


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	: str  				=logging.get_logger(__name__)

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

__lowerCAmelCase	: Dict  				={
    '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	: List[str]  				={
    'moussaKam/mbarthez': 1_0_2_4,
    'moussaKam/barthez': 1_0_2_4,
    'moussaKam/barthez-orangesum-title': 1_0_2_4,
}

__lowerCAmelCase	: Any  				='▁'
class        _lowercase      (			A__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			Optional[Any]						=		VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE__				:			Tuple						=		PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE__				:			List[Any]						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE__				:			List[str]						=		['''input_ids''', '''attention_mask''']


				def __init__(       self			:Tuple			,			lowerCAmelCase__			:int			,			lowerCAmelCase__			:List[str]="<s>"			,			lowerCAmelCase__			:Optional[int]="</s>"			,			lowerCAmelCase__			:List[Any]="</s>"			,			lowerCAmelCase__			:List[str]="<s>"			,			lowerCAmelCase__			:str="<unk>"			,			lowerCAmelCase__			:List[str]="<pad>"			,			lowerCAmelCase__			:str="<mask>"			,			lowerCAmelCase__			:Optional[Dict[str, Any]] = None			,			**lowerCAmelCase__			:Optional[int]			,			)		->			None:
										# Mask token behave like a normal word, i.e. include the space before it
										__SCREAMING_SNAKE_CASE						:     Dict					=		AddedToken(lowerCAmelCase__			,			lstrip=lowerCAmelCase__			,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__			,			lowerCAmelCase__	) else mask_token

										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		{} 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__			,			)

										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		vocab_file
										__SCREAMING_SNAKE_CASE						:     Tuple					=		spm.SentencePieceProcessor(**self.sp_model_kwargs	)
										self.sp_model.Load(str(lowerCAmelCase__	)	)

										__SCREAMING_SNAKE_CASE						:     List[str]					=		{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

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


				def 		__magic_name__(       self			:int			,			lowerCAmelCase__			:List[int]			,			lowerCAmelCase__			:Optional[List[int]] = None	)		->			List[int]:

										if token_ids_a is None:
																return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										__SCREAMING_SNAKE_CASE						:     str					=		[self.cls_token_id]
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		[self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep


				def 		__magic_name__(       self			:List[str]			,			lowerCAmelCase__			:List[int]			,			lowerCAmelCase__			:Optional[List[int]] = None			,			lowerCAmelCase__			:bool = False	)		->			List[int]:
										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 		__magic_name__(       self			:Tuple			,			lowerCAmelCase__			:List[int]			,			lowerCAmelCase__			:Optional[List[int]] = None	)		->			List[int]:
										__SCREAMING_SNAKE_CASE						:     List[str]					=		[self.sep_token_id]
										__SCREAMING_SNAKE_CASE						:     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 		__magic_name__(       self			:int	)		->			Optional[int]:
										return len(self.sp_model	)


				def 		__magic_name__(       self			:Dict	)		->			Any:
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		{self.convert_ids_to_tokens(lowerCAmelCase__	): i for i in range(self.vocab_size	)}
										vocab.update(self.added_tokens_encoder	)
										return vocab


				def 		__magic_name__(       self			:Any			,			lowerCAmelCase__			:str	)		->			List[str]:
										return self.sp_model.encode(lowerCAmelCase__			,			out_type=lowerCAmelCase__	)


				def 		__magic_name__(       self			:Union[str, Any]			,			lowerCAmelCase__			:Optional[Any]	)		->			List[Any]:
										if token in self.fairseq_tokens_to_ids:
																return self.fairseq_tokens_to_ids[token]
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		self.sp_model.PieceToId(lowerCAmelCase__	)

										return spm_id if spm_id else self.unk_token_id


				def 		__magic_name__(       self			:str			,			lowerCAmelCase__			:Any	)		->			List[Any]:
										if index in self.fairseq_ids_to_tokens:
																return self.fairseq_ids_to_tokens[index]
										return self.sp_model.IdToPiece(lowerCAmelCase__	)


				def 		__magic_name__(       self			:Any			,			lowerCAmelCase__			:Tuple	)		->			Tuple:
										__SCREAMING_SNAKE_CASE						:     int					=		[]
										__SCREAMING_SNAKE_CASE						:     Any					=		''''''
										__SCREAMING_SNAKE_CASE						:     List[str]					=		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
																						__SCREAMING_SNAKE_CASE						:     Any					=		True
																						__SCREAMING_SNAKE_CASE						:     str					=		[]
																else:
																						current_sub_tokens.append(lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		False
										out_string += self.sp_model.decode(lowerCAmelCase__	)
										return out_string.strip()


				def __getstate__(       self			:str	)		->			Union[str, Any]:
										__SCREAMING_SNAKE_CASE						:     int					=		self.__dict__.copy()
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		None
										return state


				def __setstate__(       self			:int			,			lowerCAmelCase__			:Optional[int]	)		->			str:
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		d

