





from __future__ import annotations





def       _UpperCamelCase       (a__				:Tuple    ):






							"""simple docstring"""





							if len(lowerCAmelCase_    ) == 0:
														return []
							UpperCamelCase__			       =     min(lowerCAmelCase_    ), max(lowerCAmelCase_    )
							UpperCamelCase__			       =     int(max_value - min_value    ) + 1
							UpperCamelCase__			       =     [[] for _ in range(lowerCAmelCase_    )]

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

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


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, -10, 15, 2, -2]) == [-10, -2, 0, 1, 2, 15]











import logging

from transformers.configuration_utils import PretrainedConfig


UpperCamelCase__     =	logging.getLogger(__name__)

class     __SCREAMING_SNAKE_CASE   (       _a    ):
							snake_case       : Optional[Any]         =    """masked_bert"""






							def __init__(  self					,	__lowerCAmelCase=30522					,	__lowerCAmelCase=768					,	__lowerCAmelCase=12					,	__lowerCAmelCase=12					,	__lowerCAmelCase=3072					,	__lowerCAmelCase="gelu"					,	__lowerCAmelCase=0.1					,	__lowerCAmelCase=0.1					,	__lowerCAmelCase=512					,	__lowerCAmelCase=2					,	__lowerCAmelCase=0.02					,	__lowerCAmelCase=1E-12					,	__lowerCAmelCase=0					,	__lowerCAmelCase="topK"					,	__lowerCAmelCase="constant"					,	__lowerCAmelCase=0.0					,	**__lowerCAmelCase					,	):
														super().__init__(pad_token_id=__lowerCAmelCase					,	**__lowerCAmelCase					)

														UpperCamelCase__			       =     vocab_size
														UpperCamelCase__			       =     hidden_size
														UpperCamelCase__			       =     num_hidden_layers
														UpperCamelCase__			       =     num_attention_heads
														UpperCamelCase__			       =     hidden_act
														UpperCamelCase__			       =     intermediate_size
														UpperCamelCase__			       =     hidden_dropout_prob
														UpperCamelCase__			       =     attention_probs_dropout_prob
														UpperCamelCase__			       =     max_position_embeddings
														UpperCamelCase__			       =     type_vocab_size
														UpperCamelCase__			       =     initializer_range
														UpperCamelCase__			       =     layer_norm_eps
														UpperCamelCase__			       =     pruning_method
														UpperCamelCase__			       =     mask_init
														UpperCamelCase__			       =     mask_scale




