






"""simple docstring"""






def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__				):

    def get_matched_characters(lowerCAmelCase__       ,lowerCAmelCase__				) -> str:
        A__							 =       []
        A__							 =       min(len(_stra				)       ,len(_stra				)				) // 2
        for i, l in enumerate(_stra				):
            A__							 =       int(max(0       ,i - limit				)				)
            A__							 =       int(min(i + limit + 1       ,len(_stra				)				)				)
            if l in _stra[left:right]:
                matched.append(snake_case__				)
                A__							 =       f'''{_stra[0:_stra.index(snake_case__				)]} {_stra[_stra.index(snake_case__				) + 1:]}'''

        return "".join(snake_case__				)

    # matching characters
    A__							 =       get_matched_characters(snake_case__       ,snake_case__				)
    A__							 =       get_matched_characters(snake_case__       ,snake_case__				)
    A__							 =       len(snake_case__				)

    # transposition
    A__							 =       (
        len([(ca, ca) for ca, ca in zip(snake_case__       ,snake_case__				) if ca != ca]				) // 2
    )

    if not match_count:
        A__							 =       0.0
    else:
        A__							 =       (
            1
            / 3
            * (
                match_count / len(snake_case__				)
                + match_count / len(snake_case__				)
                + (match_count - transpositions) / match_count
            )
        )

    # common prefix up to 4 characters
    A__							 =       0
    for ca, ca in zip(stra[:4]       ,stra[:4]				):
        if ca == ca:
            prefix_len += 1
        else:
            break

    return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(jaro_winkler('''hello''', '''world'''))










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

SCREAMING_SNAKE_CASE						:						List[Any]					   =       {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

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

SCREAMING_SNAKE_CASE						:						str					   =       {
    '''gpt-neox-20b''': 2_048,
}





class       snake_case_       (    _lowerCamelCase       ):



	"""simple docstring"""

	SCREAMING_SNAKE_CASE_:							Union[str, Any]   			=					VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE_:							Any   			=					PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE_:							List[Any]   			=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE_:							Optional[Any]   			=					["""input_ids""", """attention_mask"""]


	def __init__(      self  ,					__a=None  ,					__a=None  ,					__a=None  ,					__a="<|endoftext|>"  ,					__a="<|endoftext|>"  ,					__a="<|endoftext|>"  ,					__a=False  ,					**__a  ,					):


					"""simple docstring"""

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

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

					A__							 =       add_prefix_space


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a = None						):


					"""simple docstring"""

					A__							 =       self._tokenizer.model.save(__a  ,					name=__a						)
					return tuple(__a						)






	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

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


