'''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__     :	Tuple				=			logging.get_logger(__name__)

UpperCamelCase__     :	Optional[Any]				=			'▁'

UpperCamelCase__     :	List[Any]				=			{'vocab_file': 'sentencepiece.bpe.model'}

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

UpperCamelCase__     :	Tuple				=			{
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
UpperCamelCase__     :	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 				_lowercase	(      lowerCAmelCase   ):
						'''simple docstring'''


						UpperCAmelCase_      :      int      							=   VOCAB_FILES_NAMES
						UpperCAmelCase_      :      Dict      							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase_      :      Any      							=   PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase_      :      Union[str, Any]      							=   ['''input_ids''', '''attention_mask''']

						UpperCAmelCase_      :      List[int]      							=   []
						UpperCAmelCase_      :      List[int]      							=   []




						def __init__(				self					,lowerCamelCase_					,lowerCamelCase_="<s>"					,lowerCamelCase_="</s>"					,lowerCamelCase_="</s>"					,lowerCamelCase_="<s>"					,lowerCamelCase_="<unk>"					,lowerCamelCase_="<pad>"					,lowerCamelCase_="<mask>"					,lowerCamelCase_=None					,lowerCamelCase_=None					,lowerCamelCase_=None					,lowerCamelCase_ = None					,lowerCamelCase_=None					,lowerCamelCase_=False					,**lowerCamelCase_					,)			->			str:



									'''simple docstring'''



									UpperCAmelCase__							:				str   				=  AddedToken(lowerCamelCase_					,lstrip=lowerCamelCase_					,rstrip=lowerCamelCase_							) if isinstance(lowerCamelCase_					,lowerCamelCase_							) else mask_token

									UpperCAmelCase__							:				List[Any]   				=  {} if sp_model_kwargs is None else sp_model_kwargs
									UpperCAmelCase__							:				Dict   				=  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__							:				List[Any]   				=  spm.SentencePieceProcessor(**self.sp_model_kwargs							)
									self.sp_model.Load(str(lowerCamelCase_							)							)
									UpperCAmelCase__							:				Optional[int]   				=  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__							:				List[str]   				=  {'''<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__							:				List[str]   				=  1

									UpperCAmelCase__							:				List[str]   				=  len(self.sp_model							)
									UpperCAmelCase__							:				str   				=  {
									    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowerCamelCase_							)
									}
									UpperCAmelCase__							:				Any   				=  {v: k for k, v in self.lang_code_to_id.items()}
									UpperCAmelCase__							:				Dict   				=  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__							:				Optional[Any]   				=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
									UpperCAmelCase__							:				Union[str, Any]   				=  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__							:				Tuple   				=  src_lang if src_lang is not None else '''eng_Latn'''
									UpperCAmelCase__							:				Optional[Any]   				=  self.lang_code_to_id[self._src_lang]
									UpperCAmelCase__							:				str   				=  tgt_lang
									self.set_src_lang_special_tokens(self._src_lang							)




						def __getstate__(				self							)			->			Dict:



									'''simple docstring'''



									UpperCAmelCase__							:				List[Any]   				=  self.__dict__.copy()
									UpperCAmelCase__							:				Union[str, Any]   				=  None
									UpperCAmelCase__							:				str   				=  self.sp_model.serialized_model_proto()
									return state




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



									'''simple docstring'''



									UpperCAmelCase__							:				str   				=  d

									# for backward compatibility
									if not hasattr(self					,'''sp_model_kwargs'''							):
												UpperCAmelCase__							:				Any   				=  {}

									UpperCAmelCase__							:				Optional[Any]   				=  spm.SentencePieceProcessor(**self.sp_model_kwargs							)
									self.sp_model.LoadFromSerializedProto(self.sp_model_proto							)




						@property
						def 		lowerCAmelCase__					(				self							)			->			int:



									'''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							)			->			str:



									'''simple docstring'''



									return self._src_lang




						@src_lang.setter
						def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			None:



									'''simple docstring'''



									UpperCAmelCase__							:				Dict   				=  new_src_lang
									self.set_src_lang_special_tokens(self._src_lang							)




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None					,lowerCamelCase_ = 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__							:				Tuple   				=  [1] * len(self.prefix_tokens							)
									UpperCAmelCase__							:				List[str]   				=  [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 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = 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					,lowerCamelCase_					,lowerCamelCase_ = None							)			->			List[int]:



