import tensorflow as tf

                                    self.grads_and_vars, global_step=tf.contrib.framework.get_global_step())

    def predict(self, state, sess=None):
        sess = sess or tf.get_default_session()
        state=featurize_state(state);
        return sess.run(self.action, { self.state: [state] })[0]
