

import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


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

class __UpperCamelCase     (				_a		):






					'''simple docstring'''



					def __init__(				self				,      *lowerCamelCase__				,      **lowerCamelCase__						):
						warnings.warn(
						    "The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
						    " use DonutImageProcessor instead."				,      lowerCamelCase__				,      )
						super().__init__(*lowerCamelCase__				,      **lowerCamelCase__						)


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

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

# fmt: off
_lowerCAmelCase  :      Union[str, 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 __UpperCamelCase     (				_a		):






					'''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				,      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__				,      ):
						# Mask token behave like a normal word, i.e. include the space before it
						UpperCAmelCase__:	int									= AddedToken(lowerCamelCase__				,      lstrip=lowerCamelCase__				,      rstrip=lowerCamelCase__						) if isinstance(lowerCamelCase__				,      lowerCamelCase__						) else mask_token
						UpperCAmelCase__:	Tuple									= legacy_behaviour
						super().__init__(
						    vocab_file=lowerCamelCase__				,      tokenizer_file=lowerCamelCase__				,      bos_token=lowerCamelCase__				,      eos_token=lowerCamelCase__				,      sep_token=lowerCamelCase__				,      cls_token=lowerCamelCase__				,      unk_token=lowerCamelCase__				,      pad_token=lowerCamelCase__				,      mask_token=lowerCamelCase__				,      src_lang=lowerCamelCase__				,      tgt_lang=lowerCamelCase__				,      additional_special_tokens=lowerCamelCase__				,      legacy_behaviour=lowerCamelCase__				,      **lowerCamelCase__				,      )

						UpperCAmelCase__:	Optional[int]									= vocab_file
						UpperCAmelCase__:	Tuple									= False if not self.vocab_file else True

						UpperCAmelCase__:	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}						)
						UpperCAmelCase__:	Optional[int]									= {
						    lang_code: self.convert_tokens_to_ids(lowerCamelCase__						) for lang_code in FAIRSEQ_LANGUAGE_CODES
						}

						UpperCAmelCase__:	List[Any]									= src_lang if src_lang is not None else "eng_Latn"
						UpperCAmelCase__:	Union[str, Any]									= self.convert_tokens_to_ids(self._src_lang						)
						UpperCAmelCase__:	List[str]									= tgt_lang
						self.set_src_lang_special_tokens(self._src_lang						)





					@property
					def    _UpperCAmelCase    (				self						):
						return self._src_lang





					@src_lang.setter
					def    _UpperCAmelCase    (				self				,      lowerCamelCase__						):
						UpperCAmelCase__:	Any									= new_src_lang
						self.set_src_lang_special_tokens(self._src_lang						)





					def    _UpperCAmelCase    (				self				,      lowerCamelCase__				,      lowerCamelCase__ = None						):
						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				,      lowerCamelCase__				,      lowerCamelCase__ = None						):
						UpperCAmelCase__:	List[Any]									= [self.sep_token_id]
						UpperCAmelCase__:	Tuple									= [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				,      lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__				,      lowerCamelCase__				,      **lowerCamelCase__						):
						if src_lang is None or tgt_lang is None:
							raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"						)
						UpperCAmelCase__:	str									= src_lang
						UpperCAmelCase__:	Any									= self(lowerCamelCase__				,      add_special_tokens=lowerCamelCase__				,      return_tensors=lowerCamelCase__				,      **lowerCamelCase__						)
						UpperCAmelCase__:	List[Any]									= self.convert_tokens_to_ids(lowerCamelCase__						)
						UpperCAmelCase__:	int									= tgt_lang_id
						return inputs





					def    _UpperCAmelCase    (				self				,      lowerCamelCase__				,      lowerCamelCase__ = "eng_Latn"				,      lowerCamelCase__ = None				,      lowerCamelCase__ = "fra_Latn"				,      **lowerCamelCase__				,      ):
						UpperCAmelCase__:	Union[str, Any]									= src_lang
						UpperCAmelCase__:	Optional[int]									= tgt_lang
						return super().prepare_seqaseq_batch(lowerCamelCase__				,      lowerCamelCase__				,      **lowerCamelCase__						)





					def    _UpperCAmelCase    (				self						):
						return self.set_src_lang_special_tokens(self.src_lang						)





					def    _UpperCAmelCase    (				self						):
						return self.set_tgt_lang_special_tokens(self.tgt_lang						)





					def    _UpperCAmelCase    (				self				,      lowerCamelCase__						):
						UpperCAmelCase__:	int									= self.convert_tokens_to_ids(lowerCamelCase__						)

						if self.legacy_behaviour:
							UpperCAmelCase__:	List[str]									= []
							UpperCAmelCase__:	List[Any]									= [self.eos_token_id, self.cur_lang_code]
						else:
							UpperCAmelCase__:	Optional[Any]									= [self.cur_lang_code]
							UpperCAmelCase__:	List[Any]									= [self.eos_token_id]

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

						UpperCAmelCase__:	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    _UpperCAmelCase    (				self				,      lowerCamelCase__						):
						UpperCAmelCase__:	Optional[int]									= self.convert_tokens_to_ids(lowerCamelCase__						)
						if self.legacy_behaviour:
							UpperCAmelCase__:	int									= []
							UpperCAmelCase__:	str									= [self.eos_token_id, self.cur_lang_code]
						else:
							UpperCAmelCase__:	Tuple									= [self.cur_lang_code]
							UpperCAmelCase__:	Tuple									= [self.eos_token_id]

						UpperCAmelCase__:	Union[str, Any]									= self.convert_ids_to_tokens(self.prefix_tokens						)
						UpperCAmelCase__:	Optional[int]									= self.convert_ids_to_tokens(self.suffix_tokens						)

						UpperCAmelCase__:	Optional[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    _UpperCAmelCase    (				self				,      lowerCamelCase__				,      lowerCamelCase__ = None						):
						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(lowerCamelCase__						):
							logger.error(F"Vocabulary path ({save_directory}) should be a directory."						)
							return
						UpperCAmelCase__:	str									= os.path.join(
						    lowerCamelCase__				,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

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

						return (out_vocab_file,)