


'''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:
       __lowercase:		Dict    						=  None


__lowercase:		str    						=  logging.get_logger(__name__)

__lowercase:		Optional[int]    						=  {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

__lowercase:		Optional[int]    						=  {
    "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"
        ),
    },
}

__lowercase:		Union[str, Any]    						=  {
    "xlm-roberta-base": 512,
    "xlm-roberta-large": 512,
    "xlm-roberta-large-finetuned-conll02-dutch": 512,
    "xlm-roberta-large-finetuned-conll02-spanish": 512,
    "xlm-roberta-large-finetuned-conll03-english": 512,
    "xlm-roberta-large-finetuned-conll03-german": 512,
}







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):
 _lowerCamelCase			:       Union[str, Any]            =       VOCAB_FILES_NAMES
 _lowerCamelCase			:       Optional[int]            =       PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase			:       str            =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase			:       List[str]            =       ['input_ids', 'attention_mask']
 _lowerCamelCase			:       Dict            =       XLMRobertaTokenizer

 def __init__(			self			:						List[str],       a_			:						List[str]=None,       a_			:						Any=None,       a_			:						Any="<s>",       a_			:						List[str]="</s>",       a_			:						int="</s>",       a_			:						Dict="<s>",       a_			:						Tuple="<unk>",       a_			:						List[str]="<pad>",       a_			:						str="<mask>",       **a_			:						str,       ):





    """simple docstring"""



    UpperCamelCase__			    =    AddedToken(a_,       lstrip=a_,       rstrip=a_       ) if isinstance(a_,       a_       ) else mask_token

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

    UpperCamelCase__			    =    vocab_file
    UpperCamelCase__			    =    False if not self.vocab_file else True

 def 		lowercase_    (			self			:						int,       a_			:						List[int],       a_			:						Optional[List[int]] = None       ):





    """simple docstring"""



    if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
    UpperCamelCase__			    =    [self.cls_token_id]
    UpperCamelCase__			    =    [self.sep_token_id]
    return cls + token_ids_a + sep + sep + token_ids_a + sep

 def 		lowercase_    (			self			:						List[str],       a_			:						List[int],       a_			:						Optional[List[int]] = None       ):





    """simple docstring"""



    UpperCamelCase__			    =    [self.sep_token_id]
    UpperCamelCase__			    =    [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 		lowercase_    (			self			:						Dict,       a_			:						str,       a_			:						Optional[str] = None       ):





    """simple docstring"""



    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(a_       ):
       logger.error(f'Vocabulary path ({save_directory}) should be a directory.'       )
       return
    UpperCamelCase__			    =    os.path.join(
        a_,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )

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

    return (out_vocab_file,)
'''simple docstring'''


from __future__ import annotations

snake_case__	:     str      =    [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]






class 	__SCREAMING_SNAKE_CASE		:







  '''simple docstring'''






  def __init__(					self ,						snake_case_		):




       '''simple docstring'''

       UpperCAmelCase_				:  int  = -1
       UpperCAmelCase_				:  int  = -1
       UpperCAmelCase_				:  list[int]  = [-1] * length
       UpperCAmelCase_				:  Node | None  = None
       UpperCAmelCase_				:  Node | None  = None






  def __repr__(					self		):




       '''simple docstring'''

       return F'''Node(min_value={self.minn} max_value={self.maxx})'''







def    _lowerCamelCase       ( lowerCamelCase_   :				list[int]  ):



     """simple docstring"""





     UpperCAmelCase_				:  List[str]  = Node(len(lowerCamelCase_  )  )
     UpperCAmelCase_  ,     UpperCAmelCase_				:  Any  = min(lowerCamelCase_  ), max(lowerCamelCase_  )
     # Leaf node case where the node contains only one unique value
     if root.minn == root.maxx:
          return root
     UpperCAmelCase_				:  str  = (root.minn + root.maxx) // 2

     UpperCAmelCase_				:  list[int]  = []
     UpperCAmelCase_				:  list[int]  = []

     for index, num in enumerate(lowerCamelCase_  ):
          if num <= pivot:
               left_arr.append(lowerCamelCase_  )
          else:
               right_arr.append(lowerCamelCase_  )
          UpperCAmelCase_				:  Tuple  = len(lowerCamelCase_  )
     UpperCAmelCase_				:  Optional[Any]  = build_tree(lowerCamelCase_  )
     UpperCAmelCase_				:  Optional[Any]  = build_tree(lowerCamelCase_  )
     return root


def    _lowerCamelCase       ( lowerCamelCase_   :				Node | None      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int  ):



     """simple docstring"""





     if index < 0 or node is None:
          return 0
     # Leaf node cases
     if node.minn == node.maxx:
          return index + 1 if node.minn == num else 0
     UpperCAmelCase_				:  Any  = (node.minn + node.maxx) // 2
     if num <= pivot:
          # go the left subtree and map index to the left subtree
          return rank_till_index(node.left      ,	lowerCamelCase_      ,	node.map_left[index] - 1  )
     else:
          # go to the right subtree and map index to the right subtree
          return rank_till_index(node.right      ,	lowerCamelCase_      ,	index - node.map_left[index]  )


def    _lowerCamelCase       ( lowerCamelCase_   :				Node | None      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int  ):



     """simple docstring"""





     if start > end:
          return 0
     UpperCAmelCase_				:  int  = rank_till_index(lowerCamelCase_      ,	lowerCamelCase_      ,	lowerCamelCase_  )
     UpperCAmelCase_				:  List[Any]  = rank_till_index(lowerCamelCase_      ,	lowerCamelCase_      ,	start - 1  )
     return rank_till_end - rank_before_start


def    _lowerCamelCase       ( lowerCamelCase_   :				Node | None      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int  ):



     """simple docstring"""





     if index > (end - start) or start > end or node is None:
          return -1
     # Leaf node case
     if node.minn == node.maxx:
          return node.minn
     # Number of elements in the left subtree in interval [start, end]
     UpperCAmelCase_				:  Tuple  = node.map_left[end] - (
         node.map_left[start - 1] if start else 0
     )
     if num_elements_in_left_tree > index:
          return quantile(
              node.left      ,	lowerCamelCase_      ,	(node.map_left[start - 1] if start else 0)      ,	node.map_left[end] - 1      ,	)
     else:
          return quantile(
              node.right      ,	index - num_elements_in_left_tree      ,	start - (node.map_left[start - 1] if start else 0)      ,	end - node.map_left[end]      ,	)


def    _lowerCamelCase       ( lowerCamelCase_   :				Node | None      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int      ,	lowerCamelCase_   :				int  ):



     """simple docstring"""





     if (
         start > end
         or node is None
         or start_num > end_num
         or node.minn > end_num
         or node.maxx < start_num
     ):
          return 0
     if start_num <= node.minn and node.maxx <= end_num:
          return end - start + 1
     UpperCAmelCase_				:  Any  = range_counting(
         node.left      ,	(node.map_left[start - 1] if start else 0)      ,	node.map_left[end] - 1      ,	lowerCamelCase_      ,	lowerCamelCase_      ,	)
     UpperCAmelCase_				:  List[str]  = range_counting(
         node.right      ,	start - (node.map_left[start - 1] if start else 0)      ,	end - node.map_left[end]      ,	lowerCamelCase_      ,	lowerCamelCase_      ,	)
     return left + right


if __name__ == "__main__":
 import doctest

 doctest.testmod()






