




from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any




@dataclass
class 		__A      :
						UpperCamelCase     						=					42
						UpperCamelCase     						=					None
						UpperCamelCase     						=					None




def 		lowerCAmelCase_   (	):
				__magic_name__	:	Optional[Any]								=Node(1   )
				__magic_name__	:	Union[str, Any]								=Node(2   )
				__magic_name__	:	Optional[int]								=Node(3   )
				__magic_name__	:	Optional[int]								=Node(4   )
				__magic_name__	:	List[Any]								=Node(5   )
				return tree




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				return [root.data, *preorder(root.left   ), *preorder(root.right   )] if root else []




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				return postorder(root.left   ) + postorder(root.right   ) + [root.data] if root else []




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				return [*inorder(root.left   ), root.data, *inorder(root.right   )] if root else []




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				return (max(height(root.left   )	,     height(root.right   )   ) + 1) if root else 0




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				__magic_name__	:	list[Any]								=[]

				if root is None:
								return output

				__magic_name__	:	int								=deque([root]   )

				while process_queue:
								__magic_name__	:	int								=process_queue.popleft()
								output.append(node.data   )

								if node.left:
												process_queue.append(node.left   )
								if node.right:
												process_queue.append(node.right   )
				return output




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				__magic_name__	:	list[Any]								=[]

				def populate_output(lowerCamelCase	,     lowerCamelCase   ) -> None:
								if not root:
												return
								if level == 1:
												output.append(root.data   )
								elif level > 1:
												populate_output(root.left	,     level - 1   )
												populate_output(root.right	,     level - 1   )

				populate_output(lowerCamelCase__	,     lowerCamelCase__   )
				return output




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				__magic_name__	:	list[Any]								=[]

				def populate_output(lowerCamelCase	,     lowerCamelCase   ) -> None:
								if root is None:
												return
								if level == 1:
												output.append(root.data   )
								elif level > 1:
												populate_output(root.right	,     level - 1   )
												populate_output(root.left	,     level - 1   )

				populate_output(lowerCamelCase__	,     lowerCamelCase__   )
				return output




def 		lowerCAmelCase_   (	lowerCamelCase   ):


				if root is None:
								return []

				__magic_name__	:	list[Sequence[Node | None]]								=[]

				__magic_name__	:	str								=0
				__magic_name__	:	Tuple								=height(lowerCamelCase__   )

				for h in range(1	,     height_tree + 1   ):
								if not flag:
												output.append(get_nodes_from_left_to_right(lowerCamelCase__	,     lowerCamelCase__   )   )
												__magic_name__	:	Union[str, Any]								=1
								else:
												output.append(get_nodes_from_right_to_left(lowerCamelCase__	,     lowerCamelCase__   )   )
												__magic_name__	:	Optional[int]								=0

				return output




def 		lowerCAmelCase_   (	):  # Main function for testing.
				__magic_name__	:	int								=make_tree()
				print(F"In-order Traversal: {inorder(lowerCamelCase__   )}"   )
				print(F"Pre-order Traversal: {preorder(lowerCamelCase__   )}"   )
				print(F"Post-order Traversal: {postorder(lowerCamelCase__   )}"	,     """\n"""   )

				print(F"Height of Tree: {height(lowerCamelCase__   )}"	,     """\n"""   )

				print("""Complete Level Order Traversal: """   )
				print(level_order(lowerCamelCase__   )	,     """\n"""   )

				print("""Level-wise order Traversal: """   )

				for level in range(1	,     height(lowerCamelCase__   ) + 1   ):
								print(F"Level {level}:"	,     get_nodes_from_left_to_right(lowerCamelCase__	,     level=lowerCamelCase__   )   )

				print("""\nZigZag order Traversal: """   )
				print(zigzag(lowerCamelCase__   )   )


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()










from ... import PretrainedConfig


UpperCAmelCase_		:				List[str]									=     {
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}




class 		__A      (			UpperCamelCase__			):
						UpperCamelCase     						=					NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
						UpperCamelCase     						=					"""nezha"""

						def __init__(		self   :List[Any]    , __snake_case   :Optional[int]=2_11_28    , __snake_case   :Dict=7_68    , __snake_case   :str=12    , __snake_case   :List[Any]=12    , __snake_case   :Optional[int]=30_72    , __snake_case   :Any="gelu"    , __snake_case   :List[str]=0.1    , __snake_case   :Optional[int]=0.1    , __snake_case   :Dict=5_12    , __snake_case   :Optional[int]=64    , __snake_case   :Any=2    , __snake_case   :List[Any]=0.02    , __snake_case   :List[str]=1E-12    , __snake_case   :Any=0.1    , __snake_case   :str=0    , __snake_case   :int=2    , __snake_case   :str=3    , __snake_case   :Any=True    , **__snake_case   :Any    , ):
										'''simple docstring'''

										super().__init__(pad_token_id=__snake_case    , bos_token_id=__snake_case    , eos_token_id=__snake_case    , **__snake_case )

										__magic_name__	:	Tuple								=vocab_size
										__magic_name__	:	str								=hidden_size
										__magic_name__	:	Dict								=num_hidden_layers
										__magic_name__	:	str								=num_attention_heads
										__magic_name__	:	int								=hidden_act
										__magic_name__	:	Optional[int]								=intermediate_size
										__magic_name__	:	Union[str, Any]								=hidden_dropout_prob
										__magic_name__	:	Any								=attention_probs_dropout_prob
										__magic_name__	:	Union[str, Any]								=max_position_embeddings
										__magic_name__	:	str								=max_relative_position
										__magic_name__	:	Tuple								=type_vocab_size
										__magic_name__	:	str								=initializer_range
										__magic_name__	:	Tuple								=layer_norm_eps
										__magic_name__	:	Optional[int]								=classifier_dropout
										__magic_name__	:	List[str]								=use_cache




