






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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
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    							=      {'tokenizer_file': 'tokenizer.json'}

UpperCamelCase    							=      {
    'tokenizer_file': {
        'bigscience/tokenizer': 'https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json',
        'bigscience/bloom-560m': 'https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json',
        'bigscience/bloom-1b1': 'https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json',
        'bigscience/bloom-1b7': 'https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json',
        'bigscience/bloom-3b': 'https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json',
        'bigscience/bloom-7b1': 'https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json',
        'bigscience/bloom': 'https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json',
    },
}







class 		_A						( UpperCAmelCase_ ):
  lowercase_						:			List[str]						=					VOCAB_FILES_NAMES
  lowercase_						:			str						=					PRETRAINED_VOCAB_FILES_MAP
  lowercase_						:			Optional[Any]						=					['''input_ids''', '''attention_mask''']
  lowercase_						:			List[str]						=					None

  def __init__(    self						:	List[str]   ,				lowerCamelCase__						:	Any=None   ,				lowerCamelCase__						:	Any=None   ,				lowerCamelCase__						:	Tuple=None   ,				lowerCamelCase__						:	Any="<unk>"   ,				lowerCamelCase__						:	Dict="<s>"   ,				lowerCamelCase__						:	int="</s>"   ,				lowerCamelCase__						:	List[str]="<pad>"   ,				lowerCamelCase__						:	str=False   ,				lowerCamelCase__						:	Dict=False   ,				**lowerCamelCase__						:	Dict   ,				):
     """simple docstring"""

     super().__init__(
         lowerCamelCase__   ,				lowerCamelCase__   ,				tokenizer_file=lowerCamelCase__   ,				unk_token=lowerCamelCase__   ,				bos_token=lowerCamelCase__   ,				eos_token=lowerCamelCase__   ,				pad_token=lowerCamelCase__   ,				add_prefix_space=lowerCamelCase__   ,				clean_up_tokenization_spaces=lowerCamelCase__   ,				**lowerCamelCase__   ,				)
     __UpperCamelCase	:			Optional[Any]					=					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
     if pre_tok_state.get("""add_prefix_space"""   ,				lowerCamelCase__			) != add_prefix_space:
        __UpperCamelCase	:			Union[str, Any]					=					getattr(lowerCamelCase__   ,				pre_tok_state.pop("""type"""			)			)
        __UpperCamelCase	:			List[Any]					=					add_prefix_space
        __UpperCamelCase	:			int					=					pre_tok_class(**lowerCamelCase__			)

     __UpperCamelCase	:			List[str]					=					add_prefix_space

  def    a					(    self						:	List[str]   ,				*lowerCamelCase__						:	Union[str, Any]   ,				**lowerCamelCase__						:	Tuple			):
     """simple docstring"""

     __UpperCamelCase	:			Dict					=					kwargs.get("""is_split_into_words"""   ,				lowerCamelCase__			)
     if not (self.add_prefix_space or not is_split_into_words):
        raise Exception(
            f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'
            """ pretokenized inputs."""			)

     return super()._batch_encode_plus(*lowerCamelCase__   ,				**lowerCamelCase__			)

  def    a					(    self						:	Optional[Any]   ,				*lowerCamelCase__						:	str   ,				**lowerCamelCase__						:	Any			):
     """simple docstring"""

     __UpperCamelCase	:			List[Any]					=					kwargs.get("""is_split_into_words"""   ,				lowerCamelCase__			)

     if not (self.add_prefix_space or not is_split_into_words):
        raise Exception(
            f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'
            """ pretokenized inputs."""			)

     return super()._encode_plus(*lowerCamelCase__   ,				**lowerCamelCase__			)

  def    a					(    self						:	Optional[Any]   ,				lowerCamelCase__						:	str   ,				lowerCamelCase__						:	Optional[str] = None			):
     """simple docstring"""

     __UpperCamelCase	:			str					=					self._tokenizer.model.save(lowerCamelCase__   ,				name=lowerCamelCase__			)
     return tuple(lowerCamelCase__			)

  def    a					(    self						:	Any   ,				lowerCamelCase__						:	"Conversation"			):
     """simple docstring"""

     __UpperCamelCase	:			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:
        __UpperCamelCase	:			Optional[Any]					=					input_ids[-self.model_max_length :]
     return input_ids











import re

from filelock import FileLock


try:
       import nltk

       UpperCamelCase    							=      True
except (ImportError, ModuleNotFoundError):
       UpperCamelCase    							=      False

if NLTK_AVAILABLE:
       with FileLock('.lock') as lock:
              nltk.download('punkt', quiet=True)


def 				__lowerCamelCase     (							__lowerCAmelCase							:					str							)     ->  str:
   re.sub("""<n>"""					,							""""""					,							__lowerCAmelCase							)  # 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(__lowerCAmelCase							)							)



