

from __future__ import annotations






def 					lowerCamelCase_     (							UpperCAmelCase_							:     list	)						->				list:




	'''simple docstring'''




	if len(UpperCAmelCase_	) == 0:
		return []
	_UpperCamelCase	,		_UpperCamelCase   :		Any			=						min(UpperCAmelCase_	), max(UpperCAmelCase_	)
	_UpperCamelCase   :		List[Any]			=						int(max_value - min_value	) + 1
	_UpperCamelCase   :		list[list]			=						[[] for _ in range(UpperCAmelCase_	)]

	for i in my_list:
		buckets[int(i - min_value	)].append(UpperCAmelCase_	)

	return [v for bucket in buckets for v in sorted(UpperCAmelCase_	)]


if __name__ == "__main__":
							from doctest import testmod

							testmod()
							assert bucket_sort([4, 5, 3, 2, 1]) == [1, 2, 3, 4, 5]
							assert bucket_sort([0, 1, -1_0, 1_5, 2, -2]) == [-1_0, -2, 0, 1, 2, 1_5]







import logging

from transformers.configuration_utils import PretrainedConfig


lowerCAmelCase__								=		logging.getLogger(__name__)







class 	lowercase    (				_lowercase							):


		"""simple docstring"""




		a__					       =  "masked_bert"


		def __init__(				self	,       __snake_case=3_05_22	,       __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=5_12	,       __snake_case=2	,       __snake_case=0.0_2	,       __snake_case=1e-12	,       __snake_case=0	,       __snake_case="topK"	,       __snake_case="constant"	,       __snake_case=0.0	,       **__snake_case	,       ):
			super().__init__(pad_token_id=__snake_case	,       **__snake_case)

			_UpperCamelCase   :		List[Any]			=						vocab_size
			_UpperCamelCase   :		Union[str, Any]			=						hidden_size
			_UpperCamelCase   :		Optional[int]			=						num_hidden_layers
			_UpperCamelCase   :		Any			=						num_attention_heads
			_UpperCamelCase   :		int			=						hidden_act
			_UpperCamelCase   :		str			=						intermediate_size
			_UpperCamelCase   :		str			=						hidden_dropout_prob
			_UpperCamelCase   :		Any			=						attention_probs_dropout_prob
			_UpperCamelCase   :		Tuple			=						max_position_embeddings
			_UpperCamelCase   :		Dict			=						type_vocab_size
			_UpperCamelCase   :		str			=						initializer_range
			_UpperCamelCase   :		List[Any]			=						layer_norm_eps
			_UpperCamelCase   :		Tuple			=						pruning_method
			_UpperCamelCase   :		Tuple			=						mask_init
			_UpperCamelCase   :		Dict			=						mask_scale




