

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_     :    List[Any]     		=   logging.get_logger(__name__)

a_     :    List[str]     		=   "▁"

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

a_     :    int     		=   {
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    }
}

a_     :    str     		=   {
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
a_     :    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"]




class   UpperCamelCase			(  a_ ):
    __UpperCamelCase    =VOCAB_FILES_NAMES
    __UpperCamelCase    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __UpperCamelCase    =PRETRAINED_VOCAB_FILES_MAP
    __UpperCamelCase    =['''input_ids''', '''attention_mask''']

    __UpperCamelCase    =[]
    __UpperCamelCase    =[]

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

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      AddedToken(_SCREAMING_SNAKE_CASE				,     lstrip=_SCREAMING_SNAKE_CASE				,     rstrip=_SCREAMING_SNAKE_CASE     ) if isinstance(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE     ) else mask_token

     SCREAMING_SNAKE_CASE		    =      {} if sp_model_kwargs is None else sp_model_kwargs

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

     SCREAMING_SNAKE_CASE		    =      spm.SentencePieceProcessor(**self.sp_model_kwargs     )
     self.sp_model.Load(str(_SCREAMING_SNAKE_CASE     )     )
     SCREAMING_SNAKE_CASE		    =      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		    =      {'<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		    =      1

     SCREAMING_SNAKE_CASE		    =      len(self.sp_model     )
     SCREAMING_SNAKE_CASE		    =      {
         code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_SCREAMING_SNAKE_CASE     )
     }
     SCREAMING_SNAKE_CASE		    =      {v: k for k, v in self.lang_code_to_id.items()}
     SCREAMING_SNAKE_CASE		    =      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		    =      {v: k for k, v in self.fairseq_tokens_to_ids.items()}
     SCREAMING_SNAKE_CASE		    =      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]     )

     SCREAMING_SNAKE_CASE		    =      src_lang if src_lang is not None else 'en_XX'
     SCREAMING_SNAKE_CASE		    =      self.lang_code_to_id[self._src_lang]
     SCREAMING_SNAKE_CASE		    =      tgt_lang
     self.set_src_lang_special_tokens(self._src_lang     )

    def __getstate__(      self			:   Tuple     ):

     """simple docstring"""






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

    def __setstate__(      self			:   Union[str, Any]				,     snake_case__			:   Optional[Any]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      d

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

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

    @property
    def UpperCamelCase      (      self			:   List[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			:   Tuple     ):

     """simple docstring"""






     return self._src_lang

    @src_lang.setter
    def UpperCamelCase      (      self			:   Tuple				,     snake_case__			:   Tuple     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      new_src_lang
     self.set_src_lang_special_tokens(self._src_lang     )

    def UpperCamelCase      (      self			:   Any				,     snake_case__			:   Optional[Any]				,     snake_case__			:   int = None				,     snake_case__			:   Optional[Any] = False     ):

     """simple docstring"""






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

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

    def UpperCamelCase      (      self			:   List[str]				,     snake_case__			:   Dict				,     snake_case__			:   List[str] = None     ):

     """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			:   List[Any]				,     snake_case__			:   Dict				,     snake_case__			:   Optional[Any] = None     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      [self.sep_token_id]
     SCREAMING_SNAKE_CASE		    =      [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				,     snake_case__			:   Dict				,     snake_case__			:   Optional[int]				,     snake_case__			:   Any				,     snake_case__			:   str				,     **snake_case__			:   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'     )
     SCREAMING_SNAKE_CASE		    =      src_lang
     SCREAMING_SNAKE_CASE		    =      self(_SCREAMING_SNAKE_CASE				,     add_special_tokens=_SCREAMING_SNAKE_CASE				,     return_tensors=_SCREAMING_SNAKE_CASE				,     **_SCREAMING_SNAKE_CASE     )
     SCREAMING_SNAKE_CASE		    =      self.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE     )
     SCREAMING_SNAKE_CASE		    =      tgt_lang_id
     return inputs

    def UpperCamelCase      (      self			:   Optional[int]     ):

