





from __future__ import annotations

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

@dataclass
class    _UpperCAmelCase							:
      a						       =							42
      a						       =							None
      a						       =							None






def     _lowerCAmelCase		(  ):
   '''simple docstring'''


   A_     :				Optional[int]			      =	Node(1     )
   A_     :				Dict			      =	Node(2     )
   A_     :				Union[str, Any]			      =	Node(3     )
   A_     :				Any			      =	Node(4     )
   A_     :				Union[str, Any]			      =	Node(5     )
   return tree



def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


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



def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


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



def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


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



def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


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



def     _lowerCAmelCase		(  _lowerCAmelCase     ):
   '''simple docstring'''


   A_     :				list[Any]			      =	[]

   if root is None:
      return output

   A_     :				Optional[Any]			      =	deque([root]     )

   while process_queue:
      A_     :				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     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   A_     :				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     ):
   '''simple docstring'''


   A_     :				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     ):
   '''simple docstring'''


   if root is None:
      return []

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

   A_     :				Optional[Any]			      =	0
   A_     :				Union[str, Any]			      =	height(_lowerCAmelCase     )

   for h in range(1  ,height_tree + 1     ):
      if not flag:
         output.append(get_nodes_from_left_to_right(_lowerCAmelCase  ,_lowerCAmelCase     )     )
         A_     :				List[Any]			      =	1
      else:
         output.append(get_nodes_from_right_to_left(_lowerCAmelCase  ,_lowerCAmelCase     )     )
         A_     :				int			      =	0

   return output



def     _lowerCAmelCase		(  ):  # Main function for testing.
   '''simple docstring'''


   A_     :				Dict			      =	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 ....configuration_utils import PretrainedConfig
from ....utils import logging


_lowerCAmelCase 				=     logging.get_logger(__name__)

# TODO: upload to AWS
_lowerCAmelCase 				=     {
    """yjernite/retribert-base-uncased""": (
        """https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json"""
    ),
}

class    _UpperCAmelCase							(		_lowerCamelCase     ):
      a						       =							'''retribert'''
      def __init__(		self      ,       a__=30522      ,       a__=768      ,       a__=8      ,       a__=12      ,       a__=3072      ,       a__="gelu"      ,       a__=0.1      ,       a__=0.1      ,       a__=512      ,       a__=2      ,       a__=0.02      ,       a__=1E-12      ,       a__=True      ,       a__=128      ,       a__=0      ,       **a__      ,       ):
         super().__init__(pad_token_id=a__      ,       **a__       )

         A_     :				Union[str, Any]			      =	vocab_size
         A_     :				Optional[Any]			      =	hidden_size
         A_     :				Optional[Any]			      =	num_hidden_layers
         A_     :				List[str]			      =	num_attention_heads
         A_     :				Optional[int]			      =	hidden_act
         A_     :				Any			      =	intermediate_size
         A_     :				Tuple			      =	hidden_dropout_prob
         A_     :				Optional[Any]			      =	attention_probs_dropout_prob
         A_     :				Dict			      =	max_position_embeddings
         A_     :				Dict			      =	type_vocab_size
         A_     :				List[str]			      =	initializer_range
         A_     :				Optional[int]			      =	layer_norm_eps
         A_     :				Optional[Any]			      =	share_encoders
         A_     :				Dict			      =	projection_dim






