
"""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


UpperCamelCase_       :    Dict						      =			logging.get_logger(__name__)

UpperCamelCase_       :    Any						      =			'''▁'''

UpperCamelCase_       :    str						      =			{'''vocab_file''': '''sentencepiece.bpe.model'''}

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

UpperCamelCase_       :    List[Any]						      =			{
    '''facebook/nllb-200-distilled-600M''': 1024,
}

# fmt: off
UpperCamelCase_       :    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 __lowerCAmelCase					(       _lowercase   ):




			"""simple docstring"""







			snake_case						   =					VOCAB_FILES_NAMES
			snake_case						   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			snake_case						   =					PRETRAINED_VOCAB_FILES_MAP
			snake_case						   =					["input_ids", "attention_mask"]

			snake_case						   =					[]
			snake_case						   =					[]




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







								"""simple docstring"""
								# Mask token behave like a normal word, i.e. include the space before it
								A_								=    AddedToken(_snake_case							, lstrip=_snake_case							, rstrip=_snake_case						) if isinstance(_snake_case							, _snake_case						) else mask_token

								A_								=    {} if sp_model_kwargs is None else sp_model_kwargs
								A_								=    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							, )

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

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

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

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




			def __getstate__(					self    :       Optional[Any]						)   ->			Dict:







								"""simple docstring"""
								A_								=    self.__dict__.copy()
								A_								=    None
								A_								=    self.sp_model.serialized_model_proto()
								return state




			def __setstate__(					self    :       Union[str, Any]							, _snake_case    :       Dict						)   ->			int:







								"""simple docstring"""
								A_								=    d

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

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




			@property
			def   lowerCamelCase__  (					self    :       List[Any]						)   ->			Dict:







								"""simple docstring"""
								return len(self.sp_model						) + len(self.lang_code_to_id						) + self.fairseq_offset + 1  # Plus 1 for the mask token




			@property
			def   lowerCamelCase__  (					self    :       List[str]						)   ->			str:







								"""simple docstring"""
								return self._src_lang




			@src_lang.setter
			def   lowerCamelCase__  (					self    :       Optional[int]							, _snake_case    :       str						)   ->			None:







								"""simple docstring"""
								A_								=    new_src_lang
								self.set_src_lang_special_tokens(self._src_lang						)




			def   lowerCamelCase__  (					self    :       List[Any]							, _snake_case    :       List[int]							, _snake_case    :       Optional[List[int]] = None							, _snake_case    :       bool = False						)   ->			List[int]:







								"""simple docstring"""

								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						)

								A_								=    [1] * len(self.prefix_tokens						)
								A_								=    [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   lowerCamelCase__  (					self    :       Optional[Any]							, _snake_case    :       List[int]							, _snake_case    :       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    :       Any							, _snake_case    :       List[int]							, _snake_case    :       Optional[List[int]] = None						)   ->			List[int]:







								"""simple docstring"""
								A_								=    [self.sep_token_id]
								A_								=    [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    :       Union[str, Any]							, _snake_case    :       Optional[int]							, _snake_case    :       str							, _snake_case    :       Optional[str]							, _snake_case    :       Optional[str]							, **_snake_case    :       Any						)   ->			List[Any]:







								"""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"						)
								A_								=    src_lang
								A_								=    self(_snake_case							, add_special_tokens=_snake_case							, return_tensors=_snake_case							, **_snake_case						)
								A_								=    self.convert_tokens_to_ids(_snake_case						)
								A_								=    tgt_lang_id
								return inputs




			def   lowerCamelCase__  (					self    :       str						)   ->			Any:







								"""simple docstring"""
								A_								=    {self.convert_ids_to_tokens(_snake_case						): i for i in range(self.vocab_size						)}
								vocab.update(self.added_tokens_encoder						)
								return vocab




			def   lowerCamelCase__  (					self    :       Optional[int]							, _snake_case    :       str						)   ->			List[str]:







								"""simple docstring"""
								return self.sp_model.encode(_snake_case							, out_type=_snake_case						)




			def   lowerCamelCase__  (					self    :       Optional[Any]							, _snake_case    :       Any						)   ->			str:







								"""simple docstring"""
								if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
								A_								=    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   lowerCamelCase__  (					self    :       Tuple							, _snake_case    :       List[str]						)   ->			Any:







								"""simple docstring"""
								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   lowerCamelCase__  (					self    :       List[str]							, _snake_case    :       int						)   ->			Optional[Any]:







								"""simple docstring"""
								A_								=    "".join(_snake_case						).replace(_snake_case							, " "						).strip()
								return out_string




			def   lowerCamelCase__  (					self    :       List[str]							, _snake_case    :       str							, _snake_case    :       Optional[str] = None						)   ->			Tuple[str]:







								"""simple docstring"""
								if not os.path.isdir(_snake_case						):
													logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
													return
								A_								=    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:
																		A_								=    self.sp_model.serialized_model_proto()
																		fi.write(_snake_case						)

								return (out_vocab_file,)




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







								"""simple docstring"""
								A_								=    src_lang
								A_								=    tgt_lang
								return super().prepare_seqaseq_batch(_snake_case							, _snake_case							, **_snake_case						)




			def   lowerCamelCase__  (					self    :       Tuple						)   ->			Tuple:







								"""simple docstring"""
								return self.set_src_lang_special_tokens(self.src_lang						)




			def   lowerCamelCase__  (					self    :       Optional[Any]						)   ->			int:







								"""simple docstring"""
								return self.set_tgt_lang_special_tokens(self.tgt_lang						)




			def   lowerCamelCase__  (					self    :       Tuple							, _snake_case    :       Optional[int]						)   ->			None:







								"""simple docstring"""
								A_								=    self.lang_code_to_id[src_lang]
								if self.legacy_behaviour:
													A_								=    []
													A_								=    [self.eos_token_id, self.cur_lang_code]
								else:
													A_								=    [self.cur_lang_code]
													A_								=    [self.eos_token_id]






			def   lowerCamelCase__  (					self    :       Optional[Any]							, _snake_case    :       str						)   ->			None:







								"""simple docstring"""
								A_								=    self.lang_code_to_id[lang]
								if self.legacy_behaviour:
													A_								=    []
													A_								=    [self.eos_token_id, self.cur_lang_code]
								else:
													A_								=    [self.cur_lang_code]
													A_								=    [self.eos_token_id]






"""simple docstring"""





from typing import TYPE_CHECKING

from ..utils import _LazyModule


UpperCamelCase_       :    Dict						      =			{
    '''config''': [
        '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
        '''OnnxConfig''',
        '''OnnxConfigWithPast''',
        '''OnnxSeq2SeqConfigWithPast''',
        '''PatchingSpec''',
    ],
    '''convert''': ['''export''', '''validate_model_outputs'''],
    '''features''': ['''FeaturesManager'''],
    '''utils''': ['''ParameterFormat''', '''compute_serialized_parameters_size'''],
}


if TYPE_CHECKING:
		from .config import (
		    EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
		    OnnxConfig,
		    OnnxConfigWithPast,
		    OnnxSeqaSeqConfigWithPast,
		    PatchingSpec,
		)
		from .convert import export, validate_model_outputs
		from .features import FeaturesManager
		from .utils import ParameterFormat, compute_serialized_parameters_size

else:
		import sys

		UpperCamelCase_       :    List[Any]						      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