     """simple docstring"""






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

    def UpperCamelCase      (      self			:   List[Any]				,     snake_case__			:   List[str]     ):

     """simple docstring"""






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

    def UpperCamelCase      (      self			:   int				,     snake_case__			:   str     ):

     """simple docstring"""






     if token in self.fairseq_tokens_to_ids:
      return self.fairseq_tokens_to_ids[token]
     SCREAMING_SNAKE_CASE		    =      self.sp_model.PieceToId(_SCREAMING_SNAKE_CASE     )

     # 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			:   Optional[int]				,     snake_case__			:   List[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 UpperCamelCase      (      self			:   Optional[Any]				,     snake_case__			:   Any     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      ''.join(_SCREAMING_SNAKE_CASE     ).replace(_SCREAMING_SNAKE_CASE				,     ' '     ).strip()
     return out_string

    def UpperCamelCase      (      self			:   str				,     snake_case__			:   Tuple				,     snake_case__			:   Union[str, Any] = None     ):

     """simple docstring"""






     if not os.path.isdir(_SCREAMING_SNAKE_CASE     ):
      logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""     )
      return
     SCREAMING_SNAKE_CASE		    =      os.path.join(
         _SCREAMING_SNAKE_CASE				,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )

     if os.path.abspath(self.vocab_file     ) != os.path.abspath(_SCREAMING_SNAKE_CASE     ) and os.path.isfile(self.vocab_file     ):
      copyfile(self.vocab_file				,     _SCREAMING_SNAKE_CASE     )
     elif not os.path.isfile(self.vocab_file     ):
      with open(_SCREAMING_SNAKE_CASE				,     'wb'     ) as fi:
       SCREAMING_SNAKE_CASE		    =      self.sp_model.serialized_model_proto()
       fi.write(_SCREAMING_SNAKE_CASE     )

     return (out_vocab_file,)

    def UpperCamelCase      (      self			:   str				,     snake_case__			:   int				,     snake_case__			:   List[Any] = "en_XX"				,     snake_case__			:   str = None				,     snake_case__			:   int = "ro_RO"				,     **snake_case__			:   Optional[Any]				,     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      src_lang
     SCREAMING_SNAKE_CASE		    =      tgt_lang
     return super().prepare_seqaseq_batch(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     **_SCREAMING_SNAKE_CASE     )

    def UpperCamelCase      (      self			:   Union[str, Any]     ):

     """simple docstring"""






     return self.set_src_lang_special_tokens(self.src_lang     )

    def UpperCamelCase      (      self			:   Tuple     ):

     """simple docstring"""






     return self.set_tgt_lang_special_tokens(self.tgt_lang     )

    def UpperCamelCase      (      self			:   Dict				,     snake_case__			:   int     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      self.lang_code_to_id[src_lang]
     SCREAMING_SNAKE_CASE		    =      []
     SCREAMING_SNAKE_CASE		    =      [self.eos_token_id, self.cur_lang_code]




    def UpperCamelCase      (      self			:   int				,     snake_case__			:   List[str]     ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE		    =      self.lang_code_to_id[lang]
     SCREAMING_SNAKE_CASE		    =      []
     SCREAMING_SNAKE_CASE		    =      [self.eos_token_id, self.cur_lang_code]




'''simple docstring'''



def       snake_case   (	snake_case      : list					,		snake_case      : list					,		snake_case      : int					,		snake_case      : int					,		snake_case      : int			) ->  int:


    """simple docstring"""


    if index == number_of_items:
        return 0
    lowerCAmelCase 						=							0
    lowerCAmelCase 						=							0
    lowerCAmelCase 						=							knapsack(snake_case					,		snake_case					,		snake_case					,		snake_case					,		index + 1			)
    if weights[index] <= max_weight:
        lowerCAmelCase 						=							values[index] + knapsack(
            snake_case					,		snake_case					,		snake_case					,		max_weight - weights[index]					,		index + 1			)
    return max(snake_case					,		snake_case			)


if __name__ == "__main__":
     import doctest

     doctest.testmod()





