'''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


lowercase_     :   Optional[Any] 				=				logging.get_logger(__name__)

lowercase_     :   Tuple 				=				'▁'

lowercase_     :   Optional[Any] 				=				{'vocab_file': 'sentencepiece.bpe.model'}

lowercase_     :   str 				=				{
    'vocab_file': {
        'facebook/mbart-large-50-one-to-many-mmt': (
            'https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

lowercase_     :   List[str] 				=				{
    'facebook/mbart-large-50-one-to-many-mmt': 1_0_2_4,
}

# fmt: off
lowercase_     :   Union[str, Any] 				=				['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN', 'af_ZA', 'az_AZ', 'bn_IN', 'fa_IR', 'he_IL', 'hr_HR', 'id_ID', 'ka_GE', 'km_KH', 'mk_MK', 'ml_IN', 'mn_MN', 'mr_IN', 'pl_PL', 'ps_AF', 'pt_XX', 'sv_SE', 'sw_KE', 'ta_IN', 'te_IN', 'th_TH', 'tl_XX', 'uk_UA', 'ur_PK', 'xh_ZA', 'gl_ES', 'sl_SI']






class 		_lowerCamelCase		(   UpperCamelCase_    ):
    __a  =      VOCAB_FILES_NAMES
    __a  =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __a  =      PRETRAINED_VOCAB_FILES_MAP
    __a  =      ["input_ids", "attention_mask"]

    __a  =      []
    __a  =      []
    def __init__(  self , lowerCAmelCase , lowerCAmelCase=None , lowerCAmelCase=None , lowerCAmelCase="</s>" , lowerCAmelCase="</s>" , lowerCAmelCase="<s>" , lowerCAmelCase="<unk>" , lowerCAmelCase="<pad>" , lowerCAmelCase="<mask>" , lowerCAmelCase = None , **lowerCAmelCase , )       ->					None:
     # Mask token behave like a normal word, i.e. include the space before it
     SCREAMING_SNAKE_CASE__:   Dict=      AddedToken(lowerCAmelCase , lstrip=lowerCAmelCase , rstrip=lowerCAmelCase   ) if isinstance(lowerCAmelCase , lowerCAmelCase   ) else mask_token

     SCREAMING_SNAKE_CASE__:   Dict=      {} if sp_model_kwargs is None else sp_model_kwargs

     SCREAMING_SNAKE_CASE__:   Dict=      kwargs.get('''additional_special_tokens''' , []   )
     kwargs["additional_special_tokens"] += [
         code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
     ]

     super().__init__(
         src_lang=lowerCAmelCase , tgt_lang=lowerCAmelCase , eos_token=lowerCAmelCase , unk_token=lowerCAmelCase , sep_token=lowerCAmelCase , cls_token=lowerCAmelCase , pad_token=lowerCAmelCase , mask_token=lowerCAmelCase , sp_model_kwargs=self.sp_model_kwargs , **lowerCAmelCase , )

     SCREAMING_SNAKE_CASE__:   Optional[int]=      spm.SentencePieceProcessor(**self.sp_model_kwargs   )
     self.sp_model.Load(str(lowerCAmelCase   )   )
     SCREAMING_SNAKE_CASE__:   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>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
     # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

     # Mimic fairseq token-to-id alignment for the first 4 token
     SCREAMING_SNAKE_CASE__:   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
     SCREAMING_SNAKE_CASE__:   int=      1

     SCREAMING_SNAKE_CASE__:   Dict=      len(self.sp_model   )
     SCREAMING_SNAKE_CASE__:   int=      {
         code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowerCAmelCase   )
     }
     SCREAMING_SNAKE_CASE__:   int=      {v: k for k, v in self.lang_code_to_id.items()}
     SCREAMING_SNAKE_CASE__:   int=      len(self.sp_model   ) + len(self.lang_code_to_id   ) + self.fairseq_offset

     self.fairseq_tokens_to_ids.update(self.lang_code_to_id   )
     SCREAMING_SNAKE_CASE__:   List[Any]=      {v: k for k, v in self.fairseq_tokens_to_ids.items()}

     SCREAMING_SNAKE_CASE__:   Optional[Any]=      src_lang if src_lang is not None else '''en_XX'''
     SCREAMING_SNAKE_CASE__:   Tuple=      self.lang_code_to_id[self._src_lang]
     SCREAMING_SNAKE_CASE__:   List[str]=      tgt_lang
     self.set_src_lang_special_tokens(self._src_lang   )
    @property
    def 						UpperCamelCase_				(  self   )       ->					int:
     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   )       ->					str:
     return self._src_lang
    @src_lang.setter
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					None:
     SCREAMING_SNAKE_CASE__:   Tuple=      new_src_lang
     self.set_src_lang_special_tokens(self._src_lang   )
    def __getstate__(  self   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   Tuple=      self.__dict__.copy()
     SCREAMING_SNAKE_CASE__:   Dict=      None
     return state
    def __setstate__(  self , lowerCAmelCase   )       ->					None:
     SCREAMING_SNAKE_CASE__:   Dict=      d

