

'''simple docstring'''





def 							_lowerCAmelCase (      __magic_name__	:    int = 1000000	)							->     int:
						lowercase   :       Dict								=set(range(3      ,   __magic_name__      ,   2	)	)
						primes.add(2	)
						for p in range(3      ,   __magic_name__      ,   2	):
												if p not in primes:
																		continue
												primes.difference_update(set(range(p * p      ,   __magic_name__      ,   __magic_name__	)	)	)

						lowercase   :       List[Any]								=[float(__magic_name__	) for n in range(limit + 1	)]

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

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


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








'''simple docstring'''





import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


if TYPE_CHECKING:
							from ... import PreTrainedTokenizerBase, TensorType

UpperCamelCase_							=					logging.get_logger(__name__)





class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):
				lowerCamelCase_							=						'vision-encoder-decoder'
				lowerCamelCase_							=						True







				def __init__(					self    :		Optional[int]		,				**UpperCAmelCase__    :		Tuple      ):
										'''simple docstring'''
										super().__init__(**UpperCAmelCase__      )
										if "encoder" not in kwargs or "decoder" not in kwargs:
																raise ValueError(
																    F'''A configuraton of type {self.model_type} cannot be instantiated because '''
																    F'''not both `encoder` and `decoder` sub-configurations are passed, but only {kwargs}'''      )

										lowercase   :       Optional[Any]								=kwargs.pop('''encoder'''      )
										lowercase   :       List[Any]								=encoder_config.pop('''model_type'''      )
										lowercase   :       List[str]								=kwargs.pop('''decoder'''      )
										lowercase   :       Dict								=decoder_config.pop('''model_type'''      )

										lowercase   :       Union[str, Any]								=AutoConfig.for_model(UpperCAmelCase__		,				**UpperCAmelCase__      )
										lowercase   :       List[str]								=AutoConfig.for_model(UpperCAmelCase__		,				**UpperCAmelCase__      )
										lowercase   :       str								=True







				@classmethod
				def    lowerCamelCase_  (					cls    :		List[str]		,				UpperCAmelCase__    :		PretrainedConfig		,				UpperCAmelCase__    :		PretrainedConfig		,				**UpperCAmelCase__    :		Optional[int]      ):
										'''simple docstring'''
										logger.info('''Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''      )
										lowercase   :       int								=True
										lowercase   :       Optional[Any]								=True

										return cls(encoder=encoder_config.to_dict()		,				decoder=decoder_config.to_dict()		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       int								=copy.deepcopy(self.__dict__      )
										lowercase   :       Union[str, Any]								=self.encoder.to_dict()
										lowercase   :       Union[str, Any]								=self.decoder.to_dict()
										lowercase   :       int								=self.__class__.model_type
										return output





class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):
				lowerCamelCase_							=						version.parse('1.11'			)







				@property
				def    lowerCamelCase_  (					self    :		Dict      ):
										'''simple docstring'''
										return OrderedDict(
										    [
										        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
										    ]      )







				@property
				def    lowerCamelCase_  (					self    :		str      ):
										'''simple docstring'''
										return 1E-4







				@property
				def    lowerCamelCase_  (					self    :		List[str]      ):
										'''simple docstring'''
										return OrderedDict({'''last_hidden_state''': {0: '''batch''', 1: '''encoder_sequence'''}}      )





class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):







				@property
				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										lowercase   :       List[str]								=OrderedDict()
										lowercase   :       Tuple								={0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
										lowercase   :       Optional[int]								={0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
										lowercase   :       int								={0: '''batch''', 1: '''encoder_sequence'''}

										return common_inputs







				def    lowerCamelCase_  (					self    :		Optional[int]		,				UpperCAmelCase__    :		"PreTrainedTokenizerBase"		,				UpperCAmelCase__    :		int = -1		,				UpperCAmelCase__    :		int = -1		,				UpperCAmelCase__    :		bool = False		,				UpperCAmelCase__    :		Optional["TensorType"] = None		,				):
										'''simple docstring'''
										import torch

										lowercase   :       Optional[Any]								=OrderedDict()

										lowercase   :       List[Any]								=super().generate_dummy_inputs(
										    UpperCAmelCase__		,				batch_size=UpperCAmelCase__		,				seq_length=UpperCAmelCase__		,				is_pair=UpperCAmelCase__		,				framework=UpperCAmelCase__      )

										lowercase		,  lowercase   :       Optional[int]								=dummy_input['''input_ids'''].shape
										lowercase   :       Union[str, Any]								=(batch, encoder_sequence, self._config.encoder_hidden_size)
										lowercase   :       List[str]								=dummy_input.pop('''input_ids'''      )
										lowercase   :       Tuple								=dummy_input.pop('''attention_mask'''      )
										lowercase   :       Union[str, Any]								=torch.zeros(UpperCAmelCase__      )

										return common_inputs





class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):







				@property
				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										pass







				def    lowerCamelCase_  (					self    :		List[Any]		,				UpperCAmelCase__    :		PretrainedConfig      ):
										'''simple docstring'''
										return VisionEncoderDecoderEncoderOnnxConfig(UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Optional[int]		,				UpperCAmelCase__    :		PretrainedConfig		,				UpperCAmelCase__    :		PretrainedConfig		,				UpperCAmelCase__    :		str = "default"      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=encoder_config.hidden_size
										return VisionEncoderDecoderDecoderOnnxConfig(UpperCAmelCase__		,				UpperCAmelCase__      )





