


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__     					=			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__     					=			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

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

SCREAMING_SNAKE_CASE__     					=			{
    "gpt-neox-20b": 2_048,
}



class 						_UpperCAmelCase      (     lowercase							):
		lowerCamelCase_	:			List[str]       			=  VOCAB_FILES_NAMES
		lowerCamelCase_	:			List[Any]       			=  PRETRAINED_VOCAB_FILES_MAP
		lowerCamelCase_	:			Dict       			=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCamelCase_	:			int       			=  ["""input_ids""", """attention_mask"""]






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

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

				SCREAMING_SNAKE_CASE_				:List[Any]				     =						add_prefix_space






		def _snake_case		(						self				:     Optional[Any]   ,  UpperCAmelCase				:     str   ,  UpperCAmelCase				:     Optional[str] = None):
				SCREAMING_SNAKE_CASE_				:int				     =						self._tokenizer.model.save(UpperCAmelCase   ,  name=UpperCAmelCase)
				return tuple(UpperCAmelCase)







		def _snake_case		(						self				:     str   ,  UpperCAmelCase				:     "Conversation"):
				SCREAMING_SNAKE_CASE_				:Dict				     =						[]
				for is_user, text in conversation.iter_texts():
						input_ids.extend(self.encode(UpperCAmelCase   ,  add_special_tokens=UpperCAmelCase) + [self.eos_token_id])

				if len(UpperCAmelCase) > self.model_max_length:
						SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						input_ids[-self.model_max_length :]
				return input_ids










from timeit import timeit


def     lowercase	(    a ):



		'''simple docstring'''




		if number < 0:
				raise ValueError("the value of input must not be negative" )
		SCREAMING_SNAKE_CASE_				:Optional[int]				     =						0
		while number:
				number &= number - 1
				result += 1
		return result


def     lowercase	(    a ):



		'''simple docstring'''




		if number < 0:
				raise ValueError("the value of input must not be negative" )
		SCREAMING_SNAKE_CASE_				:List[Any]				     =						0
		while number:
				if number % 2 == 1:
						result += 1
				number >>= 1
		return result


def     lowercase	(    ):



		'''simple docstring'''




		def do_benchmark(a ) -> None:
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						"import __main__ as z"
				print(F"Benchmark when {number = }:" )
				print(F"{get_set_bits_count_using_modulo_operator(a ) = }" )
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						timeit("z.get_set_bits_count_using_modulo_operator(25)"     , setup=a )
				print(F"timeit() runs in {timing} seconds" )
				print(F"{get_set_bits_count_using_brian_kernighans_algorithm(a ) = }" )
				SCREAMING_SNAKE_CASE_				:str				     =						timeit(
				    "z.get_set_bits_count_using_brian_kernighans_algorithm(25)"     , setup=a     , )
				print(F"timeit() runs in {timing} seconds" )

		for number in (25, 37, 58, 0):
				do_benchmark(a )
				print()


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()






