





"""simple docstring"""


from math import isqrt, loga





def SCREAMING_SNAKE_CASE_  (			snake_case  :   int						)->						Union[str, Any]:
       _lowerCamelCase             =   [True] * max_number
       for i in range(2		,    isqrt(max_number - 1						) + 1						):
              if is_prime[i]:
                     for j in range(i**2		,    __A		,    __A						):
                            _lowerCamelCase             =   False

       return [i for i in range(2		,    __A						) if is_prime[i]]





def SCREAMING_SNAKE_CASE_  (			snake_case  :   int = 800_800		,    snake_case  :   int = 800_800						)->						Dict:
       _lowerCamelCase             =   degree * loga(__A						)
       _lowerCamelCase             =   int(__A						)
       _lowerCamelCase             =   calculate_prime_numbers(__A						)

       _lowerCamelCase             =   0
       _lowerCamelCase             =   0
       _lowerCamelCase             =   len(__A						) - 1
       while left < right:
              while (
                  prime_numbers[right] * loga(prime_numbers[left]						)
                  + prime_numbers[left] * loga(prime_numbers[right]						)
                  > upper_bound
              ):
                     right -= 1
              hybrid_integers_count += right - left
              left += 1

       return hybrid_integers_count


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









from typing import TYPE_CHECKING

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


UpperCamelCase__		 =     {
    '''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvNextConfig''', '''ConvNextOnnxConfig''']
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		 =     ['''ConvNextFeatureExtractor''']
    UpperCamelCase__		 =     ['''ConvNextImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		 =     [
        '''CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''ConvNextForImageClassification''',
        '''ConvNextModel''',
        '''ConvNextPreTrainedModel''',
        '''ConvNextBackbone''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		 =     [
        '''TFConvNextForImageClassification''',
        '''TFConvNextModel''',
        '''TFConvNextPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_convnext import ConvNextFeatureExtractor
        from .image_processing_convnext import ConvNextImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_convnext import (
            CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConvNextBackbone,
            ConvNextForImageClassification,
            ConvNextModel,
            ConvNextPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
    import sys

    UpperCamelCase__		 =     _LazyModule(__name__, globals()['''__file__'''], _import_structure)

