50b8edd467b79d7f649e5e1a6c583a4cd8db17ec,framework/Optimizers/GradientBasedOptimizer.py,GradientBasedOptimizer,evaluateGradient,#GradientBasedOptimizer#Any#Any#,181

Before Change

      opt  = optVarsValues[i*2]      //the latest opt point
      pert = optVarsValues[i*2 + 1] //the perturbed point
      //calculate grad(F) wrt each input variable
      lossDiff = pert["output"] - opt["output"]
      //cover "max" problems
      // TODO it would be good to cover this in the base class somehow, but in the previous implementation this
      //   sign flipping was only called when evaluating the gradient.
      if self.optType == "max":

After Change

      gradArray[var] = np.zeros(2) //why are we initializing to this?
    // Evaluate gradient at each point
    // first, get average opt point
    optOutAvg = np.average(list(optVarsValues[i*2]["output"] for i in range(self.gradDict["numIterForAve"])))
    // then, evaluate gradients
    for i in range(self.gradDict["numIterForAve"]):
      opt  = optVarsValues[i*2]     //the latest opt point
      pert = optVarsValues[i*2 + 1] //the perturbed point

Instances