class_docstr: The standalone GPU usage metric.
  Important: this metric approximates the real maximum GPU percentage
  usage since it sample at discrete amount of time the GPU values.
  
  Instances of this metric keeps the maximum GPU usage percentage detected.
  The `start_thread` method starts the usage tracking.
  The `stop_thread` method stops the tracking.
  
  The result, obtained using the `result` method, is the usage in mega-bytes.
  
  The reset method will bring the metric to its initial state. By default
  this metric in its initial state will return an usage value of 0.
class_docstr_tok: ["The","standalone","GPU","usage","metric",".","Important",":","this","metric","approximates","the","real","maximum","GPU","percentage","usage","since","it","sample","at","discrete","amount","of","time","the","GPU","values",".","Instances","of","this","metric","keeps","the","maximum","GPU","usage","percentage","detected",".","The","`","start_thread","`","method","starts","the","usage","tracking",".","The","`","stop_thread","`","method","stops","the","tracking",".","The","result",",","obtained","using","the","`","result","`","method",",","is","the","usage","in","mega-bytes",".","The","reset","method","will","bring","the","metric","to","its","initial","state",".","By","default","this","metric","in","its","initial","state","will","return","an","usage","value","of","0","."]
code: def update(self):
      pass
  
imports: import GPUtil
  from threading import Thread
  import time
  import warnings
  from typing import Optional, TYPE_CHECKING, List
  from avalanche.evaluation import Metric, PluginMetric, GenericPluginMetric
  from avalanche.evaluation.metric_results import MetricResult
label_desc: Use image node_id 7 for calling the MaxGPU obj's underlying member method code with example usage: obj.update() without return types