
"""simple docstring"""




def lowercase_  (   _snake_case = 1_000_000						):
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   set(range(3   ,_snake_case   ,2						)						)
							primes.add(2						)
							for p in range(3   ,_snake_case   ,2						):
														if p not in primes:
																					continue
														primes.difference_update(set(range(p * p   ,_snake_case   ,_snake_case						)						)						)

							SCREAMING_SNAKE_CASE__						:       int           =   [float(_snake_case						) for n in range(limit + 1						)]

							for p in primes:
														for n in range(_snake_case   ,limit + 1   ,_snake_case						):
																					phi[n] *= 1 - 1 / p

							return int(sum(phi[2:]						)						)


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









from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_:Any             =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:Dict             =						{
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    __lowerCamelCase			: Dict					=      "xmod"






    def __init__(       self,		lowerCamelCase__=3_0522,		lowerCamelCase__=768,		lowerCamelCase__=12,		lowerCamelCase__=12,		lowerCamelCase__=3072,		lowerCamelCase__="gelu",		lowerCamelCase__=0.1,		lowerCamelCase__=0.1,		lowerCamelCase__=512,		lowerCamelCase__=2,		lowerCamelCase__=0.02,		lowerCamelCase__=1e-12,		lowerCamelCase__=1,		lowerCamelCase__=0,		lowerCamelCase__=2,		lowerCamelCase__="absolute",		lowerCamelCase__=True,		lowerCamelCase__=None,		lowerCamelCase__=False,		lowerCamelCase__=2,		lowerCamelCase__=False,		lowerCamelCase__=True,		lowerCamelCase__=True,		lowerCamelCase__=("en_XX",),		lowerCamelCase__=None,		**lowerCamelCase__,		):
        super().__init__(pad_token_id=lowerCamelCase__,		bos_token_id=lowerCamelCase__,		eos_token_id=lowerCamelCase__,		**lowerCamelCase__		)

        A :       int          =   vocab_size
        A :       int          =   hidden_size
        A :       str          =   num_hidden_layers
        A :       List[str]          =   num_attention_heads
        A :       List[str]          =   hidden_act
        A :       Dict          =   intermediate_size
        A :       Optional[int]          =   hidden_dropout_prob
        A :       Union[str, Any]          =   attention_probs_dropout_prob
        A :       int          =   max_position_embeddings
        A :       Tuple          =   type_vocab_size
        A :       List[Any]          =   initializer_range
        A :       str          =   layer_norm_eps
        A :       Union[str, Any]          =   position_embedding_type
        A :       Any          =   use_cache
        A :       int          =   classifier_dropout
        A :       int          =   pre_norm
        A :       List[str]          =   adapter_reduction_factor
        A :       Any          =   adapter_layer_norm
        A :       Any          =   adapter_reuse_layer_norm
        A :       str          =   ln_before_adapter
        A :       Dict          =   list(lowerCamelCase__		)
        A :       Union[str, Any]          =   default_language






class SCREAMING_SNAKE_CASE__     (		SCREAMING_SNAKE_CASE__    ):




    '''simple docstring'''






    @property
    def 			_lowerCAmelCase					(       self		):
        if self.task == "multiple-choice":
            A :       Any          =   {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
            A :       int          =   {0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
            ]		)


