


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCamelCase											=       logging.get_logger(__name__)

lowerCamelCase											=       '▁'

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

lowerCamelCase											=       {
    'vocab_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

lowerCamelCase											=       {
    'xlm-roberta-base': 5_12,
    'xlm-roberta-large': 5_12,
    'xlm-roberta-large-finetuned-conll02-dutch': 5_12,
    'xlm-roberta-large-finetuned-conll02-spanish': 5_12,
    'xlm-roberta-large-finetuned-conll03-english': 5_12,
    'xlm-roberta-large-finetuned-conll03-german': 5_12,
}




class A  (   UpperCamelCase_     ):
      UpperCamelCase__							:  List[Any]      =VOCAB_FILES_NAMES
      UpperCamelCase__							:  str      =PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase__							:  List[str]      =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase__							:  Any      =['input_ids', 'attention_mask']






      def __init__(					self						:     Optional[int]			,   lowercase_						:     str			,   lowercase_						:     str="<s>"			,   lowercase_						:     Optional[int]="</s>"			,   lowercase_						:     List[str]="</s>"			,   lowercase_						:     Tuple="<s>"			,   lowercase_						:     List[str]="<unk>"			,   lowercase_						:     Optional[Any]="<pad>"			,   lowercase_						:     Dict="<mask>"			,   lowercase_						:     Optional[Dict[str, Any]] = None			,   **lowercase_						:     Tuple			,   )					->						None:
             """simple docstring"""




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

             _lowerCamelCase       :		Any		={} 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_			,   sp_model_kwargs=self.sp_model_kwargs			,   **lowercase_			,   )

             _lowerCamelCase       :		Dict		=spm.SentencePieceProcessor(**self.sp_model_kwargs )
             self.sp_model.Load(str(lowercase_ ) )
             _lowerCamelCase       :		List[str]		=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
             _lowerCamelCase       :		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
             _lowerCamelCase       :		int		=1

             _lowerCamelCase       :		int		=len(self.sp_model ) + self.fairseq_offset
             _lowerCamelCase       :		List[Any]		={v: k for k, v in self.fairseq_tokens_to_ids.items()}






      def __getstate__(					self						:     Dict )					->						int:
             """simple docstring"""




             _lowerCamelCase       :		Any		=self.__dict__.copy()
             _lowerCamelCase       :		Optional[int]		=None
             _lowerCamelCase       :		Dict		=self.sp_model.serialized_model_proto()
             return state






      def __setstate__(					self						:     Optional[Any]			,   lowercase_						:     Dict )					->						Tuple:
             """simple docstring"""




             _lowerCamelCase       :		List[str]		=d

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

             _lowerCamelCase       :		int		=spm.SentencePieceProcessor(**self.sp_model_kwargs )
             self.sp_model.LoadFromSerializedProto(self.sp_model_proto )






      def        lowerCamelCase       (					self						:     Optional[int]			,   lowercase_						:     List[int]			,   lowercase_						:     Optional[List[int]] = None )					->						List[int]:
             """simple docstring"""




             if token_ids_a is None:
                    return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
             _lowerCamelCase       :		Any		=[self.cls_token_id]
             _lowerCamelCase       :		List[Any]		=[self.sep_token_id]
             return cls + token_ids_a + sep + sep + token_ids_a + sep






      def        lowerCamelCase       (					self						:     Any			,   lowercase_						:     List[int]			,   lowercase_						:     Optional[List[int]] = None			,   lowercase_						:     bool = 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_ )

             if token_ids_a is None:
                    return [1] + ([0] * len(lowercase_ )) + [1]
             return [1] + ([0] * len(lowercase_ )) + [1, 1] + ([0] * len(lowercase_ )) + [1]






      def        lowerCamelCase       (					self						:     Any			,   lowercase_						:     List[int]			,   lowercase_						:     Optional[List[int]] = None )					->						List[int]:
             """simple docstring"""




