



'''simple docstring'''






from typing import TYPE_CHECKING

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


A_				:					Union[str, Any]							=      {
    """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:
   A_				:					List[Any]							=      [
       """DPRContextEncoderTokenizerFast""",
       """DPRQuestionEncoderTokenizerFast""",
       """DPRReaderTokenizerFast""",
   ]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_				:					List[Any]							=      [
       """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:
   A_				:					Union[str, Any]							=      [
       """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

   A_				:					str							=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









def       _a (		SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int	):
					if a < b:
										return gcd(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_	)
					if a % b == 0:
										return b
					return gcd(SCREAMING_SNAKE_CASE_ , a % b	)







def       _a (		SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int	):
					if y == 0:
										return 1
					__lowerCAmelCase							  =			power(SCREAMING_SNAKE_CASE_ , y // 2 , SCREAMING_SNAKE_CASE_	) % mod
					__lowerCAmelCase							  =			(temp * temp) % mod
					if y % 2 == 1:
										__lowerCAmelCase							  =			(temp * x) % mod
					return temp







def       _a (		SCREAMING_SNAKE_CASE_				:							int	):
					__lowerCAmelCase							  =			2
					while b < n:
										if gcd(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_	) == 1 and power(SCREAMING_SNAKE_CASE_ , n - 1 , SCREAMING_SNAKE_CASE_	) != 1:
															return False
										b += 1
					return True


if __name__ == "__main__":
					UpperCamelCase__            =     int(input("""Enter number: """).strip())
					if is_carmichael_number(number):
										print(f'''{number} is a Carmichael Number.''')
					else:
										print(f'''{number} is not a Carmichael Number.''')




