
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a   :      str       =				logging.get_logger(__name__)

_a   :      int       =				{
    """uw-madison/yoso-4096""": """https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json""",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}






class   _UpperCAmelCase					(       _snake_case):
    __lowercase				:			Dict	=       """yoso"""
    def __init__(     self    ,     snake_case_=5_02_65    ,     snake_case_=7_68    ,     snake_case_=12    ,     snake_case_=12    ,     snake_case_=30_72    ,     snake_case_="gelu"    ,     snake_case_=0.1    ,     snake_case_=0.1    ,     snake_case_=40_96    ,     snake_case_=1    ,     snake_case_=0.02    ,     snake_case_=1E-12    ,     snake_case_="absolute"    ,     snake_case_=True    ,     snake_case_=9    ,     snake_case_=64    ,     snake_case_=None    ,     snake_case_=True    ,     snake_case_=True    ,     snake_case_=1    ,     snake_case_=0    ,     snake_case_=2    ,     **snake_case_    ,     ):
      super().__init__(pad_token_id=snake_case_    ,     bos_token_id=snake_case_    ,     eos_token_id=snake_case_    ,     **snake_case_  )

      _snake_case  :    str            = vocab_size
      _snake_case  :    str            = max_position_embeddings
      _snake_case  :    List[str]            = hidden_size
      _snake_case  :    List[Any]            = num_hidden_layers
      _snake_case  :    List[Any]            = num_attention_heads
      _snake_case  :    Dict            = intermediate_size
      _snake_case  :    Tuple            = hidden_act
      _snake_case  :    Optional[Any]            = hidden_dropout_prob
      _snake_case  :    Any            = attention_probs_dropout_prob
      _snake_case  :    Dict            = initializer_range
      _snake_case  :    Dict            = type_vocab_size
      _snake_case  :    Union[str, Any]            = layer_norm_eps
      _snake_case  :    List[Any]            = position_embedding_type
      _snake_case  :    Optional[int]            = use_expectation
      _snake_case  :    List[str]            = hash_code_len
      _snake_case  :    List[Any]            = num_hash
      _snake_case  :    Optional[Any]            = conv_window
      _snake_case  :    str            = use_fast_hash
      _snake_case  :    Optional[int]            = lsh_backward









"""simple docstring"""



from itertools import combinations, product




def   _lowerCAmelCase		(				UpperCAmelCase__							:       int,    UpperCAmelCase__							:       int,    UpperCAmelCase__							:       int,    UpperCAmelCase__							:       int   )		->bool:
						if xa == ya == 0 or xa == ya == 0:
												return False
						A__    :	List[str]			=	xa * xa + ya * ya
						A__    :	List[Any]			=	xa * xa + ya * ya
						A__    :	Optional[int]			=	(xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
						return (
						    a_square + b_square == c_square
						    or a_square + c_square == b_square
						    or b_square + c_square == a_square
						)




def   _lowerCAmelCase		(				UpperCAmelCase__							:       int = 5_0   )		->int:
						return sum(
						    1
						    for pta, pta in combinations(product(range(limit + 1   ),    repeat=2   ),    2   )
						    if is_right(*UpperCAmelCase__,    *UpperCAmelCase__   )   )


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






