


"""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:
				__SCREAMING_SNAKE_CASE							:      Optional[int]						=      None


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


__SCREAMING_SNAKE_CASE							:      Union[str, Any]						=      {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

__SCREAMING_SNAKE_CASE							:      List[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							:      int						=      {
    'facebook/nllb-large-en-ro': 1_024,
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
__SCREAMING_SNAKE_CASE							:      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       (snake_case_):





							'''simple docstring'''

							__lowercase:						Tuple							 =      VOCAB_FILES_NAMES
							__lowercase:						Any							 =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase:						List[str]							 =      PRETRAINED_VOCAB_FILES_MAP
							__lowercase:						List[Any]							 =      ["""input_ids""", """attention_mask"""]
							__lowercase:						Dict							 =      NllbTokenizer

							__lowercase:						Any							 =      []
							__lowercase:						List[Any]							 =      []



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



														"""simple docstring"""



														snake_case_          =						AddedToken(UpperCAmelCase_						,    lstrip=UpperCAmelCase_						,    rstrip=UpperCAmelCase_    ) if isinstance(UpperCAmelCase_						,    UpperCAmelCase_    ) else mask_token
														snake_case_          =						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_						,    )

														snake_case_          =						vocab_file
														snake_case_          =						False if not self.vocab_file else True

														snake_case_          =						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}    )
														snake_case_          =						{
														    lang_code: self.convert_tokens_to_ids(UpperCAmelCase_    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
														}

														snake_case_          =						src_lang if src_lang is not None else 'eng_Latn'
														snake_case_          =						self.convert_tokens_to_ids(self._src_lang    )
														snake_case_          =						tgt_lang
														self.set_src_lang_special_tokens(self._src_lang    )



							@property
							def 						lowerCAmelCase    (			self							: Any    )   ->str:



														"""simple docstring"""



														return self._src_lang



							@src_lang.setter
							def 						lowerCAmelCase    (			self							: Union[str, Any]						,    UpperCAmelCase_							: str    )   ->None:



														"""simple docstring"""



														snake_case_          =						new_src_lang
														self.set_src_lang_special_tokens(self._src_lang    )



							def 						lowerCAmelCase    (			self							: str						,    UpperCAmelCase_							: List[int]						,    UpperCAmelCase_							: 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 						lowerCAmelCase    (			self							: List[str]						,    UpperCAmelCase_							: List[int]						,    UpperCAmelCase_							: Optional[List[int]] = None    )   ->List[int]:



														"""simple docstring"""



														snake_case_          =						[self.sep_token_id]
														snake_case_          =						[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 						lowerCAmelCase    (			self							: List[str]						,    UpperCAmelCase_							: int						,    UpperCAmelCase_							: str						,    UpperCAmelCase_							: Optional[str]						,    UpperCAmelCase_							: Optional[str]						,    **UpperCAmelCase_							: int    )   ->str:



														"""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"""    )
														snake_case_          =						src_lang
														snake_case_          =						self(UpperCAmelCase_						,    add_special_tokens=UpperCAmelCase_						,    return_tensors=UpperCAmelCase_						,    **UpperCAmelCase_    )
														snake_case_          =						self.convert_tokens_to_ids(UpperCAmelCase_    )
														snake_case_          =						tgt_lang_id
														return inputs



							def 						lowerCAmelCase    (			self							: Optional[int]						,    UpperCAmelCase_							: List[str]						,    UpperCAmelCase_							: str = "eng_Latn"						,    UpperCAmelCase_							: Optional[List[str]] = None						,    UpperCAmelCase_							: str = "fra_Latn"						,    **UpperCAmelCase_							: str						,    )   ->BatchEncoding:



														"""simple docstring"""



														snake_case_          =						src_lang
														snake_case_          =						tgt_lang
														return super().prepare_seqaseq_batch(UpperCAmelCase_						,    UpperCAmelCase_						,    **UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: List[str]    )   ->Tuple:



														"""simple docstring"""



														return self.set_src_lang_special_tokens(self.src_lang    )



							def 						lowerCAmelCase    (			self							: Optional[Any]    )   ->List[Any]:



														"""simple docstring"""



														return self.set_tgt_lang_special_tokens(self.tgt_lang    )



							def 						lowerCAmelCase    (			self							: Optional[int]						,    UpperCAmelCase_							: List[str]    )   ->None:



														"""simple docstring"""



														snake_case_          =						self.convert_tokens_to_ids(UpperCAmelCase_    )

														if self.legacy_behaviour:
																					snake_case_          =						[]
																					snake_case_          =						[self.eos_token_id, self.cur_lang_code]
														else:
																					snake_case_          =						[self.cur_lang_code]
																					snake_case_          =						[self.eos_token_id]

														snake_case_          =						self.convert_ids_to_tokens(self.prefix_tokens    )
														snake_case_          =						self.convert_ids_to_tokens(self.suffix_tokens    )

														snake_case_          =						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 						lowerCAmelCase    (			self							: int						,    UpperCAmelCase_							: str    )   ->None:



														"""simple docstring"""



														snake_case_          =						self.convert_tokens_to_ids(UpperCAmelCase_    )
														if self.legacy_behaviour:
																					snake_case_          =						[]
																					snake_case_          =						[self.eos_token_id, self.cur_lang_code]
														else:
																					snake_case_          =						[self.cur_lang_code]
																					snake_case_          =						[self.eos_token_id]

														snake_case_          =						self.convert_ids_to_tokens(self.prefix_tokens    )
														snake_case_          =						self.convert_ids_to_tokens(self.suffix_tokens    )

														snake_case_          =						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 						lowerCAmelCase    (			self							: Tuple						,    UpperCAmelCase_							: str						,    UpperCAmelCase_							: 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(UpperCAmelCase_    ):
																					logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""    )
																					return
														snake_case_          =						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"""
def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE = 0			)      ->			list:
							snake_case_          =						length or len(_SCREAMING_SNAKE_CASE			)
							snake_case_          =						False
							for i in range(length - 1			):
														if list_data[i] > list_data[i + 1]:
																					snake_case_    ,  snake_case_          =						list_data[i + 1], list_data[i]
																					snake_case_          =						True

							return list_data if not swapped else bubble_sort(_SCREAMING_SNAKE_CASE			,	length - 1			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()



