aaa6b9c9c0a803153ae26a3b28fe2c7fbf3e75fe,paysage/metrics.py,EnergyGap,update,#EnergyGap#,239

Before Change

        self.norm += 1
        self.energy_gap += be.mean(update_args.model
                                   .joint_energy(update_args.minibatch))
        self.energy_gap -= be.mean(update_args.model
                                   .joint_energy(update_args.random_samples))

    def value(self):
        
        Get the value of the energy gap.

After Change

        
        self.calc.reset()

    def update(self, update_args: MetricState) -> None:
        
        Update the estimate for the energy gap using a batch
        of observations and a batch of fantasy particles.

        Args:
            update_args: uses all layers of minibatch and random_samples, and model

        Returns:
            None

        
        energy_data = update_args.model.joint_energy(update_args.minibatch)
        energy_random = update_args.model.joint_energy(update_args.random_samples)
        self.calc.update(energy_data)
        self.calc.update(-energy_random)

    def value(self):
        
        Get the value of the energy gap.

Instances