def _CorrectMomentum(self, correction):
        """The MomentumSGDUpdate op implements the update V as

            V := mu * V + lr * grad,

        where mu is the momentum factor, lr is the learning rate, and grad is
        the stochastic gradient. Since V is not defined independently of the
        learning rate (as it should ideally be), when the learning rate is
        changed we should scale the update history V in order to make it
        compatible in scale with lr * grad.
        """
        logger.info(
            'Scaling update history by {:.6f} (new lr / old lr)'.
            format(correction))
        for i in range(cfg.NUM_GPUS):
            with c2_utils.CudaScope(i):
                for param in self.TrainableParams(gpu_id=i):
                    op = core.CreateOperator(
                        'Scale', [param + '_momentum'], [param + '_momentum'],
                        scale=correction)
                    workspace.RunOperatorOnce(op)
The MomentumSGDUpdate op implements the update V as

            V := mu * V + lr * grad,

        where mu is the momentum factor, lr is the learning rate, and grad is
        the stochastic gradient. Since V is not defined independently of the
        learning rate (as it should ideally be), when the learning rate is
        changed we should scale the update history V in order to make it
        compatible in scale with lr * grad.
        
detectron/modeling/detector.py