code: def _pynvml_handles():
      count = device_get_count()
      if NVML_STATE == NVMLState.DISABLED_PYNVML_NOT_AVAILABLE:
          raise RuntimeError(
              "NVML monitoring requires PyNVML and NVML to be installed"
          )
      elif NVML_STATE == NVMLState.DISABLED_LIBRARY_NOT_FOUND:
          raise RuntimeError("PyNVML is installed, but NVML is not")
      elif NVML_STATE == NVMLState.DISABLED_WSL_INSUFFICIENT_DRIVER:
          raise RuntimeError(
              "Outdated NVIDIA drivers for WSL, please upgrade to "
              f"{MINIMUM_WSL_VERSION} or newer"
          )
      elif NVML_STATE == NVMLState.DISABLED_CONFIG:
          raise RuntimeError(
              "PyNVML monitoring disabled by 'distributed.diagnostics.nvml' "
              "config setting"
          )
      elif count == 0:
          raise RuntimeError("No GPUs available")
      else:
          try:
              gpu_idx = next(
                  map(
                      int,
                      os.environ.get("CUDA_VISIBLE_DEVICES", "").split(
                          ","
                      ),
                  )
              )
          except ValueError:
              # CUDA_VISIBLE_DEVICES is not set, take first device
              gpu_idx = 0
          return pynvml.nvmlDeviceGetHandleByIndex(gpu_idx)
  
imports: from __future__ import annotations
  import os
  from enum import IntEnum, auto
  from platform import uname
  from typing import NamedTuple
  from packaging.version import parse
  import dask
label_desc: Use image node_id 5 for calling a global function with example usage: _pynvml_handles() and returns: pynvml