




"""simple docstring"""



def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		int:
 A__	=    len(lowercase_						)
 A__	=    sum(lowercase_						)

 A__	=    [[False for x in range(s + 1						)] for y in range(n + 1						)]

 for i in range(1      ,			n + 1						):
  A__	=    True

 for i in range(1      ,			s + 1						):
  A__	=    False

 for i in range(1      ,			n + 1						):
  for j in range(1      ,			s + 1						):
   A__	=    dp[i][j - 1]

   if arr[i - 1] <= j:
    A__	=    dp[i][j] or dp[i - 1][j - arr[i - 1]]

 for j in range(int(s / 2						)      ,			-1      ,			-1						):
  if dp[n][j] is True:
   A__	=    s - 2 * j
   break

 return diff











"""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    =	None


SCREAMING_SNAKE_CASE    =	logging.get_logger(__name__)


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

SCREAMING_SNAKE_CASE    =	{
    "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    =	{
    "facebook/nllb-large-en-ro": 1024,
    "facebook/nllb-200-distilled-600M": 1024,
}

# fmt: off
SCREAMING_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_  (						A_							):
    lowercase__						 =				VOCAB_FILES_NAMES
    lowercase__						 =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase__						 =				PRETRAINED_VOCAB_FILES_MAP
    lowercase__						 =				['''input_ids''', '''attention_mask''']
    lowercase__						 =				NllbTokenizer

    lowercase__						 =				[]
    lowercase__						 =				[]




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




     '''simple docstring'''

     A__	=    AddedToken(snake_case_     ,			lstrip=snake_case_     ,			rstrip=snake_case_				) if isinstance(snake_case_     ,			snake_case_				) else mask_token
     A__	=    legacy_behaviour
     super().__init__(
         vocab_file=snake_case_     ,			tokenizer_file=snake_case_     ,			bos_token=snake_case_     ,			eos_token=snake_case_     ,			sep_token=snake_case_     ,			cls_token=snake_case_     ,			unk_token=snake_case_     ,			pad_token=snake_case_     ,			mask_token=snake_case_     ,			src_lang=snake_case_     ,			tgt_lang=snake_case_     ,			additional_special_tokens=snake_case_     ,			legacy_behaviour=snake_case_     ,			**snake_case_     ,			)

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

     A__	=    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}				)
     A__	=    {
         lang_code: self.convert_tokens_to_ids(snake_case_				) for lang_code in FAIRSEQ_LANGUAGE_CODES
     }

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




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




     '''simple docstring'''

     return self._src_lang




    @src_lang.setter
    def 							__magic_name__							(   self						:	Optional[int]     ,			snake_case_						:	str				)				->							None:




     '''simple docstring'''

     A__	=    new_src_lang
     self.set_src_lang_special_tokens(self._src_lang				)




    def 							__magic_name__							(   self						:	Optional[int]     ,			snake_case_						:	List[int]     ,			snake_case_						:	Optional[List[int]] = 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 							__magic_name__							(   self						:	Any     ,			snake_case_						:	List[int]     ,			snake_case_						:	Optional[List[int]] = 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 							__magic_name__							(   self						:	int     ,			snake_case_						:	Tuple     ,			snake_case_						:	str     ,			snake_case_						:	Optional[str]     ,			snake_case_						:	Optional[str]     ,			**snake_case_						:	Tuple				)				->							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(snake_case_     ,			add_special_tokens=snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)
     A__	=    self.convert_tokens_to_ids(snake_case_				)
     A__	=    tgt_lang_id
     return inputs




    def 							__magic_name__							(   self						:	int     ,			snake_case_						:	List[str]     ,			snake_case_						:	str = "eng_Latn"     ,			snake_case_						:	Optional[List[str]] = None     ,			snake_case_						:	str = "fra_Latn"     ,			**snake_case_						:	Dict     ,			)				->							BatchEncoding:




     '''simple docstring'''

     A__	=    src_lang
     A__	=    tgt_lang
     return super().prepare_seqaseq_batch(snake_case_     ,			snake_case_     ,			**snake_case_				)




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




     '''simple docstring'''

     return self.set_src_lang_special_tokens(self.src_lang				)




    def 							__magic_name__							(   self						:	Tuple				)				->							Dict:




     '''simple docstring'''

     return self.set_tgt_lang_special_tokens(self.tgt_lang				)




    def 							__magic_name__							(   self						:	List[Any]     ,			snake_case_						:	Dict				)				->							None:




     '''simple docstring'''

     A__	=    self.convert_tokens_to_ids(snake_case_				)

     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]

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

     A__	=    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 							__magic_name__							(   self						:	List[Any]     ,			snake_case_						:	str				)				->							None:




     '''simple docstring'''

     A__	=    self.convert_tokens_to_ids(snake_case_				)
     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]

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

     A__	=    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 							__magic_name__							(   self						:	List[str]     ,			snake_case_						:	str     ,			snake_case_						:	Optional[str] = None				)				->							Tuple[str]:




     '''simple docstring'''

     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(snake_case_				):
      logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""				)
      return
     A__	=    os.path.join(
         snake_case_     ,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)

     if os.path.abspath(self.vocab_file				) != os.path.abspath(snake_case_				):
      copyfile(self.vocab_file     ,			snake_case_				)

     return (out_vocab_file,)





