a9ae9989261da6aa85e452ace0c9915fe7c90d22,src/garage/tf/baselines/gaussian_cnn_baseline.py,GaussianCNNBaseline,fit,#GaussianCNNBaseline#Any#,256

Before Change

            // recompute normalizing constants for outputs
            self._y_mean.load(np.mean(ys, axis=0, keepdims=True))
            self._y_std.load(np.std(ys, axis=0, keepdims=True) + 1e-8)
        if self._use_trust_region:
            old_means, old_log_stds = self._f_pdists(xs)
            inputs = [xs, ys, old_means, old_log_stds]
        else:
            inputs = [xs, ys]
        loss_before = self._optimizer.loss(inputs)
        tabular.record("{}/LossBefore".format(self._name), loss_before)
        self._optimizer.optimize(inputs)
        loss_after = self._optimizer.loss(inputs)

After Change

            // recompute normalizing constants for outputs
            self._y_mean.load(np.mean(ys, axis=0, keepdims=True))
            self._y_std.load(np.std(ys, axis=0, keepdims=True) + 1e-8)
            self._old_network.y_mean.load(np.mean(ys, axis=0, keepdims=True))
            self._old_network.y_std.load(
                np.std(ys, axis=0, keepdims=True) + 1e-8)
        inputs = [xs, ys]
        loss_before = self._optimizer.loss(inputs)
        tabular.record("{}/LossBefore".format(self._name), loss_before)

Instances