


from typing import TYPE_CHECKING

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


UpperCAmelCase     =       {
    """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:
   UpperCAmelCase     =       [
       """DPRContextEncoderTokenizerFast""",
       """DPRQuestionEncoderTokenizerFast""",
       """DPRReaderTokenizerFast""",
   ]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase     =       [
       """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:
   UpperCAmelCase     =       [
       """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

   UpperCAmelCase     =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



def 			__lowerCAmelCase       (SCREAMING_SNAKE_CASE   )->    list:




      """simple docstring"""

      snake_case_			= [True for i in range(n + 1   )]
      snake_case_			= [i - 1 for i in range(n + 1   )]
      snake_case_			= []
      for i in range(2   ,   n + 1   ):
            if is_prime[i]:
                  primes.append(SCREAMING_SNAKE_CASE   )
            for j in range(0   ,   len(SCREAMING_SNAKE_CASE   )   ):
                  if i * primes[j] >= n:
                        break
                  snake_case_			= False

                  if i % primes[j] == 0:
                        snake_case_			= totients[i] * primes[j]
                        break

                  snake_case_			= totients[i] * (primes[j] - 1)

      return totients


if __name__ == "__main__":
   import doctest

   doctest.testmod()