class_docstr: Keeps track of mean and standard deviation for some value.
code: def add(self, value, n=1):
      self.val = value
      self.sum += value
      self.var += value * value
      self.n += n
  
      if self.n == 0:
          self.mean, self.std = np.nan, np.nan
      elif self.n == 1:
          self.mean = (
              0.0 + self.sum
          )  # This is to force a copy in torch/numpy
          self.std = np.inf
          self.mean_old = self.mean
          self.m_s = 0.0
      else:
          self.mean = self.mean_old + (
              value - n * self.mean_old
          ) / float(self.n)
          self.m_s += (value - self.mean_old) * (value - self.mean)
          self.mean_old = self.mean
          self.std = np.sqrt(self.m_s / (self.n - 1.0))
  
imports: import numpy
  from .None import meter
label_desc: Use image node_id 2 for calling the AverageValueMeter obj's underlying member method code with example usage: obj.add(value, n) without return types