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

lowercase__  :      int        =					"▁"

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

lowercase__  :      List[Any]        =					{
    "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"
        ),
    }
}

lowercase__  :      int        =					{
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
lowercase__  :      int        =					["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 lowerCamelCase							(	_UpperCamelCase					):




  '''simple docstring'''



  lowerCAmelCase__										=	VOCAB_FILES_NAMES
  lowerCAmelCase__										=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowerCAmelCase__										=	PRETRAINED_VOCAB_FILES_MAP
  lowerCAmelCase__										=	['''input_ids''', '''attention_mask''']

  lowerCAmelCase__										=	[]
  lowerCAmelCase__										=	[]






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

        UpperCAmelCase_            =  {} if sp_model_kwargs is None else sp_model_kwargs

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

        UpperCAmelCase_            =  spm.SentencePieceProcessor(**self.sp_model_kwargs  )
        self.sp_model.Load(str(_UpperCAmelCase  )  )
        UpperCAmelCase_            =  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
        UpperCAmelCase_            =  {'''<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_            =  1

        UpperCAmelCase_            =  len(self.sp_model  )
        UpperCAmelCase_            =  {
            code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_UpperCAmelCase  )
        }
        UpperCAmelCase_            =  {v: k for k, v in self.lang_code_to_id.items()}
        UpperCAmelCase_            =  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_            =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
        UpperCAmelCase_            =  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_            =  src_lang if src_lang is not None else '''en_XX'''
        UpperCAmelCase_            =  self.lang_code_to_id[self._src_lang]
        UpperCAmelCase_            =  tgt_lang
        self.set_src_lang_special_tokens(self._src_lang  )






  def __getstate__(      self			:       Union[str, Any]  )				->Optional[int]:
        UpperCAmelCase_            =  self.__dict__.copy()
        UpperCAmelCase_            =  None
        UpperCAmelCase_            =  self.sp_model.serialized_model_proto()
        return state






  def __setstate__(      self			:       List[str]  ,							UpperCAmelCase__			:       Optional[Any]  )				->Optional[int]:
        UpperCAmelCase_            =  d

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

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






  @property
  def  lowerCAmelCase__ (      self			:       List[str]  )				->str:
        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			:       int  )				->Union[str, Any]:
        return self._src_lang






  @src_lang.setter
  def  lowerCAmelCase__ (      self			:       int  ,							UpperCAmelCase__			:       List[str]  )				->Any:
        UpperCAmelCase_            =  new_src_lang
        self.set_src_lang_special_tokens(self._src_lang  )






  def  lowerCAmelCase__ (      self			:       str  ,							UpperCAmelCase__			:       str  ,							UpperCAmelCase__			:       Union[str, Any] = None  ,							UpperCAmelCase__			:       Optional[Any] = False  )				->int:

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

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






  def  lowerCAmelCase__ (      self			:       Union[str, Any]  ,							UpperCAmelCase__			:       Tuple  ,							UpperCAmelCase__			:       Dict = None  )				->Dict:
        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			:       Optional[int]  ,							UpperCAmelCase__			:       int  ,							UpperCAmelCase__			:       Dict = None  )				->Optional[Any]:
        UpperCAmelCase_            =  [self.sep_token_id]
        UpperCAmelCase_            =  [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			:       Any  ,							UpperCAmelCase__			:       int  ,							UpperCAmelCase__			:       Dict  ,							UpperCAmelCase__			:       Dict  ,							UpperCAmelCase__			:       Dict  ,							**UpperCAmelCase__			:       Optional[int]  )				->Tuple:
        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_            =  src_lang
        UpperCAmelCase_            =  self(_UpperCAmelCase  ,							add_special_tokens=_UpperCAmelCase  ,							return_tensors=_UpperCAmelCase  ,							**_UpperCAmelCase  )
        UpperCAmelCase_            =  self.convert_tokens_to_ids(_UpperCAmelCase  )
        UpperCAmelCase_            =  tgt_lang_id
        return inputs






  def  lowerCAmelCase__ (      self			:       List[str]  )				->int:
        UpperCAmelCase_            =  {self.convert_ids_to_tokens(_UpperCAmelCase  ): i for i in range(self.vocab_size  )}
        vocab.update(self.added_tokens_encoder  )
        return vocab






  def  lowerCAmelCase__ (      self			:       Any  ,							UpperCAmelCase__			:       Optional[int]  )				->List[str]:
        return self.sp_model.encode(_UpperCAmelCase  ,							out_type=_UpperCAmelCase  )






  def  lowerCAmelCase__ (      self			:       Tuple  ,							UpperCAmelCase__			:       str  )				->Optional[Any]:
        if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
        UpperCAmelCase_            =  self.sp_model.PieceToId(_UpperCAmelCase  )

