a295cb67923eeb5ab5390f1541c04e70f67e893a,src/garage/tf/regressors/bernoulli_mlp_regressor.py,BernoulliMLPRegressor,fit,#BernoulliMLPRegressor#Any#Any#,126

Before Change

        if self.normalize_inputs:
            // recompute normalizing constants for inputs
            new_mean = np.mean(xs, axis=0, keepdims=True)
            new_std = np.std(xs, axis=0, keepdims=True) + 1e-8
            tf.compat.v1.get_default_session().run(
                tf.group(
                    tf.compat.v1.assign(self.x_mean_var, new_mean),
                    tf.compat.v1.assign(self.x_std_var, new_std),
                ))
            // self._x_mean_var.set_value(np.mean(xs, axis=0, keepdims=True))
            // self._x_std_var.set_value(
            //     np.std(xs, axis=0, keepdims=True) + 1e-8)
        if self.use_trust_region and self.first_optimized:

After Change

            // recompute normalizing constants for inputs
            self.model.networks["default"].x_mean.load(
                np.mean(xs, axis=0, keepdims=True))
            self.model.networks["default"].x_std.load(
                np.std(xs, axis=0, keepdims=True) + 1e-8)

        if self._use_trust_region and self._first_optimized:
            // To use trust region constraint and optimizer
            old_prob = self._f_prob(xs)

Instances