






'''simple docstring'''







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


_A	:			Optional[int]         =logging.get_logger(__name__)

_A	:			Optional[Any]         ={
    '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/config.json''',
    '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/config.json'''
    # See all FNet models at https://huggingface.co/models?filter=fnet
}

class _lowercase	(				_lowercase		):
							a				      =       """fnet"""




							def __init__(							self:				Dict			,							UpperCamelCase__:				List[Any]=32_000			,							UpperCamelCase__:				Optional[int]=768			,							UpperCamelCase__:				List[str]=12			,							UpperCamelCase__:				str=3_072			,							UpperCamelCase__:				List[Any]="gelu_new"			,							UpperCamelCase__:				Optional[Any]=0.1			,							UpperCamelCase__:				List[str]=512			,							UpperCamelCase__:				List[Any]=4			,							UpperCamelCase__:				Optional[Any]=0.02			,							UpperCamelCase__:				Union[str, Any]=1e-12			,							UpperCamelCase__:				Optional[Any]=False			,							UpperCamelCase__:				Optional[int]=512			,							UpperCamelCase__:				Union[str, Any]=3			,							UpperCamelCase__:				Optional[Any]=1			,							UpperCamelCase__:				Optional[int]=2			,							**UpperCamelCase__:				Dict			,							):
														super().__init__(pad_token_id=UpperCamelCase__			,							bos_token_id=UpperCamelCase__			,							eos_token_id=UpperCamelCase__			,							**UpperCamelCase__     )

														lowerCamelCase__					:	List[Any]         =       vocab_size
														lowerCamelCase__					:	Optional[Any]         =       max_position_embeddings
														lowerCamelCase__					:	List[Any]         =       hidden_size
														lowerCamelCase__					:	Optional[Any]         =       num_hidden_layers
														lowerCamelCase__					:	str         =       intermediate_size
														lowerCamelCase__					:	Dict         =       hidden_act
														lowerCamelCase__					:	Optional[int]         =       hidden_dropout_prob
														lowerCamelCase__					:	List[Any]         =       initializer_range
														lowerCamelCase__					:	Optional[int]         =       type_vocab_size
														lowerCamelCase__					:	Tuple         =       layer_norm_eps
														lowerCamelCase__					:	Optional[int]         =       use_tpu_fourier_optimizations
														lowerCamelCase__					:	int         =       tpu_short_seq_length









'''simple docstring'''







def  SCREAMING_SNAKE_CASE_       (UpperCamelCase = 1000      )      ->       int:
							lowerCamelCase__					:	str         =       -1
							lowerCamelCase__					:	Dict         =       0
							for a in range(1				,			n // 3      ):
														# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
														lowerCamelCase__					:	Dict         =       (n * n - 2 * a * n) // (2 * n - 2 * a)
														lowerCamelCase__					:	Any         =       n - a - b
														if c * c == (a * a + b * b):
																					lowerCamelCase__					:	Dict         =       a * b * c
																					if candidate >= product:
																												lowerCamelCase__					:	Union[str, Any]         =       candidate
							return product


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

