


'''simple docstring'''


import argparse
import os


_UpperCamelCase          =     {
    """pytorch""": {
        """1.13""": {
            """torch""": """1.13.1""",
            """torchvision""": """0.14.1""",
            """torchaudio""": """0.13.1""",
            """python""": 3.9,
            """cuda""": """cu116""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu116"""
            ),
            """base_image""": """nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.12""": {
            """torch""": """1.12.1""",
            """torchvision""": """0.13.1""",
            """torchaudio""": """0.12.1""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.11""": {
            """torch""": """1.11.0""",
            """torchvision""": """0.12.0""",
            """torchaudio""": """0.11.0""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.10""": {
            """torch""": """1.10.2""",
            """torchvision""": """0.11.3""",
            """torchaudio""": """0.10.2""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        """1.9""": {
            """torch""": """1.9.1""",
            """torchvision""": """0.10.1""",
            """torchaudio""": """0.9.1""",
            """python""": 3.9,
            """cuda""": """cu111""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu111"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
    },
    """tensorflow""": {
        """2.11""": {
            """tensorflow""": """2.11.1""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.11.1""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.10""": {
            """tensorflow""": """2.10.1""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.10.1""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.9""": {
            """tensorflow""": """2.9.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.9.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.8""": {
            """tensorflow""": """2.8.2""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.8.2""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.7""": {
            """tensorflow""": """2.7.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.7.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.6""": {
            """tensorflow""": """2.6.5""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.6.5""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.5""": {
            """tensorflow""": """2.5.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.5.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
    },
}


if __name__ == "__main__":
      _UpperCamelCase          =     argparse.ArgumentParser("""Choose the framework and version to install""")
      parser.add_argument(
          """--framework""", help="""The framework to install. Should be `torch` or `tensorflow`""", type=str, required=True
      )
      parser.add_argument("""--version""", help="""The version of the framework to install.""", type=str, required=True)
      _UpperCamelCase          =     parser.parse_args()

      _UpperCamelCase          =     past_versions_testing[args.framework][args.version]

      os.system(F"""echo \"export INSTALL_CMD=\'{info['install']}\'\" >> ~/.profile""")
      print(F"""echo \"export INSTALL_CMD=\'{info['install']}\'\" >> ~/.profile""")

      _UpperCamelCase          =     """"""
      if args.framework == "pytorch":
            _UpperCamelCase          =     info["""cuda"""]
      os.system(F"""echo \"export CUDA='{cuda}'\" >> ~/.profile""")
      print(F"""echo \"export CUDA='{cuda}'\" >> ~/.profile""")





'''simple docstring'''


import math
from collections.abc import Generator


def 		_lowercase   (SCREAMING_SNAKE_CASE       ):




     '''simple docstring'''





     __A  :					Generator						     =       (i for i in range(1					,				(max_n + 1)       ))
     for i in (n for n in numbers if n > 1):
          for j in range(2					,				SCREAMING_SNAKE_CASE       ):
               if (i % j) == 0:
                    break
          else:
               yield i


def 		_lowercase   (SCREAMING_SNAKE_CASE       ):




     '''simple docstring'''





     __A  :					Generator						     =       (i for i in range(1					,				(max_n + 1)       ))
     for i in (n for n in numbers if n > 1):
          # only need to check for factors up to sqrt(i)
          __A  :					Optional[Any]						     =       int(math.sqrt(SCREAMING_SNAKE_CASE       )       ) + 1
          for j in range(2					,				SCREAMING_SNAKE_CASE       ):
               if (i % j) == 0:
                    break
          else:
               yield i


def 		_lowercase   (SCREAMING_SNAKE_CASE       ):




     '''simple docstring'''





     __A  :					Generator						     =       (i for i in range(1					,				(max_n + 1)					,				2       ))
     # It's useless to test even numbers as they will not be prime
     if max_n > 2:
          yield 2  # Because 2 will not be tested, it's necessary to yield it now
     for i in (n for n in numbers if n > 1):
          __A  :					List[str]						     =       int(math.sqrt(SCREAMING_SNAKE_CASE       )       ) + 1
          for j in range(3					,				SCREAMING_SNAKE_CASE					,				2       ):
               # As we removed the even numbers, we don't need them now
               if (i % j) == 0:
                    break
          else:
               yield i


def 		_lowercase   ():




     '''simple docstring'''





     from timeit import timeit

     __A  :					List[str]						     =       "from __main__ import slow_primes, primes, fast_primes"
     print(timeit("slow_primes(1_000_000_000_000)"					,				setup=SCREAMING_SNAKE_CASE					,				number=100_0000       )       )
     print(timeit("primes(1_000_000_000_000)"					,				setup=SCREAMING_SNAKE_CASE					,				number=100_0000       )       )
     print(timeit("fast_primes(1_000_000_000_000)"					,				setup=SCREAMING_SNAKE_CASE					,				number=100_0000       )       )


if __name__ == "__main__":
      _UpperCamelCase          =     int(input("""Calculate primes up to:\n>> """).strip())
      for ret in primes(number):
            print(ret)
      benchmark()

