'''simple docstring'''




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:
  __SCREAMING_SNAKE_CASE			:	Any	=    None


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


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

__SCREAMING_SNAKE_CASE			:	Optional[int]	=    {
    """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"""
        ),
    },
}

__SCREAMING_SNAKE_CASE			:	List[Any]	=    {
    """facebook/nllb-large-en-ro""": 1_024,
    """facebook/nllb-200-distilled-600M""": 1_024,
}

# fmt: off
__SCREAMING_SNAKE_CASE			:	Union[str, 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       lowerCamelCase_      (_a       ):
      '''simple docstring'''

      __UpperCamelCase:    str         =		VOCAB_FILES_NAMES
      __UpperCamelCase:    Optional[Any]         =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __UpperCamelCase:    Dict         =		PRETRAINED_VOCAB_FILES_MAP
      __UpperCamelCase:    Dict         =		["input_ids", "attention_mask"]
      __UpperCamelCase:    Optional[Any]         =		NllbTokenizer

      __UpperCamelCase:    str         =		[]
      __UpperCamelCase:    str         =		[]




      def __init__(			self		:							Dict		,   A		:							List[str]=None		,   A		:							Dict=None		,   A		:							Dict="<s>"		,   A		:							Optional[int]="</s>"		,   A		:							int="</s>"		,   A		:							Union[str, Any]="<s>"		,   A		:							Dict="<unk>"		,   A		:							Tuple="<pad>"		,   A		:							List[Any]="<mask>"		,   A		:							List[Any]=None		,   A		:							Union[str, Any]=None		,   A		:							List[Any]=None		,   A		:							str=False		,   **A		:							Any		,   ):
             # Mask token behave like a normal word, i.e. include the space before it
             _UpperCAmelCase	:    int				 =       AddedToken(lowerCamelCase__		,   lstrip=lowerCamelCase__		,   rstrip=lowerCamelCase__			) if isinstance(lowerCamelCase__		,   lowerCamelCase__			) else mask_token
             _UpperCAmelCase	:    Tuple				 =       legacy_behaviour
             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__		,   legacy_behaviour=lowerCamelCase__		,   **lowerCamelCase__		,   )

             _UpperCAmelCase	:    Optional[int]				 =       vocab_file
             _UpperCAmelCase	:    Tuple				 =       False if not self.vocab_file else True

             _UpperCAmelCase	:    str				 =       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}			)
             _UpperCAmelCase	:    Optional[int]				 =       {
                 lang_code: self.convert_tokens_to_ids(lowerCamelCase__			) for lang_code in FAIRSEQ_LANGUAGE_CODES
             }

             _UpperCAmelCase	:    List[Any]				 =       src_lang if src_lang is not None else "eng_Latn"
             _UpperCAmelCase	:    Union[str, Any]				 =       self.convert_tokens_to_ids(self._src_lang			)
             _UpperCAmelCase	:    List[str]				 =       tgt_lang
             self.set_src_lang_special_tokens(self._src_lang			)




      @property
      def 	_A      (			self		:							List[str]			):
             return self._src_lang




      @src_lang.setter
      def 	_A      (			self		:							int		,   A		:							str			):
             _UpperCAmelCase	:    Any				 =       new_src_lang
             self.set_src_lang_special_tokens(self._src_lang			)




      def 	_A      (			self		:							Any		,   A		:							int		,   A		:							str = None			):
             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 	_A      (			self		:							Tuple		,   A		:							Tuple		,   A		:							int = None			):
             _UpperCAmelCase	:    List[Any]				 =       [self.sep_token_id]
             _UpperCAmelCase	:    Tuple				 =       [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 	_A      (			self		:							Tuple		,   A		:							int		,   A		:							str		,   A		:							int		,   A		:							List[Any]		,   **A		:							Optional[Any]			):
             if src_lang is None or tgt_lang is None:
                    raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"			)
             _UpperCAmelCase	:    str				 =       src_lang
             _UpperCAmelCase	:    Any				 =       self(lowerCamelCase__		,   add_special_tokens=lowerCamelCase__		,   return_tensors=lowerCamelCase__		,   **lowerCamelCase__			)
             _UpperCAmelCase	:    List[Any]				 =       self.convert_tokens_to_ids(lowerCamelCase__			)
             _UpperCAmelCase	:    int				 =       tgt_lang_id
             return inputs




