
import math
from timeit import timeit






def    lowercase	(  lowerCAmelCase__	):
			lowerCamelCase_ 		=     0
			lowerCamelCase_ 		=     abs(lowerCAmelCase__	)
			while True:
						lowerCamelCase_ 		=     n // 10
						digits += 1
						if n == 0:
									break
			return digits






def    lowercase	(  lowerCAmelCase__	):
			return 1 if n == 0 else math.floor(math.log(abs(lowerCAmelCase__	)  ,10	) + 1	)






def    lowercase	(  lowerCAmelCase__	):
			return len(str(abs(lowerCAmelCase__	)	)	)






def    lowercase	(  ):
			from collections.abc import Callable

			def benchmark_a_function(lowerCAmelCase__  ,lowerCAmelCase__	) -> None:
						lowerCamelCase_ 		=     f"{func.__name__}({value})"
						lowerCamelCase_ 		=     timeit(f"__main__.{call}"  ,setup='''import __main__'''	)
						print(f"{call}: {func(lowerCAmelCase__	)} -- {timing} seconds"	)

			for value in (262_144, 1_125_899_906_842_624, 1_267_650_600_228_229_401_496_703_205_376):
						for func in (num_digits, num_digits_fast, num_digits_faster):
									benchmark_a_function(lowerCAmelCase__  ,lowerCAmelCase__	)
						print()


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						benchmark()





"""simple docstring"""


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


A_						       =				logging.get_logger(__name__)

A_						       =				{
    """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    __lowerCamelCase     (   lowerCAmelCase ):
				a__:			Dict									=						'yoso'




				def __init__(							self       ,	UpperCAmelCase=5_0265       ,	UpperCAmelCase=768       ,	UpperCAmelCase=12       ,	UpperCAmelCase=12       ,	UpperCAmelCase=3072       ,	UpperCAmelCase="gelu"       ,	UpperCAmelCase=0.1       ,	UpperCAmelCase=0.1       ,	UpperCAmelCase=4096       ,	UpperCAmelCase=1       ,	UpperCAmelCase=0.0_2       ,	UpperCAmelCase=1e-1_2       ,	UpperCAmelCase="absolute"       ,	UpperCAmelCase=True       ,	UpperCAmelCase=9       ,	UpperCAmelCase=64       ,	UpperCAmelCase=None       ,	UpperCAmelCase=True       ,	UpperCAmelCase=True       ,	UpperCAmelCase=1       ,	UpperCAmelCase=0       ,	UpperCAmelCase=2       ,	**UpperCAmelCase       ,	):
							super().__init__(pad_token_id=UpperCAmelCase       ,	bos_token_id=UpperCAmelCase       ,	eos_token_id=UpperCAmelCase       ,	**UpperCAmelCase      )

							lowerCamelCase_ 		=     vocab_size
							lowerCamelCase_ 		=     max_position_embeddings
							lowerCamelCase_ 		=     hidden_size
							lowerCamelCase_ 		=     num_hidden_layers
							lowerCamelCase_ 		=     num_attention_heads
							lowerCamelCase_ 		=     intermediate_size
							lowerCamelCase_ 		=     hidden_act
							lowerCamelCase_ 		=     hidden_dropout_prob
							lowerCamelCase_ 		=     attention_probs_dropout_prob
							lowerCamelCase_ 		=     initializer_range
							lowerCamelCase_ 		=     type_vocab_size
							lowerCamelCase_ 		=     layer_norm_eps
							lowerCamelCase_ 		=     position_embedding_type
							lowerCamelCase_ 		=     use_expectation
							lowerCamelCase_ 		=     hash_code_len
							lowerCamelCase_ 		=     num_hash
							lowerCamelCase_ 		=     conv_window
							lowerCamelCase_ 		=     use_fast_hash
							lowerCamelCase_ 		=     lsh_backward



