





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     :int
      _UpperCAmelCase     :Node | None						   =       None
      _UpperCAmelCase     :Node | None						   =       None



def 		A_    (					)						->			Node | None:
 UpperCamelCase     : Union[str, Any]	     =       Node(1					)
 UpperCamelCase     : List[str]	     =       Node(2					)
 UpperCamelCase     : Any	     =       Node(3					)
 UpperCamelCase     : Union[str, Any]	     =       Node(4					)
 UpperCamelCase     : Union[str, Any]	     =       Node(5					)
 return tree



def 		A_    (					_lowerCAmelCase					)						->			list[int]:
 return [root.data, *preorder(root.left					), *preorder(root.right					)] if root else []



def 		A_    (					_lowerCAmelCase					)						->			list[int]:
 return postorder(root.left					) + postorder(root.right					) + [root.data] if root else []



def 		A_    (					_lowerCAmelCase					)						->			list[int]:
 return [*inorder(root.left					), root.data, *inorder(root.right					)] if root else []



def 		A_    (					_lowerCAmelCase					)						->			int:
 return (max(height(root.left					)							,       height(root.right					)					) + 1) if root else 0



def 		A_    (					_lowerCAmelCase					)						->			Sequence[Node | None]:
 UpperCamelCase     : Union[str, Any]	     =       []

 if root is None:
  return output

 UpperCamelCase     : int	     =       deque([root]					)

 while process_queue:
  UpperCamelCase     : List[Any]	     =       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 		A_    (					_lowerCAmelCase							,       _lowerCAmelCase					)						->			Sequence[Node | None]:
 UpperCamelCase     : Union[str, 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(a_							,       a_					)
 return output



def 		A_    (					_lowerCAmelCase							,       _lowerCAmelCase					)						->			Sequence[Node | None]:
 UpperCamelCase     : Optional[int]	     =       []

 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(a_							,       a_					)
 return output



def 		A_    (					_lowerCAmelCase					)						->			Sequence[Node | None] | list[Any]:
 if root is None:
  return []

 UpperCamelCase     : Optional[Any]	     =       []

 UpperCamelCase     : Optional[int]	     =       0
 UpperCamelCase     : Any	     =       height(a_					)

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

 return output



def 		A_    (					)						->			None:  # Main function for testing.
 UpperCamelCase     : Dict	     =       make_tree()
 print(F"""In-order Traversal: {inorder(a_					)}"""					)
 print(F"""Pre-order Traversal: {preorder(a_					)}"""					)
 print(F"""Post-order Traversal: {postorder(a_					)}"""							,       "\n"					)

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

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

 print("Level-wise order Traversal: "					)

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

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


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    main()







import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCamelCase	:					Dict			  =					get_tests_dir("""fixtures/spiece.model""")



@require_sentencepiece
@require_tokenizers
class  A__       (	__snake_case	,       unittest.TestCase      ):
      _UpperCAmelCase     :int						   =       AlbertTokenizer
      _UpperCAmelCase     :int						   =       AlbertTokenizerFast
      _UpperCAmelCase     :int						   =       True
      _UpperCAmelCase     :List[str]						   =       True
      _UpperCAmelCase     :Optional[Any]						   =       True





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       super().setUp()

       # We have a SentencePiece fixture for testing
       UpperCamelCase     : List[str]	     =       AlbertTokenizer(A_       )
       tokenizer.save_pretrained(self.tmpdirname       )





      def 	__UpperCamelCase(			self	,							A_       ):
       '''simple docstring'''




       UpperCamelCase     : List[Any]	     =       "this is a test"
       UpperCamelCase     : List[Any]	     =       "this is a test"
       return input_text, output_text





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Union[str, Any]	     =       "<pad>"
       UpperCamelCase     : Dict	     =       0

