




class       _A				:






		def __init__(    self						,		_SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			val
								_UpperCAmelCase      =			None
								_UpperCAmelCase      =			None






		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE			):
								if self.val:
														if val < self.val:
																				if self.left is None:
																										_UpperCAmelCase      =			Node(_SCREAMING_SNAKE_CASE			)
																				else:
																										self.left.insert(_SCREAMING_SNAKE_CASE			)
														elif val > self.val:
																				if self.right is None:
																										_UpperCAmelCase      =			Node(_SCREAMING_SNAKE_CASE			)
																				else:
																										self.right.insert(_SCREAMING_SNAKE_CASE			)
								else:
														_UpperCAmelCase      =			val




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case       )						->				List[Any]:
						# Recursive traversal
						if root:
												inorder(root.left			,     snake_case       )
												res.append(root.val       )
												inorder(root.right			,     snake_case       )




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				Optional[Any]:
						# Build BST
						if len(snake_case       ) == 0:
												return arr
						_UpperCAmelCase      =			Node(arr[0]       )
						for i in range(1			,     len(snake_case       )       ):
												root.insert(arr[i]       )
						# Traverse BST in order.
						_UpperCAmelCase      =			[]
						inorder(snake_case			,     snake_case       )
						return res


if __name__ == "__main__":
				print(tree_sort([10, 1, 3, 2, 9, 14, 13]))





import logging

from transformers.configuration_utils import PretrainedConfig


a													=			logging.getLogger(__name__)




class       _A				(		__lowercase     ):
		__a					    =       """masked_bert"""






		def __init__(    self						,		_SCREAMING_SNAKE_CASE=3_0522						,		_SCREAMING_SNAKE_CASE=768						,		_SCREAMING_SNAKE_CASE=12						,		_SCREAMING_SNAKE_CASE=12						,		_SCREAMING_SNAKE_CASE=3072						,		_SCREAMING_SNAKE_CASE="gelu"						,		_SCREAMING_SNAKE_CASE=0.1						,		_SCREAMING_SNAKE_CASE=0.1						,		_SCREAMING_SNAKE_CASE=512						,		_SCREAMING_SNAKE_CASE=2						,		_SCREAMING_SNAKE_CASE=0.02						,		_SCREAMING_SNAKE_CASE=1e-12						,		_SCREAMING_SNAKE_CASE=0						,		_SCREAMING_SNAKE_CASE="topK"						,		_SCREAMING_SNAKE_CASE="constant"						,		_SCREAMING_SNAKE_CASE=0.0						,		**_SCREAMING_SNAKE_CASE						,		):
								super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE						,		**_SCREAMING_SNAKE_CASE			)

								_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