									'''simple docstring'''



									UpperCAmelCase__							:				Optional[Any]   				=  [self.sep_token_id]
									UpperCAmelCase__							:				List[Any]   				=  [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					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_					,**lowerCamelCase_							)			->			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__							:				int   				=  src_lang
									UpperCAmelCase__							:				Any   				=  self(lowerCamelCase_					,add_special_tokens=lowerCamelCase_					,return_tensors=lowerCamelCase_					,**lowerCamelCase_							)
									UpperCAmelCase__							:				Any   				=  self.convert_tokens_to_ids(lowerCamelCase_							)
									UpperCAmelCase__							:				List[Any]   				=  tgt_lang_id
									return inputs




						def 		lowerCAmelCase__					(				self							)			->			Any:



									'''simple docstring'''



									UpperCAmelCase__							:				str   				=  {self.convert_ids_to_tokens(lowerCamelCase_							): i for i in range(self.vocab_size							)}
									vocab.update(self.added_tokens_encoder							)
									return vocab




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			List[str]:



									'''simple docstring'''



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




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Optional[Any]:



									'''simple docstring'''



									if token in self.fairseq_tokens_to_ids:
												return self.fairseq_tokens_to_ids[token]
									UpperCAmelCase__							:				List[Any]   				=  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 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Union[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					,lowerCamelCase_							)			->			Union[str, Any]:



									'''simple docstring'''



									UpperCAmelCase__							:				Any   				=  ''''''.join(lowerCamelCase_							).replace(lowerCamelCase_					,''' '''							).strip()
									return out_string




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None							)			->			Tuple[str]:



									'''simple docstring'''



									if not os.path.isdir(lowerCamelCase_							):
												logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''							)
												return
									UpperCAmelCase__							:				Dict   				=  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__							:				Optional[Any]   				=  self.sp_model.serialized_model_proto()
															fi.write(lowerCamelCase_							)

									return (out_vocab_file,)




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = "eng_Latn"					,lowerCamelCase_ = None					,lowerCamelCase_ = "fra_Latn"					,**lowerCamelCase_					,)			->			BatchEncoding:



									'''simple docstring'''



									UpperCAmelCase__							:				Any   				=  src_lang
									UpperCAmelCase__							:				Any   				=  tgt_lang
									return super().prepare_seqaseq_batch(lowerCamelCase_					,lowerCamelCase_					,**lowerCamelCase_							)




						def 		lowerCAmelCase__					(				self							)			->			List[Any]:



									'''simple docstring'''



									return self.set_src_lang_special_tokens(self.src_lang							)




						def 		lowerCAmelCase__					(				self							)			->			int:



									'''simple docstring'''



									return self.set_tgt_lang_special_tokens(self.tgt_lang							)




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			None:



									'''simple docstring'''



									UpperCAmelCase__							:				Union[str, Any]   				=  self.lang_code_to_id[src_lang]
									if self.legacy_behaviour:
												UpperCAmelCase__							:				int   				=  []
												UpperCAmelCase__							:				List[Any]   				=  [self.eos_token_id, self.cur_lang_code]
									else:
												UpperCAmelCase__							:				int   				=  [self.cur_lang_code]
												UpperCAmelCase__							:				Tuple   				=  [self.eos_token_id]




						def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			None:



									'''simple docstring'''



									UpperCAmelCase__							:				str   				=  self.lang_code_to_id[lang]
									if self.legacy_behaviour:
												UpperCAmelCase__							:				Any   				=  []
												UpperCAmelCase__							:				str   				=  [self.eos_token_id, self.cur_lang_code]
									else:
												UpperCAmelCase__							:				Union[str, Any]   				=  [self.cur_lang_code]
												UpperCAmelCase__							:				Optional[int]   				=  [self.eos_token_id]





'''simple docstring'''

import os
from shutil import copyfile
from typing import List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


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

UpperCamelCase__     :	str				=			{'vocab_file': 'sentencepiece.model'}

UpperCamelCase__     :	int				=			{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

