code: def installed_cuda_version(name=""):
      import torch.utils.cpp_extension
  
      cuda_home = torch.utils.cpp_extension.CUDA_HOME
      if cuda_home is None:
          raise MissingCUDAException(
              "CUDA_HOME does not exist, unable to compile CUDA op(s)"
          )
      # Ensure there is not a cuda version mismatch between torch and nvcc compiler
      output = subprocess.check_output(
          [cuda_home + "/bin/nvcc", "-V"], universal_newlines=True
      )
      output_split = output.split()
      release_idx = output_split.index("release")
      release = (
          output_split[release_idx + 1].replace(",", "").split(".")
      )
      # Ignore patch versions, only look at major + minor
      cuda_major, cuda_minor = release[:2]
      return int(cuda_major), int(cuda_minor)
  
imports: import os
  import sys
  import time
  import importlib
  from pathlib import Path
  import subprocess
  import shlex
  import shutil
  import tempfile
  import distutils.ccompiler
  import distutils.log
  import distutils.sysconfig
  from distutils.errors import CompileError, LinkError
  from abc import ABC, abstractmethod
  from typing import List
label_desc: Use image node_id 1 for calling a global function with example usage: installed_cuda_version(name) and returns: int,  int