def    a__       (						__UpperCamelCase = 1_0_0_0_0_0_0 ):
      SCREAMING_SNAKE_CASE_      =     [i - 1 for i in range(limit + 1 )]

      for i in range(2   ,					limit + 1 ):
            if phi[i] == i - 1:
                  for j in range(2 * i   ,					limit + 1   ,					__UpperCamelCase ):
                        phi[j] -= phi[j] // i

      return sum(phi[2 : limit + 1] )


if __name__ == "__main__":
      print(solution())



from ....configuration_utils import PretrainedConfig
from ....utils import logging


A   :     str       =				logging.get_logger(__name__)

# TODO: upload to AWS
A   :     Dict       =				{
    "yjernite/retribert-base-uncased": (
        "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"
    ),
}


class      lowerCamelCase    (SCREAMING_SNAKE_CASE__    ):
  """simple docstring"""







  lowerCamelCase__   =  '''retribert'''







  def __init__(							self       :				Optional[int]     ,   __magic_name__       :				Optional[Any]=30_522     ,   __magic_name__       :				int=768     ,   __magic_name__       :				Dict=8     ,   __magic_name__       :				List[Any]=12     ,   __magic_name__       :				Tuple=3_072     ,   __magic_name__       :				List[Any]="gelu"     ,   __magic_name__       :				Any=0.1     ,   __magic_name__       :				Any=0.1     ,   __magic_name__       :				Tuple=512     ,   __magic_name__       :				Dict=2     ,   __magic_name__       :				int=0.02     ,   __magic_name__       :				List[Any]=1e-12     ,   __magic_name__       :				List[str]=True     ,   __magic_name__       :				Dict=128     ,   __magic_name__       :				Union[str, Any]=0     ,   **__magic_name__       :				List[Any]     ,   )     ->		Dict:
        super().__init__(pad_token_id=__magic_name__     ,   **__magic_name__      )

        SCREAMING_SNAKE_CASE_      =     vocab_size
        SCREAMING_SNAKE_CASE_      =     hidden_size
        SCREAMING_SNAKE_CASE_      =     num_hidden_layers
        SCREAMING_SNAKE_CASE_      =     num_attention_heads
        SCREAMING_SNAKE_CASE_      =     hidden_act
        SCREAMING_SNAKE_CASE_      =     intermediate_size
        SCREAMING_SNAKE_CASE_      =     hidden_dropout_prob
        SCREAMING_SNAKE_CASE_      =     attention_probs_dropout_prob
        SCREAMING_SNAKE_CASE_      =     max_position_embeddings
        SCREAMING_SNAKE_CASE_      =     type_vocab_size
        SCREAMING_SNAKE_CASE_      =     initializer_range
        SCREAMING_SNAKE_CASE_      =     layer_norm_eps
        SCREAMING_SNAKE_CASE_      =     share_encoders
        SCREAMING_SNAKE_CASE_      =     projection_dim


