





from __future__ import annotations

import math
import random
from typing import Any





class 						_A:


				"""simple docstring"""


				def __init__(			self     ):
									__A	:						list[Any]       =				[]
									__A	:						int       =				0
									__A	:						int       =				0



				def 					UpperCAmelCase_		(			self     ):
									return self.head == self.tail



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									self.data.append(_A     )
									__A	:						List[str]       =				self.tail + 1



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[str]       =				self.data[self.head]
									__A	:						Tuple       =				self.head + 1
									return ret



				def 					UpperCAmelCase_		(			self     ):
									return self.tail - self.head





				def 					UpperCAmelCase_		(			self     ):
									print(self.data     )
									print('**************'     )
									print(self.data[self.head : self.tail]     )





class 						_A:


				"""simple docstring"""


				def __init__(			self     ,					_A     ):
									__A	:						Any       =				data
									__A	:						MyNode | None       =				None
									__A	:						MyNode | None       =				None
									__A	:						int       =				1



				def 					UpperCAmelCase_		(			self     ):
									return self.data



				def 					UpperCAmelCase_		(			self     ):
									return self.left



				def 					UpperCAmelCase_		(			self     ):
									return self.right



				def 					UpperCAmelCase_		(			self     ):
									return self.height



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									__A	:						Dict       =				data



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									__A	:						Optional[int]       =				node



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									__A	:						List[str]       =				node





				def 					UpperCAmelCase_		(			self     ,					_A     ):
									__A	:						int       =				height







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      int:
					if node is None:
										return 0
					return node.get_height()







def  _SCREAMING_SNAKE_CASE				(   a					,						a  )      ->      int:
					if a > b:
										return a
					return b







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      MyNode:
					print('left rotation node:'					,						node.get_data()  )
					__A	:						int       =				node.get_left()
					assert ret is not None
					node.set_left(ret.get_right()  )
					ret.set_right(a  )
					__A	:						List[Any]       =				my_max(get_height(node.get_right()  )					,						get_height(node.get_left()  )  ) + 1
					node.set_height(a  )
					__A	:						int       =				my_max(get_height(ret.get_right()  )					,						get_height(ret.get_left()  )  ) + 1
					ret.set_height(a  )
					return ret







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      MyNode:
					print('right rotation node:'					,						node.get_data()  )
					__A	:						Optional[int]       =				node.get_right()
					assert ret is not None
					node.set_right(ret.get_left()  )
					ret.set_left(a  )
					__A	:						Dict       =				my_max(get_height(node.get_right()  )					,						get_height(node.get_left()  )  ) + 1
					node.set_height(a  )
					__A	:						Tuple       =				my_max(get_height(ret.get_right()  )					,						get_height(ret.get_left()  )  ) + 1
					ret.set_height(a  )
					return ret







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      MyNode:
					__A	:						List[Any]       =				node.get_left()
					assert left_child is not None
					node.set_left(left_rotation(a  )  )
					return right_rotation(a  )







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      MyNode:
					__A	:						Tuple       =				node.get_right()
					assert right_child is not None
					node.set_right(right_rotation(a  )  )
					return left_rotation(a  )







def  _SCREAMING_SNAKE_CASE				(   a					,						a  )      ->      MyNode | None:
					if node is None:
										return MyNode(a  )
					if data < node.get_data():
										node.set_left(insert_node(node.get_left()					,						a  )  )
										if (
										    get_height(node.get_left()  ) - get_height(node.get_right()  ) == 2
										):  # an unbalance detected
															__A	:						Optional[Any]       =				node.get_left()
															assert left_child is not None
															if (
															    data < left_child.get_data()
															):  # new node is the left child of the left child
																				__A	:						Optional[Any]       =				right_rotation(a  )
															else:
																				__A	:						Optional[Any]       =				lr_rotation(a  )
					else:
										node.set_right(insert_node(node.get_right()					,						a  )  )
										if get_height(node.get_right()  ) - get_height(node.get_left()  ) == 2:
															__A	:						Tuple       =				node.get_right()
															assert right_child is not None
															if data < right_child.get_data():
																				__A	:						int       =				rl_rotation(a  )
															else:
																				__A	:						int       =				left_rotation(a  )
					__A	:						Any       =				my_max(get_height(node.get_right()  )					,						get_height(node.get_left()  )  ) + 1
					node.set_height(a  )
					return node







