




"""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


A_						=				logging.get_logger(__name__)

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

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

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






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					VOCAB_FILES_NAMES
 lowercase__ 					=					PRETRAINED_VOCAB_FILES_MAP
 lowercase__ 					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__ 					=					["input_ids", "attention_mask"]


 def __init__(				self:		Dict,      a_:		Dict=None,      a_:		Tuple=None,      a_:		Dict=None,      a_:		str="<|endoftext|>",      a_:		Union[str, Any]="<|endoftext|>",      a_:		Tuple="<|endoftext|>",      a_:		Optional[int]=False,      **a_:		str,      ):




   '''simple docstring'''



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

   _snake_case							:		int								=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
   if pre_tok_state.get("""add_prefix_space""",      a_		) != add_prefix_space:
     _snake_case							:		Optional[int]								=  getattr(a_,      pre_tok_state.pop("""type"""		)		)
     _snake_case							:		Any								=  add_prefix_space
     _snake_case							:		List[str]								=  pre_tok_class(**a_		)

   _snake_case							:		Tuple								=  add_prefix_space


 def  UpperCamelCase_   (				self:		List[Any],      a_:		str,      a_:		Optional[str] = None		):




   '''simple docstring'''



   _snake_case							:		Dict								=  self._tokenizer.model.save(a_,      name=a_		)
   return tuple(a_		)


 def  UpperCamelCase_   (				self:		List[Any],      a_:		"Conversation"		):




   '''simple docstring'''



   _snake_case							:		List[Any]								=  []
   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:
     _snake_case							:		int								=  input_ids[-self.model_max_length :]
   return input_ids










import os

# Precomputes a list of the 100 first triangular numbers
__UpperCAmelCase								=						[int(0.5 * n * (n + 1)) for n in range(1, 101)]




def      lowercase__      (     ):


					'''simple docstring'''


					UpperCAmelCase_    :      Any            =						os.path.dirname(os.path.realpath(__snake_case  )  )
					UpperCAmelCase_    :      Optional[Any]            =						os.path.join(__snake_case     ,       'words.txt'  )

					UpperCAmelCase_    :      Union[str, Any]            =						''
					with open(__snake_case  ) as f:
										UpperCAmelCase_    :      List[Any]            =						f.readline()

					UpperCAmelCase_    :      Optional[int]            =						[word.strip('"'  ) for word in words.strip('\r\n'  ).split(','  )]
					UpperCAmelCase_    :      Optional[int]            =						[
					    word
					    for word in [sum(ord(__snake_case  ) - 64 for x in word  ) for word in words]
					    if word in TRIANGULAR_NUMBERS
					]
					return len(__snake_case  )


if __name__ == "__main__":
		print(solution())






