






from __future__ import annotations

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


@dataclass
class 					_snake_case						:
	_A          =   42
	_A          =   None
	_A          =   None





def 					lowercase_ (    )     -> Node | None:





				'''simple docstring'''


				snake_case__      :str         =   Node(1      )
				snake_case__      :Tuple         =   Node(2      )
				snake_case__      :Optional[int]         =   Node(3      )
				snake_case__      :List[str]         =   Node(4      )
				snake_case__      :List[str]         =   Node(5      )
				return tree





def 					lowercase_ (    __snake_case     :							Node | None      )     -> list[int]:





				'''simple docstring'''


				return [root.data, *preorder(root.left      ), *preorder(root.right      )] if root else []





def 					lowercase_ (    __snake_case     :							Node | None      )     -> list[int]:





				'''simple docstring'''


				return postorder(root.left      ) + postorder(root.right      ) + [root.data] if root else []





def 					lowercase_ (    __snake_case     :							Node | None      )     -> list[int]:





				'''simple docstring'''


				return [*inorder(root.left      ), root.data, *inorder(root.right      )] if root else []





def 					lowercase_ (    __snake_case     :							Node | None      )     -> int:





				'''simple docstring'''


				return (max(height(root.left      )	,	height(root.right      )      ) + 1) if root else 0





def 					lowercase_ (    __snake_case     :							Node | None      )     -> Sequence[Node | None]:





				'''simple docstring'''


				snake_case__      :list[Any]         =   []

				if root is None:
								return output

				snake_case__      :Optional[int]         =   deque([root]      )

				while process_queue:
								snake_case__      :List[str]         =   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 					lowercase_ (    __snake_case     :							Node | None	,	__snake_case     :							int      )     -> Sequence[Node | None]:





				'''simple docstring'''


				snake_case__      :list[Any]         =   []

				def populate_output(__snake_case     :							Node | None	,	__snake_case     :							int      ) -> 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(__snake_case	,	__snake_case      )
				return output





def 					lowercase_ (    __snake_case     :							Node | None	,	__snake_case     :							int      )     -> Sequence[Node | None]:





				'''simple docstring'''


				snake_case__      :list[Any]         =   []

				def populate_output(__snake_case     :							Node | None	,	__snake_case     :							int      ) -> 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(__snake_case	,	__snake_case      )
				return output





def 					lowercase_ (    __snake_case     :							Node | None      )     -> Sequence[Node | None] | list[Any]:





				'''simple docstring'''


				if root is None:
								return []

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

				snake_case__      :List[Any]         =   0
				snake_case__      :int         =   height(__snake_case      )

				for h in range(1	,	height_tree + 1      ):
								if not flag:
												output.append(get_nodes_from_left_to_right(__snake_case	,	__snake_case      )      )
												snake_case__      :int         =   1
								else:
												output.append(get_nodes_from_right_to_left(__snake_case	,	__snake_case      )      )
												snake_case__      :Tuple         =   0

				return output





def 					lowercase_ (    )     -> None:  # Main function for testing.





				'''simple docstring'''


				snake_case__      :Optional[int]         =   make_tree()
				print(F'In-order Traversal: {inorder(__snake_case      )}'      )
				print(F'Pre-order Traversal: {preorder(__snake_case      )}'      )
				print(F'Post-order Traversal: {postorder(__snake_case      )}'	,	"\n"      )

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

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

				print("Level-wise order Traversal: "      )

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

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


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()







import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin


class 					_snake_case						(			_A       ,    _A       ,    _A ):






	@register_to_config
	def __init__(		self					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase					,UpperCamelCase = False					,)						->    int:
					super().__init__()

					snake_case__      :Union[str, Any]         =   nn.Embedding(UpperCamelCase					,UpperCamelCase       )

					snake_case__      :int         =   nn.Embedding(UpperCamelCase					,UpperCamelCase       )
					snake_case__      :Any         =   False

					snake_case__      :List[Any]         =   nn.Dropout(p=UpperCamelCase       )

					snake_case__      :Tuple         =   TaConfig(
					    vocab_size=UpperCamelCase					,d_model=UpperCamelCase					,num_heads=UpperCamelCase					,d_kv=UpperCamelCase					,d_ff=UpperCamelCase					,dropout_rate=UpperCamelCase					,feed_forward_proj=UpperCamelCase					,is_decoder=UpperCamelCase					,is_encoder_decoder=UpperCamelCase					,)

					snake_case__      :List[str]         =   nn.ModuleList()
					for lyr_num in range(UpperCamelCase       ):
									snake_case__      :List[Any]         =   TaBlock(UpperCamelCase       )
									self.encoders.append(UpperCamelCase       )

					snake_case__      :Optional[Any]         =   TaLayerNorm(UpperCamelCase       )
					snake_case__      :Any         =   nn.Dropout(p=UpperCamelCase       )






	def    lowerCAmelCase_							(		self					,UpperCamelCase					,UpperCamelCase       )						->    int:
					snake_case__      :str         =   self.token_embedder(UpperCamelCase       )

					snake_case__      :int         =   encoder_input_tokens.shape[1]
					snake_case__      :List[Any]         =   torch.arange(UpperCamelCase					,device=encoder_input_tokens.device       )
					x += self.position_encoding(UpperCamelCase       )

					snake_case__      :Optional[int]         =   self.dropout_pre(UpperCamelCase       )

					# inverted the attention mask
					snake_case__      :Optional[Any]         =   encoder_input_tokens.size()
					snake_case__      :Dict         =   self.get_extended_attention_mask(UpperCamelCase					,UpperCamelCase       )

					for lyr in self.encoders:
									snake_case__      :str         =   lyr(UpperCamelCase					,UpperCamelCase       )[0]
					snake_case__      :List[Any]         =   self.layer_norm(UpperCamelCase       )

					return self.dropout_post(UpperCamelCase       ), encoder_inputs_mask