docstr: Return the avergage val from the list of vals filtered to remove 2
  std-deviations from the original average.
docstr_tok: ["Return","the","avergage","val","from","the","list","of","vals","filtered","to","remove","2","std-deviations","from","the","original","average","."]
code: def __computeValue(self, vals):
      """
      Return the avergage val from the list of vals filtered to remove 2
      std-deviations from the original average.
      """
      avg = np.mean(vals)
      std = np.std(vals)
      filtered = [
          x
          for x in vals
          if ((avg - (2 * std)) <= x <= (avg + (2 * std)))
      ]
      if len(filtered) != len(vals):
          print("filtered outliers: %s" % (set(vals) - set(filtered)))
  
      return np.average(filtered)
  
imports: from time import clock_gettime, CLOCK_MONOTONIC_RAW
  import numpy
  from gpu_metric_poller import startGpuMetricPolling, stopGpuMetricPolling
label_desc: Use image node_id 3 for calling the Benchmark obj's underlying member method code with example usage: obj.__computeValue(vals) and returns: np