


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


_SCREAMING_SNAKE_CASE      :			Any      				=   logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      :			List[str]      				=   {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

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

_SCREAMING_SNAKE_CASE      :			List[Any]      				=   {
    "gpt-neox-20b": 20_48,
}

class   A__ (   __a     ):







    """simple docstring"""

    __magic_name__        =		VOCAB_FILES_NAMES
    __magic_name__        =		PRETRAINED_VOCAB_FILES_MAP
    __magic_name__        =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __magic_name__        =		["""input_ids""", """attention_mask"""]
    def __init__(	self      , __snake_case=None      , __snake_case=None      , __snake_case=None      , __snake_case="<|endoftext|>"      , __snake_case="<|endoftext|>"      , __snake_case="<|endoftext|>"      , __snake_case=False      , **__snake_case      , ):
         super().__init__(
             a__      , a__      , tokenizer_file=a__      , unk_token=a__      , bos_token=a__      , eos_token=a__      , add_prefix_space=a__      , **a__      , )

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

         snake_case					=    add_prefix_space
    def 		a_      (	self      , __snake_case      , __snake_case = None   ):
         snake_case					=    self._tokenizer.model.save(a__      , name=a__   )
         return tuple(a__   )




    def 		a_      (	self      , __snake_case   ):
         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:
              snake_case					=    input_ids[-self.model_max_length :]
         return input_ids








import re

from filelock import FileLock


try:
 import nltk

 _SCREAMING_SNAKE_CASE      :			Union[str, Any]      				=   True
except (ImportError, ModuleNotFoundError):
 _SCREAMING_SNAKE_CASE      :			Optional[Any]      				=   False

if NLTK_AVAILABLE:
 with FileLock(".lock") as lock:
  nltk.download("punkt", quiet=True)
def       UpperCAmelCase__						(UpperCamelCase_    ):



     """simple docstring"""






     re.sub('''<n>'''							,''''''							,UpperCamelCase_    )  # remove pegasus newline char
     assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
     return "\n".join(nltk.sent_tokenize(UpperCamelCase_    )    )




