


from __future__ import annotations

__lowerCAmelCase									=				[2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]





class     __a     :
 def __init__(  self							,					lowerCAmelCase__					)   ->							None:




        '''simple docstring'''
        lowercase__:  int         =  -1
        lowercase__:  List[Any]         =  -1
        lowercase__:  Any         =  [-1] * length
        lowercase__:  Any         =  None
        lowercase__:  int         =  None
 def __repr__(  self					)   ->							str:




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





def   snake_case_	(    snake_case	)    ->							int:
       lowercase__:  str         =  Node(len(UpperCAmelCase__	)	)
       lowercase__     ,		lowercase__:  str         =  min(UpperCAmelCase__	), max(UpperCAmelCase__	)
       # Leaf node case where the node contains only one unique value
       if root.minn == root.maxx:
              return root
       lowercase__:  Union[str, Any]         =  (root.minn + root.maxx) // 2

       lowercase__:  str         =  []
       lowercase__:  str         =  []

       for index, num in enumerate(UpperCAmelCase__	):
              if num <= pivot:
                     left_arr.append(UpperCAmelCase__	)
              else:
                     right_arr.append(UpperCAmelCase__	)
              lowercase__:  Union[str, Any]         =  len(UpperCAmelCase__	)
       lowercase__:  str         =  build_tree(UpperCAmelCase__	)
       lowercase__:  Optional[Any]         =  build_tree(UpperCAmelCase__	)
       return root




def   snake_case_	(    snake_case     ,				snake_case     ,				snake_case	)    ->							str:

       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
       lowercase__:  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     ,				UpperCAmelCase__     ,				node.map_left[index] - 1	)
       else:
              # go to the right subtree and map index to the right subtree
              return rank_till_index(node.right     ,				UpperCAmelCase__     ,				index - node.map_left[index]	)




def   snake_case_	(    snake_case     ,				snake_case     ,				snake_case     ,				snake_case	)    ->							int:

       if start > end:
              return 0
       lowercase__:  Dict         =  rank_till_index(UpperCAmelCase__     ,				UpperCAmelCase__     ,				UpperCAmelCase__	)
       lowercase__:  str         =  rank_till_index(UpperCAmelCase__     ,				UpperCAmelCase__     ,				start - 1	)
       return rank_till_end - rank_before_start




def   snake_case_	(    snake_case     ,				snake_case     ,				snake_case     ,				snake_case	)    ->							Tuple:

       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]
       lowercase__:  str         =  node.map_left[end] - (
           node.map_left[start - 1] if start else 0
       )
       if num_elements_in_left_tree > index:
              return quantile(
                  node.left     ,				UpperCAmelCase__     ,				(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   snake_case_	(    snake_case     ,				snake_case     ,				snake_case     ,				snake_case     ,				snake_case	)    ->							int:

       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
       lowercase__:  str         =  range_counting(
           node.left     ,				(node.map_left[start - 1] if start else 0)     ,				node.map_left[end] - 1     ,				UpperCAmelCase__     ,				UpperCAmelCase__     ,				)
       lowercase__:  List[Any]         =  range_counting(
           node.right     ,				start - (node.map_left[start - 1] if start else 0)     ,				end - node.map_left[end]     ,				UpperCAmelCase__     ,				UpperCAmelCase__     ,				)
       return left + right


if __name__ == "__main__":
 import doctest

 doctest.testmod()







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

from tokenizers import processors

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


if is_sentencepiece_available():
     from .tokenization_mbartaa import MBartaaTokenizer
else:
     A_		:  Any										=  None


A_		:  Tuple										=  logging.get_logger(__name__)

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

A_		:  List[Any]										=  {
    '''vocab_file''': {
        '''facebook/mbart-large-50-one-to-many-mmt''': (
            '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-50-one-to-many-mmt''': (
            '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json'''
        ),
    },
}

A_		:  Optional[Any]										=  {
    '''facebook/mbart-large-50-one-to-many-mmt''': 10_24,
}

# fmt: off
A_		:  List[str]										=  ['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''', '''af_ZA''', '''az_AZ''', '''bn_IN''', '''fa_IR''', '''he_IL''', '''hr_HR''', '''id_ID''', '''ka_GE''', '''km_KH''', '''mk_MK''', '''ml_IN''', '''mn_MN''', '''mr_IN''', '''pl_PL''', '''ps_AF''', '''pt_XX''', '''sv_SE''', '''sw_KE''', '''ta_IN''', '''te_IN''', '''th_TH''', '''tl_XX''', '''uk_UA''', '''ur_PK''', '''xh_ZA''', '''gl_ES''', '''sl_SI''']



class 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      VOCAB_FILES_NAMES
   _UpperCAmelCase  						=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _UpperCAmelCase  						=      PRETRAINED_VOCAB_FILES_MAP
   _UpperCAmelCase  						=      ['''input_ids''', '''attention_mask''']
   _UpperCAmelCase  						=      MBartaaTokenizer

   _UpperCAmelCase  						=      []
   _UpperCAmelCase  						=      []