     # for backward compatibility
     if not hasattr(self , '''sp_model_kwargs'''   ):
      SCREAMING_SNAKE_CASE__:   List[str]=      {}

     SCREAMING_SNAKE_CASE__:   Tuple=      spm.SentencePieceProcessor(**self.sp_model_kwargs   )
     self.sp_model.Load(self.vocab_file   )
    def 						UpperCamelCase_				(  self   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      {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 , lowerCAmelCase   )       ->					List[str]:
     return self.sp_model.encode(lowerCAmelCase , out_type=lowerCAmelCase   )
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					int:
     if token in self.fairseq_tokens_to_ids:
      return self.fairseq_tokens_to_ids[token]
     SCREAMING_SNAKE_CASE__:   int=      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 , lowerCAmelCase   )       ->					str:
     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 , lowerCAmelCase   )       ->					List[Any]:
     SCREAMING_SNAKE_CASE__:   Any=      []
     SCREAMING_SNAKE_CASE__:   Any=      ''''''
     SCREAMING_SNAKE_CASE__:   Dict=      False
     for token in tokens:
      # make sure that special tokens are not decoded using sentencepiece model
      if token in self.all_special_tokens:
       if not prev_is_special:
        out_string += " "
       out_string += self.sp_model.decode(lowerCAmelCase   ) + token
       SCREAMING_SNAKE_CASE__:   Tuple=      True
       SCREAMING_SNAKE_CASE__:   Optional[int]=      []
      else:
       current_sub_tokens.append(lowerCAmelCase   )
       SCREAMING_SNAKE_CASE__:   Tuple=      False
     out_string += self.sp_model.decode(lowerCAmelCase   )
     return out_string.strip()
    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase = None   )       ->					Tuple[str]:
     if not os.path.isdir(lowerCAmelCase   ):
      logger.error(f'Vocabulary path ({save_directory}) should be a directory'   )
      return
     SCREAMING_SNAKE_CASE__:   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:
       SCREAMING_SNAKE_CASE__:   Tuple=      self.sp_model.serialized_model_proto()
       fi.write(lowerCAmelCase   )

     return (out_vocab_file,)
    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase = None , lowerCAmelCase = False   )       ->					List[int]:

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

     SCREAMING_SNAKE_CASE__:   Optional[Any]=      [1] * len(self.prefix_tokens   )
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      [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 , 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 , lowerCAmelCase , lowerCAmelCase , **lowerCAmelCase   )       ->					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'''   )
     SCREAMING_SNAKE_CASE__:   Dict=      src_lang
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      self(lowerCAmelCase , add_special_tokens=lowerCAmelCase , return_tensors=lowerCAmelCase , **lowerCAmelCase   )
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self.convert_tokens_to_ids(lowerCAmelCase   )
     SCREAMING_SNAKE_CASE__:   Optional[int]=      tgt_lang_id
     return inputs
    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase = "en_XX" , lowerCAmelCase = None , lowerCAmelCase = "ro_RO" , **lowerCAmelCase , )       ->					BatchEncoding:
     SCREAMING_SNAKE_CASE__:   str=      src_lang
     SCREAMING_SNAKE_CASE__:   int=      tgt_lang
     return super().prepare_seqaseq_batch(lowerCAmelCase , lowerCAmelCase , **lowerCAmelCase   )
    def 						UpperCamelCase_				(  self   )       ->					Dict:
     return self.set_src_lang_special_tokens(self.src_lang   )
    def 						UpperCamelCase_				(  self   )       ->					Tuple:
     return self.set_tgt_lang_special_tokens(self.tgt_lang   )
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					None:
     SCREAMING_SNAKE_CASE__:   List[str]=      self.lang_code_to_id[src_lang]
     SCREAMING_SNAKE_CASE__:   Dict=      [self.cur_lang_code_id]
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      [self.eos_token_id]



    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					None:
     SCREAMING_SNAKE_CASE__:   Any=      self.lang_code_to_id[tgt_lang]
     SCREAMING_SNAKE_CASE__:   Tuple=      [self.cur_lang_code_id]
     SCREAMING_SNAKE_CASE__:   List[Any]=      [self.eos_token_id]


from ..utils import DummyObject, requires_backends






class 		_lowerCamelCase		(   metaclass=UpperCamelCase_    ):
    __a  =      ["torch", "scipy"]
    def __init__(  self , *lowerCAmelCase , **lowerCAmelCase   )       ->					Any:
     requires_backends(self , ['''torch''', '''scipy''']   )
    @classmethod
    def 						UpperCamelCase_				(  cls , *lowerCAmelCase , **lowerCAmelCase   )       ->					List[str]:
     requires_backends(cls , ['''torch''', '''scipy''']   )



    @classmethod
    def 						UpperCamelCase_				(  cls , *lowerCAmelCase , **lowerCAmelCase   )       ->					Tuple:
     requires_backends(cls , ['''torch''', '''scipy''']   )

