class_docstr: Accelerator for NVIDIA CUDA devices.
class_docstr_tok: ["Accelerator","for","NVIDIA","CUDA","devices","."]
code: def is_available() -> bool:
      return num_cuda_devices() > 0
  
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 9 for calling the CUDAAccelerator obj's underlying member method code with example usage: obj.is_available() and returns: unknown