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


    """simple docstring"""






    a							=		AddedToken(__lowerCAmelCase				, lstrip=__lowerCAmelCase				, rstrip=__lowerCAmelCase				) if isinstance(__lowerCAmelCase				, __lowerCAmelCase				) else mask_token

    a							=		kwargs.get("additional_special_tokens"				, []				)
    kwargs["additional_special_tokens"] += [
        code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
    ]

    super().__init__(
        __lowerCAmelCase				, src_lang=__lowerCAmelCase				, tgt_lang=__lowerCAmelCase				, tokenizer_file=__lowerCAmelCase				, eos_token=__lowerCAmelCase				, sep_token=__lowerCAmelCase				, cls_token=__lowerCAmelCase				, unk_token=__lowerCAmelCase				, pad_token=__lowerCAmelCase				, mask_token=__lowerCAmelCase				, **__lowerCAmelCase				, )

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

    a							=		{
        lang_code: self.convert_tokens_to_ids(__lowerCAmelCase				) for lang_code in FAIRSEQ_LANGUAGE_CODES
    }

    a							=		src_lang if src_lang is not None else "en_XX"
    a							=		tgt_lang
    a							=		self.lang_code_to_id[self._src_lang]
    self.set_src_lang_special_tokens(self._src_lang				)

   @property
   def 		A				(   self      :							Dict				)							->					str:


    """simple docstring"""






    return self._src_lang

   @src_lang.setter
   def 		A				(   self      :							Dict				, __lowerCAmelCase      :							str				)							->					None:


    """simple docstring"""






    a							=		new_src_lang
    self.set_src_lang_special_tokens(self._src_lang				)

   def 		A				(   self      :							Dict				, __lowerCAmelCase      :							List[int]				, __lowerCAmelCase      :							Optional[List[int]] = None				)							->					List[int]:


    """simple docstring"""






    if token_ids_a is None:
     return self.prefix_tokens + token_ids_a + self.suffix_tokens
    # We don't expect to process pairs, but leave the pair logic for API consistency
    return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens

   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							List[str]				, __lowerCAmelCase      :							str = "en_XX"				, __lowerCAmelCase      :							Optional[List[str]] = None				, __lowerCAmelCase      :							str = "ro_RO"				, **__lowerCAmelCase      :							Dict				, )							->					BatchEncoding:


    """simple docstring"""






    a							=		src_lang
    a							=		tgt_lang
    return super().prepare_seqaseq_batch(__lowerCAmelCase				, __lowerCAmelCase				, **__lowerCAmelCase				)

   def 		A				(   self      :							List[str]				)							->					List[str]:


    """simple docstring"""






    return self.set_src_lang_special_tokens(self.src_lang				)

   def 		A				(   self      :							str				)							->					int:


    """simple docstring"""






    return self.set_tgt_lang_special_tokens(self.tgt_lang				)

   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							str				)							->					None:


    """simple docstring"""






    a							=		self.convert_tokens_to_ids(__lowerCAmelCase				)
    a							=		[self.cur_lang_code_id]
    a							=		[self.eos_token_id]

    a							=		self.convert_ids_to_tokens(self.prefix_tokens				)
    a							=		self.convert_ids_to_tokens(self.suffix_tokens				)

    a							=		processors.TemplateProcessing(
        single=prefix_tokens_str + ["$A"] + suffix_tokens_str				, pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str				, special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str				, self.prefix_tokens + self.suffix_tokens				)				)				, )

   def 		A				(   self      :							List[str]				, __lowerCAmelCase      :							str				)							->					None:


    """simple docstring"""






    a							=		self.convert_tokens_to_ids(__lowerCAmelCase				)
    a							=		[self.cur_lang_code_id]
    a							=		[self.eos_token_id]

    a							=		self.convert_ids_to_tokens(self.prefix_tokens				)
    a							=		self.convert_ids_to_tokens(self.suffix_tokens				)

    a							=		processors.TemplateProcessing(
        single=prefix_tokens_str + ["$A"] + suffix_tokens_str				, pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str				, special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str				, self.prefix_tokens + self.suffix_tokens				)				)				, )

   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							Dict				, __lowerCAmelCase      :							str				, __lowerCAmelCase      :							Optional[str]				, __lowerCAmelCase      :							Optional[str]				, **__lowerCAmelCase      :							Any				)							->					Union[str, Any]:


    """simple docstring"""






    if src_lang is None or tgt_lang is None:
     raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"				)
    a							=		src_lang
    a							=		self(__lowerCAmelCase				, add_special_tokens=__lowerCAmelCase				, return_tensors=__lowerCAmelCase				, **__lowerCAmelCase				)
    a							=		self.convert_tokens_to_ids(__lowerCAmelCase				)
    a							=		tgt_lang_id
    return inputs




   def 		A				(   self      :							Union[str, Any]				, __lowerCAmelCase      :							str				, __lowerCAmelCase      :							Optional[str] = None				)							->					Tuple[str]:


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

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

    return (out_vocab_file,)

