




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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_albert import AlbertTokenizer
else:
       lowerCamelCase       :       str        =    None

lowerCamelCase       :       List[Any]        =    logging.get_logger(__name__)
lowerCamelCase       :       List[str]        =    {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase       :       Optional[int]        =    {
    """vocab_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/spiece.model""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/spiece.model""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/spiece.model""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/spiece.model""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json""",
    },
}

lowerCamelCase       :       Optional[Any]        =    {
    """albert-base-v1""": 5_1_2,
    """albert-large-v1""": 5_1_2,
    """albert-xlarge-v1""": 5_1_2,
    """albert-xxlarge-v1""": 5_1_2,
    """albert-base-v2""": 5_1_2,
    """albert-large-v2""": 5_1_2,
    """albert-xlarge-v2""": 5_1_2,
    """albert-xxlarge-v2""": 5_1_2,
}

lowerCamelCase       :       Optional[int]        =    """▁"""




class 						__lowercase		(__UpperCamelCase							):




      """simple docstring"""





      _snake_case							     =						VOCAB_FILES_NAMES
      _snake_case							     =						PRETRAINED_VOCAB_FILES_MAP
      _snake_case							     =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _snake_case							     =						AlbertTokenizer

      def __init__(      self				,      A=None				,      A=None				,      A=True				,      A=True				,      A=False				,      A="[CLS]"				,      A="[SEP]"				,      A="<unk>"				,      A="[SEP]"				,      A="<pad>"				,      A="[CLS]"				,      A="[MASK]"				,      **A				,      )		->				Dict:
         # Mask token behave like a normal word, i.e. include the space before it and
         # is included in the raw text, there should be a match in a non-normalized sentence.
         snake_case      :				Any				=       (
             AddedToken(A				,      lstrip=A				,      rstrip=A				,      normalized=A	)
             if isinstance(A				,      A	)
             else mask_token
         )

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

         snake_case      :				Union[str, Any]				=       do_lower_case
         snake_case      :				List[Any]				=       remove_space
         snake_case      :				Optional[Any]				=       keep_accents
         snake_case      :				Tuple				=       vocab_file
         snake_case      :				Tuple				=       False if not self.vocab_file else True

      def 	UpperCAmelCase      (      self				,      A				,      A = None	)		->				List[int]:
         snake_case      :				Optional[Any]				=       [self.sep_token_id]
         snake_case      :				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 	UpperCAmelCase      (      self				,      A				,      A = None	)		->				List[int]:
         snake_case      :				List[str]				=       [self.sep_token_id]
         snake_case      :				int				=       [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 	UpperCAmelCase      (      self				,      A				,      A = None	)		->				Tuple[str]:
         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(A	):
            logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
            return
         snake_case      :				List[str]				=       os.path.join(
             A				,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)

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

         return (out_vocab_file,)












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:
    _UpperCAmelCase				:       int	   =				None


_UpperCAmelCase				:       Dict	   =				logging.get_logger(__name__)


_UpperCAmelCase				:       Optional[int]	   =				{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

_UpperCAmelCase				:       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"""
        ),
    },
}

_UpperCAmelCase				:       List[str]	   =				{
    """facebook/nllb-large-en-ro""": 10_24,
    """facebook/nllb-200-distilled-600M""": 10_24,
}

# fmt: off
_UpperCAmelCase				:       Optional[int]	   =				["""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							(					__UpperCamelCase			):
 UpperCAmelCase__													=		VOCAB_FILES_NAMES
 UpperCAmelCase__													=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase__													=		PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase__													=		["""input_ids""", """attention_mask"""]
 UpperCAmelCase__													=		NllbTokenizer

 UpperCAmelCase__													=		[]
 UpperCAmelCase__													=		[]
 def __init__(      self  :      Tuple			,     UpperCAmelCase  :      int=None			,     UpperCAmelCase  :      Any=None			,     UpperCAmelCase  :      str="<s>"			,     UpperCAmelCase  :      Optional[Any]="</s>"			,     UpperCAmelCase  :      str="</s>"			,     UpperCAmelCase  :      Tuple="<s>"			,     UpperCAmelCase  :      Optional[Any]="<unk>"			,     UpperCAmelCase  :      List[str]="<pad>"			,     UpperCAmelCase  :      Union[str, Any]="<mask>"			,     UpperCAmelCase  :      Tuple=None			,     UpperCAmelCase  :      int=None			,     UpperCAmelCase  :      Dict=None			,     UpperCAmelCase  :      Any=False			,     **UpperCAmelCase  :      Optional[int]			,     )			->	Tuple:
     # Mask token behave like a normal word, i.e. include the space before it
     lowerCamelCase__    :      List[Any]					 =		AddedToken(UpperCAmelCase			,     lstrip=UpperCAmelCase			,     rstrip=UpperCAmelCase	) if isinstance(UpperCAmelCase			,     UpperCAmelCase	) else mask_token
     lowerCamelCase__    :      Union[str, Any]					 =		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			,     )

     lowerCamelCase__    :      List[Any]					 =		vocab_file
     lowerCamelCase__    :      Dict					 =		False if not self.vocab_file else True

