


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


_snake_case             =     logging.get_logger(__name__)

_snake_case             =     '''▁'''

_snake_case             =     {'''vocab_file''': '''sentencepiece.bpe.model'''}

_snake_case             =     {
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'''
        ),
    }
}

_snake_case             =     {
    '''facebook/nllb-200-distilled-600M''': 10_24,
}

# fmt: off
_snake_case             =     ['''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 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   __A :      List[str]     		=		VOCAB_FILES_NAMES
   __A :      Optional[int]     		=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __A :      Dict     		=		PRETRAINED_VOCAB_FILES_MAP
   __A :      Union[str, Any]     		=		["input_ids", "attention_mask"]

   __A :      List[int]     		=		[]
   __A :      List[int]     		=		[]






   def __init__(		self						,				__A						,				__A="<s>"						,				__A="</s>"						,				__A="</s>"						,				__A="<s>"						,				__A="<unk>"						,				__A="<pad>"						,				__A="<mask>"						,				__A=None						,				__A=None						,				__A=None						,				__A = None						,				__A=None						,				__A=False						,				**__A						,				):






     """simple docstring"""





     lowerCamelCase :					Optional[Any]    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else mask_token

     lowerCamelCase :					Union[str, Any]    =				{} if sp_model_kwargs is None else sp_model_kwargs
     lowerCamelCase :					Optional[Any]    =				legacy_behaviour

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

     lowerCamelCase :					Union[str, Any]    =				spm.SentencePieceProcessor(**self.sp_model_kwargs )
     self.sp_model.Load(str(__A ) )
     lowerCamelCase :					str    =				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
     lowerCamelCase :					int    =				{"<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
     lowerCamelCase :					List[str]    =				1

     lowerCamelCase :					Optional[Any]    =				len(self.sp_model )
     lowerCamelCase :					List[Any]    =				{
         code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(__A )
     }
     lowerCamelCase :					int    =				{v: k for k, v in self.lang_code_to_id.items()}
     lowerCamelCase :					str    =				len(self.sp_model ) + len(self.lang_code_to_id ) + self.fairseq_offset

     self.fairseq_tokens_to_ids.update(self.lang_code_to_id )
     lowerCamelCase :					List[Any]    =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}
     lowerCamelCase :					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] )

     lowerCamelCase :					Union[str, Any]    =				src_lang if src_lang is not None else "eng_Latn"
     lowerCamelCase :					Union[str, Any]    =				self.lang_code_to_id[self._src_lang]
     lowerCamelCase :					Optional[int]    =				tgt_lang
     self.set_src_lang_special_tokens(self._src_lang )






   def __getstate__(		self ):






     """simple docstring"""





     lowerCamelCase :					int    =				self.__dict__.copy()
     lowerCamelCase :					Any    =				None
     lowerCamelCase :					Tuple    =				self.sp_model.serialized_model_proto()
     return state






   def __setstate__(		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				d

     # for backward compatibility
     if not hasattr(self						,				"sp_model_kwargs" ):
       lowerCamelCase :					Optional[Any]    =				{}

     lowerCamelCase :					int    =				spm.SentencePieceProcessor(**self.sp_model_kwargs )
     self.sp_model.LoadFromSerializedProto(self.sp_model_proto )






   @property
   def _snake_case    (		self ):






     """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 _snake_case    (		self ):






     """simple docstring"""





     return self._src_lang






   @src_lang.setter
   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					List[Any]    =				new_src_lang
     self.set_src_lang_special_tokens(self._src_lang )






   def _snake_case    (		self						,				__A						,				__A = None						,				__A = False ):






     """simple docstring"""





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

     lowerCamelCase :					Optional[Any]    =				[1] * len(self.prefix_tokens )
     lowerCamelCase :					List[Any]    =				[1] * len(self.suffix_tokens )
     if token_ids_a is None:
       return prefix_ones + ([0] * len(__A )) + suffix_ones
     return prefix_ones + ([0] * len(__A )) + ([0] * len(__A )) + suffix_ones






   def _snake_case    (		self						,				__A						,				__A = 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 _snake_case    (		self						,				__A						,				__A = None ):






