Method GetCUDADeviceInfo

Modules/PythonSegmentation/src/mitknnInteractiveTool.cpp:758–800

}

bool mitk::nnInteractiveTool::GetCUDADeviceInfo(CUDADeviceInfo& info) const
{
  auto prefs = GetPreferences();
  const auto gpuBackend = prefs->Get("nnInteractive/gpuBackend", "cuda:0");
  auto cudaDevice = parseCUDADevice(gpuBackend);

  if (!cudaDevice.has_value())
    return false;

  std::ostringstream pyCommands; pyCommands
    << "import torch\n"
    << "is_cuda_available = False\n"
    << "try:\n"
    << "    if torch.cuda.is_available():\n"
    << "        name = torch.cuda.get_device_name(" << cudaDevice.value() << ")\n"
    << "        props = torch.cuda.get_device_properties(" << cudaDevice.value() << ")\n"
    << "        total_memory_mb = props.total_memory // (1024 ** 2)\n"
    << "        major = props.major\n"
    << "        minor = props.minor\n"
    << "        is_cuda_available = True\n"
    << "except Exception:\n"
    << "    pass\n";

  try
  {
    auto pythonContext = m_Impl->GetPythonContext();
    pythonContext->Execute(pyCommands.str());

    if (!pythonContext->GetVariableAsBool("is_cuda_available").value_or(false))
      return false;

    info.Name = pythonContext->GetVariableAsString("name").value_or("");
    info.TotalMemoryMB = pythonContext->GetVariableAsInt("total_memory_mb").value_or(0);
    info.Major = pythonContext->GetVariableAsInt("major").value_or(0);
    info.Minor = pythonContext->GetVariableAsInt("minor").value_or(0);

    return true;
  }
  catch (...)
  {
    return false;
  }
}

void mitk::nnInteractiveTool::StartSession()
{