




'''simple docstring'''


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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase_      :  Union[str, Any]				     =  logging.get_logger(__name__)

lowerCAmelCase_      :  Any				     =  '▁'

lowerCAmelCase_      :  str				     =  {'vocab_file': 'sentencepiece.bpe.model'}

lowerCAmelCase_      :  Union[str, Any]				     =  {
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'
        ),
    }
}

lowerCAmelCase_      :  Any				     =  {
    'facebook/nllb-200-distilled-600M': 1024,
}

# fmt: off
lowerCAmelCase_      :  int				     =  ['ace_Arab', 'ace_Latn', 'acm_Arab', 'acq_Arab', 'aeb_Arab', 'afr_Latn', 'ajp_Arab', 'aka_Latn', 'amh_Ethi', 'apc_Arab', 'arb_Arab', 'ars_Arab', 'ary_Arab', 'arz_Arab', 'asm_Beng', 'ast_Latn', 'awa_Deva', 'ayr_Latn', 'azb_Arab', 'azj_Latn', 'bak_Cyrl', 'bam_Latn', 'ban_Latn', 'bel_Cyrl', 'bem_Latn', 'ben_Beng', 'bho_Deva', 'bjn_Arab', 'bjn_Latn', 'bod_Tibt', 'bos_Latn', 'bug_Latn', 'bul_Cyrl', 'cat_Latn', 'ceb_Latn', 'ces_Latn', 'cjk_Latn', 'ckb_Arab', 'crh_Latn', 'cym_Latn', 'dan_Latn', 'deu_Latn', 'dik_Latn', 'dyu_Latn', 'dzo_Tibt', 'ell_Grek', 'eng_Latn', 'epo_Latn', 'est_Latn', 'eus_Latn', 'ewe_Latn', 'fao_Latn', 'pes_Arab', 'fij_Latn', 'fin_Latn', 'fon_Latn', 'fra_Latn', 'fur_Latn', 'fuv_Latn', 'gla_Latn', 'gle_Latn', 'glg_Latn', 'grn_Latn', 'guj_Gujr', 'hat_Latn', 'hau_Latn', 'heb_Hebr', 'hin_Deva', 'hne_Deva', 'hrv_Latn', 'hun_Latn', 'hye_Armn', 'ibo_Latn', 'ilo_Latn', 'ind_Latn', 'isl_Latn', 'ita_Latn', 'jav_Latn', 'jpn_Jpan', 'kab_Latn', 'kac_Latn', 'kam_Latn', 'kan_Knda', 'kas_Arab', 'kas_Deva', 'kat_Geor', 'knc_Arab', 'knc_Latn', 'kaz_Cyrl', 'kbp_Latn', 'kea_Latn', 'khm_Khmr', 'kik_Latn', 'kin_Latn', 'kir_Cyrl', 'kmb_Latn', 'kon_Latn', 'kor_Hang', 'kmr_Latn', 'lao_Laoo', 'lvs_Latn', 'lij_Latn', 'lim_Latn', 'lin_Latn', 'lit_Latn', 'lmo_Latn', 'ltg_Latn', 'ltz_Latn', 'lua_Latn', 'lug_Latn', 'luo_Latn', 'lus_Latn', 'mag_Deva', 'mai_Deva', 'mal_Mlym', 'mar_Deva', 'min_Latn', 'mkd_Cyrl', 'plt_Latn', 'mlt_Latn', 'mni_Beng', 'khk_Cyrl', 'mos_Latn', 'mri_Latn', 'zsm_Latn', 'mya_Mymr', 'nld_Latn', 'nno_Latn', 'nob_Latn', 'npi_Deva', 'nso_Latn', 'nus_Latn', 'nya_Latn', 'oci_Latn', 'gaz_Latn', 'ory_Orya', 'pag_Latn', 'pan_Guru', 'pap_Latn', 'pol_Latn', 'por_Latn', 'prs_Arab', 'pbt_Arab', 'quy_Latn', 'ron_Latn', 'run_Latn', 'rus_Cyrl', 'sag_Latn', 'san_Deva', 'sat_Beng', 'scn_Latn', 'shn_Mymr', 'sin_Sinh', 'slk_Latn', 'slv_Latn', 'smo_Latn', 'sna_Latn', 'snd_Arab', 'som_Latn', 'sot_Latn', 'spa_Latn', 'als_Latn', 'srd_Latn', 'srp_Cyrl', 'ssw_Latn', 'sun_Latn', 'swe_Latn', 'swh_Latn', 'szl_Latn', 'tam_Taml', 'tat_Cyrl', 'tel_Telu', 'tgk_Cyrl', 'tgl_Latn', 'tha_Thai', 'tir_Ethi', 'taq_Latn', 'taq_Tfng', 'tpi_Latn', 'tsn_Latn', 'tso_Latn', 'tuk_Latn', 'tum_Latn', 'tur_Latn', 'twi_Latn', 'tzm_Tfng', 'uig_Arab', 'ukr_Cyrl', 'umb_Latn', 'urd_Arab', 'uzn_Latn', 'vec_Latn', 'vie_Latn', 'war_Latn', 'wol_Latn', 'xho_Latn', 'ydd_Hebr', 'yor_Latn', 'yue_Hant', 'zho_Hans', 'zho_Hant', 'zul_Latn']







class      SCREAMING_SNAKE_CASE    (						snake_case_				):
      __magic_name__  :       Dict   							=					VOCAB_FILES_NAMES
      __magic_name__  :       str   							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __magic_name__  :       Tuple   							=					PRETRAINED_VOCAB_FILES_MAP
      __magic_name__  :       Union[str, Any]   							=					['''input_ids''', '''attention_mask''']