     lowerCamelCase__    :      Optional[Any]					 =		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}	)
     lowerCamelCase__    :      str					 =		{
         lang_code: self.convert_tokens_to_ids(UpperCAmelCase	) for lang_code in FAIRSEQ_LANGUAGE_CODES
     }

     lowerCamelCase__    :      int					 =		src_lang if src_lang is not None else 'eng_Latn'
     lowerCamelCase__    :      List[Any]					 =		self.convert_tokens_to_ids(self._src_lang	)
     lowerCamelCase__    :      str					 =		tgt_lang
     self.set_src_lang_special_tokens(self._src_lang	)
 @property
 def      A_	(      self  :      int	)			->	str:
     return self._src_lang
 @src_lang.setter
 def      A_	(      self  :      List[Any]			,     UpperCAmelCase  :      str	)			->	None:
     lowerCamelCase__    :      Any					 =		new_src_lang
     self.set_src_lang_special_tokens(self._src_lang	)
 def      A_	(      self  :      Optional[Any]			,     UpperCAmelCase  :      List[int]			,     UpperCAmelCase  :      Optional[List[int]] = None	)			->	List[int]:
     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      A_	(      self  :      Optional[Any]			,     UpperCAmelCase  :      List[int]			,     UpperCAmelCase  :      Optional[List[int]] = None	)			->	List[int]:
     lowerCamelCase__    :      Dict					 =		[self.sep_token_id]
     lowerCamelCase__    :      List[str]					 =		[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      A_	(      self  :      int			,     UpperCAmelCase  :      int			,     UpperCAmelCase  :      str			,     UpperCAmelCase  :      Optional[str]			,     UpperCAmelCase  :      Optional[str]			,     **UpperCAmelCase  :      List[str]	)			->	Dict:
     if src_lang is None or tgt_lang is None:
         raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'	)
     lowerCamelCase__    :      Optional[int]					 =		src_lang
     lowerCamelCase__    :      Optional[int]					 =		self(UpperCAmelCase			,     add_special_tokens=UpperCAmelCase			,     return_tensors=UpperCAmelCase			,     **UpperCAmelCase	)
     lowerCamelCase__    :      Optional[Any]					 =		self.convert_tokens_to_ids(UpperCAmelCase	)
     lowerCamelCase__    :      Union[str, Any]					 =		tgt_lang_id
     return inputs
 def      A_	(      self  :      Dict			,     UpperCAmelCase  :      List[str]			,     UpperCAmelCase  :      str = "eng_Latn"			,     UpperCAmelCase  :      Optional[List[str]] = None			,     UpperCAmelCase  :      str = "fra_Latn"			,     **UpperCAmelCase  :      Dict			,     )			->	BatchEncoding:
     lowerCamelCase__    :      Any					 =		src_lang
     lowerCamelCase__    :      int					 =		tgt_lang
     return super().prepare_seqaseq_batch(UpperCAmelCase			,     UpperCAmelCase			,     **UpperCAmelCase	)
 def      A_	(      self  :      Union[str, Any]	)			->	Optional[int]:
     return self.set_src_lang_special_tokens(self.src_lang	)
 def      A_	(      self  :      Any	)			->	Union[str, Any]:
     return self.set_tgt_lang_special_tokens(self.tgt_lang	)
 def      A_	(      self  :      str			,     UpperCAmelCase  :      Optional[Any]	)			->	None:
     lowerCamelCase__    :      int					 =		self.convert_tokens_to_ids(UpperCAmelCase	)

     if self.legacy_behaviour:
         lowerCamelCase__    :      int					 =		[]
         lowerCamelCase__    :      str					 =		[self.eos_token_id, self.cur_lang_code]
     else:
         lowerCamelCase__    :      int					 =		[self.cur_lang_code]
         lowerCamelCase__    :      Tuple					 =		[self.eos_token_id]

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

     lowerCamelCase__    :      str					 =		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      A_	(      self  :      int			,     UpperCAmelCase  :      str	)			->	None:
     lowerCamelCase__    :      Union[str, Any]					 =		self.convert_tokens_to_ids(UpperCAmelCase	)
     if self.legacy_behaviour:
         lowerCamelCase__    :      Dict					 =		[]
         lowerCamelCase__    :      Union[str, Any]					 =		[self.eos_token_id, self.cur_lang_code]
     else:
         lowerCamelCase__    :      Any					 =		[self.cur_lang_code]
         lowerCamelCase__    :      Optional[Any]					 =		[self.eos_token_id]

     lowerCamelCase__    :      Union[str, Any]					 =		self.convert_ids_to_tokens(self.prefix_tokens	)
     lowerCamelCase__    :      List[Any]					 =		self.convert_ids_to_tokens(self.suffix_tokens	)

     lowerCamelCase__    :      Optional[int]					 =		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      A_	(      self  :      Union[str, Any]			,     UpperCAmelCase  :      str			,     UpperCAmelCase  :      Optional[str] = None	)			->	Tuple[str]:
     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
     lowerCamelCase__    :      int					 =		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,)





