

'''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


lowerCamelCase			:				Tuple 			=					logging.get_logger(__name__)

lowerCamelCase			:				Dict 			=					{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

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

lowerCamelCase			:				List[Any] 			=					{
    "gpt-neox-20b": 2_0_4_8,
}







class 							A__   (	A__  ):
  A__					=    VOCAB_FILES_NAMES
  A__					=    PRETRAINED_VOCAB_FILES_MAP
  A__					=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A__					=    ['input_ids', 'attention_mask']





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





       '''simple docstring'''






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

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

       _SCREAMING_SNAKE_CASE							   =add_prefix_space





  def 						A  (		self				:     Union[str, Any]							, _a				:     str							, _a				:     Optional[str] = None			)     ->   Tuple[str]:





       '''simple docstring'''






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





  def 						A  (		self				:     Union[str, Any]							, _a				:     "Conversation"			)     ->   List[int]:





       '''simple docstring'''






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

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



'''simple docstring'''
from ..utils import DummyObject, requires_backends







class 							A__   (	metaclass=A__  ):
  A__					=    ['note_seq']





  def __init__(		self				:     List[str]							, *_a				:     Any							, **_a				:     Dict			)     ->   Optional[Any]:





       '''simple docstring'''






       requires_backends(self							, ['note_seq']			)





  @classmethod
  def 						A  (		cls				:     Any							, *_a				:     str							, **_a				:     List[Any]			)     ->   List[str]:





       '''simple docstring'''






       requires_backends(cls							, ['note_seq']			)





  @classmethod
  def 						A  (		cls				:     int							, *_a				:     Optional[Any]							, **_a				:     Optional[int]			)     ->   Tuple:





       '''simple docstring'''






       requires_backends(cls							, ['note_seq']			)
