





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__UpperCamelCase     :						Tuple						       =  {
    '''configuration_rag''': ['''RagConfig'''],
    '''retrieval_rag''': ['''RagRetriever'''],
    '''tokenization_rag''': ['''RagTokenizer'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase     :						Optional[int]						       =  [
           '''RagModel''',
           '''RagPreTrainedModel''',
           '''RagSequenceForGeneration''',
           '''RagTokenForGeneration''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase     :						Tuple						       =  [
           '''TFRagModel''',
           '''TFRagPreTrainedModel''',
           '''TFRagSequenceForGeneration''',
           '''TFRagTokenForGeneration''',
       ]


if TYPE_CHECKING:
       from .configuration_rag import RagConfig
       from .retrieval_rag import RagRetriever
       from .tokenization_rag import RagTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_rag import (
                  TFRagModel,
                  TFRagPreTrainedModel,
                  TFRagSequenceForGeneration,
                  TFRagTokenForGeneration,
              )

else:
       import sys

       __UpperCamelCase     :						List[str]						       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







"""simple docstring"""




from __future__ import annotations

import math



def 							_lowerCamelCase			(			__a     ):

		if num <= 0:
				SCREAMING_SNAKE_CASE_    			=			F'{num}: Invalid input, please enter a positive integer.'
				raise ValueError(__a     )

		SCREAMING_SNAKE_CASE_    			=			[True] * (num + 1)
		SCREAMING_SNAKE_CASE_    			=			[]
		SCREAMING_SNAKE_CASE_    			=			2
		SCREAMING_SNAKE_CASE_    			=			int(math.sqrt(__a     )     )

		while start <= end:
				# If start is a prime
				if sieve[start] is True:
						prime.append(__a     )

						# Set multiples of start be False
						for i in range(start * start,				num + 1,				__a     ):
								if sieve[i] is True:
										SCREAMING_SNAKE_CASE_    			=			False

				start += 1

		for j in range(end + 1,				num + 1     ):
				if sieve[j] is True:
						prime.append(__a     )

		return prime


if __name__ == "__main__":
						print(prime_sieve(int(input('Enter a positive integer: ').strip())))