





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_nllb import NllbTokenizer
else:
       _A :   Tuple  			=  None


_A :   Optional[Any]  			=  logging.get_logger(__name__)


_A :   Optional[int]  			=  {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

_A :   Optional[Any]  			=  {
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json'
        ),
    },
}

_A :   List[str]  			=  {
    'facebook/nllb-large-en-ro': 10_24,
    'facebook/nllb-200-distilled-600M': 10_24,
}

# fmt: off
_A :   Optional[Any]  			=  ['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      (			lowerCAmelCase_ ):
       _UpperCAmelCase				:  Optional[Any]			   =   VOCAB_FILES_NAMES
       _UpperCAmelCase				:  Any			   =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       _UpperCAmelCase				:  Tuple			   =   PRETRAINED_VOCAB_FILES_MAP
       _UpperCAmelCase				:  Union[str, Any]			   =   ["input_ids", "attention_mask"]
       _UpperCAmelCase				:  List[Any]			   =   NllbTokenizer

       _UpperCAmelCase				:  List[int]			   =   []
       _UpperCAmelCase				:  List[int]			   =   []







       def __init__(				self					:     str		, A					:     Any=None		, A					:     int=None		, A					:     Union[str, Any]="<s>"		, A					:     List[Any]="</s>"		, A					:     Union[str, Any]="</s>"		, A					:     Dict="<s>"		, A					:     Optional[Any]="<unk>"		, A					:     int="<pad>"		, A					:     str="<mask>"		, A					:     Optional[int]=None		, A					:     Tuple=None		, A					:     Dict=None		, A					:     Any=False		, **A					:     Optional[Any]		, )       ->Tuple:
          # Mask token behave like a normal word, i.e. include the space before it
          lowerCamelCase__        =							AddedToken(A		, lstrip=A		, rstrip=A      ) if isinstance(A		, A      ) else mask_token
          lowerCamelCase__        =							legacy_behaviour
          super().__init__(
              vocab_file=A		, tokenizer_file=A		, bos_token=A		, eos_token=A		, sep_token=A		, cls_token=A		, unk_token=A		, pad_token=A		, mask_token=A		, src_lang=A		, tgt_lang=A		, additional_special_tokens=A		, legacy_behaviour=A		, **A		, )

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

          lowerCamelCase__        =							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}      )
          lowerCamelCase__        =							{
              lang_code: self.convert_tokens_to_ids(A      ) for lang_code in FAIRSEQ_LANGUAGE_CODES
          }

          lowerCamelCase__        =							src_lang if src_lang is not None else '''eng_Latn'''
          lowerCamelCase__        =							self.convert_tokens_to_ids(self._src_lang      )
          lowerCamelCase__        =							tgt_lang
          self.set_src_lang_special_tokens(self._src_lang      )







       @property
       def 						__lowerCamelCase   (				self					:     Any      )       ->str:
          return self._src_lang







       @src_lang.setter
       def 						__lowerCamelCase   (				self					:     int		, A					:     str      )       ->None:
          lowerCamelCase__        =							new_src_lang
          self.set_src_lang_special_tokens(self._src_lang      )







       def 						__lowerCamelCase   (				self					:     Optional[Any]		, A					:     List[int]		, A					:     Optional[List[int]] = None      )       ->List[int]:
          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 						__lowerCamelCase   (				self					:     str		, A					:     List[int]		, A					:     Optional[List[int]] = None      )       ->List[int]:
          lowerCamelCase__        =							[self.sep_token_id]
          lowerCamelCase__        =							[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 						__lowerCamelCase   (				self					:     List[Any]		, A					:     List[str]		, A					:     str		, A					:     Optional[str]		, A					:     Optional[str]		, **A					:     int      )       ->int:
          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__        =							src_lang
          lowerCamelCase__        =							self(A		, add_special_tokens=A		, return_tensors=A		, **A      )
          lowerCamelCase__        =							self.convert_tokens_to_ids(A      )
          lowerCamelCase__        =							tgt_lang_id
          return inputs







       def 						__lowerCamelCase   (				self					:     Optional[int]		, A					:     List[str]		, A					:     str = "eng_Latn"		, A					:     Optional[List[str]] = None		, A					:     str = "fra_Latn"		, **A					:     Optional[int]		, )       ->BatchEncoding:
          lowerCamelCase__        =							src_lang
          lowerCamelCase__        =							tgt_lang
          return super().prepare_seqaseq_batch(A		, A		, **A      )







       def 						__lowerCamelCase   (				self					:     Optional[int]      )       ->Dict:
          return self.set_src_lang_special_tokens(self.src_lang      )







       def 						__lowerCamelCase   (				self					:     Optional[int]      )       ->Any:
          return self.set_tgt_lang_special_tokens(self.tgt_lang      )







       def 						__lowerCamelCase   (				self					:     List[str]		, A					:     str      )       ->None:
          lowerCamelCase__        =							self.convert_tokens_to_ids(A      )

          if self.legacy_behaviour:
             lowerCamelCase__        =							[]
             lowerCamelCase__        =							[self.eos_token_id, self.cur_lang_code]
          else:
             lowerCamelCase__        =							[self.cur_lang_code]
             lowerCamelCase__        =							[self.eos_token_id]

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

          lowerCamelCase__        =							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 						__lowerCamelCase   (				self					:     str		, A					:     str      )       ->None:
          lowerCamelCase__        =							self.convert_tokens_to_ids(A      )
          if self.legacy_behaviour:
             lowerCamelCase__        =							[]
             lowerCamelCase__        =							[self.eos_token_id, self.cur_lang_code]
          else:
             lowerCamelCase__        =							[self.cur_lang_code]
             lowerCamelCase__        =							[self.eos_token_id]

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

          lowerCamelCase__        =							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 						__lowerCamelCase   (				self					:     Any		, A					:     str		, A					:     Optional[str] = None      )       ->Tuple[str]:
          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(A      ):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory."      )
             return
          lowerCamelCase__        =							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      ):
             copyfile(self.vocab_file		, A      )

          return (out_vocab_file,)










def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase					)    ->    Dict:







   """simple docstring"""
   if b == 0:
      return 1
   if (b % 2) == 0:
      return actual_power(UpperCAmelCase      ,  int(b / 2					)					) * actual_power(UpperCAmelCase      ,  int(b / 2					)					)
   else:
      return a * actual_power(UpperCAmelCase      ,  int(b / 2					)					) * actual_power(UpperCAmelCase      ,  int(b / 2					)					)



def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase					)    ->    float:







   """simple docstring"""
   if b < 0:
      return 1 / actual_power(UpperCAmelCase      ,  UpperCAmelCase					)
   return actual_power(UpperCAmelCase      ,  UpperCAmelCase					)


if __name__ == "__main__":
       print(power(-2, -3))



