


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


UpperCAmelCase					:  Tuple			=						logging.get_logger(__name__)

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

UpperCAmelCase					:  Dict			=						{
    'tokenizer_file': {
        'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json',
    },
}

UpperCAmelCase					:  Any			=						{
    'gpt-neox-20b': 20_48,
}







class     __lowercase    (				__UpperCAmelCase   ):



		"""simple docstring"""

		UpperCamelCase			: Tuple           =						VOCAB_FILES_NAMES
		UpperCamelCase			: Optional[Any]           =						PRETRAINED_VOCAB_FILES_MAP
		UpperCamelCase			: Optional[Any]           =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		UpperCamelCase			: List[Any]           =						["input_ids", "attention_mask"]







		def __init__(      self						,	A=None						,	A=None						,	A=None						,	A="<|endoftext|>"						,	A="<|endoftext|>"						,	A="<|endoftext|>"						,	A=False						,	**A						,	)   ->      Optional[int]:







					'''simple docstring'''







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

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

					lowerCamelCase  						=   add_prefix_space







		def  __A					(      self						,	A						,	A = None     )   ->      Optional[int]:







					'''simple docstring'''







					lowerCamelCase  						=   self._tokenizer.model.save(lowerCamelCase__						,	name=lowerCamelCase__     )
					return tuple(lowerCamelCase__     )







		def  __A					(      self						,	A     )   ->      List[Any]:







					'''simple docstring'''







					lowerCamelCase  						=   []
					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:
								lowerCamelCase  						=   input_ids[-self.model_max_length :]
					return input_ids


"""simple docstring"""






import functools



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							len(lowerCamelCase       )
				UpperCAmelCase__             =							len(lowerCamelCase       )

				@functools.cache
				def min_distance(lowerCamelCase					,			lowerCamelCase       ) -> int:
								# if first word index is overflow - delete all from the second word
								if indexa >= len_worda:
												return len_worda - indexa
								# if second word index is overflow - delete all from the first word
								if indexa >= len_worda:
												return len_worda - indexa
								UpperCAmelCase__             =							int(worda[indexa] != worda[indexa]       )  # current letters not identical
								return min(
								    1 + min_distance(indexa + 1					,			lowerCamelCase       )					,			1 + min_distance(lowerCamelCase					,			indexa + 1       )					,			diff + min_distance(indexa + 1					,			indexa + 1       )					,			)

				return min_distance(0					,			0       )


if __name__ == "__main__":
						import doctest

						doctest.testmod()



