"""simple docstring"""






import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_xlm_roberta import XLMRobertaTokenizer
else:
				UpperCamelCase     					=     None


UpperCamelCase     					=     logging.get_logger(__name__)

UpperCamelCase     					=     {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase     					=     {
    'vocab_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'
        ),
    },
}

UpperCamelCase     					=     {
    'xlm-roberta-base': 5_12,
    'xlm-roberta-large': 5_12,
    'xlm-roberta-large-finetuned-conll02-dutch': 5_12,
    'xlm-roberta-large-finetuned-conll02-spanish': 5_12,
    'xlm-roberta-large-finetuned-conll03-english': 5_12,
    'xlm-roberta-large-finetuned-conll03-german': 5_12,
}
class   UpperCAmelCase__				(    __lowerCamelCase			):


	"""simple docstring"""
	lowerCAmelCase__    :					List[Any]						      =							VOCAB_FILES_NAMES
	lowerCAmelCase__    :					Tuple						      =							PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase__    :					Union[str, Any]						      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase__    :					int						      =							["""input_ids""", """attention_mask"""]
	lowerCAmelCase__    :					Optional[Any]						      =							XLMRobertaTokenizer







	def __init__(			self       ,     _SCREAMING_SNAKE_CASE=None       ,     _SCREAMING_SNAKE_CASE=None       ,     _SCREAMING_SNAKE_CASE="<s>"       ,     _SCREAMING_SNAKE_CASE="</s>"       ,     _SCREAMING_SNAKE_CASE="</s>"       ,     _SCREAMING_SNAKE_CASE="<s>"       ,     _SCREAMING_SNAKE_CASE="<unk>"       ,     _SCREAMING_SNAKE_CASE="<pad>"       ,     _SCREAMING_SNAKE_CASE="<mask>"       ,     **_SCREAMING_SNAKE_CASE       ,     )    ->	List[Any]:
							# Mask token behave like a normal word, i.e. include the space before it
							a_							:			Any     		=					AddedToken(_SCREAMING_SNAKE_CASE       ,     lstrip=_SCREAMING_SNAKE_CASE       ,     rstrip=_SCREAMING_SNAKE_CASE ) if isinstance(_SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE ) else mask_token

							super().__init__(
							    _SCREAMING_SNAKE_CASE       ,     tokenizer_file=_SCREAMING_SNAKE_CASE       ,     bos_token=_SCREAMING_SNAKE_CASE       ,     eos_token=_SCREAMING_SNAKE_CASE       ,     sep_token=_SCREAMING_SNAKE_CASE       ,     cls_token=_SCREAMING_SNAKE_CASE       ,     unk_token=_SCREAMING_SNAKE_CASE       ,     pad_token=_SCREAMING_SNAKE_CASE       ,     mask_token=_SCREAMING_SNAKE_CASE       ,     **_SCREAMING_SNAKE_CASE       ,     )

							a_							:			Any     		=					vocab_file
							a_							:			Optional[Any]     		=					False if not self.vocab_file else True







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE = None )    ->	List[int]:

							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							a_							:			Union[str, Any]     		=					[self.cls_token_id]
							a_							:			int     		=					[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE = None )    ->	List[int]:
							a_							:			List[str]     		=					[self.sep_token_id]
							a_							:			List[str]     		=					[self.cls_token_id]

							if token_ids_a is None:
													return len(cls + token_ids_a + sep ) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE = None )    ->	Tuple[str]:
							if not self.can_save_slow_tokenizer:
													raise ValueError(
													    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
													    "tokenizer." )

							if not os.path.isdir(_SCREAMING_SNAKE_CASE ):
													logger.error(f'''Vocabulary path ({save_directory}) should be a directory.''' )
													return
							a_							:			str     		=					os.path.join(
							    _SCREAMING_SNAKE_CASE       ,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )

							if os.path.abspath(self.vocab_file ) != os.path.abspath(_SCREAMING_SNAKE_CASE ):
													copyfile(self.vocab_file       ,     _SCREAMING_SNAKE_CASE )

							return (out_vocab_file,)