             _lowerCamelCase       :		Any		=[self.sep_token_id]
             _lowerCamelCase       :		Tuple		=[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]






      @property
      def        lowerCamelCase       (					self						:     Optional[Any] )					->						Optional[Any]:
             """simple docstring"""




             return len(self.sp_model ) + self.fairseq_offset + 1  # Add the <mask> token






      def        lowerCamelCase       (					self						:     Dict )					->						Tuple:
             """simple docstring"""




             _lowerCamelCase       :		str		={self.convert_ids_to_tokens(lowercase_ ): i for i in range(self.vocab_size )}
             vocab.update(self.added_tokens_encoder )
             return vocab






      def        lowerCamelCase       (					self						:     List[str]			,   lowercase_						:     str )					->						List[str]:
             """simple docstring"""




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






      def        lowerCamelCase       (					self						:     Dict			,   lowercase_						:     Any )					->						Tuple:
             """simple docstring"""




             if token in self.fairseq_tokens_to_ids:
                    return self.fairseq_tokens_to_ids[token]
             _lowerCamelCase       :		List[str]		=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        lowerCamelCase       (					self						:     str			,   lowercase_						:     Optional[Any] )					->						List[str]:
             """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        lowerCamelCase       (					self						:     Any			,   lowercase_						:     str )					->						Optional[Any]:
             """simple docstring"""




             _lowerCamelCase       :		Optional[int]		=''.join(lowercase_ ).replace(lowercase_			,   ' ' ).strip()
             return out_string






      def        lowerCamelCase       (					self						:     int			,   lowercase_						:     str			,   lowercase_						:     Optional[str] = None )					->						Tuple[str]:
             """simple docstring"""




             if not os.path.isdir(lowercase_ ):
                    logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
                    return
             _lowerCamelCase       :		Dict		=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:
                           _lowerCamelCase       :		str		=self.sp_model.serialized_model_proto()
                           fi.write(lowercase_ )

             return (out_vocab_file,)






def 	a_      (    SCREAMING_SNAKE_CASE__					:      str		,			SCREAMING_SNAKE_CASE__					:      str     ):
       '''simple docstring'''





       assert x is not None
       assert y is not None

       _lowerCamelCase       :		Dict		=len(SCREAMING_SNAKE_CASE__     )
       _lowerCamelCase       :		Optional[Any]		=len(SCREAMING_SNAKE_CASE__     )

       # declaring the array for storing the dp values
       _lowerCamelCase       :		Optional[int]		=[[0] * (n + 1) for _ in range(m + 1     )]  # noqa: E741

       for i in range(1		,			m + 1     ):
              for j in range(1		,			n + 1     ):
                     _lowerCamelCase       :		int		=1 if x[i - 1] == y[j - 1] else 0

                     _lowerCamelCase       :		Union[str, Any]		=max(l[i - 1][j]		,			l[i][j - 1]		,			l[i - 1][j - 1] + match     )

       _lowerCamelCase       :		Optional[int]		=''
       _lowerCamelCase	,     _lowerCamelCase       :		Dict		=m, n
       while i > 0 and j > 0:
              _lowerCamelCase       :		int		=1 if x[i - 1] == y[j - 1] else 0

              if l[i][j] == l[i - 1][j - 1] + match:
                     if match == 1:
                            _lowerCamelCase       :		Union[str, Any]		=x[i - 1] + seq
                     i -= 1
                     j -= 1
              elif l[i][j] == l[i - 1][j]:
                     i -= 1
              else:
                     j -= 1

       return l[m][n], seq


if __name__ == "__main__":
 lowerCamelCase											=       'AGGTAB'
 lowerCamelCase											=       'GXTXAYB'
 lowerCamelCase											=       4
 lowerCamelCase											=       'GTAB'

 lowerCamelCase					,				lowerCamelCase											=       longest_common_subsequence(a, b)
 print('len =', ln, ', sub-sequence =', subseq)
 import doctest

 doctest.testmod()


