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


a_							=      logging.get_logger(__name__)

a_							=      """▁"""

a_							=      {"""vocab_file""": """sentencepiece.bpe.model"""}

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

a_							=      {
    """facebook/nllb-200-distilled-600M""": 1024,
}

# fmt: off
a_							=      ["""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__    (		snake_case					):



  """simple docstring"""






  lowerCAmelCase__		:	List[str]    		= VOCAB_FILES_NAMES
  lowerCAmelCase__		:	Optional[int]    		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowerCAmelCase__		:	int    		= PRETRAINED_VOCAB_FILES_MAP
  lowerCAmelCase__		:	Tuple    		= ['input_ids', 'attention_mask']

  lowerCAmelCase__		:	List[int]    		= []
  lowerCAmelCase__		:	List[int]    		= []






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




    '''simple docstring'''




    __UpperCAmelCase						    =       AddedToken(__lowerCAmelCase				,				lstrip=__lowerCAmelCase				,				rstrip=__lowerCAmelCase   ) if isinstance(__lowerCAmelCase				,				__lowerCAmelCase   ) else mask_token

    __UpperCAmelCase						    =       {} if sp_model_kwargs is None else sp_model_kwargs
    __UpperCAmelCase						    =       legacy_behaviour

    super().__init__(
        bos_token=__lowerCAmelCase				,				eos_token=__lowerCAmelCase				,				unk_token=__lowerCAmelCase				,				sep_token=__lowerCAmelCase				,				cls_token=__lowerCAmelCase				,				pad_token=__lowerCAmelCase				,				mask_token=__lowerCAmelCase				,				tokenizer_file=__lowerCAmelCase				,				src_lang=__lowerCAmelCase				,				tgt_lang=__lowerCAmelCase				,				additional_special_tokens=__lowerCAmelCase				,				sp_model_kwargs=self.sp_model_kwargs				,				legacy_behaviour=__lowerCAmelCase				,				**__lowerCAmelCase				,				)

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

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

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

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






  def __getstate__(				self:			str   ) -> Dict:




    '''simple docstring'''




    __UpperCAmelCase						    =       self.__dict__.copy()
    __UpperCAmelCase						    =       None
    __UpperCAmelCase						    =       self.sp_model.serialized_model_proto()
    return state






  def __setstate__(				self:			Optional[Any]				,				__lowerCAmelCase:			Union[str, Any]   ) -> Any:




    '''simple docstring'''




    __UpperCAmelCase						    =       d

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

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






  @property
  def 	_UpperCAmelCase				(				self:			int   ) -> str:




    '''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 	_UpperCAmelCase				(				self:			Optional[Any]   ) -> str:




    '''simple docstring'''




    return self._src_lang






  @src_lang.setter
  def 	_UpperCAmelCase				(				self:			int				,				__lowerCAmelCase:			str   ) -> None:




    '''simple docstring'''




    __UpperCAmelCase						    =       new_src_lang
    self.set_src_lang_special_tokens(self._src_lang   )






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




    '''simple docstring'''




    if already_has_special_tokens:
      return super().get_special_tokens_mask(
          token_ids_a=__lowerCAmelCase				,				token_ids_a=__lowerCAmelCase				,				already_has_special_tokens=__lowerCAmelCase   )

    __UpperCAmelCase						    =       [1] * len(self.prefix_tokens   )
    __UpperCAmelCase						    =       [1] * len(self.suffix_tokens   )
    if token_ids_a is None:
      return prefix_ones + ([0] * len(__lowerCAmelCase   )) + suffix_ones
    return prefix_ones + ([0] * len(__lowerCAmelCase   )) + ([0] * len(__lowerCAmelCase   )) + suffix_ones






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




    '''simple docstring'''




    __UpperCAmelCase						    =       [self.sep_token_id]
    __UpperCAmelCase						    =       [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:			Tuple				,				__lowerCAmelCase:			Optional[int]				,				__lowerCAmelCase:			str				,				__lowerCAmelCase:			Optional[str]				,				__lowerCAmelCase:			Optional[str]				,				**__lowerCAmelCase:			Union[str, Any]   ) -> Dict:




    '''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"   )
    __UpperCAmelCase						    =       src_lang
    __UpperCAmelCase						    =       self(__lowerCAmelCase				,				add_special_tokens=__lowerCAmelCase				,				return_tensors=__lowerCAmelCase				,				**__lowerCAmelCase   )
    __UpperCAmelCase						    =       self.convert_tokens_to_ids(__lowerCAmelCase   )
    __UpperCAmelCase						    =       tgt_lang_id
    return inputs






  def 	_UpperCAmelCase				(				self:			Tuple   ) -> Tuple:




