




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


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

lowerCamelCase__ :   Optional[int]					=							{'tokenizer_file': 'tokenizer.json'}

lowerCamelCase__ :   str					=							{
    '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        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 lowercase_				    =    VOCAB_FILES_NAMES
 lowercase_				    =    PRETRAINED_VOCAB_FILES_MAP
 lowercase_				    =    ["input_ids", "attention_mask"]
 lowercase_				    =    None



 def __init__(							self  :		Optional[int]				,				_lowerCAmelCase  :		List[str]=None				,				_lowerCAmelCase  :		Union[str, Any]=None				,				_lowerCAmelCase  :		Any=None				,				_lowerCAmelCase  :		Optional[Any]="<unk>"				,				_lowerCAmelCase  :		List[str]="<s>"				,				_lowerCAmelCase  :		Dict="</s>"				,				_lowerCAmelCase  :		str="<pad>"				,				_lowerCAmelCase  :		Union[str, Any]=False				,				_lowerCAmelCase  :		List[str]=False				,				**_lowerCAmelCase  :		List[str]				,				):
       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				,				)
       SCREAMING_SNAKE_CASE_							=			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
       if pre_tok_state.get('add_prefix_space'				,				_lowerCAmelCase						) != add_prefix_space:
             SCREAMING_SNAKE_CASE_							=			getattr(_lowerCAmelCase				,				pre_tok_state.pop('type'						)						)
             SCREAMING_SNAKE_CASE_							=			add_prefix_space
             SCREAMING_SNAKE_CASE_							=			pre_tok_class(**_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_							=			add_prefix_space



 def       lowerCAmelCase_  (							self  :		List[Any]				,				*_lowerCAmelCase  :		Tuple				,				**_lowerCAmelCase  :		List[Any]						):
       SCREAMING_SNAKE_CASE_							=			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       lowerCAmelCase_  (							self  :		Any				,				*_lowerCAmelCase  :		Optional[Any]				,				**_lowerCAmelCase  :		int						):
       SCREAMING_SNAKE_CASE_							=			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       lowerCAmelCase_  (							self  :		List[Any]				,				_lowerCAmelCase  :		str				,				_lowerCAmelCase  :		Optional[str] = None						):
       SCREAMING_SNAKE_CASE_							=			self._tokenizer.model.save(_lowerCAmelCase				,				name=_lowerCAmelCase						)
       return tuple(_lowerCAmelCase						)




 def       lowerCAmelCase_  (							self  :		Optional[int]				,				_lowerCAmelCase  :		"Conversation"						):
       SCREAMING_SNAKE_CASE_							=			[]
       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_							=			input_ids[-self.model_max_length :]
       return input_ids





import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


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





class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 def __init__(							self  :		str				,				*_lowerCAmelCase  :		Optional[Any]				,				**_lowerCAmelCase  :		Optional[Any]						):
       warnings.warn(
           'The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use ImageGPTImageProcessor instead.'				,				_lowerCAmelCase				,				)
       super().__init__(*_lowerCAmelCase				,				**_lowerCAmelCase						)