


'''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,)


class      lowerCamelCase_ :




 def __init__(			self  ,  _UpperCAmelCase							):
   __UpperCAmelCase	:  Any		=     data
   __UpperCAmelCase	:  BinaryTreeNode | None		=     None
   __UpperCAmelCase	:  BinaryTreeNode | None		=     None





def  _snake_case		(snake_case_					:     BinaryTreeNode | None    ,       snake_case_					:     int  )							->		BinaryTreeNode | None:
  if node is None:
    __UpperCAmelCase	:  List[Any]		=     BinaryTreeNode(snake_case_  )
    return node

  # binary search tree is not empty,
  # so we will insert it into the tree
  # if new_value is less than value of data in node,
  #  add it to left subtree and proceed recursively
  if new_value < node.data:
    __UpperCAmelCase	:  Union[str, Any]		=     insert(node.left_child    ,       snake_case_  )
  else:
    # if new_value is greater than value of data in node,
    #  add it to right subtree and proceed recursively
    __UpperCAmelCase	:  Tuple		=     insert(node.right_child    ,       snake_case_  )
  return node





def  _snake_case		(snake_case_					:     None | BinaryTreeNode  )							->		list[int]:  # if node is None,return
  if node:
    __UpperCAmelCase	:  str		=     inorder(node.left_child  )
    __UpperCAmelCase	:  Optional[int]		=     [*inorder_array, node.data]
    __UpperCAmelCase	:  str		=     inorder_array + inorder(node.right_child  )
  else:
    __UpperCAmelCase	:  Union[str, Any]		=     []
  return inorder_array





def  _snake_case		()							->		BinaryTreeNode | None:
  __UpperCAmelCase	:  Tuple		=     insert(snake_case_    ,       15  )
  insert(snake_case_    ,       10  )
  insert(snake_case_    ,       25  )
  insert(snake_case_    ,       6  )
  insert(snake_case_    ,       14  )
  insert(snake_case_    ,       20  )
  insert(snake_case_    ,       60  )
  return root





def  _snake_case		()							->		None:
  # main function
  __UpperCAmelCase	:  Any		=     make_tree()
  print('Printing values of binary search tree in Inorder Traversal.'  )
  inorder(snake_case_  )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()