"""simple docstring"""






from __future__ import annotations

from queue import Queue

def  lowerCAmelCase_      (_SCREAMING_SNAKE_CASE	:int		,			_SCREAMING_SNAKE_CASE	:int  )				-> tuple[int, int]:
						a ^= b
						b ^= a
						a ^= b
						return a, b

def  lowerCAmelCase_      (_SCREAMING_SNAKE_CASE	:int		,			_SCREAMING_SNAKE_CASE	:list[list[int]]  )				-> list[list[int]]:
						a_							:			List[str]     		=					1
						while (1 << j) < max_node:
												for i in range(1		,			max_node + 1  ):
																		a_							:			Union[str, Any]     		=					parent[j - 1][parent[j - 1][i]]
												j += 1
						return parent

def  lowerCAmelCase_      (_SCREAMING_SNAKE_CASE	:int		,			_SCREAMING_SNAKE_CASE	:int		,			_SCREAMING_SNAKE_CASE	:list[int]		,			_SCREAMING_SNAKE_CASE	:list[list[int]]  )				-> int:
						# u must be deeper in the tree than v
						if level[u] < level[v]:
												a_		,					a_							:			Tuple     		=					swap(_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )
						# making depth of u same as depth of v
						for i in range(18		,			-1		,			-1  ):
												if level[u] - (1 << i) >= level[v]:
																		a_							:			Union[str, Any]     		=					parent[i][u]
    # at the same depth if u==v that mean lca is found
						if u == v:
												return u
						# moving both nodes upwards till lca in found
						for i in range(18		,			-1		,			-1  ):
												if parent[i][u] not in [0, parent[i][v]]:
																		a_		,					a_							:			Optional[Any]     		=					parent[i][u], parent[i][v]
    # returning longest common ancestor of u,v
						return parent[0][u]

def  lowerCAmelCase_      (_SCREAMING_SNAKE_CASE	:list[int]		,			_SCREAMING_SNAKE_CASE	:list[list[int]]		,			_SCREAMING_SNAKE_CASE	:int		,			_SCREAMING_SNAKE_CASE	:dict[int, list[int]]		,			_SCREAMING_SNAKE_CASE	:int = 1		,			)				-> tuple[list[int], list[list[int]]]:
						a_							:			List[Any]     		=					0
						a_							:			Queue[int]     		=					Queue(maxsize=_SCREAMING_SNAKE_CASE  )
						q.put(_SCREAMING_SNAKE_CASE  )
						while q.qsize() != 0:
												a_							:			List[str]     		=					q.get()
												for v in graph[u]:
																		if level[v] == -1:
																								a_							:			Tuple     		=					level[u] + 1
																								q.put(_SCREAMING_SNAKE_CASE  )
																								a_							:			Optional[int]     		=					u
						return level, parent

def  lowerCAmelCase_      ()				-> None:
						a_							:			List[Any]     		=					13
						# initializing with 0
						a_							:			Dict     		=					[[0 for _ in range(max_node + 10  )] for _ in range(20  )]
						# initializing with -1 which means every node is unvisited
						a_							:			Optional[int]     		=					[-1 for _ in range(max_node + 10  )]
						a_							:			dict[int, list[int]]     		=					{
						    1: [2, 3, 4],
						    2: [5],
						    3: [6, 7],
						    4: [8],
						    5: [9, 10],
						    6: [11],
						    7: [],
						    8: [12, 13],
						    9: [],
						    10: [],
						    11: [],
						    12: [],
						    13: [],
						}
						a_		,					a_							:			Any     		=					breadth_first_search(_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE		,			1  )
						a_							:			Any     		=					create_sparse(_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )
						print("LCA of node 1 and 3 is: "		,			lowest_common_ancestor(1		,			3		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )  )
						print("LCA of node 5 and 6 is: "		,			lowest_common_ancestor(5		,			6		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )  )
						print("LCA of node 7 and 11 is: "		,			lowest_common_ancestor(7		,			11		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )  )
						print("LCA of node 6 and 7 is: "		,			lowest_common_ancestor(6		,			7		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )  )
						print("LCA of node 4 and 12 is: "		,			lowest_common_ancestor(4		,			12		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )  )
						print("LCA of node 8 and 8 is: "		,			lowest_common_ancestor(8		,			8		,			_SCREAMING_SNAKE_CASE		,			_SCREAMING_SNAKE_CASE  )  )


if __name__ == "__main__":
				main()




