import tensorflow as tf

        if full_tensorboard_log:
            tf.summary.histogram('rewards', rew_t_ph)
            tf.summary.histogram('importance_weights', importance_weights_ph)
            if tf_util.is_image(obs_phs[0]):
                tf.summary.image('observation', obs_phs[0])
            elif len(obs_phs[0].shape) == 1:
                tf.summary.histogram('observation', obs_phs[0])

    optimize_expr = optimizer.apply_gradients(gradients)

    summary = tf.summary.merge_all()

