'''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


lowercase_     		= logging.get_logger(__name__)

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

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

lowercase_     		= {
    '''gpt-neox-20b''': 2048,
}
class   SCREAMING_SNAKE_CASE			(						__lowercase):







		"""simple docstring"""
		lowercase   :      List[str]       =							VOCAB_FILES_NAMES
		lowercase   :      Optional[Any]       =							PRETRAINED_VOCAB_FILES_MAP
		lowercase   :      Tuple       =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowercase   :      Tuple       =							['input_ids', 'attention_mask']






		def __init__(   self		,						__A=None		,						__A=None		,						__A=None		,						__A="<|endoftext|>"		,						__A="<|endoftext|>"		,						__A="<|endoftext|>"		,						__A=False		,						**__A		,						) ->     List[Any]:
								super().__init__(
								    __A		,						__A		,						tokenizer_file=__A		,						unk_token=__A		,						bos_token=__A		,						eos_token=__A		,						add_prefix_space=__A		,						**__A		,						)

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

								_lowerCAmelCase										=add_prefix_space






		def 		UpperCamelCase__       (   self		,						__A		,						__A = None				) ->     Tuple[str]:
								_lowerCAmelCase										=self._tokenizer.model.save(__A		,						name=__A				)
								return tuple(__A				)






		def 		UpperCamelCase__       (   self		,						__A				) ->     List[int]:
								_lowerCAmelCase										=[]
								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:
														_lowerCAmelCase										=input_ids[-self.model_max_length :]
								return input_ids






'''simple docstring'''

from __future__ import annotations

lowercase_     		= 10



def 							UpperCamelCase__			(			a__      ):


						'''simple docstring'''






						_lowerCAmelCase										=1
						_lowerCAmelCase										=max(a__      )
						while placement <= max_digit:
												# declare and initialize empty buckets
												_lowerCAmelCase										=[[] for _ in range(a__      )]
												# split list_of_ints between the buckets
												for i in list_of_ints:
																		_lowerCAmelCase										=int((i / placement) % RADIX      )
																		buckets[tmp].append(a__      )
												# put each buckets' contents into list_of_ints
												_lowerCAmelCase										=0
												for b in range(a__      ):
																		for i in buckets[b]:
																								_lowerCAmelCase										=i
																								a += 1
        # move to next
												placement *= RADIX
						return list_of_ints


if __name__ == "__main__":
							import doctest

							doctest.testmod()





