



'''simple docstring'''





from __future__ import annotations

A__    :   Optional[Any]           =					[True] * 1_0_0_0_0_0_1
A__    :   Optional[Any]           =					2
while i * i <= 1_0_0_0_0_0_0:
    if seive[i]:
        for j in range(i * i, 1_0_0_0_0_0_1, i):
            A__    :   Optional[int]           =					False
    i += 1





def   a_   (		_UpperCAmelCase    :      int				)    ->  bool:
      return seive[n]





def   a_   (		_UpperCAmelCase    :      int				)    ->  bool:
      return any(digit in '02468' for digit in str(_UpperCAmelCase				)				)





def   a_   (		_UpperCAmelCase    :      int = 1_00_00_00				)    ->  list[int]:
      __snake_case :   Union[str, Any]													=    [2]  # result already includes the number 2.
      for num in range(3 ,limit + 1 ,2				):
            if is_prime(_UpperCAmelCase				) and not contains_an_even_digit(_UpperCAmelCase				):
                  __snake_case :   Any													=    str(_UpperCAmelCase				)
                  __snake_case :   str													=    [int(str_num[j:] + str_num[:j]				) for j in range(len(_UpperCAmelCase				)				)]
                  if all(is_prime(_UpperCAmelCase				) for i in list_nums				):
                        result.append(_UpperCAmelCase				)
      return result





def   a_   (		)    ->  int:
      return len(find_circular_primes()				)


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








'''simple docstring'''





from typing import TYPE_CHECKING

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


A__    :   Optional[Any]           =					{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   Tuple           =					['''SqueezeBertTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   str           =					[
        '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''SqueezeBertForMaskedLM''',
        '''SqueezeBertForMultipleChoice''',
        '''SqueezeBertForQuestionAnswering''',
        '''SqueezeBertForSequenceClassification''',
        '''SqueezeBertForTokenClassification''',
        '''SqueezeBertModel''',
        '''SqueezeBertModule''',
        '''SqueezeBertPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_squeezebert import (
        SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SqueezeBertConfig,
        SqueezeBertOnnxConfig,
    )
    from .tokenization_squeezebert import SqueezeBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_squeezebert import (
            SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            SqueezeBertForMaskedLM,
            SqueezeBertForMultipleChoice,
            SqueezeBertForQuestionAnswering,
            SqueezeBertForSequenceClassification,
            SqueezeBertForTokenClassification,
            SqueezeBertModel,
            SqueezeBertModule,
            SqueezeBertPreTrainedModel,
        )

else:
    import sys

    A__    :   List[Any]           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