      __magic_name__  :       List[int]   							=					[]
      __magic_name__  :       List[int]   							=					[]






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


           '''simple docstring'''

           a_     :							List[str]     						=  AddedToken(lowercase__						,						lstrip=lowercase__						,						rstrip=lowercase__       ) if isinstance(lowercase__						,						lowercase__       ) else mask_token

           a_     :							Any     						=  {} if sp_model_kwargs is None else sp_model_kwargs
           a_     :							Tuple     						=  legacy_behaviour

           super().__init__(
               bos_token=lowercase__						,						eos_token=lowercase__						,						unk_token=lowercase__						,						sep_token=lowercase__						,						cls_token=lowercase__						,						pad_token=lowercase__						,						mask_token=lowercase__						,						tokenizer_file=lowercase__						,						src_lang=lowercase__						,						tgt_lang=lowercase__						,						additional_special_tokens=lowercase__						,						sp_model_kwargs=self.sp_model_kwargs						,						legacy_behaviour=lowercase__						,						**lowercase__						,						)

           a_     :							List[Any]     						=  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
           self.sp_model.Load(str(lowercase__       )       )
           a_     :							Optional[Any]     						=  vocab_file
           # Original fairseq vocab and spm vocab must be "aligned":
           # Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
           # -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
           # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
           # spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

           # Mimic fairseq token-to-id alignment for the first 4 token
           a_     :							Tuple     						=  {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

           # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
           a_     :							Dict     						=  1

           a_     :							Any     						=  len(self.sp_model       )
           a_     :							Union[str, Any]     						=  {
               code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowercase__       )
           }
           a_     :							Dict     						=  {v: k for k, v in self.lang_code_to_id.items()}
           a_     :							Dict     						=  len(self.sp_model       ) + len(self.lang_code_to_id       ) + self.fairseq_offset

           self.fairseq_tokens_to_ids.update(self.lang_code_to_id       )
           a_     :							Any     						=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
           a_     :							Optional[Any]     						=  list(self.lang_code_to_id.keys()       )

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

           a_     :							List[str]     						=  src_lang if src_lang is not None else """eng_Latn"""
           a_     :							List[Any]     						=  self.lang_code_to_id[self._src_lang]
           a_     :							Optional[Any]     						=  tgt_lang
           self.set_src_lang_special_tokens(self._src_lang       )






      def __getstate__( self   :  Any       ):


           '''simple docstring'''

           a_     :							Union[str, Any]     						=  self.__dict__.copy()
           a_     :							int     						=  None
           a_     :							int     						=  self.sp_model.serialized_model_proto()
           return state






      def __setstate__( self   :  Tuple						,						lowercase__   :  List[str]       ):


           '''simple docstring'''

           a_     :							List[Any]     						=  d

           # for backward compatibility
           if not hasattr(self						,						"""sp_model_kwargs"""       ):
                a_     :							List[str]     						=  {}

           a_     :							Tuple     						=  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
           self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )






      @property
      def 							lowercase_						( self   :  Dict       ):


           '''simple docstring'''

           return len(self.sp_model       ) + len(self.lang_code_to_id       ) + self.fairseq_offset + 1  # Plus 1 for the mask token






      @property
      def 							lowercase_						( self   :  Optional[Any]       ):


           '''simple docstring'''

           return self._src_lang






      @src_lang.setter
      def 							lowercase_						( self   :  Union[str, Any]						,						lowercase__   :  str       ):


           '''simple docstring'''

           a_     :							Optional[int]     						=  new_src_lang
           self.set_src_lang_special_tokens(self._src_lang       )






      def 							lowercase_						( self   :  Optional[Any]						,						lowercase__   :  List[int]						,						lowercase__   :  Optional[List[int]] = None						,						lowercase__   :  bool = False       ):


           '''simple docstring'''

           if already_has_special_tokens:
                return super().get_special_tokens_mask(
                    token_ids_a=lowercase__						,						token_ids_a=lowercase__						,						already_has_special_tokens=lowercase__       )

           a_     :							int     						=  [1] * len(self.prefix_tokens       )
           a_     :							str     						=  [1] * len(self.suffix_tokens       )
           if token_ids_a is None:
                return prefix_ones + ([0] * len(lowercase__       )) + suffix_ones
           return prefix_ones + ([0] * len(lowercase__       )) + ([0] * len(lowercase__       )) + suffix_ones






