



'''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


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

UpperCamelCase_       :  Dict					=  {"""vocab_file""": """sentencepiece.bpe.model"""}

UpperCamelCase_       :  Union[str, Any]					=  {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

UpperCamelCase_       :  Dict					=  {
    """camembert-base""": 512,
}

UpperCamelCase_       :  Any					=  """▁"""



class    lowerCamelCase__				(			__lowerCamelCase						):






      """simple docstring"""
      UpperCamelCase__			 =     VOCAB_FILES_NAMES
      UpperCamelCase__			 =     PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase__			 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase__			 =     ['''input_ids''', '''attention_mask''']




      def __init__(       self							:     int			,a__							:     Any			,a__							:     Any="<s>"			,a__							:     Dict="</s>"			,a__							:     str="</s>"			,a__							:     Optional[Any]="<s>"			,a__							:     List[Any]="<unk>"			,a__							:     Dict="<pad>"			,a__							:     Optional[int]="<mask>"			,a__							:     Optional[Any]=["<s>NOTUSED", "</s>NOTUSED"]			,a__							:     Optional[Dict[str, Any]] = None			,**a__							:     List[str]			,):
             a__								= AddedToken(__lowercase			,lstrip=__lowercase			,rstrip=__lowercase   ) if isinstance(__lowercase			,__lowercase   ) else mask_token

             a__								= {} 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			,additional_special_tokens=__lowercase			,sp_model_kwargs=self.sp_model_kwargs			,**__lowercase			,)
             a__								= spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(str(__lowercase   )   )
             a__								= vocab_file
             # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
             # sentencepiece vocabulary (this is the case for <s> and </s>
             a__								= {"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
             a__								= len(self.fairseq_tokens_to_ids   )
             a__								= len(self.sp_model   ) + len(self.fairseq_tokens_to_ids   )
             a__								= {v: k for k, v in self.fairseq_tokens_to_ids.items()}




      def lowerCAmelCase_					(       self							:     Dict			,a__							:     List[int]			,a__							:     Optional[List[int]] = None   ):







             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							:     List[Any]			,a__							:     List[int]			,a__							:     Optional[List[int]] = None			,a__							:     bool = False   ):







             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			,a__							:     List[int]			,a__							:     Optional[List[int]] = None   ):
             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]   ):
             return len(self.fairseq_tokens_to_ids   ) + len(self.sp_model   )




      def lowerCAmelCase_					(       self							:     Dict   ):
             a__								= {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							:     Any			,a__							:     str   ):
             return self.sp_model.encode(__lowercase			,out_type=__lowercase   )




      def lowerCAmelCase_					(       self							:     Tuple			,a__							:     Union[str, Any]   ):







             if token in self.fairseq_tokens_to_ids:
                    return self.fairseq_tokens_to_ids[token]
             elif self.sp_model.PieceToId(__lowercase   ) == 0:
                    # Convert sentence piece unk token to fairseq unk token index
                    return self.unk_token_id
             return self.fairseq_offset + self.sp_model.PieceToId(__lowercase   )




      def lowerCAmelCase_					(       self							:     List[str]			,a__							:     Any   ):







             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			,a__							:     Union[str, Any]   ):
             a__								= []
             a__								= ""
             a__								= 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(__lowercase   ) + token
                           a__								= True
                           a__								= []
                    else:
                           current_sub_tokens.append(__lowercase   )
                           a__								= False
             out_string += self.sp_model.decode(__lowercase   )
             return out_string.strip()




      def __getstate__(       self							:     Union[str, Any]   ):
             a__								= self.__dict__.copy()
             a__								= None
             return state




      def __setstate__(       self							:     int			,a__							:     Tuple   ):
             a__								= d

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

             a__								= spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(self.vocab_file   )




      def lowerCAmelCase_					(       self							:     Optional[int]			,a__							:     str			,a__							:     Optional[str] = None   ):







             if not os.path.isdir(__lowercase   ):
                    logger.error(f'Vocabulary path ({save_directory}) should be a directory'   )
                    return
             a__								= 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:
                           a__								= self.sp_model.serialized_model_proto()
                           fi.write(__lowercase   )

             return (out_vocab_file,)



'''simple docstring'''

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


UpperCAmelCase					 =	logging.get_logger(__name__)

UpperCAmelCase					 =	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase					 =	{
    '''tokenizer_file''': {
        '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase					 =	{
    '''gpt-neox-20b''': 2048,
}


class 	lowerCAmelCase  (   A ):
       lowerCAmelCase_												=			VOCAB_FILES_NAMES
       lowerCAmelCase_												=			PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase_												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase_												=			["input_ids", "attention_mask"]







       def __init__(				self      :			Tuple    ,   __lowercase      :			Union[str, Any]=None    ,   __lowercase      :			Union[str, Any]=None    ,   __lowercase      :			str=None    ,   __lowercase      :			Optional[int]="<|endoftext|>"    ,   __lowercase      :			List[Any]="<|endoftext|>"    ,   __lowercase      :			Tuple="<|endoftext|>"    ,   __lowercase      :			Optional[int]=False    ,   **__lowercase      :			List[Any]    ,   ):







            """simple docstring"""







            super().__init__(
                __lowercase    ,   __lowercase    ,   tokenizer_file=__lowercase    ,   unk_token=__lowercase    ,   bos_token=__lowercase    ,   eos_token=__lowercase    ,   add_prefix_space=__lowercase    ,   **__lowercase    ,   )

            __lowercase      		=json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
            if pre_tok_state.get('add_prefix_space'    ,   __lowercase   ) != add_prefix_space:
                 __lowercase      		=getattr(__lowercase    ,   pre_tok_state.pop('type'   )   )
                 __lowercase      		=add_prefix_space
                 __lowercase      		=pre_tok_class(**__lowercase   )

            __lowercase      		=add_prefix_space







       def       snake_case (				self      :			Optional[Any]    ,   __lowercase      :			str    ,   __lowercase      :			Optional[str] = None   ):







            """simple docstring"""







            __lowercase      		=self._tokenizer.model.save(__lowercase    ,   name=__lowercase   )
            return tuple(__lowercase   )







       def       snake_case (				self      :			Optional[Any]    ,   __lowercase      :			"Conversation"   ):







            """simple docstring"""







            __lowercase      		=[]
            for is_user, text in conversation.iter_texts():
                 input_ids.extend(self.encode(__lowercase    ,   add_special_tokens=__lowercase   ) + [self.eos_token_id]   )

            if len(__lowercase   ) > self.model_max_length:
                 __lowercase      		=input_ids[-self.model_max_length :]
            return input_ids


