
from __future__ import annotations

from collections.abc import Generator



def 	UpperCamelCase   (							):
					'''simple docstring'''
					lowercase						     =						{}
					lowercase						     =						2
					while True:
										lowercase						     =						factor_map.pop(lowerCAmelCase__			,      lowerCAmelCase__		)
										if factor:
															lowercase						     =						factor + prime
															while x in factor_map:
																				x += factor
															lowercase						     =						factor
										else:
															lowercase						     =						prime
															yield prime
										prime += 1



def 	UpperCamelCase   (							lowerCAmelCase__ = 1E10		):
					'''simple docstring'''
					lowercase						     =						sieve()

					lowercase						     =						1
					while True:
										lowercase						     =						next(lowerCAmelCase__		)
										if (2 * prime * n) > limit:
															return n
										# Ignore the next prime as the reminder will be 2.
										next(lowerCAmelCase__		)
										n += 2


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






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__		:Dict			  =   {
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[str]			  =   [
							    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "LukeForEntityClassification",
							    "LukeForEntityPairClassification",
							    "LukeForEntitySpanClassification",
							    "LukeForMultipleChoice",
							    "LukeForQuestionAnswering",
							    "LukeForSequenceClassification",
							    "LukeForTokenClassification",
							    "LukeForMaskedLM",
							    "LukeModel",
							    "LukePreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
							from .tokenization_luke import LukeTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_luke import (
														    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LukeForEntityClassification,
														    LukeForEntityPairClassification,
														    LukeForEntitySpanClassification,
														    LukeForMaskedLM,
														    LukeForMultipleChoice,
														    LukeForQuestionAnswering,
														    LukeForSequenceClassification,
														    LukeForTokenClassification,
														    LukeModel,
														    LukePreTrainedModel,
														)

else:
							import sys

							lowercase__		:Tuple			  =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




