






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


__UpperCamelCase					:		int	  =						logging.get_logger(__name__)

__UpperCamelCase					:		Dict	  =						{
    """uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}


class   __SCREAMING_SNAKE_CASE(	a_	):
							_UpperCAmelCase     =       "mra"
							def __init__(     self:      int       ,	UpperCamelCase:      Optional[int]=5_02_65       ,	UpperCamelCase:      Optional[int]=7_68       ,	UpperCamelCase:      Optional[int]=12       ,	UpperCamelCase:      str=12       ,	UpperCamelCase:      List[Any]=30_72       ,	UpperCamelCase:      Tuple="gelu"       ,	UpperCamelCase:      Tuple=0.1       ,	UpperCamelCase:      Dict=0.1       ,	UpperCamelCase:      Optional[int]=5_12       ,	UpperCamelCase:      Tuple=1       ,	UpperCamelCase:      Any=0.02       ,	UpperCamelCase:      Union[str, Any]=1e-5       ,	UpperCamelCase:      Union[str, Any]="absolute"       ,	UpperCamelCase:      Dict=4       ,	UpperCamelCase:      Optional[int]="full"       ,	UpperCamelCase:      List[Any]=0       ,	UpperCamelCase:      int=0       ,	UpperCamelCase:      Optional[Any]=1       ,	UpperCamelCase:      Tuple=0       ,	UpperCamelCase:      List[Any]=2       ,	**UpperCamelCase:      Optional[Any]       ,	)		->		int:
											super().__init__(pad_token_id=UpperCamelCase       ,	bos_token_id=UpperCamelCase       ,	eos_token_id=UpperCamelCase       ,	**UpperCamelCase						)

											snake_case__									=     vocab_size
											snake_case__									=     max_position_embeddings
											snake_case__									=     hidden_size
											snake_case__									=     num_hidden_layers
											snake_case__									=     num_attention_heads
											snake_case__									=     intermediate_size
											snake_case__									=     hidden_act
											snake_case__									=     hidden_dropout_prob
											snake_case__									=     attention_probs_dropout_prob
											snake_case__									=     initializer_range
											snake_case__									=     type_vocab_size
											snake_case__									=     layer_norm_eps
											snake_case__									=     position_embedding_type
											snake_case__									=     block_per_row
											snake_case__									=     approx_mode
											snake_case__									=     initial_prior_first_n_blocks
											snake_case__									=     initial_prior_diagonal_n_blocks












def      a_ (      _A = 4000000  )			->			int:







				"""simple docstring"""
				snake_case__									=     [0, 1]
				snake_case__									=     0
				while fib[i] <= n:
								fib.append(fib[i] + fib[i + 1]  )
								if fib[i + 2] > n:
												break
								i += 1
				snake_case__									=     0
				for j in range(len(_A  ) - 1  ):
								if fib[j] % 2 == 0:
												total += fib[j]

				return total


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




