





'''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, PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase :					List[str] 							=logging.get_logger(__name__)

lowerCAmelCase :					Optional[int] 							='''▁'''

lowerCAmelCase :					Optional[int] 							={'''vocab_file''': '''sentencepiece.bpe.model'''}

lowerCAmelCase :					Union[str, Any] 							={
    '''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 :					Tuple 							={
    '''xlm-roberta-base''': 512,
    '''xlm-roberta-large''': 512,
    '''xlm-roberta-large-finetuned-conll02-dutch''': 512,
    '''xlm-roberta-large-finetuned-conll02-spanish''': 512,
    '''xlm-roberta-large-finetuned-conll03-english''': 512,
    '''xlm-roberta-large-finetuned-conll03-german''': 512,
}
class 				a_       (    _lowerCAmelCase							):
     __A								=      VOCAB_FILES_NAMES
     __A								=      PRETRAINED_VOCAB_FILES_MAP
     __A								=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __A								=      ["input_ids", "attention_mask"]





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





        """simple docstring"""




        lowercase_      :List[Any]         =			AddedToken(lowercase     ,				lstrip=lowercase     ,				rstrip=lowercase						) if isinstance(lowercase     ,				lowercase						) else mask_token

        lowercase_      :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     ,				sp_model_kwargs=self.sp_model_kwargs     ,				**lowercase     ,				)

        lowercase_      :str         =			spm.SentencePieceProcessor(**self.sp_model_kwargs						)
        self.sp_model.Load(str(lowercase						)						)
        lowercase_      :Tuple         =			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
        lowercase_      :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
        lowercase_      :Union[str, Any]         =			1

        lowercase_      :Dict         =			len(self.sp_model						) + self.fairseq_offset
        lowercase_      :List[str]         =			{v: k for k, v in self.fairseq_tokens_to_ids.items()}





     def __getstate__(			self		: Tuple						):





        """simple docstring"""




        lowercase_      :Tuple         =			self.__dict__.copy()
        lowercase_      :Optional[Any]         =			None
        lowercase_      :List[Any]         =			self.sp_model.serialized_model_proto()
        return state





     def __setstate__(			self		: str     ,				lowercase		: List[Any]						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			d

        # for backward compatibility
        if not hasattr(self     ,				"sp_model_kwargs"						):
           lowercase_      :Optional[Any]         =			{}

        lowercase_      :Union[str, Any]         =			spm.SentencePieceProcessor(**self.sp_model_kwargs						)
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)





     def 							lowercase__				(			self		: Dict     ,				lowercase		: List[int]     ,				lowercase		: Optional[List[int]] = None						):





        """simple docstring"""




        if token_ids_a is None:
           return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        lowercase_      :Tuple         =			[self.cls_token_id]
        lowercase_      :str         =			[self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep





     def 							lowercase__				(			self		: List[str]     ,				lowercase		: List[int]     ,				lowercase		: Optional[List[int]] = None     ,				lowercase		: bool = False						):





        """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 							lowercase__				(			self		: List[str]     ,				lowercase		: List[int]     ,				lowercase		: Optional[List[int]] = None						):





        """simple docstring"""




        lowercase_      :str         =			[self.sep_token_id]
        lowercase_      :str         =			[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 							lowercase__				(			self		: Any						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: Any						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: Optional[Any]     ,				lowercase		: str						):





        """simple docstring"""




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





     def 							lowercase__				(			self		: Dict     ,				lowercase		: str						):





        """simple docstring"""




        if token in self.fairseq_tokens_to_ids:
           return self.fairseq_tokens_to_ids[token]
        lowercase_      :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 							lowercase__				(			self		: str     ,				lowercase		: 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 							lowercase__				(			self		: str     ,				lowercase		: Dict						):





        """simple docstring"""




        lowercase_      :Any         =			"".join(lowercase						).replace(lowercase     ,				" "						).strip()
        return out_string







     def 							lowercase__				(			self		: str     ,				lowercase		: str     ,				lowercase		: Optional[str] = None						):





        """simple docstring"""




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

        return (out_vocab_file,)









'''simple docstring'''


def 							UpperCAmelCase_  (						__lowerCamelCase : str     ,__lowerCamelCase : str			):
   lowercase_      :Optional[Any]         =			len(__lowerCamelCase			)
   lowercase_      :List[Any]         =			[]
   for i in range(len(__lowerCamelCase			) - pat_len + 1			):
      lowercase_      :Dict         =			True
      for j in range(__lowerCamelCase			):
         if s[i + j] != pattern[j]:
            lowercase_      :int         =			False
            break
      if match_found:
         position.append(__lowerCamelCase			)
   return position


if __name__ == "__main__":
 assert naive_pattern_search('''ABCDEFG''', '''DE''') == [3]
 print(naive_pattern_search('''ABAAABCDBBABCDDEBCABC''', '''ABC'''))