        # 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			:       Optional[Any]  ,							UpperCAmelCase__			:       Dict  )				->int:
        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			:       int  ,							UpperCAmelCase__			:       List[str]  )				->Any:
        UpperCAmelCase_            =  ''''''.join(_UpperCAmelCase  ).replace(_UpperCAmelCase  ,							''' '''  ).strip()
        return out_string






  def  lowerCAmelCase__ (      self			:       str  ,							UpperCAmelCase__			:       List[str]  ,							UpperCAmelCase__			:       List[Any] = None  )				->Any:
        if not os.path.isdir(_UpperCAmelCase  ):
              logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
              return
        UpperCAmelCase_            =  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  ) and os.path.isfile(self.vocab_file  ):
              copyfile(self.vocab_file  ,							_UpperCAmelCase  )
        elif not os.path.isfile(self.vocab_file  ):
              with open(_UpperCAmelCase  ,							'''wb'''  ) as fi:
                    UpperCAmelCase_            =  self.sp_model.serialized_model_proto()
                    fi.write(_UpperCAmelCase  )

        return (out_vocab_file,)






  def  lowerCAmelCase__ (      self			:       int  ,							UpperCAmelCase__			:       Optional[Any]  ,							UpperCAmelCase__			:       int = "en_XX"  ,							UpperCAmelCase__			:       Dict = None  ,							UpperCAmelCase__			:       Optional[Any] = "ro_RO"  ,							**UpperCAmelCase__			:       Optional[int]  ,							)				->Any:
        UpperCAmelCase_            =  src_lang
        UpperCAmelCase_            =  tgt_lang
        return super().prepare_seqaseq_batch(_UpperCAmelCase  ,							_UpperCAmelCase  ,							**_UpperCAmelCase  )






  def  lowerCAmelCase__ (      self			:       Optional[int]  )				->Union[str, Any]:
        return self.set_src_lang_special_tokens(self.src_lang  )






  def  lowerCAmelCase__ (      self			:       Optional[Any]  )				->str:
        return self.set_tgt_lang_special_tokens(self.tgt_lang  )






  def  lowerCAmelCase__ (      self			:       List[Any]  ,							UpperCAmelCase__			:       str  )				->Tuple:
        UpperCAmelCase_            =  self.lang_code_to_id[src_lang]
        UpperCAmelCase_            =  []
        UpperCAmelCase_            =  [self.eos_token_id, self.cur_lang_code]






  def  lowerCAmelCase__ (      self			:       Any  ,							UpperCAmelCase__			:       str  )				->Optional[int]:
        UpperCAmelCase_            =  self.lang_code_to_id[lang]
        UpperCAmelCase_            =  []
        UpperCAmelCase_            =  [self.eos_token_id, self.cur_lang_code]






'''simple docstring'''
from __future__ import annotations



def  __lowerCamelCase       (      _UpperCamelCase  :  tuple[int, int]							,    _UpperCamelCase  :  int					):


      '''simple docstring'''


      UpperCAmelCase_      ,		UpperCAmelCase_            =  position
      UpperCAmelCase_            =  [
          (y + 1, x + 2),
          (y - 1, x + 2),
          (y + 1, x - 2),
          (y - 1, x - 2),
          (y + 2, x + 1),
          (y + 2, x - 1),
          (y - 2, x + 1),
          (y - 2, x - 1),
      ]
      UpperCAmelCase_            =  []

      for position in positions:
            UpperCAmelCase_      ,		UpperCAmelCase_            =  position
            if 0 <= y_test < n and 0 <= x_test < n:
                  permissible_positions.append(_UpperCamelCase					)

      return permissible_positions



def  __lowerCamelCase       (      _UpperCamelCase  :  list[list[int]]					):


      '''simple docstring'''


      return not any(elem == 0 for row in board for elem in row					)



def  __lowerCamelCase       (      _UpperCamelCase  :  list[list[int]]							,    _UpperCamelCase  :  tuple[int, int]							,    _UpperCamelCase  :  int					):


      '''simple docstring'''


      if is_complete(_UpperCamelCase					):
            return True

      for position in get_valid_pos(_UpperCamelCase							,    len(_UpperCamelCase					)					):
            UpperCAmelCase_      ,		UpperCAmelCase_            =  position

            if board[y][x] == 0:
                  UpperCAmelCase_            =  curr + 1
                  if open_knight_tour_helper(_UpperCamelCase							,    _UpperCamelCase							,    curr + 1					):
                        return True
                  UpperCAmelCase_            =  0

      return False



def  __lowerCamelCase       (      _UpperCamelCase  :  int					):


      '''simple docstring'''


      UpperCAmelCase_            =  [[0 for i in range(_UpperCamelCase					)] for j in range(_UpperCamelCase					)]

      for i in range(_UpperCamelCase					):
            for j in range(_UpperCamelCase					):
                  UpperCAmelCase_            =  1
                  if open_knight_tour_helper(_UpperCamelCase							,    (i, j)							,    1					):
                        return board
                  UpperCAmelCase_            =  0

      UpperCAmelCase_            =  F"""Open Kight Tour cannot be performed on a board of size {n}"""
      raise ValueError(_UpperCamelCase					)


if __name__ == "__main__":
      import doctest

      doctest.testmod()





