class_docstr: maintains an exponential moving average
code: def __call__(self):
      if self.num_updates() > self.valid_after:
          return self.f_ma[-1]
      else:
          return np.nan
  
file_path: nni/nni/algorithms/feature_engineering/gradient_selector/utils.py
imports: import numpy
label_desc: Use image node_id 6 for calling the EMA obj's underlying member method code with example usage: obj.__call__() and returns: self, np