





"""simple docstring"""





import math


def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		int     ):







      '''simple docstring'''




      lowerCAmelCase    		=			[]
      lowerCAmelCase    		=			2
      lowerCAmelCase    		=			int(math.sqrt(__lowercase     )     )  # Size of every segment
      lowerCAmelCase    		=			[True] * (end + 1)
      lowerCAmelCase    		=			[]

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

      lowerCAmelCase    		=			end + 1
      lowerCAmelCase    		=			min(2 * end				,		__lowercase     )

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

                  for j in range(__lowercase				,		high + 1				,		__lowercase     ):
                        lowerCAmelCase    		=			False

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

            lowerCAmelCase    		=			high + 1
            lowerCAmelCase    		=			min(high + end				,		__lowercase     )

      return prime






print(sieve(10**6))














from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCamelCase			:	Any								={
    'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCamelCase			:	Optional[Any]								=[
	    'MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'MegatronBertForCausalLM',
	    'MegatronBertForMaskedLM',
	    'MegatronBertForMultipleChoice',
	    'MegatronBertForNextSentencePrediction',
	    'MegatronBertForPreTraining',
	    'MegatronBertForQuestionAnswering',
	    'MegatronBertForSequenceClassification',
	    'MegatronBertForTokenClassification',
	    'MegatronBertModel',
	    'MegatronBertPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_megatron_bert import (
		    MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MegatronBertForCausalLM,
		    MegatronBertForMaskedLM,
		    MegatronBertForMultipleChoice,
		    MegatronBertForNextSentencePrediction,
		    MegatronBertForPreTraining,
		    MegatronBertForQuestionAnswering,
		    MegatronBertForSequenceClassification,
		    MegatronBertForTokenClassification,
		    MegatronBertModel,
		    MegatronBertPreTrainedModel,
		)

else:
	import sys

	_UpperCamelCase			:	Optional[int]								=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



