'''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


SCREAMING_SNAKE_CASE_:     Optional[int]  =logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:     Optional[int]  ='▁'

SCREAMING_SNAKE_CASE_:     List[str]  ={'vocab_file': 'sentencepiece.bpe.model'}

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

SCREAMING_SNAKE_CASE_:     Tuple  ={
    'facebook/nllb-200-distilled-600M': 10_24,
}

# 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        __A      ( A_	):
    a__       :						Any          =  VOCAB_FILES_NAMES
    a__       :						List[str]          =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__       :						List[str]          =  PRETRAINED_VOCAB_FILES_MAP
    a__       :						int          =  ["input_ids", "attention_mask"]

    a__       :						List[int]          =  []
    a__       :						List[int]          =  []



    def __init__(self    :    Optional[int]   ,			__a    :    str   ,			__a    :    int="<s>"   ,			__a    :    int="</s>"   ,			__a    :    Tuple="</s>"   ,			__a    :    Optional[Any]="<s>"   ,			__a    :    Tuple="<unk>"   ,			__a    :    Tuple="<pad>"   ,			__a    :    Union[str, Any]="<mask>"   ,			__a    :    int=None   ,			__a    :    Tuple=None   ,			__a    :    Tuple=None   ,			__a    :    Optional[Dict[str, Any]] = None   ,			__a    :    Tuple=None   ,			__a    :    Dict=False   ,			**__a    :    Optional[int]   ,			):
         UpperCAmelCase_           =   AddedToken(snake_case__   ,			lstrip=snake_case__   ,			rstrip=snake_case__ ) if isinstance(snake_case__   ,			snake_case__ ) else mask_token

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

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

         UpperCAmelCase_           =   spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.Load(str(snake_case__ ) )
         UpperCAmelCase_           =   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
         UpperCAmelCase_           =   {"<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
         UpperCAmelCase_           =   1

         UpperCAmelCase_           =   len(self.sp_model )
         UpperCAmelCase_           =   {
             code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(snake_case__ )
         }
         UpperCAmelCase_           =   {v: k for k, v in self.lang_code_to_id.items()}
         UpperCAmelCase_           =   len(self.sp_model ) + len(self.lang_code_to_id ) + self.fairseq_offset

         self.fairseq_tokens_to_ids.update(self.lang_code_to_id )
         UpperCAmelCase_           =   {v: k for k, v in self.fairseq_tokens_to_ids.items()}
         UpperCAmelCase_           =   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] )

         UpperCAmelCase_           =   src_lang if src_lang is not None else "eng_Latn"
         UpperCAmelCase_           =   self.lang_code_to_id[self._src_lang]
         UpperCAmelCase_           =   tgt_lang
         self.set_src_lang_special_tokens(self._src_lang )



    def __getstate__(self    :    Optional[int] ):
         UpperCAmelCase_           =   self.__dict__.copy()
         UpperCAmelCase_           =   None
         UpperCAmelCase_           =   self.sp_model.serialized_model_proto()
         return state



    def __setstate__(self    :    Optional[Any]   ,			__a    :    Tuple ):
         UpperCAmelCase_           =   d

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

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



    @property
    def 					_lowercase						(self    :    Optional[Any] ):
         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    :    Optional[int] ):
         return self._src_lang



    @src_lang.setter
    def 					_lowercase						(self    :    List[str]   ,			__a    :    str ):
         UpperCAmelCase_           =   new_src_lang
         self.set_src_lang_special_tokens(self._src_lang )



    def 					_lowercase						(self    :    Any   ,			__a    :    List[int]   ,			__a    :    Optional[List[int]] = None   ,			__a    :    bool = False ):


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

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



    def 					_lowercase						(self    :    List[Any]   ,			__a    :    List[int]   ,			__a    :    Optional[List[int]] = 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 					_lowercase						(self    :    int   ,			__a    :    List[int]   ,			__a    :    Optional[List[int]] = None ):
         UpperCAmelCase_           =   [self.sep_token_id]
         UpperCAmelCase_           =   [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    :    Any   ,			__a    :    int   ,			__a    :    str   ,			__a    :    Optional[str]   ,			__a    :    Optional[str]   ,			**__a    :    Tuple ):


