


'''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:
       lowerCAmelCase    :     Any					=						None


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


lowerCAmelCase    :     Optional[int]					=						{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCAmelCase    :     Dict					=						{
    """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    :     Optional[Any]					=						{
    """facebook/nllb-large-en-ro""": 10_24,
    """facebook/nllb-200-distilled-600M""": 10_24,
}

# fmt: off
lowerCAmelCase    :     str					=						["""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__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     __magic_name__    			=    VOCAB_FILES_NAMES
     __magic_name__    			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __magic_name__    			=    PRETRAINED_VOCAB_FILES_MAP
     __magic_name__    			=    ["input_ids", "attention_mask"]
     __magic_name__    			=    NllbTokenizer

     __magic_name__    			=    []
     __magic_name__    			=    []







     def __init__( self      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__="<s>"      ,	snake_case__="</s>"      ,	snake_case__="</s>"      ,	snake_case__="<s>"      ,	snake_case__="<unk>"      ,	snake_case__="<pad>"      ,	snake_case__="<mask>"      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__=False      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							Dict   			=       AddedToken(snake_case__      ,	lstrip=snake_case__      ,	rstrip=snake_case__   ) if isinstance(snake_case__      ,	snake_case__   ) else mask_token
            _lowerCAmelCase    :							Any   			=       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__      ,	)

            _lowerCAmelCase    :							Optional[Any]   			=       vocab_file
            _lowerCAmelCase    :							Tuple   			=       False if not self.vocab_file else True

            _lowerCAmelCase    :							List[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}   )
            _lowerCAmelCase    :							Dict   			=       {
                lang_code: self.convert_tokens_to_ids(snake_case__   ) for lang_code in FAIRSEQ_LANGUAGE_CODES
            }

            _lowerCAmelCase    :							str   			=       src_lang if src_lang is not None else 'eng_Latn'
            _lowerCAmelCase    :							int   			=       self.convert_tokens_to_ids(self._src_lang   )
            _lowerCAmelCase    :							int   			=       tgt_lang
            self.set_src_lang_special_tokens(self._src_lang   )







     @property
     def a	( self   ):

            '''simple docstring'''

            return self._src_lang







     @src_lang.setter
     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							str   			=       new_src_lang
            self.set_src_lang_special_tokens(self._src_lang   )







     def a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''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      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Dict   			=       [self.sep_token_id]
            _lowerCAmelCase    :							List[Any]   			=       [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      ,	snake_case__      ,	snake_case__      ,	snake_case__      ,	snake_case__      ,	**snake_case__   ):

            '''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    :							Union[str, Any]   			=       src_lang
            _lowerCAmelCase    :							List[Any]   			=       self(snake_case__      ,	add_special_tokens=snake_case__      ,	return_tensors=snake_case__      ,	**snake_case__   )
            _lowerCAmelCase    :							Optional[int]   			=       self.convert_tokens_to_ids(snake_case__   )
            _lowerCAmelCase    :							List[Any]   			=       tgt_lang_id
            return inputs







     def a	( self      ,	snake_case__      ,	snake_case__ = "eng_Latn"      ,	snake_case__ = None      ,	snake_case__ = "fra_Latn"      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							Dict   			=       src_lang
            _lowerCAmelCase    :							Tuple   			=       tgt_lang
            return super().prepare_seqaseq_batch(snake_case__      ,	snake_case__      ,	**snake_case__   )







     def a	( self   ):

            '''simple docstring'''

            return self.set_src_lang_special_tokens(self.src_lang   )







     def a	( self   ):

            '''simple docstring'''

            return self.set_tgt_lang_special_tokens(self.tgt_lang   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[Any]   			=       self.convert_tokens_to_ids(snake_case__   )

            if self.legacy_behaviour:
                   _lowerCAmelCase    :							List[Any]   			=       []
                   _lowerCAmelCase    :							Dict   			=       [self.eos_token_id, self.cur_lang_code]
            else:
                   _lowerCAmelCase    :							Optional[int]   			=       [self.cur_lang_code]
                   _lowerCAmelCase    :							int   			=       [self.eos_token_id]

            _lowerCAmelCase    :							Dict   			=       self.convert_ids_to_tokens(self.prefix_tokens   )
            _lowerCAmelCase    :							Optional[int]   			=       self.convert_ids_to_tokens(self.suffix_tokens   )

            _lowerCAmelCase    :							int   			=       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      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       self.convert_tokens_to_ids(snake_case__   )
            if self.legacy_behaviour:
                   _lowerCAmelCase    :							List[str]   			=       []
                   _lowerCAmelCase    :							Tuple   			=       [self.eos_token_id, self.cur_lang_code]
            else:
                   _lowerCAmelCase    :							int   			=       [self.cur_lang_code]
                   _lowerCAmelCase    :							List[Any]   			=       [self.eos_token_id]

            _lowerCAmelCase    :							Optional[int]   			=       self.convert_ids_to_tokens(self.prefix_tokens   )
            _lowerCAmelCase    :							Optional[int]   			=       self.convert_ids_to_tokens(self.suffix_tokens   )

            _lowerCAmelCase    :							List[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      ,	snake_case__      ,	snake_case__ = None   ):

            '''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
            _lowerCAmelCase    :							int   			=       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,)





'''simple docstring'''







from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *

