





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_mbart import MBartTokenizer
else:
      SCREAMING_SNAKE_CASE_						       =	None


SCREAMING_SNAKE_CASE_						       =	logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_						       =	{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

SCREAMING_SNAKE_CASE_						       =	{
    """vocab_file""": {
        """facebook/mbart-large-en-ro""": (
            """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"""
        ),
        """facebook/mbart-large-cc25""": (
            """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """facebook/mbart-large-en-ro""": """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json""",
        """facebook/mbart-large-cc25""": """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json""",
    },
}

SCREAMING_SNAKE_CASE_						       =	{
    """facebook/mbart-large-en-ro""": 1_0_2_4,
    """facebook/mbart-large-cc25""": 1_0_2_4,
}

# fmt: off
SCREAMING_SNAKE_CASE_						       =	["""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"""]

class 		UpperCamelCase__			(				lowerCamelCase__       ):



     '''simple docstring'''

     __snake_case   :     Tuple		     =      VOCAB_FILES_NAMES
     __snake_case   :     Any		     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __snake_case   :     str		     =      PRETRAINED_VOCAB_FILES_MAP
     __snake_case   :     int		     =      ['input_ids', 'attention_mask']
     __snake_case   :     Union[str, Any]		     =      MBartTokenizer

     __snake_case   :     List[int]		     =      []
     __snake_case   :     List[int]		     =      []






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




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=   AddedToken(lowerCamelCase__						,lstrip=lowerCamelCase__						,rstrip=lowerCamelCase__	) if isinstance(lowerCamelCase__						,lowerCamelCase__	) else mask_token

           super().__init__(
               vocab_file=lowerCamelCase__						,tokenizer_file=lowerCamelCase__						,bos_token=lowerCamelCase__						,eos_token=lowerCamelCase__						,sep_token=lowerCamelCase__						,cls_token=lowerCamelCase__						,unk_token=lowerCamelCase__						,pad_token=lowerCamelCase__						,mask_token=lowerCamelCase__						,src_lang=lowerCamelCase__						,tgt_lang=lowerCamelCase__						,additional_special_tokens=lowerCamelCase__						,**lowerCamelCase__						,)

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

           SCREAMING_SNAKE_CASE		=   FAIRSEQ_LANGUAGE_CODES.copy()

           if additional_special_tokens is not None:
                 # Only add those special tokens if they are not already there.
                 _additional_special_tokens.extend(
                     [t for t in additional_special_tokens if t not in _additional_special_tokens]	)

           self.add_special_tokens({"""additional_special_tokens""": _additional_special_tokens}	)
           SCREAMING_SNAKE_CASE		=   {
               lang_code: self.convert_tokens_to_ids(lowerCamelCase__	) for lang_code in FAIRSEQ_LANGUAGE_CODES
           }

           SCREAMING_SNAKE_CASE		=   src_lang if src_lang is not None else """en_XX"""
           SCREAMING_SNAKE_CASE		=   self.convert_tokens_to_ids(self._src_lang	)
           SCREAMING_SNAKE_CASE		=   tgt_lang
           self.set_src_lang_special_tokens(self._src_lang	)






     @property
     def     SCREAMING_SNAKE_CASE__  (							self						:   str	)					->		Any:




           '''simple docstring'''


           return self._src_lang






     @src_lang.setter
     def     SCREAMING_SNAKE_CASE__  (							self						:   str						,lowerCamelCase__						:   Tuple	)					->		Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=   new_src_lang
           self.set_src_lang_special_tokens(self._src_lang	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Any						,lowerCamelCase__						:   Optional[int]						,lowerCamelCase__						:   Tuple = None	)					->		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     SCREAMING_SNAKE_CASE__  (							self						:   Optional[Any]						,lowerCamelCase__						:   Any						,lowerCamelCase__						:   Optional[int] = None	)					->		Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=   [self.sep_token_id]
           SCREAMING_SNAKE_CASE		=   [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     SCREAMING_SNAKE_CASE__  (							self						:   Any						,lowerCamelCase__						:   Optional[int]						,lowerCamelCase__						:   str						,lowerCamelCase__						:   int						,lowerCamelCase__						:   List[Any]						,**lowerCamelCase__						:   Optional[Any]	)					->		Tuple:




           '''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"""	)
           SCREAMING_SNAKE_CASE		=   src_lang
           SCREAMING_SNAKE_CASE		=   self(lowerCamelCase__						,add_special_tokens=lowerCamelCase__						,return_tensors=lowerCamelCase__						,**lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=   self.convert_tokens_to_ids(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=   tgt_lang_id
           return inputs






     def     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]						,lowerCamelCase__						:   Any						,lowerCamelCase__						:   Dict = "en_XX"						,lowerCamelCase__						:   int = None						,lowerCamelCase__						:   List[Any] = "ro_RO"						,**lowerCamelCase__						:   Optional[int]						,)					->		Union[str, Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=   src_lang
           SCREAMING_SNAKE_CASE		=   tgt_lang
           return super().prepare_seqaseq_batch(lowerCamelCase__						,lowerCamelCase__						,**lowerCamelCase__	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]	)					->		List[Any]:




           '''simple docstring'''


           return self.set_src_lang_special_tokens(self.src_lang	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Tuple	)					->		str:




           '''simple docstring'''


           return self.set_tgt_lang_special_tokens(self.tgt_lang	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   str						,lowerCamelCase__						:   Union[str, Any]	)					->		Any:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=   self.convert_tokens_to_ids(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=   []
           SCREAMING_SNAKE_CASE		=   [self.eos_token_id, self.cur_lang_code]

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

           SCREAMING_SNAKE_CASE		=   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     SCREAMING_SNAKE_CASE__  (							self						:   Any						,lowerCamelCase__						:   str	)					->		int:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=   self.convert_tokens_to_ids(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=   []
           SCREAMING_SNAKE_CASE		=   [self.eos_token_id, self.cur_lang_code]

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

           SCREAMING_SNAKE_CASE		=   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     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]						,lowerCamelCase__						:   Any						,lowerCamelCase__						:   Dict = None	)					->		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
           SCREAMING_SNAKE_CASE		=   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,)









from __future__ import annotations



def        __lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )			->       list[int]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						0
      SCREAMING_SNAKE_CASE		=						len(_SCREAMING_SNAKE_CASE     ) - 1

      while i < j:
            if nums[i] + nums[j] == target:
                  return [i, j]
            elif nums[i] + nums[j] < target:
                  SCREAMING_SNAKE_CASE		=						i + 1
            else:
                  SCREAMING_SNAKE_CASE		=						j - 1

      return []


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      print(F'''{two_pointer([2, 7, 1_1, 1_5], 9) = }''')