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


           '''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 							lowercase_						( self   :  Dict						,						lowercase__   :  List[int]						,						lowercase__   :  Optional[List[int]] = None       ):


           '''simple docstring'''

           a_     :							List[str]     						=  [self.sep_token_id]
           a_     :							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 							lowercase_						( self   :  int						,						lowercase__   :  int						,						lowercase__   :  str						,						lowercase__   :  Optional[str]						,						lowercase__   :  Optional[str]						,						**lowercase__   :  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"""       )
           a_     :							int     						=  src_lang
           a_     :							Dict     						=  self(lowercase__						,						add_special_tokens=lowercase__						,						return_tensors=lowercase__						,						**lowercase__       )
           a_     :							Optional[int]     						=  self.convert_tokens_to_ids(lowercase__       )
           a_     :							Optional[Any]     						=  tgt_lang_id
           return inputs






      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							Optional[Any]     						=  {self.convert_ids_to_tokens(lowercase__       ): i for i in range(self.vocab_size       )}
           vocab.update(self.added_tokens_encoder       )
           return vocab






      def 							lowercase_						( self   :  List[str]						,						lowercase__   :  str       ):


           '''simple docstring'''

           return self.sp_model.encode(lowercase__						,						out_type=lowercase__       )






      def 							lowercase_						( self   :  Any						,						lowercase__   :  List[Any]       ):


           '''simple docstring'''

           if token in self.fairseq_tokens_to_ids:
                return self.fairseq_tokens_to_ids[token]
           a_     :							int     						=  self.sp_model.PieceToId(lowercase__       )

           # Need to return unknown token if the SP model returned 0
           return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






      def 							lowercase_						( self   :  Optional[int]						,						lowercase__   :  Tuple       ):


           '''simple docstring'''

           if index in self.fairseq_ids_to_tokens:
                return self.fairseq_ids_to_tokens[index]
           return self.sp_model.IdToPiece(index - self.fairseq_offset       )






      def 							lowercase_						( self   :  Union[str, Any]						,						lowercase__   :  Any       ):


           '''simple docstring'''

           a_     :							List[str]     						=  """""".join(lowercase__       ).replace(lowercase__						,						""" """       ).strip()
           return out_string






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


           '''simple docstring'''

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

           if os.path.abspath(self.vocab_file       ) != os.path.abspath(lowercase__       ) and os.path.isfile(self.vocab_file       ):
                copyfile(self.vocab_file						,						lowercase__       )
           elif not os.path.isfile(self.vocab_file       ):
                with open(lowercase__						,						"""wb"""       ) as fi:
                     a_     :							str     						=  self.sp_model.serialized_model_proto()
                     fi.write(lowercase__       )

           return (out_vocab_file,)






      def 							lowercase_						( self   :  List[str]						,						lowercase__   :  List[str]						,						lowercase__   :  str = "eng_Latn"						,						lowercase__   :  Optional[List[str]] = None						,						lowercase__   :  str = "fra_Latn"						,						**lowercase__   :  Optional[Any]						,						):


           '''simple docstring'''

           a_     :							Optional[Any]     						=  src_lang
           a_     :							Union[str, Any]     						=  tgt_lang
           return super().prepare_seqaseq_batch(lowercase__						,						lowercase__						,						**lowercase__       )






      def 							lowercase_						( self   :  Union[str, Any]       ):


           '''simple docstring'''

           return self.set_src_lang_special_tokens(self.src_lang       )






      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           return self.set_tgt_lang_special_tokens(self.tgt_lang       )






      def 							lowercase_						( self   :  Union[str, Any]						,						lowercase__   :  List[str]       ):


           '''simple docstring'''

           a_     :							Dict     						=  self.lang_code_to_id[src_lang]
           if self.legacy_behaviour:
                a_     :							Union[str, Any]     						=  []
                a_     :							Dict     						=  [self.eos_token_id, self.cur_lang_code]
           else:
                a_     :							Any     						=  [self.cur_lang_code]
                a_     :							Optional[int]     						=  [self.eos_token_id]






      def 							lowercase_						( self   :  Tuple						,						lowercase__   :  str       ):


           '''simple docstring'''

           a_     :							Dict     						=  self.lang_code_to_id[lang]
           if self.legacy_behaviour:
                a_     :							Dict     						=  []
                a_     :							List[Any]     						=  [self.eos_token_id, self.cur_lang_code]
           else:
                a_     :							Optional[Any]     						=  [self.cur_lang_code]
                a_     :							List[str]     						=  [self.eos_token_id]






'''simple docstring'''


from __future__ import annotations



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					list[float]				):




     """simple docstring"""


     if len(UpperCamelCase__				) < 2:
          raise ValueError("""Monogons and Digons are not polygons in the Euclidean space"""				)
     if any(i <= 0 for i in nums				):
          raise ValueError("""All values must be greater than 0"""				)
     a_     :							int     						=  nums.copy()
     copy_nums.sort()
     return copy_nums[-1] < sum(copy_nums[:-1]				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
