TypeError：无法散列的类型：TensorFlow的feed_dict中的'list'

如何解决TypeError：无法散列的类型：TensorFlow的feed_dict中的'list'

我遇到以下错误：TypeError：不可哈希类型：'list'的以下代码，专门用于：

disc_rewards: discounted_normalized_rewards

此处是代码：

with tf.name_scope('input_'):
  inputs=tf.placeholder(tf.float32,[None,4],name='inputs')
  actions=tf.placeholder(tf.int32,action_size],name='actions')
  disc_rewards=tf.placeholder(tf.float32,],name='disc_rewards')

  fc1=tf.keras.layers.Dense(64,activation='relu')(inputs)
  fc2=tf.keras.layers.Dense(32,activation='relu')(fc1)
  fc3=tf.keras.layers.Dense(16,activation='relu')(fc2)
  fc4=tf.keras.layers.Dense(action_size,activation='softmax')(fc3)
  out=tf.nn.softmax(fc4)
  loss=tf.nn.softmax_cross_entropy_with_logits_v2(labels=actions,logits=out)
  weighted_loss=loss*disc_rewards
  final_loss=tf.reduce_mean(weighted_loss)
  trainer=tf.train.AdamOptimizer(0.01).minimize(final_loss)

该tf正在运行：

with tf.Session() as sess:
  sess.run(tf.global_variables_initializer())
  for episode in range(max_episodes):
    total_reward_ep=0
    state=env.reset()
    while True:
      env.render()
      action_prob=sess.run(out,feed_dict={inputs:state.reshape([1,4])})
      action = np.random.choice(range(action_prob.shape[1]),p=action_prob.ravel())
      next_state,reward,done,_=env.step(action)
      action_=np.zeros(action_size)
      action_[action]=1
      states.append(state)
      rewards.append(reward)
      actions.append(action_)
      state=next_state
      if done:
        break
    show_video()
    discounted_normalized_rewards=disc_norm(rewards)
    loss_,_ = sess.run([final_loss,trainer],feed_dict={inputs: np.vstack(np.array(states)),actions: np.vstack(np.array(actions)),disc_rewards: discounted_normalized_rewards 
                                                                })

错误：

     31     loss_,32                                                                  actions: np.vstack(np.array(actions)),---> 33                                                                  disc_rewards: discounted_normalized_rewards
     34                                                                 })
     35     total_reward_ep=np.sum(rewards)

TypeError: unhashable type: 'list'

我尝试了很多事情，但是无法解决此问题。请让我知道我犯了什么错误。谢谢！