import tensorflow as tf

                self.loss_d_rot = self.loss_d + self.weight_rotation_loss_d * self.real_pc_rot_loss
                self.loss_g_rot = self.loss_g + self.weight_rotation_loss_g * self.gen_out_rot_loss
            
            # Compute gradient penalty at interpolated points
            ndims = self.real_pc.get_shape().ndims #(1024, 3)
            alpha = tf.random_uniform(shape=[self.batch_size] + [1] * (ndims - 1), minval=0., maxval=1.)
            differences = self.generator_out - self.real_pc
            interpolates = self.real_pc + (alpha * differences)

            with tf.variable_scope('discriminator') as scope:
