizer,
  			)
  
  			try:
  						if not is_tokenizers_available():
  									raise OptionalDependencyNotAvailable()
  			except OptionalDependencyNotAvailable:
  						pass
  			else:
  						from .tokenization_dpr_fast import (
  						    DPRContextEncoderTokenizerFast,
  						    DPRQuestionEncoderTokenizerFast,
  						    DPRReaderTokenizerFast,
  						)
  
  			try:
  						if not is_torch_available():
  									raise OptionalDependencyNotAvailable()
  			except OptionalDependencyNotAvailable:
  						pass
  			else:
  						from .modeling_dpr import (
  						    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
  						    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
  						    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
  						    DPRContextEncoder,
  						    DPRPretrainedContextEncoder,
  						    DPRPreTrainedModel,
  						    DPRPretrainedQuestionEncoder,
  						    DPRPretrainedReader,
  						    DPRQuestionEncoder,
  						    DPRReader,
  						)
  
  			try:
  						if not is_tf_available():
  									raise OptionalDependencyNotAvailable()
  			except OptionalDependencyNotAvailable:
  						pass
  			else:
  						from .modeling_tf_dpr import (
  						    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
  						    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
  						    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
  						    TFDPRContextEncoder,
  						    TFDPRPretrainedContextEncoder,
  						    TFDPRPretrainedQuestionEncoder,
  						    TFDPRPretrainedReader,
  						    TFDPRQuestionEncoder,
  						    TFDPRReader,
  						)
  
  else:
  			import sys
  
  			lowerCAmelCase__	:  int 		=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  
style_context: 
  
  
  
  def 			__lowercase     (				a__							,     a__     )       ->				List[str]:
  							if n == 0:
  														return 1
  
  							elif n % 2 == 1:
  														return binary_exponentiation(a__							,     n - 1     ) * a
  
  							else:
  														__SCREAMING_SNAKE_CASE								=      binary_exponentiation(a__							,     n / 2     )
  														return b * b
  
  
  if __name__ == "__main__":
  			try:
  						lowerCAmelCase__	:  str 		=int(input('''Enter Base : ''').strip())
  						lowerCAmelCase__	:  Optional[int] 		=int(input('''Enter Power : ''').strip())
  			except ValueError:
  						print('''Invalid literal for integer''')
  
  			lowerCAmelCase__	:  Any 		=binary_exponentiation(BASE, POWER)
  			print(F'''{BASE}^({POWER}) : {RESULT}''')
  
  
  
  
  
  
  