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(A_       )	,							A_       )
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(A_       )	,							A_       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Dict	     =       list(self.get_tokenizer().get_vocab().keys()       )

       self.assertEqual(vocab_keys[0]	,							"<pad>"       )
       self.assertEqual(vocab_keys[1]	,							"<unk>"       )
       self.assertEqual(vocab_keys[-1]	,							"▁eloquent"       )
       self.assertEqual(len(A_       )	,							3_0000       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       self.assertEqual(self.get_tokenizer().vocab_size	,							3_0000       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       if not self.test_rust_tokenizer:
        return

       UpperCamelCase     : Any	     =       self.get_tokenizer()
       UpperCamelCase     : Optional[int]	     =       self.get_rust_tokenizer()

       UpperCamelCase     : List[Any]	     =       "I was born in 92000, and this is falsé."

       UpperCamelCase     : Optional[Any]	     =       tokenizer.tokenize(A_       )
       UpperCamelCase     : Optional[int]	     =       rust_tokenizer.tokenize(A_       )
       self.assertListEqual(A_	,							A_       )

       UpperCamelCase     : Optional[Any]	     =       tokenizer.encode(A_	,							add_special_tokens=A_       )
       UpperCamelCase     : Optional[int]	     =       rust_tokenizer.encode(A_	,							add_special_tokens=A_       )
       self.assertListEqual(A_	,							A_       )

       UpperCamelCase     : List[Any]	     =       self.get_rust_tokenizer()
       UpperCamelCase     : Union[str, Any]	     =       tokenizer.encode(A_       )
       UpperCamelCase     : Optional[int]	     =       rust_tokenizer.encode(A_       )
       self.assertListEqual(A_	,							A_       )





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : List[Any]	     =       AlbertTokenizer(A_	,							keep_accents=A_       )

       UpperCamelCase     : Optional[int]	     =       tokenizer.tokenize("This is a test"       )
       self.assertListEqual(A_	,							["▁this", "▁is", "▁a", "▁test"]       )

       self.assertListEqual(tokenizer.convert_tokens_to_ids(A_       )	,							[48, 25, 21, 1289]       )

       UpperCamelCase     : Optional[Any]	     =       tokenizer.tokenize("I was born in 92000, and this is falsé."       )
       self.assertListEqual(
           A_	,							["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]       )
       UpperCamelCase     : Optional[int]	     =       tokenizer.convert_tokens_to_ids(A_       )
       self.assertListEqual(A_	,							[31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]       )

       UpperCamelCase     : List[str]	     =       tokenizer.convert_ids_to_tokens(A_       )
       self.assertListEqual(
           A_	,							["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]	,							)





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Optional[int]	     =       AlbertTokenizer(A_       )

       UpperCamelCase     : Dict	     =       tokenizer.encode("sequence builders"       )
       UpperCamelCase     : Tuple	     =       tokenizer.encode("multi-sequence build"       )

       UpperCamelCase     : str	     =       tokenizer.build_inputs_with_special_tokens(A_       )
       UpperCamelCase     : int	     =       tokenizer.build_inputs_with_special_tokens(A_	,							A_       )

       assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
       assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
           tokenizer.sep_token_id
       ]





      @slow
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : List[Any]	     =       {"attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "input_ids": [[2, 2_1970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 1_2051, 18, 17, 7103, 2153, 673, 8, 3515, 1_8684, 8, 4461, 6, 1927, 297, 8, 1_2060, 2607, 18, 13, 5, 4461, 15, 1_0538, 38, 8, 135, 15, 822, 58, 15, 993, 1_0363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 1_0641, 6, 29, 84, 2512, 2430, 782, 1_8684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 1_1712, 15, 7103, 2153, 673, 17, 2_4883, 9990, 9, 3], [2, 1_1502, 25, 1006, 20, 782, 8, 1_1809, 855, 1732, 1_9393, 1_8667, 37, 367, 2_1018, 69, 1854, 34, 1_1860, 1_9124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 14, 2231, 886, 2385, 1_7659, 84, 14, 1_6792, 1952, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=A_	,							model_name="albert-base-v2"	,							revision="6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"	,							)
