'''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


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

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

SCREAMING_SNAKE_CASE_:     Optional[int]  ={
    'tokenizer_file': {
        'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json',
    },
}

SCREAMING_SNAKE_CASE_:     Optional[Any]  ={
    'gpt-neox-20b': 20_48,
}




class        __A      ( A_	):
    a__       :						List[Any]          =  VOCAB_FILES_NAMES
    a__       :						List[Any]          =  PRETRAINED_VOCAB_FILES_MAP
    a__       :						Any          =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__       :						Optional[Any]          =  ["""input_ids""", """attention_mask"""]



    def __init__(self    :    Dict   ,			__a    :    str=None   ,			__a    :    List[str]=None   ,			__a    :    str=None   ,			__a    :    List[str]="<|endoftext|>"   ,			__a    :    Optional[Any]="<|endoftext|>"   ,			__a    :    List[str]="<|endoftext|>"   ,			__a    :    Dict=False   ,			**__a    :    Union[str, Any]   ,			):
         super().__init__(
             _lowerCamelCase   ,			_lowerCamelCase   ,			tokenizer_file=_lowerCamelCase   ,			unk_token=_lowerCamelCase   ,			bos_token=_lowerCamelCase   ,			eos_token=_lowerCamelCase   ,			add_prefix_space=_lowerCamelCase   ,			**_lowerCamelCase   ,			)

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

         UpperCAmelCase_           =   add_prefix_space



    def 					_lowercase						(self    :    Union[str, Any]   ,			__a    :    str   ,			__a    :    Optional[str] = None ):
         UpperCAmelCase_           =   self._tokenizer.model.save(_lowerCamelCase   ,			name=_lowerCamelCase )
         return tuple(_lowerCamelCase )






    def 					_lowercase						(self    :    int   ,			__a    :    "Conversation" ):
         UpperCAmelCase_           =   []
         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_           =   input_ids[-self.model_max_length :]
         return input_ids






"""simple docstring"""



UpperCAmelCase__          = {
    'Pillow': 'Pillow',
    'accelerate': 'accelerate>=0.11.0',
    'compel': 'compel==0.1.8',
    'black': 'black~=23.1',
    'datasets': 'datasets',
    'filelock': 'filelock',
    'flax': 'flax>=0.4.1',
    'hf-doc-builder': 'hf-doc-builder>=0.3.0',
    'huggingface-hub': 'huggingface-hub>=0.13.2',
    'requests-mock': 'requests-mock==1.10.0',
    'importlib_metadata': 'importlib_metadata',
    'invisible-watermark': 'invisible-watermark',
    'isort': 'isort>=5.5.4',
    'jax': 'jax>=0.2.8,!=0.3.2',
    'jaxlib': 'jaxlib>=0.1.65',
    'Jinja2': 'Jinja2',
    'k-diffusion': 'k-diffusion>=0.0.12',
    'torchsde': 'torchsde',
    'note_seq': 'note_seq',
    'librosa': 'librosa',
    'numpy': 'numpy',
    'omegaconf': 'omegaconf',
    'parameterized': 'parameterized',
    'protobuf': 'protobuf>=3.20.3,<4',
    'pytest': 'pytest',
    'pytest-timeout': 'pytest-timeout',
    'pytest-xdist': 'pytest-xdist',
    'ruff': 'ruff>=0.0.241',
    'safetensors': 'safetensors',
    'sentencepiece': 'sentencepiece>=0.1.91,!=0.1.92',
    'scipy': 'scipy',
    'onnx': 'onnx',
    'regex': 'regex!=2019.12.17',
    'requests': 'requests',
    'tensorboard': 'tensorboard',
    'torch': 'torch>=1.4',
    'torchvision': 'torchvision',
    'transformers': 'transformers>=4.25.1',
    'urllib3': 'urllib3<=2.0.0',
}



