code: def _device_count_nvml() -> int:
      """Return number of devices as reported by NVML taking CUDA_VISIBLE_DEVICES into account.
  
      Negative value is returned if NVML discovery or initialization has failed.
  
      """
      visible_devices = _parse_visible_devices()
      if not visible_devices:
          return 0
      try:
          if isinstance(visible_devices[0], str):
              # Skip MIG parsing
              if visible_devices[0].startswith("MIG-"):
                  return -1
              uuids = _raw_device_uuid_nvml()
              if uuids is None:
                  return -1
              visible_devices = _transform_uuid_to_ordinals(
                  cast(List[str], visible_devices), uuids
              )
          else:
              raw_cnt = _raw_device_count_nvml()
              if raw_cnt <= 0:
                  return raw_cnt
              # Trim the list up to a maximum available device
              for idx, val in enumerate(visible_devices):
                  if cast(int, val) >= raw_cnt:
                      return idx
      except (OSError, AttributeError):
          return -1
      return len(visible_devices)
  
imports: import os
  import warnings
  from contextlib import contextmanager
  from functools import lru_cache
  from typing import Generator, List, Optional, Union, cast
  import torch
  from typing_extensions import override
  from lightning.fabric.accelerators.accelerator import Accelerator
  from lightning.fabric.accelerators.registry import _AcceleratorRegistry
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.fabric.utilities.rank_zero import rank_zero_info
label_desc: Use image node_id 10 for calling a global function with example usage: _device_count_nvml() and returns: len, int, unknown, unknown, unknown, raw_cnt, idx