code: def get_devices():
      """
      Get the appropriate Torch device(s) based on CUDA availability and compatibility.
  
      This function determines the appropriate Torch device(s) to be used for
      computations based on the availability of CUDA and compatible devices. It checks
      if CUDA is available and if the available CUDA devices are compatible according to
      the 'is_cuda_compatible()' function. If compatible devices are found, the function
      selects either the first available CUDA device or a randomly selected one based on
      the 'RANDOM_GPU' environment variable. If CUDA is not available or no compatible
      devices are found, the function returns the CPU device.
  
      Returns:
          Tuple: A tuple containing the selected Torch device and the number of available
          devices.
      Example:
          >>> device, num_devices = get_devices()
          >>> print(device)
          cuda:0
          >>> print(num_devices)
          1
      """
      if torch.cuda.is_available() and is_cuda_compatible():
          device_str = "cuda"
          available_devices = torch.cuda.device_count()
  
          if available_devices > 1:
              if os.environ.get("RANDOM_GPU", False) in [
                  "1",
                  "true",
                  "True",
                  True,
                  1,
              ]:
                  device_str = "cuda:" + str(
                      randint(0, available_devices - 1)
                  )
                  available_devices = 1
      else:
          device_str = "cpu"
          available_devices = 0
  
      return torch.device(device_str), available_devices
  
imports: import torch
  import os
  from random import randint
  from torch.cuda import device_count, get_device_capability
label_desc: Use image node_id 2 for calling a global function with example usage: get_devices() and returns: torch,  available_devices