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:
      lowercase_     :   Union[str, Any] 				=				None


lowercase_     :   Any 				=				logging.get_logger(__name__)


lowercase_     :   int 				=				{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

lowercase_     :   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'
        ),
    },
}

lowercase_     :   Any 				=				{
    'facebook/nllb-large-en-ro': 1_0_2_4,
    'facebook/nllb-200-distilled-600M': 1_0_2_4,
}

# fmt: off
lowercase_     :   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 		_lowerCamelCase		(   __a    ):
    __a  =      VOCAB_FILES_NAMES
    __a  =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __a  =      PRETRAINED_VOCAB_FILES_MAP
    __a  =      ["input_ids", "attention_mask"]
    __a  =      NllbTokenizer

    __a  =      []
    __a  =      []
    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 , )       ->					List[Any]:
     # Mask token behave like a normal word, i.e. include the space before it
     SCREAMING_SNAKE_CASE__:   Any=      AddedToken(A__ , lstrip=A__ , rstrip=A__   ) if isinstance(A__ , A__   ) else mask_token
     SCREAMING_SNAKE_CASE__:   str=      legacy_behaviour
     super().__init__(
         vocab_file=A__ , tokenizer_file=A__ , bos_token=A__ , eos_token=A__ , sep_token=A__ , cls_token=A__ , unk_token=A__ , pad_token=A__ , mask_token=A__ , src_lang=A__ , tgt_lang=A__ , additional_special_tokens=A__ , legacy_behaviour=A__ , **A__ , )

     SCREAMING_SNAKE_CASE__:   Optional[Any]=      vocab_file
     SCREAMING_SNAKE_CASE__:   List[str]=      False if not self.vocab_file else True

     SCREAMING_SNAKE_CASE__:   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}   )
     SCREAMING_SNAKE_CASE__:   List[Any]=      {
         lang_code: self.convert_tokens_to_ids(A__   ) for lang_code in FAIRSEQ_LANGUAGE_CODES
     }

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

     if self.legacy_behaviour:
      SCREAMING_SNAKE_CASE__:   Optional[int]=      []
      SCREAMING_SNAKE_CASE__:   Any=      [self.eos_token_id, self.cur_lang_code]
     else:
      SCREAMING_SNAKE_CASE__:   Optional[Any]=      [self.cur_lang_code]
      SCREAMING_SNAKE_CASE__:   int=      [self.eos_token_id]

     SCREAMING_SNAKE_CASE__:   int=      self.convert_ids_to_tokens(self.prefix_tokens   )
     SCREAMING_SNAKE_CASE__:   List[str]=      self.convert_ids_to_tokens(self.suffix_tokens   )

     SCREAMING_SNAKE_CASE__:   List[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   )       ->					None:
     SCREAMING_SNAKE_CASE__:   Any=      self.convert_tokens_to_ids(A__   )
     if self.legacy_behaviour:
      SCREAMING_SNAKE_CASE__:   str=      []
      SCREAMING_SNAKE_CASE__:   List[Any]=      [self.eos_token_id, self.cur_lang_code]
     else:
      SCREAMING_SNAKE_CASE__:   str=      [self.cur_lang_code]
      SCREAMING_SNAKE_CASE__:   List[str]=      [self.eos_token_id]

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

     SCREAMING_SNAKE_CASE__:   Dict=      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   )       ->					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
     SCREAMING_SNAKE_CASE__:   int=      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,)


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_     :   Dict 				=				{
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_     :   str 				=				[
          'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
          'AutoformerForPrediction',
          'AutoformerModel',
          'AutoformerPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_autoformer import (
          AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          AutoformerConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_autoformer import (
                AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                AutoformerForPrediction,
                AutoformerModel,
                AutoformerPreTrainedModel,
            )

else:
      import sys

      lowercase_     :   Tuple 				=				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