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      Any:
					while True:
										__A	:						int       =				root.get_right()
										if right_child is None:
															break
										__A	:						Any       =				right_child
					return root.get_data()







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      Any:
					while True:
										__A	:						Tuple       =				root.get_left()
										if left_child is None:
															break
										__A	:						str       =				left_child
					return root.get_data()







def  _SCREAMING_SNAKE_CASE				(   a					,						a  )      ->      MyNode | None:
					__A	:						str       =				root.get_left()
					__A	:						List[str]       =				root.get_right()
					if root.get_data() == data:
										if left_child is not None and right_child is not None:
															__A	:						str       =				get_left_most(a  )
															root.set_data(a  )
															root.set_right(del_node(a					,						a  )  )
										elif left_child is not None:
															__A	:						Any       =				left_child
										elif right_child is not None:
															__A	:						Tuple       =				right_child
										else:
															return None
					elif root.get_data() > data:
										if left_child is None:
															print('No such data'  )
															return root
										else:
															root.set_left(del_node(a					,						a  )  )
					else:  # root.get_data() < data
										if right_child is None:
															return root
										else:
															root.set_right(del_node(a					,						a  )  )

					if get_height(a  ) - get_height(a  ) == 2:
										assert right_child is not None
										if get_height(right_child.get_right()  ) > get_height(right_child.get_left()  ):
															__A	:						Any       =				left_rotation(a  )
										else:
															__A	:						str       =				rl_rotation(a  )
					elif get_height(a  ) - get_height(a  ) == -2:
										assert left_child is not None
										if get_height(left_child.get_left()  ) > get_height(left_child.get_right()  ):
															__A	:						Union[str, Any]       =				right_rotation(a  )
										else:
															__A	:						Any       =				lr_rotation(a  )
					__A	:						Dict       =				my_max(get_height(root.get_right()  )					,						get_height(root.get_left()  )  ) + 1
					root.set_height(a  )
					return root





class 						_A:


				"""simple docstring"""


				def __init__(			self     ):
									__A	:						MyNode | None       =				None



				def 					UpperCAmelCase_		(			self     ):
									return get_height(self.root     )



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									print('insert:' + str(_A     )     )
									__A	:						int       =				insert_node(self.root     ,					_A     )



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									print('delete:' + str(_A     )     )
									if self.root is None:
														print('Tree is empty!'     )
														return
									__A	:						Optional[int]       =				del_node(self.root     ,					_A     )





				def __str__(			self     ,					):  # a level traversale, gives a more intuitive look on the tree
									__A	:						Dict       =				''
									__A	:						Optional[Any]       =				MyQueue()
									q.push(self.root     )
									__A	:						Dict       =				self.get_height()
									if layer == 0:
														return output
									__A	:						List[Any]       =				0
									while not q.is_empty():
														__A	:						Optional[Any]       =				q.pop()
														__A	:						Optional[Any]       =				' ' * int(math.pow(2     ,					layer - 1     )     )
														output += space
														if node is None:
																			output += "*"
																			q.push(_A     )
																			q.push(_A     )
														else:
																			output += str(node.get_data()     )
																			q.push(node.get_left()     )
																			q.push(node.get_right()     )
														output += space
														__A	:						str       =				cnt + 1
														for i in range(100     ):
																			if cnt == math.pow(2     ,					_A     ) - 1:
																								__A	:						Any       =				layer - 1
																								if layer == 0:
																													output += "\n*************************************"
																													return output
																								output += "\n"
																								break
									output += "\n*************************************"
									return output







def  _SCREAMING_SNAKE_CASE				(   )      ->      None:
					import doctest

					doctest.testmod()


if __name__ == "__main__":
				_test()
				UpperCAmelCase						:   Optional[int]			  =     AVLtree()
				UpperCAmelCase						:   Any			  =     list(range(10))
				random.shuffle(lst)
				for i in lst:
								t.insert(i)
								print(str(t))
				random.shuffle(lst)
				for i in lst:
								t.del_node(i)
								print(str(t))











import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase						:   List[str]			  =     '''▁'''

UpperCAmelCase						:   Optional[Any]			  =     get_tests_dir('''fixtures/test_sentencepiece.model''')





@require_sentencepiece
class 						_A(					snake_case__				, unittest.TestCase   ):


				"""simple docstring"""