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

										__SCREAMING_SNAKE_CASE						:     Any					=		spm.SentencePieceProcessor(**self.sp_model_kwargs	)
										self.sp_model.Load(self.vocab_file	)



				def 		__magic_name__(       self			:Any			,			lowerCAmelCase__			:str			,			lowerCAmelCase__			:Optional[str] = None	)		->			Tuple[str]:
										if not os.path.isdir(lowerCAmelCase__	):
																logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
																return
										__SCREAMING_SNAKE_CASE						:     Optional[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:
																						__SCREAMING_SNAKE_CASE						:     Tuple					=		self.sp_model.serialized_model_proto()
																						fi.write(lowerCAmelCase__	)

										return (out_vocab_file,)




import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
						from transformers.pipelines.conversational import Conversation


__lowerCAmelCase	: Optional[int]  				=logging.get_logger(__name__)

__lowerCAmelCase	: Optional[Any]  				={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

__lowerCAmelCase	: List[str]  				={
    'tokenizer_file': {
        'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json',
    },
}

__lowerCAmelCase	: Optional[int]  				={
    'gpt-neox-20b': 2_0_4_8,
}
class        _lowercase      (			A__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			str						=		VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE__				:			Dict						=		PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE__				:			Any						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE__				:			Optional[Any]						=		['''input_ids''', '''attention_mask''']


				def __init__(       self			:int			,			lowerCAmelCase__			:Any=None			,			lowerCAmelCase__			:Optional[Any]=None			,			lowerCAmelCase__			:List[Any]=None			,			lowerCAmelCase__			:str="<|endoftext|>"			,			lowerCAmelCase__			:str="<|endoftext|>"			,			lowerCAmelCase__			:Dict="<|endoftext|>"			,			lowerCAmelCase__			:Union[str, Any]=False			,			**lowerCAmelCase__			:List[str]			,			)		->			Any:
										super().__init__(
										    lowerCAmelCase__			,			lowerCAmelCase__			,			tokenizer_file=lowerCAmelCase__			,			unk_token=lowerCAmelCase__			,			bos_token=lowerCAmelCase__			,			eos_token=lowerCAmelCase__			,			add_prefix_space=lowerCAmelCase__			,			**lowerCAmelCase__			,			)

										__SCREAMING_SNAKE_CASE						:     List[Any]					=		json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
										if pre_tok_state.get('''add_prefix_space'''			,			lowerCAmelCase__	) != add_prefix_space:
																__SCREAMING_SNAKE_CASE						:     List[str]					=		getattr(lowerCAmelCase__			,			pre_tok_state.pop('''type'''	)	)
																__SCREAMING_SNAKE_CASE						:     str					=		add_prefix_space
																__SCREAMING_SNAKE_CASE						:     Any					=		pre_tok_class(**lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		add_prefix_space


				def 		__magic_name__(       self			:Union[str, Any]			,			lowerCAmelCase__			:str			,			lowerCAmelCase__			:Optional[str] = None	)		->			Tuple[str]:
										__SCREAMING_SNAKE_CASE						:     List[str]					=		self._tokenizer.model.save(lowerCAmelCase__			,			name=lowerCAmelCase__	)
										return tuple(lowerCAmelCase__	)



				def 		__magic_name__(       self			:Optional[Any]			,			lowerCAmelCase__			:"Conversation"	)		->			List[int]:
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		[]
										for is_user, text in conversation.iter_texts():
																input_ids.extend(self.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	) + [self.eos_token_id]	)

										if len(lowerCAmelCase__	) > self.model_max_length:
																__SCREAMING_SNAKE_CASE						:     List[str]					=		input_ids[-self.model_max_length :]
										return input_ids
