0e6f7cea4abae753c8e496bbbe6465af6818ad92,tensorforce/models/distribution_model.py,DistributionModel,tf_regularization_losses,#DistributionModel#Any#Any#,149

Before Change

            losses["network"] = network_loss

        if any(distribution.regularization_loss() is not None for distribution in self.distributions.values()):
            losses["distributions"] = tf.add_n(inputs=[
                distribution.regularization_loss() for distribution in self.distributions.values()
                if distribution.regularization_loss() is not None
            ])

        if self.entropy_regularization is not None and self.entropy_regularization > 0.0:
            entropies = list()
            embedding = self.network.apply(x=states, internals=internals)

After Change

                if "distributions" in losses:
                    losses["distributions"] += regularization_loss
                else:
                    losses["distributions"] = regularization_loss

        if self.entropy_regularization is not None and self.entropy_regularization > 0.0:
            entropies = list()

Instances