      def 	_A      (			self		:							Union[str, Any]		,   A		:							Dict		,   A		:							Any = "eng_Latn"		,   A		:							List[Any] = None		,   A		:							Optional[int] = "fra_Latn"		,   **A		:							Union[str, Any]		,   ):
             _UpperCAmelCase	:    Union[str, Any]				 =       src_lang
             _UpperCAmelCase	:    Optional[int]				 =       tgt_lang
             return super().prepare_seqaseq_batch(lowerCamelCase__		,   lowerCamelCase__		,   **lowerCamelCase__			)




      def 	_A      (			self		:							Optional[int]			):
             return self.set_src_lang_special_tokens(self.src_lang			)




      def 	_A      (			self		:							Optional[int]			):
             return self.set_tgt_lang_special_tokens(self.tgt_lang			)




      def 	_A      (			self		:							List[Any]		,   A		:							Optional[int]			):
             _UpperCAmelCase	:    int				 =       self.convert_tokens_to_ids(lowerCamelCase__			)

             if self.legacy_behaviour:
                    _UpperCAmelCase	:    List[str]				 =       []
                    _UpperCAmelCase	:    List[Any]				 =       [self.eos_token_id, self.cur_lang_code]
             else:
                    _UpperCAmelCase	:    Optional[Any]				 =       [self.cur_lang_code]
                    _UpperCAmelCase	:    List[Any]				 =       [self.eos_token_id]

             _UpperCAmelCase	:    Optional[Any]				 =       self.convert_ids_to_tokens(self.prefix_tokens			)
             _UpperCAmelCase	:    Optional[Any]				 =       self.convert_ids_to_tokens(self.suffix_tokens			)

             _UpperCAmelCase	:    Any				 =       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 	_A      (			self		:							Optional[Any]		,   A		:							Dict			):
             _UpperCAmelCase	:    Optional[int]				 =       self.convert_tokens_to_ids(lowerCamelCase__			)
             if self.legacy_behaviour:
                    _UpperCAmelCase	:    int				 =       []
                    _UpperCAmelCase	:    str				 =       [self.eos_token_id, self.cur_lang_code]
             else:
                    _UpperCAmelCase	:    Tuple				 =       [self.cur_lang_code]
                    _UpperCAmelCase	:    Tuple				 =       [self.eos_token_id]

             _UpperCAmelCase	:    Union[str, Any]				 =       self.convert_ids_to_tokens(self.prefix_tokens			)
             _UpperCAmelCase	:    Optional[int]				 =       self.convert_ids_to_tokens(self.suffix_tokens			)

             _UpperCAmelCase	:    Optional[Any]				 =       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 	_A      (			self		:							List[str]		,   A		:							List[str]		,   A		:							int = None			):
             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
             _UpperCAmelCase	:    str				 =       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,)




def 			_A	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Tuple									= int(SCREAMING_SNAKE_CASE      )
	if decimal in (0, 1):  # Exit cases for the recursion
		return str(SCREAMING_SNAKE_CASE      )
	UpperCAmelCase__							,						UpperCAmelCase__:	Union[str, Any]									= divmod(SCREAMING_SNAKE_CASE	,2      )
	return binary_recursive(SCREAMING_SNAKE_CASE      ) + str(SCREAMING_SNAKE_CASE      )



def 			_A	(      SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	List[str]									= str(SCREAMING_SNAKE_CASE      ).strip()
	if not number:
		raise ValueError("No input value was provided"      )
	UpperCAmelCase__:	Tuple									= "-" if number.startswith("-"      ) else ""
	UpperCAmelCase__:	Any									= number.lstrip("-"      )
	if not number.isnumeric():
		raise ValueError("Input value is not an integer"      )
	return f"{negative}0b{binary_recursive(int(SCREAMING_SNAKE_CASE      )      )}"


if __name__ == "__main__":
					from doctest import testmod

					testmod()