



'''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


lowercase							       =			logging.get_logger(__name__)

lowercase							       =			'''▁'''

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

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

lowercase							       =			{
    '''facebook/nllb-200-distilled-600M''': 1_024,
}

# fmt: off
lowercase							       =			['''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	(		__a):


 '''simple docstring'''




 __magic_name__					: Any  =      VOCAB_FILES_NAMES
 __magic_name__					: List[str]  =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __magic_name__					: str  =      PRETRAINED_VOCAB_FILES_MAP
 __magic_name__					: Any  =      ["input_ids", "attention_mask"]

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




 def __init__(   self							,  lowerCAmelCase_							,  lowerCAmelCase_="<s>"							,  lowerCAmelCase_="</s>"							,  lowerCAmelCase_="</s>"							,  lowerCAmelCase_="<s>"							,  lowerCAmelCase_="<unk>"							,  lowerCAmelCase_="<pad>"							,  lowerCAmelCase_="<mask>"							,  lowerCAmelCase_=None							,  lowerCAmelCase_=None							,  lowerCAmelCase_=None							,  lowerCAmelCase_ = None							,  lowerCAmelCase_=None							,  lowerCAmelCase_=False							,  **lowerCAmelCase_							,  ) ->      List[str]:



      """simple docstring"""







      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else mask_token

      a_       		={} if sp_model_kwargs is None else sp_model_kwargs
      a_       		=legacy_behaviour

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

      a_       		=spm.SentencePieceProcessor(**self.sp_model_kwargs)
      self.sp_model.Load(str(lowerCAmelCase_))
      a_       		=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_       		={"<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_       		=1

      a_       		=len(self.sp_model)
      a_       		={
          code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowerCAmelCase_)
      }
      a_       		={v: k for k, v in self.lang_code_to_id.items()}
      a_       		=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_       		={v: k for k, v in self.fairseq_tokens_to_ids.items()}
      a_       		=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_       		=src_lang if src_lang is not None else "eng_Latn"
      a_       		=self.lang_code_to_id[self._src_lang]
      a_       		=tgt_lang
      self.set_src_lang_special_tokens(self._src_lang)




 def __getstate__(   self) ->      int:



      """simple docstring"""







      a_       		=self.__dict__.copy()
      a_       		=None
      a_       		=self.sp_model.serialized_model_proto()
      return state




 def __setstate__(   self							,  lowerCAmelCase_) ->      str:



      """simple docstring"""







      a_       		=d

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

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




 @property
 def       lowercase_  (   self) ->      Union[str, Any]:



      """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) ->      str:



      """simple docstring"""







      return self._src_lang




 @src_lang.setter
 def       lowercase_  (   self							,  lowerCAmelCase_) ->      None:



      """simple docstring"""







      a_       		=new_src_lang
      self.set_src_lang_special_tokens(self._src_lang)




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None							,  lowerCAmelCase_ = False) ->      List[int]:



      """simple docstring"""







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

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




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = 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       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None) ->      List[int]:



      """simple docstring"""







      a_       		=[self.sep_token_id]
      a_       		=[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							,  lowerCAmelCase_							,  lowerCAmelCase_							,  lowerCAmelCase_							,  lowerCAmelCase_							,  **lowerCAmelCase_) ->      List[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       lowercase_  (   self) ->      Tuple:



      """simple docstring"""







      a_       		={self.convert_ids_to_tokens(lowerCAmelCase_): i for i in range(self.vocab_size)}
      vocab.update(self.added_tokens_encoder)
      return vocab




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      List[str]:



      """simple docstring"""







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




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      Dict:



      """simple docstring"""







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

      # 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							,  lowerCAmelCase_) ->      Optional[Any]:



      """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							,  lowerCAmelCase_) ->      Optional[int]:



      """simple docstring"""







      a_       		="".join(lowerCAmelCase_).replace(lowerCAmelCase_							,  " ").strip()
      return out_string




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None) ->      Tuple[str]:



      """simple docstring"""







      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_) and os.path.isfile(self.vocab_file):
           copyfile(self.vocab_file							,  lowerCAmelCase_)
      elif not os.path.isfile(self.vocab_file):
           with open(lowerCAmelCase_							,  "wb") as fi:
                a_       		=self.sp_model.serialized_model_proto()
                fi.write(lowerCAmelCase_)

      return (out_vocab_file,)




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = "eng_Latn"							,  lowerCAmelCase_ = None							,  lowerCAmelCase_ = "fra_Latn"							,  **lowerCAmelCase_							,  ) ->      BatchEncoding:



      """simple docstring"""







      a_       		=src_lang
      a_       		=tgt_lang
      return super().prepare_seqaseq_batch(lowerCAmelCase_							,  lowerCAmelCase_							,  **lowerCAmelCase_)




 def       lowercase_  (   self) ->      Optional[Any]:



      """simple docstring"""







      return self.set_src_lang_special_tokens(self.src_lang)




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



      """simple docstring"""







      return self.set_tgt_lang_special_tokens(self.tgt_lang)




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      None:



      """simple docstring"""







      a_       		=self.lang_code_to_id[src_lang]
      if self.legacy_behaviour:
           a_       		=[]
           a_       		=[self.eos_token_id, self.cur_lang_code]
      else:
           a_       		=[self.cur_lang_code]
           a_       		=[self.eos_token_id]




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      None:



      """simple docstring"""







      a_       		=self.lang_code_to_id[lang]
      if self.legacy_behaviour:
           a_       		=[]
           a_       		=[self.eos_token_id, self.cur_lang_code]
      else:
           a_       		=[self.cur_lang_code]
           a_       		=[self.eos_token_id]







'''simple docstring'''


import os

# Precomputes a list of the 100 first triangular numbers
lowercase							       =			[int(0.5 * n * (n + 1)) for n in range(1, 101)]






def  UpperCAmelCase_       (		):


     '''simple docstring'''







     a_       		=os.path.dirname(os.path.realpath(lowercase__       )       )
     a_       		=os.path.join(lowercase__       ,	"words.txt"       )

     a_       		=""
     with open(lowercase__       ) as f:
          a_       		=f.readline()

     a_       		=[word.strip("\""       ) for word in words.strip("\r\n"       ).split(","       )]
     a_       		=[
         word
         for word in [sum(ord(lowercase__       ) - 6_4 for x in word       ) for word in words]
         if word in TRIANGULAR_NUMBERS
     ]
     return len(lowercase__       )


if __name__ == "__main__":
  print(solution())


