from typing import TYPE_CHECKING

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


__lowerCamelCase    :				Union[str, Any]							     =	{
    '''configuration_mobilebert''': [
        '''MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileBertConfig''',
        '''MobileBertOnnxConfig''',
    ],
    '''tokenization_mobilebert''': ['''MobileBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase    :				List[Any]							     =	['''MobileBertTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase    :				str							     =	[
       '''MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''MobileBertForMaskedLM''',
       '''MobileBertForMultipleChoice''',
       '''MobileBertForNextSentencePrediction''',
       '''MobileBertForPreTraining''',
       '''MobileBertForQuestionAnswering''',
       '''MobileBertForSequenceClassification''',
       '''MobileBertForTokenClassification''',
       '''MobileBertLayer''',
       '''MobileBertModel''',
       '''MobileBertPreTrainedModel''',
       '''load_tf_weights_in_mobilebert''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase    :				List[Any]							     =	[
       '''TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFMobileBertForMaskedLM''',
       '''TFMobileBertForMultipleChoice''',
       '''TFMobileBertForNextSentencePrediction''',
       '''TFMobileBertForPreTraining''',
       '''TFMobileBertForQuestionAnswering''',
       '''TFMobileBertForSequenceClassification''',
       '''TFMobileBertForTokenClassification''',
       '''TFMobileBertMainLayer''',
       '''TFMobileBertModel''',
       '''TFMobileBertPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_mobilebert import (
       MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       MobileBertConfig,
       MobileBertOnnxConfig,
   )
   from .tokenization_mobilebert import MobileBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_mobilebert_fast import MobileBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mobilebert import (
          MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          MobileBertForMaskedLM,
          MobileBertForMultipleChoice,
          MobileBertForNextSentencePrediction,
          MobileBertForPreTraining,
          MobileBertForQuestionAnswering,
          MobileBertForSequenceClassification,
          MobileBertForTokenClassification,
          MobileBertLayer,
          MobileBertModel,
          MobileBertPreTrainedModel,
          load_tf_weights_in_mobilebert,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mobilebert import (
          TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFMobileBertForMaskedLM,
          TFMobileBertForMultipleChoice,
          TFMobileBertForNextSentencePrediction,
          TFMobileBertForPreTraining,
          TFMobileBertForQuestionAnswering,
          TFMobileBertForSequenceClassification,
          TFMobileBertForTokenClassification,
          TFMobileBertMainLayer,
          TFMobileBertModel,
          TFMobileBertPreTrainedModel,
      )

else:
   import sys

   __lowerCamelCase    :				str							     =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

from math import isqrt



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: int			)							->      bool:







  """simple docstring"""





  return all(number % divisor != 0 for divisor in range(2				,  isqrt(__UpperCamelCase			) + 1			)			)



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: int = 10**6			)							->      int:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   0
  SCREAMING_SNAKE_CASE__    							=   1
  SCREAMING_SNAKE_CASE__    							=   7
  while prime_candidate < max_prime:
    primes_count += is_prime(__UpperCamelCase			)

    cube_index += 1
    prime_candidate += 6 * cube_index

  return primes_count


if __name__ == "__main__":
   print(F"""{solution() = }""")
