code: def get_gpu_usage(device=None):
      r"""Return the reserved memory and total memory of given device in a string.
      Args:
          device: cuda.device. It is the device that the model run on.
  
      Returns:
          str: it contains the info about reserved memory and total memory of given device.
      """
  
      reserved = torch.cuda.max_memory_reserved(device) / 1024**3
      total = (
          torch.cuda.get_device_properties(device).total_memory
          / 1024**3
      )
  
      return "{:.2f} G/{:.2f} G".format(reserved, total)
  
imports: import datetime
  import importlib
  import os
  import random
  import pandas
  import numpy
  import torch
  import torch.nn
  from torch.utils.tensorboard import SummaryWriter
  from texttable import Texttable
  from recbole.utils.enum_type import ModelType
label_desc: Use image node_id 10 for calling a global function with example usage: get_gpu_usage(device) and returns: str