


import math


def 				lowerCamelCase__	(      a	:   int				)    ->	list[int]:





			"""simple docstring"""
			a__ :Dict						  =    []
			a__ :Optional[Any]						  =    2
			a__ :int						  =    int(math.sqrt(a				)				)  # Size of every segment
			a__ :Optional[int]						  =    [True] * (end + 1)
			a__ :List[str]						  =    []

			while start <= end:
						if temp[start] is True:
									in_prime.append(a				)
									for i in range(start * start	,  end + 1	,  a				):
												a__ :Optional[int]						  =    False
						start += 1
			prime += in_prime

			a__ :Dict						  =    end + 1
			a__ :Optional[int]						  =    min(2 * end	,  a				)

			while low <= n:
						a__ :Dict						  =    [True] * (high - low + 1)
						for each in in_prime:
									a__ :Union[str, Any]						  =    math.floor(low / each				) * each
									if t < low:
												t += each

									for j in range(a	,  high + 1	,  a				):
												a__ :Tuple						  =    False

						for j in range(len(a				)				):
									if temp[j] is True:
												prime.append(j + low				)

						a__ :int						  =    high + 1
						a__ :List[Any]						  =    min(high + end	,  a				)

			return prime







print(sieve(10**6))






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


snake_case__			 =						logging.get_logger(__name__)

snake_case__			 =						{
    '''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}


class 					lowerCAmelCase_ (       _a):
						lowerCamelCase_         =     'pegasus'
						lowerCamelCase_         =     ['past_key_values']
						lowerCamelCase_         =     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}




						def __init__(	self						:   Any   ,     __A						:   Dict=50265   ,     __A						:   List[Any]=1024   ,     __A						:   int=12   ,     __A						:   Optional[Any]=4096   ,     __A						:   Optional[int]=16   ,     __A						:   Dict=12   ,     __A						:   List[Any]=4096   ,     __A						:   List[str]=16   ,     __A						:   Optional[int]=0.0   ,     __A						:   List[Any]=0.0   ,     __A						:   List[str]=True   ,     __A						:   Optional[int]=True   ,     __A						:   str="gelu"   ,     __A						:   Tuple=1024   ,     __A						:   Any=0.1   ,     __A						:   List[Any]=0.0   ,     __A						:   List[str]=0.0   ,     __A						:   Tuple=0.02   ,     __A						:   Union[str, Any]=0   ,     __A						:   Union[str, Any]=False   ,     __A						:   Optional[Any]=0   ,     __A						:   Tuple=1   ,     __A						:   str=1   ,     **__A						:   Any   ,     )      ->Union[str, Any]:






									"""simple docstring"""






									a__ :Any						  =    vocab_size
									a__ :List[str]						  =    max_position_embeddings
									a__ :int						  =    d_model
									a__ :Union[str, Any]						  =    encoder_ffn_dim
									a__ :List[Any]						  =    encoder_layers
									a__ :Union[str, Any]						  =    encoder_attention_heads
									a__ :Tuple						  =    decoder_ffn_dim
									a__ :List[Any]						  =    decoder_layers
									a__ :Tuple						  =    decoder_attention_heads
									a__ :Optional[int]						  =    dropout
									a__ :str						  =    attention_dropout
									a__ :Optional[int]						  =    activation_dropout
									a__ :str						  =    activation_function
									a__ :Dict						  =    init_std
									a__ :Any						  =    encoder_layerdrop
									a__ :int						  =    decoder_layerdrop
									a__ :Union[str, Any]						  =    use_cache
									a__ :List[Any]						  =    encoder_layers
									a__ :Dict						  =    scale_embedding  # scale factor will be sqrt(d_model) if True
									super().__init__(
									    pad_token_id=__A   ,     eos_token_id=__A   ,     is_encoder_decoder=__A   ,     decoder_start_token_id=__A   ,     forced_eos_token_id=__A   ,     **__A   ,     )




						@property
						def  _snake_case					(	self						:   Optional[Any]						)      ->int:






									"""simple docstring"""






									return self.encoder_attention_heads






						@property
						def  _snake_case					(	self						:   Union[str, Any]						)      ->int:






									"""simple docstring"""






									return self.d_model


