



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": 2048,
}



class 	lowerCamelCase      (						lowercase__  ):
					lowerCAmelCase_				:    int									=  VOCAB_FILES_NAMES
					lowerCAmelCase_				:    Optional[int]									=  PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_				:    Optional[int]									=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_				:    List[str]									=  ['input_ids', 'attention_mask']



					def __init__(			self    ,	lowerCAmelCase=None    ,	lowerCAmelCase=None    ,	lowerCAmelCase=None    ,	lowerCAmelCase="<|endoftext|>"    ,	lowerCAmelCase="<|endoftext|>"    ,	lowerCAmelCase="<|endoftext|>"    ,	lowerCAmelCase=False    ,	**lowerCAmelCase    ,	):
							super().__init__(
							    lowerCAmelCase    ,	lowerCAmelCase    ,	tokenizer_file=lowerCAmelCase    ,	unk_token=lowerCAmelCase    ,	bos_token=lowerCAmelCase    ,	eos_token=lowerCAmelCase    ,	add_prefix_space=lowerCAmelCase    ,	**lowerCAmelCase    ,	)

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

							UpperCAmelCase_						=				add_prefix_space



					def    A__		(			self    ,	lowerCAmelCase    ,	lowerCAmelCase = None     ):
							UpperCAmelCase_						=				self._tokenizer.model.save(lowerCAmelCase    ,	name=lowerCAmelCase     )
							return tuple(lowerCAmelCase     )



					def    A__		(			self    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				[]
							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:
									UpperCAmelCase_						=				input_ids[-self.model_max_length :]
							return input_ids






import math







def snake_case__  (			__SCREAMING_SNAKE_CASE )		->							list[int]:
		UpperCAmelCase_						=				[]
		UpperCAmelCase_						=				2
		UpperCAmelCase_						=				int(math.sqrt(__SCREAMING_SNAKE_CASE ) )  # Size of every segment
		UpperCAmelCase_						=				[True] * (end + 1)
		UpperCAmelCase_						=				[]

		while start <= end:
				if temp[start] is True:
						in_prime.append(__SCREAMING_SNAKE_CASE )
						for i in range(start * start			,     end + 1			,     __SCREAMING_SNAKE_CASE ):
								UpperCAmelCase_						=				False
				start += 1
		prime += in_prime

		UpperCAmelCase_						=				end + 1
		UpperCAmelCase_						=				min(2 * end			,     __SCREAMING_SNAKE_CASE )

		while low <= n:
				UpperCAmelCase_						=				[True] * (high - low + 1)
				for each in in_prime:
						UpperCAmelCase_						=				math.floor(low / each ) * each
						if t < low:
								t += each

						for j in range(__SCREAMING_SNAKE_CASE			,     high + 1			,     __SCREAMING_SNAKE_CASE ):
								UpperCAmelCase_						=				False

				for j in range(len(__SCREAMING_SNAKE_CASE ) ):
						if temp[j] is True:
								prime.append(j + low )

				UpperCAmelCase_						=				high + 1
				UpperCAmelCase_						=				min(high + end			,     __SCREAMING_SNAKE_CASE )

		return prime

print(sieve(10**6))

