





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


_UpperCamelCase				=       logging.get_logger(__name__)

_UpperCamelCase				=       '''▁'''

_UpperCamelCase				=       {'''vocab_file''': '''sentencepiece.bpe.model'''}

_UpperCamelCase				=       {
    '''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'''
        ),
    }
}

_UpperCamelCase				=       {
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 1024,
}

# fmt: off
_UpperCamelCase				=       ['''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"""






      UpperCAmelCase_  :					int      			=VOCAB_FILES_NAMES
      UpperCAmelCase_  :					List[str]      			=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCAmelCase_  :					List[str]      			=PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase_  :					Dict      			=["""input_ids""", """attention_mask"""]

      UpperCAmelCase_  :					List[int]      			=[]
      UpperCAmelCase_  :					List[int]      			=[]







      def __init__(       self ,  UpperCAmelCase ,  UpperCAmelCase="<s>" ,  UpperCAmelCase="</s>" ,  UpperCAmelCase="</s>" ,  UpperCAmelCase="<s>" ,  UpperCAmelCase="<unk>" ,  UpperCAmelCase="<pad>" ,  UpperCAmelCase="<mask>" ,  UpperCAmelCase=None ,  UpperCAmelCase=None ,  UpperCAmelCase=None ,  UpperCAmelCase = None ,  UpperCAmelCase=None ,  **UpperCAmelCase ,  )				->      List[Any]:






        '''simple docstring'''






        __snake_case      : Optional[int]						=				AddedToken(__lowercase ,  lstrip=__lowercase ,  rstrip=__lowercase      ) if isinstance(__lowercase ,  __lowercase      ) else mask_token

        __snake_case      : Tuple						=				{} if sp_model_kwargs is None else sp_model_kwargs

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

        __snake_case      : List[Any]						=				spm.SentencePieceProcessor(**self.sp_model_kwargs      )
        self.sp_model.Load(str(__lowercase      )      )
        __snake_case      : Dict						=				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
        __snake_case      : List[Any]						=				{'''<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
        __snake_case      : Tuple						=				1

        __snake_case      : List[Any]						=				len(self.sp_model      )
        __snake_case      : Optional[int]						=				{
            code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(__lowercase      )
        }
        __snake_case      : Union[str, Any]						=				{v: k for k, v in self.lang_code_to_id.items()}
        __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      )
        __snake_case      : Optional[int]						=				{v: k for k, v in self.fairseq_tokens_to_ids.items()}
        __snake_case      : Optional[int]						=				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]      )

        __snake_case      : List[str]						=				src_lang if src_lang is not None else '''en_XX'''
        __snake_case      : Dict						=				self.lang_code_to_id[self._src_lang]
        __snake_case      : List[Any]						=				tgt_lang
        self.set_src_lang_special_tokens(self._src_lang      )







      def __getstate__(       self      )				->      Tuple:






        '''simple docstring'''






        __snake_case      : Dict						=				self.__dict__.copy()
        __snake_case      : Union[str, Any]						=				None
        __snake_case      : Tuple						=				self.sp_model.serialized_model_proto()
        return state







      def __setstate__(       self ,  UpperCAmelCase      )				->      Any:






        '''simple docstring'''






        __snake_case      : Optional[Any]						=				d

        # for backward compatibility
        if not hasattr(self ,  "sp_model_kwargs"      ):
          __snake_case      : str						=				{}

        __snake_case      : Optional[Any]						=				spm.SentencePieceProcessor(**self.sp_model_kwargs      )
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto      )







      @property
      def   UpperCAmelCase						(       self      )				->      Optional[Any]:






        '''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      )				->      str:






        '''simple docstring'''






        return self._src_lang







      @src_lang.setter
      def   UpperCAmelCase						(       self ,  UpperCAmelCase      )				->      None:






        '''simple docstring'''






        __snake_case      : List[str]						=				new_src_lang
        self.set_src_lang_special_tokens(self._src_lang      )







      def   UpperCAmelCase						(       self ,  UpperCAmelCase ,  UpperCAmelCase = None ,  UpperCAmelCase = False      )				->      List[int]:






        '''simple docstring'''






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

        __snake_case      : Optional[int]						=				[1] * len(self.prefix_tokens      )
        __snake_case      : List[Any]						=				[1] * len(self.suffix_tokens      )
        if token_ids_a is None:
          return prefix_ones + ([0] * len(__lowercase      )) + suffix_ones
        return prefix_ones + ([0] * len(__lowercase      )) + ([0] * len(__lowercase      )) + suffix_ones







      def   UpperCAmelCase						(       self ,  UpperCAmelCase ,  UpperCAmelCase = None      )				->      List[int]:






        '''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 ,  UpperCAmelCase ,  UpperCAmelCase = None      )				->      List[int]:






        '''simple docstring'''






        __snake_case      : Dict						=				[self.sep_token_id]
        __snake_case      : Optional[Any]						=				[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 ,  UpperCAmelCase ,  UpperCAmelCase ,  UpperCAmelCase ,  UpperCAmelCase ,  **UpperCAmelCase      )				->      Optional[Any]:






        '''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"      )
        __snake_case      : List[Any]						=				src_lang
        __snake_case      : Dict						=				self(__lowercase ,  add_special_tokens=__lowercase ,  return_tensors=__lowercase ,  **__lowercase      )
        __snake_case      : str						=				self.convert_tokens_to_ids(__lowercase      )
        __snake_case      : List[Any]						=				tgt_lang_id
        return inputs







      def   UpperCAmelCase						(       self      )				->      Tuple:






        '''simple docstring'''






        __snake_case      : Optional[int]						=				{self.convert_ids_to_tokens(__lowercase      ): i for i in range(self.vocab_size      )}
        vocab.update(self.added_tokens_encoder      )
        return vocab







      def   UpperCAmelCase						(       self ,  UpperCAmelCase      )				->      List[str]:






