




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


_snake_case				:				Tuple       							=		logging.get_logger(__name__)

_snake_case				:				List[Any]       							=		'▁'

_snake_case				:				List[str]       							=		{'vocab_file': 'sentencepiece.bpe.model'}

_snake_case				:				List[str]       							=		{
    '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'
        ),
    }
}

_snake_case				:				List[str]       							=		{
    '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   (		_a   ):
							lowercase_          =    VOCAB_FILES_NAMES
							lowercase_          =    PRETRAINED_VOCAB_FILES_MAP
							lowercase_          =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_          =    ['input_ids', 'attention_mask']







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


														"""simple docstring"""


														_a     					=    AddedToken(lowerCAmelCase_							,      lstrip=lowerCAmelCase_							,      rstrip=lowerCAmelCase_ ) if isinstance(lowerCAmelCase_							,      lowerCAmelCase_ ) else mask_token

														_a     					=    {} if sp_model_kwargs is None else sp_model_kwargs

														super().__init__(
														    bos_token=lowerCAmelCase_							,      eos_token=lowerCAmelCase_							,      unk_token=lowerCAmelCase_							,      sep_token=lowerCAmelCase_							,      cls_token=lowerCAmelCase_							,      pad_token=lowerCAmelCase_							,      mask_token=lowerCAmelCase_							,      sp_model_kwargs=self.sp_model_kwargs							,      **lowerCAmelCase_							,      )

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

														_a     					=    len(self.sp_model ) + self.fairseq_offset
														_a     					=    {v: k for k, v in self.fairseq_tokens_to_ids.items()}







							def __getstate__(  self	:  Optional[Any] )      ->							Dict:


														"""simple docstring"""


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







							def __setstate__(  self	:  Union[str, Any]							,      lowerCAmelCase_	:  str )      ->							Tuple:


														"""simple docstring"""


														_a     					=    d

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

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







							def        __lowerCAmelCase      (  self	:  Tuple							,      lowerCAmelCase_	:  List[int]							,      lowerCAmelCase_	:  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]
														_a     					=    [self.cls_token_id]
														_a     					=    [self.sep_token_id]
														return cls + token_ids_a + sep + sep + token_ids_a + sep







							def        __lowerCAmelCase      (  self	:  Union[str, Any]							,      lowerCAmelCase_	:  List[int]							,      lowerCAmelCase_	:  Optional[List[int]] = None							,      lowerCAmelCase_	:  bool = False )      ->							List[int]:


														"""simple docstring"""


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

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







							def        __lowerCAmelCase      (  self	:  Any							,      lowerCAmelCase_	:  List[int]							,      lowerCAmelCase_	:  Optional[List[int]] = None )      ->							List[int]:


														"""simple docstring"""


														_a     					=    [self.sep_token_id]
														_a     					=    [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] )      ->							List[Any]:


														"""simple docstring"""


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







							def        __lowerCAmelCase      (  self	:  List[Any] )      ->							Dict:


														"""simple docstring"""


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







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


														"""simple docstring"""


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







							def        __lowerCAmelCase      (  self	:  int							,      lowerCAmelCase_	:  List[str] )      ->							Optional[int]:


														"""simple docstring"""


														if token in self.fairseq_tokens_to_ids:
																					return self.fairseq_tokens_to_ids[token]
														_a     					=    self.sp_model.PieceToId(lowerCAmelCase_ )

														# 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	:  Tuple							,      lowerCAmelCase_	:  int )      ->							int:


														"""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	:  int							,      lowerCAmelCase_	:  Union[str, Any] )      ->							Union[str, Any]:


														"""simple docstring"""


														_a     					=    ''''''.join(lowerCAmelCase_ ).replace(lowerCAmelCase_							,      ''' ''' ).strip()
														return out_string







							def        __lowerCAmelCase      (  self	:  Optional[Any]							,      lowerCAmelCase_	:  str							,      lowerCAmelCase_	:  Optional[str] = None )      ->							Tuple[str]:


														"""simple docstring"""


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

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

														return (out_vocab_file,)







'''simple docstring'''


from __future__ import annotations
def 		snake_case_   (UpperCamelCase	:  list[int]				):





							'''simple docstring'''


							if not nums:
														return 0
							_a     					=    nums[0]
							_a     					=    0
							for num in nums[1:]:
														_a					,							_a     					=    (
														    max_excluding + num,
														    max(UpperCamelCase			,						UpperCamelCase				),
														)
							return max(UpperCamelCase			,						UpperCamelCase				)


if __name__ == "__main__":
				import doctest

				doctest.testmod()

