




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:
 lowerCamelCase       :	str									=     None


lowerCamelCase       :	List[Any]									=     logging.get_logger(__name__)


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

lowerCamelCase       :	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"
        ),
    },
}

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

# fmt: off
lowerCamelCase       :	List[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 						A(		UpperCamelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		VOCAB_FILES_NAMES
 UpperCamelCase		     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCamelCase		     =		PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase		     =		['''input_ids''', '''attention_mask''']
 UpperCamelCase		     =		NllbTokenizer

 UpperCamelCase		     =		[]
 UpperCamelCase		     =		[]

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

       """simple docstring"""






       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        a__				(       self      :						Optional[Any]						)     ->			str:

       """simple docstring"""






       return self._src_lang

 @src_lang.setter
 def        a__				(       self      :						Dict		,							A_      :						str						)     ->			None:

       """simple docstring"""






       lowerCamelCase_	  =					new_src_lang
       self.set_src_lang_special_tokens(self._src_lang						)

 def        a__				(       self      :						Any		,							A_      :						List[int]		,							A_      :						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        a__				(       self      :						Optional[int]		,							A_      :						List[int]		,							A_      :						Optional[List[int]] = None						)     ->			List[int]:

       """simple docstring"""






       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        a__				(       self      :						str		,							A_      :						int		,							A_      :						str		,							A_      :						Optional[str]		,							A_      :						Optional[str]		,							**A_      :						int						)     ->			int:

       """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_	  =					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        a__				(       self      :						Tuple		,							A_      :						List[str]		,							A_      :						str = "eng_Latn"		,							A_      :						Optional[List[str]] = None		,							A_      :						str = "fra_Latn"		,							**A_      :						Tuple		,							)     ->			BatchEncoding:

       """simple docstring"""






       lowerCamelCase_	  =					src_lang
       lowerCamelCase_	  =					tgt_lang
       return super().prepare_seqaseq_batch(A_		,							A_		,							**A_						)

 def        a__				(       self      :						str						)     ->			Union[str, Any]:

       """simple docstring"""






       return self.set_src_lang_special_tokens(self.src_lang						)

 def        a__				(       self      :						str						)     ->			str:

       """simple docstring"""






       return self.set_tgt_lang_special_tokens(self.tgt_lang						)

 def        a__				(       self      :						Optional[int]		,							A_      :						Dict						)     ->			None:

       """simple docstring"""






       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        a__				(       self      :						str		,							A_      :						str						)     ->			None:

       """simple docstring"""






       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        a__				(       self      :						List[str]		,							A_      :						str		,							A_      :						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(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,)





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass







@dataclass
class 						A:



 '''simple docstring'''


 UpperCamelCase		     =		42
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None

lowerCamelCase       :	str									=     namedtuple("CoinsDistribResult", "moves excess")

def     _SCREAMING_SNAKE_CASE    (							lowercase			: TreeNode | None  ):


      '''simple docstring'''



      if root is None:
            return 0

      # Validation
      def count_nodes(lowercase			: TreeNode | None  ) -> int:
            if node is None:
                  return 0

            return count_nodes(node.left  ) + count_nodes(node.right  ) + 1

      def count_coins(lowercase			: TreeNode | None  ) -> int:
            if node is None:
                  return 0

            return count_coins(node.left  ) + count_coins(node.right  ) + node.data

      if count_nodes(lowercase  ) != count_coins(lowercase  ):
            raise ValueError('The nodes number should be same as the number of coins'  )

      # Main calculation
      def get_distrib(lowercase			: TreeNode | None  ) -> CoinsDistribResult:

            if node is None:
                  return CoinsDistribResult(0			,							1  )

            lowerCamelCase_  ,       lowerCamelCase_	  =					get_distrib(node.left  )
            lowerCamelCase_  ,       lowerCamelCase_	  =					get_distrib(node.right  )

            lowerCamelCase_	  =					1 - left_distrib_excess
            lowerCamelCase_	  =					1 - right_distrib_excess

            lowerCamelCase_	  =					(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowercase  )
                + abs(lowercase  )
            )
            lowerCamelCase_	  =					node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowercase			,							lowercase  )

      return get_distrib(lowercase  )[0]


if __name__ == "__main__":
 import doctest

 doctest.testmod()