        '''simple docstring'''






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







      def   UpperCAmelCase						(       self ,  UpperCAmelCase      )				->      List[str]:






        '''simple docstring'''






        if token in self.fairseq_tokens_to_ids:
          return self.fairseq_tokens_to_ids[token]
        __snake_case      : Union[str, Any]						=				self.sp_model.PieceToId(__lowercase      )

        # 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 ,  UpperCAmelCase      )				->      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 ,  UpperCAmelCase      )				->      List[str]:






        '''simple docstring'''






        __snake_case      : List[Any]						=				''''''.join(__lowercase      ).replace(__lowercase ,  " "      ).strip()
        return out_string







      def   UpperCAmelCase						(       self ,  UpperCAmelCase ,  UpperCAmelCase = None      )				->      Tuple[str]:






        '''simple docstring'''






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

        if os.path.abspath(self.vocab_file      ) != os.path.abspath(__lowercase      ) and os.path.isfile(self.vocab_file      ):
          copyfile(self.vocab_file ,  __lowercase      )
        elif not os.path.isfile(self.vocab_file      ):
          with open(__lowercase ,  "wb"      ) as fi:
            __snake_case      : List[str]						=				self.sp_model.serialized_model_proto()
            fi.write(__lowercase      )

        return (out_vocab_file,)







      def   UpperCAmelCase						(       self ,  UpperCAmelCase ,  UpperCAmelCase = "en_XX" ,  UpperCAmelCase = None ,  UpperCAmelCase = "ro_RO" ,  **UpperCAmelCase ,  )				->      BatchEncoding:






        '''simple docstring'''






        __snake_case      : Optional[int]						=				src_lang
        __snake_case      : str						=				tgt_lang
        return super().prepare_seqaseq_batch(__lowercase ,  __lowercase ,  **__lowercase      )







      def   UpperCAmelCase						(       self      )				->      List[str]:






        '''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 ,  UpperCAmelCase      )				->      None:






        '''simple docstring'''






        __snake_case      : Optional[Any]						=				self.lang_code_to_id[src_lang]
        __snake_case      : Optional[Any]						=				[]
        __snake_case      : Tuple						=				[self.eos_token_id, self.cur_lang_code]







      def   UpperCAmelCase						(       self ,  UpperCAmelCase      )				->      None:






        '''simple docstring'''






        __snake_case      : str						=				self.lang_code_to_id[lang]
        __snake_case      : Any						=				[]
        __snake_case      : Dict						=				[self.eos_token_id, self.cur_lang_code]


from __future__ import annotations

from PIL import Image

# Define glider example
__lowercase							 =					[
    [0, 1, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0, 0],
    [1, 1, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
]

# Define blinker example
__lowercase							 =					[[0, 1, 0], [0, 1, 0], [0, 1, 0]]



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :int			  =		[]
    for i in range(len(SCREAMING_SNAKE_CASE	)	):
        __UpperCamelCase     :Dict			  =		[]
        for j in range(len(cells[i]	)	):
            # Get the number of live neighbours
            __UpperCamelCase     :List[str]			  =		0
            if i > 0 and j > 0:
                neighbour_count += cells[i - 1][j - 1]
            if i > 0:
                neighbour_count += cells[i - 1][j]
            if i > 0 and j < len(cells[i]	) - 1:
                neighbour_count += cells[i - 1][j + 1]
            if j > 0:
                neighbour_count += cells[i][j - 1]
            if j < len(cells[i]	) - 1:
                neighbour_count += cells[i][j + 1]
            if i < len(SCREAMING_SNAKE_CASE	) - 1 and j > 0:
                neighbour_count += cells[i + 1][j - 1]
            if i < len(SCREAMING_SNAKE_CASE	) - 1:
                neighbour_count += cells[i + 1][j]
            if i < len(SCREAMING_SNAKE_CASE	) - 1 and j < len(cells[i]	) - 1:
                neighbour_count += cells[i + 1][j + 1]

            # Rules of the game of life (excerpt from Wikipedia):
            # 1. Any live cell with two or three live neighbours survives.
            # 2. Any dead cell with three live neighbours becomes a live cell.
            # 3. All other live cells die in the next generation.
            #    Similarly, all other dead cells stay dead.
            __UpperCamelCase     :List[str]			  =		cells[i][j] == 1
            if (
                (alive and 2 <= neighbour_count <= 3)
                or not alive
                and neighbour_count == 3
            ):
                next_generation_row.append(1	)
            else:
                next_generation_row.append(0	)

        next_generation.append(SCREAMING_SNAKE_CASE	)
    return next_generation



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :Optional[Any]			  =		[]
    for _ in range(SCREAMING_SNAKE_CASE	):
        # Create output image
        __UpperCamelCase     :Dict			  =		Image.new('''RGB'''  ,			(len(cells[0]	), len(SCREAMING_SNAKE_CASE	))	)
        __UpperCamelCase     :Any			  =		img.load()

        # Save cells to image
        for x in range(len(SCREAMING_SNAKE_CASE	)	):
            for y in range(len(cells[0]	)	):
                __UpperCamelCase     :Optional[Any]			  =		255 - cells[y][x] * 255
                __UpperCamelCase     :int			  =		(colour, colour, colour)

        # Save image
        images.append(SCREAMING_SNAKE_CASE	)
        __UpperCamelCase     :Optional[int]			  =		new_generation(SCREAMING_SNAKE_CASE	)
    return images


if __name__ == "__main__":
    __lowercase							 =					generate_images(GLIDER, 16)
    images[0].save('''out.gif''', save_all=True, append_images=images[1:])





