code: def wmape(actual, prediction):
      filtered = np.abs(actual) > EPS
      actual = actual[filtered]
      prediction = prediction[filtered]
      weights = np.abs(actual) / np.sum(np.abs(actual))
      return np.sum(weights * np.abs((actual - prediction) / actual))
  
file_path: orbit/orbit/diagnostics/metrics.py
imports: import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: wmape(actual, prediction) and returns: np