"""simple docstring"""






from typing import TYPE_CHECKING

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


__lowerCAmelCase					: Optional[Any]        ={
    """configuration_bridgetower""": [
        """BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BridgeTowerConfig""",
        """BridgeTowerTextConfig""",
        """BridgeTowerVisionConfig""",
    ],
    """processing_bridgetower""": ["""BridgeTowerProcessor"""],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCAmelCase					: Optional[Any]        =["""BridgeTowerImageProcessor"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCAmelCase					: Union[str, Any]        =[
           """BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """BridgeTowerForContrastiveLearning""",
           """BridgeTowerForImageAndTextRetrieval""",
           """BridgeTowerForMaskedLM""",
           """BridgeTowerModel""",
           """BridgeTowerPreTrainedModel""",
       ]


if TYPE_CHECKING:
       from .configuration_bridgetower import (
           BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
           BridgeTowerConfig,
           BridgeTowerTextConfig,
           BridgeTowerVisionConfig,
       )
       from .processing_bridgetower import BridgeTowerProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_bridgetower import BridgeTowerImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_bridgetower import (
                  BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BridgeTowerForContrastiveLearning,
                  BridgeTowerForImageAndTextRetrieval,
                  BridgeTowerForMaskedLM,
                  BridgeTowerModel,
                  BridgeTowerPreTrainedModel,
              )


else:
       import sys

       __lowerCAmelCase					: Dict        =_LazyModule(__name__, globals()["""__file__"""], _import_structure)




"""simple docstring"""






from __future__ import annotations

import math


def     UpperCAmelCase__ (       lowerCAmelCase__  :int	)				->					list[int]:
      '''simple docstring'''


      if num <= 0:
            lowercase														=			f'{num}: Invalid input, please enter a positive integer.'
            raise ValueError(lowerCAmelCase__	)

      lowercase														=			[True] * (num + 1)
      lowercase														=			[]
      lowercase														=			2
      lowercase														=			int(math.sqrt(lowerCAmelCase__	)	)

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

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

            start += 1

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

      return prime


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