         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_           =   src_lang
         UpperCAmelCase_           =   self(snake_case__   ,			add_special_tokens=snake_case__   ,			return_tensors=snake_case__   ,			**snake_case__ )
         UpperCAmelCase_           =   self.convert_tokens_to_ids(snake_case__ )
         UpperCAmelCase_           =   tgt_lang_id
         return inputs



    def 					_lowercase						(self    :    Any ):
         UpperCAmelCase_           =   {self.convert_ids_to_tokens(snake_case__ ): i for i in range(self.vocab_size )}
         vocab.update(self.added_tokens_encoder )
         return vocab



    def 					_lowercase						(self    :    List[str]   ,			__a    :    str ):
         return self.sp_model.encode(snake_case__   ,			out_type=snake_case__ )



    def 					_lowercase						(self    :    Any   ,			__a    :    Any ):


         if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
         UpperCAmelCase_           =   self.sp_model.PieceToId(snake_case__ )

         # 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    :    List[str]   ,			__a    :    Tuple ):


         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    :    Dict   ,			__a    :    Optional[Any] ):
         UpperCAmelCase_           =   "".join(snake_case__ ).replace(snake_case__   ,			" " ).strip()
         return out_string



    def 					_lowercase						(self    :    Optional[int]   ,			__a    :    str   ,			__a    :    Optional[str] = None ):


         if not os.path.isdir(snake_case__ ):
              logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
              return
         UpperCAmelCase_           =   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__ ) and os.path.isfile(self.vocab_file ):
              copyfile(self.vocab_file   ,			snake_case__ )
         elif not os.path.isfile(self.vocab_file ):
              with open(snake_case__   ,			"wb" ) as fi:
                   UpperCAmelCase_           =   self.sp_model.serialized_model_proto()
                   fi.write(snake_case__ )

         return (out_vocab_file,)



    def 					_lowercase						(self    :    List[Any]   ,			__a    :    List[str]   ,			__a    :    str = "eng_Latn"   ,			__a    :    Optional[List[str]] = None   ,			__a    :    str = "fra_Latn"   ,			**__a    :    int   ,			):
         UpperCAmelCase_           =   src_lang
         UpperCAmelCase_           =   tgt_lang
         return super().prepare_seqaseq_batch(snake_case__   ,			snake_case__   ,			**snake_case__ )



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



    def 					_lowercase						(self    :    str ):
         return self.set_tgt_lang_special_tokens(self.tgt_lang )



    def 					_lowercase						(self    :    Optional[Any]   ,			__a    :    str ):
         UpperCAmelCase_           =   self.lang_code_to_id[src_lang]
         if self.legacy_behaviour:
              UpperCAmelCase_           =   []
              UpperCAmelCase_           =   [self.eos_token_id, self.cur_lang_code]
         else:
              UpperCAmelCase_           =   [self.cur_lang_code]
              UpperCAmelCase_           =   [self.eos_token_id]






    def 					_lowercase						(self    :    List[str]   ,			__a    :    str ):
         UpperCAmelCase_           =   self.lang_code_to_id[lang]
         if self.legacy_behaviour:
              UpperCAmelCase_           =   []
              UpperCAmelCase_           =   [self.eos_token_id, self.cur_lang_code]
         else:
              UpperCAmelCase_           =   [self.cur_lang_code]
              UpperCAmelCase_           =   [self.eos_token_id]






__lowerCamelCase							=       {
    "joule": 1.0,
    "kilojoule": 10_00,
    "megajoule": 1_00_00_00,
    "gigajoule": 10_00_00_00_00,
    "wattsecond": 1.0,
    "watthour": 36_00,
    "kilowatthour": 3_60_00_00,
    "newtonmeter": 1.0,
    "calorie_nutr": 41_86.8,
    "kilocalorie_nutr": 4_18_68_00.00,
    "electronvolt": 1.602_176_634e-19,
    "britishthermalunit_it": 10_55.0_55_85,
    "footpound": 1.35_5818,
}


def 			UpperCamelCase					(    __lowerCamelCase     : str				,					__lowerCamelCase     : str				,					__lowerCamelCase     : float    ):
       if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
              snake_case       :   List[Any]							=      (
                  f"""Incorrect 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
                  f"""Valid values are: {', '.join(__lowerCamelCase    )}"""
              )
              raise ValueError(__lowerCamelCase    )
       return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
   import doctest

   doctest.testmod()