UpperCamelCase__     :	Any				=			{
    'google/rembert': 256,
}


class 				_lowercase	(      lowerCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      List[Any]      							=   VOCAB_FILES_NAMES
      UpperCAmelCase_      :      List[Any]      							=   PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase_      :      Tuple      							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




      def __init__(				self					,lowerCamelCase_					,lowerCamelCase_=False					,lowerCamelCase_=True					,lowerCamelCase_=True					,lowerCamelCase_="[CLS]"					,lowerCamelCase_="[SEP]"					,lowerCamelCase_="[UNK]"					,lowerCamelCase_="[SEP]"					,lowerCamelCase_="[PAD]"					,lowerCamelCase_="[CLS]"					,lowerCamelCase_="[MASK]"					,**lowerCamelCase_					,)			->			Tuple:



         '''simple docstring'''



         super().__init__(
             do_lower_case=lowerCamelCase_					,remove_space=lowerCamelCase_					,keep_accents=lowerCamelCase_					,bos_token=lowerCamelCase_					,eos_token=lowerCamelCase_					,unk_token=lowerCamelCase_					,sep_token=lowerCamelCase_					,pad_token=lowerCamelCase_					,cls_token=lowerCamelCase_					,mask_token=lowerCamelCase_					,**lowerCamelCase_					,)

         UpperCAmelCase__							:				Union[str, Any]   				=  do_lower_case
         UpperCAmelCase__							:				str   				=  remove_space
         UpperCAmelCase__							:				Optional[Any]   				=  keep_accents
         UpperCAmelCase__							:				List[Any]   				=  vocab_file

         UpperCAmelCase__							:				Dict   				=  spm.SentencePieceProcessor()
         self.sp_model.Load(lowerCamelCase_							)




      @property
      def 		lowerCAmelCase__					(				self							)			->			Optional[Any]:



         '''simple docstring'''



         return len(self.sp_model							)




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[int]   				=  {self.convert_ids_to_tokens(lowerCamelCase_							): i for i in range(self.vocab_size							)}
         vocab.update(self.added_tokens_encoder							)
         return vocab




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



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[int]   				=  self.__dict__.copy()
         UpperCAmelCase__							:				Any   				=  None
         return state




      def __setstate__(				self					,lowerCamelCase_							)			->			Optional[Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				List[str]   				=  d
         UpperCAmelCase__							:				Any   				=  spm.SentencePieceProcessor()
         self.sp_model.Load(self.vocab_file							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_=False							)			->			Tuple:



         '''simple docstring'''



         UpperCAmelCase__							:				str   				=  self.sp_model.EncodeAsPieces(lowerCamelCase_							)
         return pieces




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			str:



         '''simple docstring'''



         return self.sp_model.PieceToId(lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Optional[int]:



         '''simple docstring'''



         return self.sp_model.IdToPiece(lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			List[Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				List[Any]   				=  self.sp_model.decode_pieces(lowerCamelCase_							)
         return out_string




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None							)			->			List[int]:



         '''simple docstring'''



         UpperCAmelCase__							:				Union[str, Any]   				=  [self.sep_token_id]
         UpperCAmelCase__							:				List[Any]   				=  [self.cls_token_id]
         if token_ids_a is None:
            return cls + token_ids_a + sep
         return cls + token_ids_a + sep + token_ids_a + sep




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None					,lowerCamelCase_ = False							)			->			List[int]:



         '''simple docstring'''



         if already_has_special_tokens:
            if token_ids_a is not None:
               raise ValueError(
                   '''You should not supply a second sequence if the provided sequence of '''
                   '''ids is already formatted with special tokens for the model.'''							)
            return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

         if token_ids_a is not None:
            return [1] + ([0] * len(lowerCamelCase_							)) + [1] + ([0] * len(lowerCamelCase_							)) + [1]
         return [1] + ([0] * len(lowerCamelCase_							)) + [1]




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None							)			->			List[int]:



         '''simple docstring'''



         UpperCAmelCase__							:				Tuple   				=  [self.sep_token_id]
         UpperCAmelCase__							:				List[Any]   				=  [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							) * [0] + len(token_ids_a + sep							) * [1]




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_ = None							)			->			Tuple[str]:



         '''simple docstring'''



         if not os.path.isdir(lowerCamelCase_							):
            logger.error('''Vocabulary path ({}) should be a directory'''.format(lowerCamelCase_							)							)
            return
         UpperCAmelCase__							:				Union[str, Any]   				=  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,)




