class_docstr: Accelerator for NVIDIA CUDA devices.
class_docstr_tok: ["Accelerator","for","NVIDIA","CUDA","devices","."]
docstr: Get the devices when set to auto.
docstr_tok: ["Get","the","devices","when","set","to","auto","."]
code: def auto_device_count() -> int:
      """Get the devices when set to auto."""
      return num_cuda_devices()
  
imports: import logging
  import os
  import shutil
  import subprocess
  from typing import Any, Dict, List, Optional, Union
  import torch
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.accelerators import _AcceleratorRegistry
  from lightning.fabric.accelerators.cuda import _check_cuda_matmul_precision, _clear_cuda_memory, num_cuda_devices
  from lightning.fabric.utilities.device_parser import _parse_gpu_ids
  from lightning.fabric.utilities.types import _DEVICE
  from lightning.pytorch.accelerators.accelerator import Accelerator
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
label_desc: Use image node_id 8 for calling the CUDAAccelerator obj's underlying member method code with example usage: obj.auto_device_count() and returns: num_cuda_devices