


'''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__    	=     logging.get_logger(__name__)

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

lowerCamelCase__    	=     {
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
}

lowerCamelCase__    	=     {
    'moussaKam/mbarthez': 1_024,
    'moussaKam/barthez': 1_024,
    'moussaKam/barthez-orangesum-title': 1_024,
}

lowerCamelCase__    	=     '▁'






class 	lowerCAmelCase__			(			UpperCAmelCase__	):
			lowerCAmelCase :	Any          =     VOCAB_FILES_NAMES
			lowerCAmelCase :	Optional[Any]          =     PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase :	Union[str, Any]          =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase :	List[str]          =     ["input_ids", "attention_mask"]




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



					'''simple docstring'''







					_UpperCAmelCase		:       Optional[Any]								=      AddedToken(lowerCamelCase__	,  lstrip=lowerCamelCase__	,  rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__	,  lowerCamelCase__ ) else mask_token

					_UpperCAmelCase		:       Union[str, Any]								=      {} 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__	,  )

					_UpperCAmelCase		:       Tuple								=      vocab_file
					_UpperCAmelCase		:       int								=      spm.SentencePieceProcessor(**self.sp_model_kwargs )
					self.sp_model.Load(str(lowerCamelCase__ ) )

					_UpperCAmelCase		:       List[Any]								=      {"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

					_UpperCAmelCase		:       List[str]								=      len(self.sp_model ) - 1
					_UpperCAmelCase		:       str								=      {v: k for k, v in self.fairseq_tokens_to_ids.items()}




			def 							lowerCAmelCase__    (		self  :     Union[str, Any]	,  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]
					_UpperCAmelCase		:       Optional[int]								=      [self.cls_token_id]
					_UpperCAmelCase		:       List[Any]								=      [self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep




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



					'''simple docstring'''







					_UpperCAmelCase		:       List[str]								=      [self.sep_token_id]
					_UpperCAmelCase		:       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  :     int )   ->Dict:



					'''simple docstring'''







					return len(self.sp_model )




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



					'''simple docstring'''







					_UpperCAmelCase		:       Dict								=      {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  :     List[str]	,  lowerCamelCase__  :     str )   ->List[str]:



					'''simple docstring'''







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




			def 							lowerCAmelCase__    (		self  :     Tuple	,  lowerCamelCase__  :     Dict )   ->str:



					'''simple docstring'''







					if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
					_UpperCAmelCase		:       Optional[int]								=      self.sp_model.PieceToId(lowerCamelCase__ )

					return spm_id if spm_id else self.unk_token_id




			def 							lowerCAmelCase__    (		self  :     List[str]	,  lowerCamelCase__  :     int )   ->Optional[int]:



					'''simple docstring'''







					if index in self.fairseq_ids_to_tokens:
							return self.fairseq_ids_to_tokens[index]
					return self.sp_model.IdToPiece(lowerCamelCase__ )




			def 							lowerCAmelCase__    (		self  :     List[str]	,  lowerCamelCase__  :     int )   ->Dict:



					'''simple docstring'''







					_UpperCAmelCase		:       List[str]								=      []
					_UpperCAmelCase		:       Tuple								=      ""
					_UpperCAmelCase		:       Optional[Any]								=      False
					for token in tokens:
							# make sure that special tokens are not decoded using sentencepiece model
							if token in self.all_special_tokens:
									if not prev_is_special:
											out_string += " "
									out_string += self.sp_model.decode(lowerCamelCase__ ) + token
									_UpperCAmelCase		:       str								=      True
									_UpperCAmelCase		:       List[Any]								=      []
							else:
									current_sub_tokens.append(lowerCamelCase__ )
									_UpperCAmelCase		:       Union[str, Any]								=      False
					out_string += self.sp_model.decode(lowerCamelCase__ )
					return out_string.strip()




			def __getstate__(		self  :     Dict )   ->str:



					'''simple docstring'''







					_UpperCAmelCase		:       int								=      self.__dict__.copy()
					_UpperCAmelCase		:       Optional[Any]								=      None
					return state




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



					'''simple docstring'''







					_UpperCAmelCase		:       List[Any]								=      d

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

					_UpperCAmelCase		:       Tuple								=      spm.SentencePieceProcessor(**self.sp_model_kwargs )
					self.sp_model.Load(self.vocab_file )






			def 							lowerCAmelCase__    (		self  :     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
					_UpperCAmelCase		:       Any								=      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:
									_UpperCAmelCase		:       Optional[int]								=      self.sp_model.serialized_model_proto()
									fi.write(lowerCamelCase__ )

					return (out_vocab_file,)







'''simple docstring'''


from __future__ import annotations

import numpy as np






def  __lowerCAmelCase (__lowerCAmelCase   ):
		return np.maximum(0      , __lowerCAmelCase   )


if __name__ == "__main__":
						print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]