				UpperCamelCase    :  Optional[int]					    =	BertGenerationTokenizer
				UpperCamelCase    :  str					    =	False
				UpperCamelCase    :  Tuple					    =	True



				def 					UpperCAmelCase_		(			self     ):
									super().setUp()

									__A	:						Tuple       =				BertGenerationTokenizer(_A     ,					keep_accents=_A     )
									tokenizer.save_pretrained(self.tmpdirname     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				'<s>'
									__A	:						str       =				1

									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     ):
									__A	:						int       =				list(self.get_tokenizer().get_vocab().keys()     )

									self.assertEqual(vocab_keys[0]     ,					'<unk>'     )
									self.assertEqual(vocab_keys[1]     ,					'<s>'     )
									self.assertEqual(vocab_keys[-1]     ,					'<pad>'     )
									self.assertEqual(len(_A     )     ,					1002     )



				def 					UpperCAmelCase_		(			self     ):
									self.assertEqual(self.get_tokenizer().vocab_size     ,					1000     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				BertGenerationTokenizer(_A     ,					keep_accents=_A     )

									__A	:						Dict       =				tokenizer.tokenize('This is a test'     )
									self.assertListEqual(_A     ,					['▁This', '▁is', '▁a', '▁t', 'est']     )

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(_A     )     ,					[285, 46, 10, 170, 382]     ,					)

									__A	:						int       =				tokenizer.tokenize('I was born in 92000, and this is falsé.'     )
									self.assertListEqual(
									    _A     ,					[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '9',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        'é',
									        '.',
									    ]     ,					)
									__A	:						Dict       =				tokenizer.convert_tokens_to_ids(_A     )
									self.assertListEqual(
									    _A     ,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]     ,					)

									__A	:						Optional[int]       =				tokenizer.convert_ids_to_tokens(_A     )
									self.assertListEqual(
									    _A     ,					[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '<unk>',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        '<unk>',
									        '.',
									    ]     ,					)



				@cached_property
				def 					UpperCAmelCase_		(			self     ):
									return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'     )



				@slow
				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				'Hello World!'
									__A	:						Optional[Any]       =				[18536, 2260, 101]

									self.assertListEqual(_A     ,					self.big_tokenizer.encode(_A     )     )



				@slow
				def 					UpperCAmelCase_		(			self     ):
									__A	:						Dict       =				(
									    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
									    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
									)
									__A	:						int       =				[
									    871,
									    419,
									    358,
									    946,
									    991,
									    2521,
									    452,
									    358,
									    1357,
									    387,
									    7751,
									    3536,
									    112,
									    985,
									    456,
									    126,
									    865,
									    938,
									    5400,
									    5734,
									    458,
									    1368,
									    467,
									    786,
									    2462,
									    5246,
									    1159,
									    633,
									    865,
									    4519,
									    457,
									    582,
									    852,
									    2557,
									    427,
									    916,
									    508,
									    405,
									    34324,
									    497,
									    391,
									    408,
									    11342,
									    1244,
									    385,
									    100,
									    938,
									    985,
									    456,
									    574,
									    362,
									    12597,
									    3200,
									    3129,
									    1172,
									]

									self.assertListEqual(_A     ,					self.big_tokenizer.encode(_A     )     )



				@require_torch
				@slow
				def 					UpperCAmelCase_		(			self     ):
									import torch

									from transformers import BertGenerationConfig, BertGenerationEncoder

									# Build sequence
									__A	:						Tuple       =				list(self.big_tokenizer.get_vocab().keys()     )[:10]
									__A	:						List[Any]       =				' '.join(_A     )
									__A	:						Union[str, Any]       =				self.big_tokenizer.encode_plus(_A     ,					return_tensors='pt'     ,					return_token_type_ids=_A     )
									__A	:						Optional[Any]       =				self.big_tokenizer.batch_encode_plus(
									    [sequence + ' ' + sequence]     ,					return_tensors='pt'     ,					return_token_type_ids=_A     )

									__A	:						int       =				BertGenerationConfig()
									__A	:						List[str]       =				BertGenerationEncoder(_A     )

									assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

									with torch.no_grad():
														model(**_A     )
														model(**_A     )





				@slow
				def 					UpperCAmelCase_		(			self     ):
									# fmt: off
									__A	:						str       =				{'input_ids': [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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='google/bert_for_seq_generation_L-24_bbc_encoder'     ,					revision='c817d1fd1be2ffa69431227a1fe320544943d4db'     ,					)




