






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__      :			Optional[int]							=		None


SCREAMING_SNAKE_CASE__      :			Optional[Any]							=		logging.get_logger(__name__)


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

SCREAMING_SNAKE_CASE__      :			Union[str, 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"
        ),
    },
}

SCREAMING_SNAKE_CASE__      :			Any							=		{
    "facebook/nllb-large-en-ro": 10_24,
    "facebook/nllb-200-distilled-600M": 10_24,
}

# fmt: off
SCREAMING_SNAKE_CASE__      :			Tuple							=		["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 						lowerCamelCase_				(      UpperCamelCase_ ):
    a__					       =  VOCAB_FILES_NAMES
    a__					       =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__					       =  PRETRAINED_VOCAB_FILES_MAP
    a__					       =  ["""input_ids""", """attention_mask"""]
    a__					       =  NllbTokenizer

    a__					       =  []
    a__					       =  []







    def __init__(						self       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase="<s>"       ,					__lowerCAmelCase="</s>"       ,					__lowerCAmelCase="</s>"       ,					__lowerCAmelCase="<s>"       ,					__lowerCAmelCase="<unk>"       ,					__lowerCAmelCase="<pad>"       ,					__lowerCAmelCase="<mask>"       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=False       ,					**__lowerCAmelCase       ,					):
        """simple docstring"""
        __magic_name__		:Optional[Any]        =      AddedToken(_a       ,					lstrip=_a       ,					rstrip=_a     ) if isinstance(_a       ,					_a     ) else mask_token
        __magic_name__		:Optional[int]        =      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       ,					)

        __magic_name__		:Optional[int]        =      vocab_file
        __magic_name__		:str        =      False if not self.vocab_file else True

        __magic_name__		:Dict        =      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}     )
        __magic_name__		:List[str]        =      {
            lang_code: self.convert_tokens_to_ids(_a     ) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        __magic_name__		:Dict        =      src_lang if src_lang is not None else """eng_Latn"""
        __magic_name__		:List[str]        =      self.convert_tokens_to_ids(self._src_lang     )
        __magic_name__		:Dict        =      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       ,					__lowerCAmelCase     ):
        """simple docstring"""
        __magic_name__		:int        =      new_src_lang
        self.set_src_lang_special_tokens(self._src_lang     )







    def 			A	(						self       ,					__lowerCAmelCase       ,					__lowerCAmelCase = 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       ,					__lowerCAmelCase       ,					__lowerCAmelCase = None     ):
        """simple docstring"""
        __magic_name__		:int        =      [self.sep_token_id]
        __magic_name__		:str        =      [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       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					**__lowerCAmelCase     ):
        """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'''     )
        __magic_name__		:Dict        =      src_lang
        __magic_name__		:Dict        =      self(_a       ,					add_special_tokens=_a       ,					return_tensors=_a       ,					**_a     )
        __magic_name__		:Union[str, Any]        =      self.convert_tokens_to_ids(_a     )
        __magic_name__		:List[Any]        =      tgt_lang_id
        return inputs







    def 			A	(						self       ,					__lowerCAmelCase       ,					__lowerCAmelCase = "eng_Latn"       ,					__lowerCAmelCase = None       ,					__lowerCAmelCase = "fra_Latn"       ,					**__lowerCAmelCase       ,					):
        """simple docstring"""
        __magic_name__		:Tuple        =      src_lang
        __magic_name__		:Dict        =      tgt_lang
        return super().prepare_seqaseq_batch(_a       ,					_a       ,					**_a     )







    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       ,					__lowerCAmelCase     ):
        """simple docstring"""
        __magic_name__		:List[Any]        =      self.convert_tokens_to_ids(_a     )

        if self.legacy_behaviour:
            __magic_name__		:str        =      []
            __magic_name__		:Dict        =      [self.eos_token_id, self.cur_lang_code]
        else:
            __magic_name__		:Dict        =      [self.cur_lang_code]
            __magic_name__		:Dict        =      [self.eos_token_id]

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

        __magic_name__		: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       ,					__lowerCAmelCase     ):
        """simple docstring"""
        __magic_name__		:str        =      self.convert_tokens_to_ids(_a     )
        if self.legacy_behaviour:
            __magic_name__		:List[Any]        =      []
            __magic_name__		:Optional[int]        =      [self.eos_token_id, self.cur_lang_code]
        else:
            __magic_name__		:Optional[int]        =      [self.cur_lang_code]
            __magic_name__		:Union[str, Any]        =      [self.eos_token_id]

        __magic_name__		:Any        =      self.convert_ids_to_tokens(self.prefix_tokens     )
        __magic_name__		:Union[str, Any]        =      self.convert_ids_to_tokens(self.suffix_tokens     )

        __magic_name__		:Tuple        =      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       ,					__lowerCAmelCase       ,					__lowerCAmelCase = 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(_a     ):
            logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''     )
            return
        __magic_name__		:Dict        =      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 urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url

@pytest.mark.parametrize('''repo_id''',  ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''',  ['''filename.csv''', '''filename with blanks.csv'''] )
@pytest.mark.parametrize('''revision''',  [None, '''v2'''] )
def      __lowercase					( snake_case,  snake_case,  snake_case ):







				"""simple docstring"""






				__magic_name__		:Tuple        =      hf_hub_url(repo_id=snake_case,  path=snake_case,  revision=snake_case )
				assert url == f'''https://huggingface.co/datasets/{repo_id}/resolve/{revision or "main"}/{quote(snake_case )}'''






