


'''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:
       __snake_case    						=None


__snake_case    						=logging.get_logger(__name__)


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

__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"""
        ),
    },
}

__snake_case    						={
    """facebook/nllb-large-en-ro""": 1_024,
    """facebook/nllb-200-distilled-600M""": 1_024,
}

# fmt: off
__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_      (  __lowercase		):
     lowerCamelCase				:	Tuple		=     VOCAB_FILES_NAMES
     lowerCamelCase				:	List[str]		=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCamelCase				:	Any		=     PRETRAINED_VOCAB_FILES_MAP
     lowerCamelCase				:	Optional[Any]		=     ['''input_ids''', '''attention_mask''']
     lowerCamelCase				:	str		=     NllbTokenizer

     lowerCamelCase				:	List[int]		=     []
     lowerCamelCase				:	List[int]		=     []





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

        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(UpperCAmelCase__    ) 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 							__UpperCAmelCase      ( self       :      List[Any]    )				->  str:
        return self._src_lang





     @src_lang.setter
     def 							__UpperCAmelCase      ( self       :      List[Any]    ,      UpperCAmelCase__       :      str    )				->  None:
        lowerCAmelCase     =			new_src_lang
        self.set_src_lang_special_tokens(self._src_lang    )





     def 							__UpperCAmelCase      ( self       :      Union[str, Any]    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      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 							__UpperCAmelCase      ( self       :      List[str]    ,      UpperCAmelCase__       :      List[int]    ,      UpperCAmelCase__       :      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 							__UpperCAmelCase      ( self       :      int    ,      UpperCAmelCase__       :      Dict    ,      UpperCAmelCase__       :      str    ,      UpperCAmelCase__       :      Optional[str]    ,      UpperCAmelCase__       :      Optional[str]    ,      **UpperCAmelCase__       :      int    )				->  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'    )
        lowerCAmelCase     =			src_lang
        lowerCAmelCase     =			self(UpperCAmelCase__    ,      add_special_tokens=UpperCAmelCase__    ,      return_tensors=UpperCAmelCase__    ,      **UpperCAmelCase__    )
        lowerCAmelCase     =			self.convert_tokens_to_ids(UpperCAmelCase__    )
        lowerCAmelCase     =			tgt_lang_id
        return inputs





     def 							__UpperCAmelCase      ( self       :      Tuple    ,      UpperCAmelCase__       :      List[str]    ,      UpperCAmelCase__       :      str = "eng_Latn"    ,      UpperCAmelCase__       :      Optional[List[str]] = None    ,      UpperCAmelCase__       :      str = "fra_Latn"    ,      **UpperCAmelCase__       :      List[Any]    ,      )				->  BatchEncoding:
        lowerCAmelCase     =			src_lang
        lowerCAmelCase     =			tgt_lang
        return super().prepare_seqaseq_batch(UpperCAmelCase__    ,      UpperCAmelCase__    ,      **UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      int    )				->  List[str]:
        return self.set_src_lang_special_tokens(self.src_lang    )





     def 							__UpperCAmelCase      ( self       :      Tuple    )				->  List[str]:
        return self.set_tgt_lang_special_tokens(self.tgt_lang    )





     def 							__UpperCAmelCase      ( self       :      List[Any]    ,      UpperCAmelCase__       :      Any    )				->  None:
        lowerCAmelCase     =			self.convert_tokens_to_ids(UpperCAmelCase__    )

        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 							__UpperCAmelCase      ( self       :      Dict    ,      UpperCAmelCase__       :      str    )				->  None:
        lowerCAmelCase     =			self.convert_tokens_to_ids(UpperCAmelCase__    )
        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 							__UpperCAmelCase      ( self       :      Tuple    ,      UpperCAmelCase__       :      str    ,      UpperCAmelCase__       :      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(UpperCAmelCase__    ):
           logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''    )
           return
        lowerCAmelCase     =			os.path.join(
            UpperCAmelCase__    ,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )

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

        return (out_vocab_file,)









'''simple docstring'''




import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


__snake_case    						=logging.getLogger(__name__)

@dataclass
@add_start_docstrings(TrainingArguments.__doc__		)
class 		UpperCAmelCase_      (  __lowercase		):
     lowerCamelCase				:	bool		=     field(default=__lowercase       ,	metadata={'''help''': '''Whether to use SortishSampler or not.'''}		)
     lowerCamelCase				:	bool		=     field(
         default=__lowercase       ,	metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}		)
     lowerCamelCase				:	Optional[int]		=     field(
         default=__lowercase       ,	metadata={
             '''help''': (
                 '''The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default '''
                 '''to the `max_length` value of the model configuration.'''
             )
         }       ,	)
     lowerCamelCase				:	Optional[int]		=     field(
         default=__lowercase       ,	metadata={
             '''help''': (
                 '''The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default '''
                 '''to the `num_beams` value of the model configuration.'''
             )
         }       ,	)
     lowerCamelCase				:	Optional[Union[str, Path, GenerationConfig]]		=     field(
         default=__lowercase       ,	metadata={
             '''help''': '''Model id, file path or url pointing to a GenerationConfig json file, to use during prediction.'''
         }       ,	)





     def 							__UpperCAmelCase      ( self       :      Dict    )				->  List[str]:
        lowerCAmelCase     =			super().to_dict()
        for k, v in d.items():
           if isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    ):
              lowerCAmelCase     =			v.to_dict()
        return d