    '''simple docstring'''




    __UpperCAmelCase						    =       {self.convert_ids_to_tokens(__lowerCAmelCase   ): i for i in range(self.vocab_size   )}
    vocab.update(self.added_tokens_encoder   )
    return vocab






  def 	_UpperCAmelCase				(				self:			Optional[Any]				,				__lowerCAmelCase:			str   ) -> List[str]:




    '''simple docstring'''




    return self.sp_model.encode(__lowerCAmelCase				,				out_type=__lowerCAmelCase   )






  def 	_UpperCAmelCase				(				self:			Optional[int]				,				__lowerCAmelCase:			Tuple   ) -> str:




    '''simple docstring'''




    if token in self.fairseq_tokens_to_ids:
      return self.fairseq_tokens_to_ids[token]
    __UpperCAmelCase						    =       self.sp_model.PieceToId(__lowerCAmelCase   )

    # 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 	_UpperCAmelCase				(				self:			int				,				__lowerCAmelCase:			str   ) -> List[str]:




    '''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 	_UpperCAmelCase				(				self:			Any				,				__lowerCAmelCase:			Tuple   ) -> Optional[Any]:




    '''simple docstring'''




    __UpperCAmelCase						    =       "".join(__lowerCAmelCase   ).replace(__lowerCAmelCase				,				" "   ).strip()
    return out_string






  def 	_UpperCAmelCase				(				self:			Optional[int]				,				__lowerCAmelCase:			str				,				__lowerCAmelCase:			Optional[str] = None   ) -> Tuple[str]:




    '''simple docstring'''




    if not os.path.isdir(__lowerCAmelCase   ):
      logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
      return
    __UpperCAmelCase						    =       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   ) and os.path.isfile(self.vocab_file   ):
      copyfile(self.vocab_file				,				__lowerCAmelCase   )
    elif not os.path.isfile(self.vocab_file   ):
      with open(__lowerCAmelCase				,				"wb"   ) as fi:
        __UpperCAmelCase						    =       self.sp_model.serialized_model_proto()
        fi.write(__lowerCAmelCase   )

    return (out_vocab_file,)






  def 	_UpperCAmelCase				(				self:			Union[str, Any]				,				__lowerCAmelCase:			List[str]				,				__lowerCAmelCase:			str = "eng_Latn"				,				__lowerCAmelCase:			Optional[List[str]] = None				,				__lowerCAmelCase:			str = "fra_Latn"				,				**__lowerCAmelCase:			Tuple				,				) -> BatchEncoding:




    '''simple docstring'''




    __UpperCAmelCase						    =       src_lang
    __UpperCAmelCase						    =       tgt_lang
    return super().prepare_seqaseq_batch(__lowerCAmelCase				,				__lowerCAmelCase				,				**__lowerCAmelCase   )






  def 	_UpperCAmelCase				(				self:			Tuple   ) -> Dict:




    '''simple docstring'''




    return self.set_src_lang_special_tokens(self.src_lang   )






  def 	_UpperCAmelCase				(				self:			Optional[Any]   ) -> Optional[Any]:




    '''simple docstring'''




    return self.set_tgt_lang_special_tokens(self.tgt_lang   )






  def 	_UpperCAmelCase				(				self:			Optional[Any]				,				__lowerCAmelCase:			Any   ) -> None:




    '''simple docstring'''




    __UpperCAmelCase						    =       self.lang_code_to_id[src_lang]
    if self.legacy_behaviour:
      __UpperCAmelCase						    =       []
      __UpperCAmelCase						    =       [self.eos_token_id, self.cur_lang_code]
    else:
      __UpperCAmelCase						    =       [self.cur_lang_code]
      __UpperCAmelCase						    =       [self.eos_token_id]






  def 	_UpperCAmelCase				(				self:			Optional[int]				,				__lowerCAmelCase:			str   ) -> None:




    '''simple docstring'''




    __UpperCAmelCase						    =       self.lang_code_to_id[lang]
    if self.legacy_behaviour:
      __UpperCAmelCase						    =       []
      __UpperCAmelCase						    =       [self.eos_token_id, self.cur_lang_code]
    else:
      __UpperCAmelCase						    =       [self.cur_lang_code]
      __UpperCAmelCase						    =       [self.eos_token_id]






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


a_							=      {"""processing_layoutxlm""": ["""LayoutXLMProcessor"""]}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_							=      ["""LayoutXLMTokenizer"""]

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_							=      ["""LayoutXLMTokenizerFast"""]

if TYPE_CHECKING:
       from .processing_layoutxlm import LayoutXLMProcessor

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_layoutxlm import LayoutXLMTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
       import sys

       a_							=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