     """simple docstring"""





     lowerCamelCase :					str    =				[self.sep_token_id]
     lowerCamelCase :					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 _snake_case    (		self						,				__A						,				__A						,				__A						,				__A						,				**__A ):






     """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" )
     lowerCamelCase :					Any    =				src_lang
     lowerCamelCase :					Optional[int]    =				self(__A						,				add_special_tokens=__A						,				return_tensors=__A						,				**__A )
     lowerCamelCase :					int    =				self.convert_tokens_to_ids(__A )
     lowerCamelCase :					List[str]    =				tgt_lang_id
     return inputs






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					str    =				{self.convert_ids_to_tokens(__A ): i for i in range(self.vocab_size )}
     vocab.update(self.added_tokens_encoder )
     return vocab






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





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






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     if token in self.fairseq_tokens_to_ids:
       return self.fairseq_tokens_to_ids[token]
     lowerCamelCase :					str    =				self.sp_model.PieceToId(__A )

     # 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 _snake_case    (		self						,				__A ):






     """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 _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Tuple    =				"".join(__A ).replace(__A						,				" " ).strip()
     return out_string






   def _snake_case    (		self						,				__A						,				__A = None ):






     """simple docstring"""





     if not os.path.isdir(__A ):
       logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
       return
     lowerCamelCase :					Union[str, Any]    =				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 ) and os.path.isfile(self.vocab_file ):
       copyfile(self.vocab_file						,				__A )
     elif not os.path.isfile(self.vocab_file ):
       with open(__A						,				"wb" ) as fi:
         lowerCamelCase :					Optional[int]    =				self.sp_model.serialized_model_proto()
         fi.write(__A )

     return (out_vocab_file,)






   def _snake_case    (		self						,				__A						,				__A = "eng_Latn"						,				__A = None						,				__A = "fra_Latn"						,				**__A						,				):






     """simple docstring"""





     lowerCamelCase :					str    =				src_lang
     lowerCamelCase :					Tuple    =				tgt_lang
     return super().prepare_seqaseq_batch(__A						,				__A						,				**__A )






   def _snake_case    (		self ):






     """simple docstring"""





     return self.set_src_lang_special_tokens(self.src_lang )






   def _snake_case    (		self ):






     """simple docstring"""





     return self.set_tgt_lang_special_tokens(self.tgt_lang )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Optional[int]    =				self.lang_code_to_id[src_lang]
     if self.legacy_behaviour:
       lowerCamelCase :					Optional[int]    =				[]
       lowerCamelCase :					Dict    =				[self.eos_token_id, self.cur_lang_code]
     else:
       lowerCamelCase :					int    =				[self.cur_lang_code]
       lowerCamelCase :					Tuple    =				[self.eos_token_id]






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Union[str, Any]    =				self.lang_code_to_id[lang]
     if self.legacy_behaviour:
       lowerCamelCase :					Union[str, Any]    =				[]
       lowerCamelCase :					Tuple    =				[self.eos_token_id, self.cur_lang_code]
     else:
       lowerCamelCase :					List[str]    =				[self.cur_lang_code]
       lowerCamelCase :					Optional[Any]    =				[self.eos_token_id]







def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  if divisor % 5 == 0 or divisor % 2 == 0:
    return 0
  lowerCamelCase :					List[Any]    =				1
  lowerCamelCase :					Union[str, Any]    =				1
  while repunit:
    lowerCamelCase :					Union[str, Any]    =				(10 * repunit + 1) % divisor
    repunit_index += 1
  return repunit_index






def 		lowercase_(  SCREAMING_SNAKE_CASE_ = 1000000	):


  '''simple docstring'''

  lowerCamelCase :					List[str]    =				limit - 1
  if divisor % 2 == 0:
    divisor += 1
  while least_divisible_repunit(SCREAMING_SNAKE_CASE_	) <= limit:
    divisor += 2
  return divisor


if __name__ == "__main__":
   print(f'''{solution() = }''')



