Python 提要的值不能是tf.Tensor对象

我正在尝试读取cifar10数据集并将其用于训练模型，因此我尝试读取批并按如下方式运行会话：

 # Optimizer
    opt = tf.train.AdamOptimizer(0.0001)
    global_step = tf.get_variable('global_step', initializer=tf.constant(0), trainable=False)
    train_op = opt.apply_gradients(zip(grads, var_list), global_step=global_step)

    (x_train, y_train), (x_test, y_test) = keras.datasets.cifar10.load_data()

    image_batch, label_batch = tf.train.batch([x_train, y_train], batch_size=batch_size)
    #image_batch_uint8 = tf.cast(image_batch, tf.uint8)

    # Train
    with tf.Session() as sess:

        coord = tf.train.Coordinator()
        threads = tf.train.start_queue_runners(sess=sess, coord=coord)

        sess.run(tf.global_variables_initializer())
        for i in range(10000000):
            _loss_value, _reward_value, _ = sess.run([loss, reward, train_op], feed_dict={
                images_ph: image_batch,
                labels_ph: label_batch
            })
            if i % 100 == 0:
                print('iter: ', i, '\tloss: ', _loss_value, '\treward: ', _reward_value)

但是我得到了这个错误：

 File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 900, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1086, in _run
    'feed with key ' + str(feed) + '.')
The value of a feed cannot be a tf.Tensor object. Acceptable feed values include Python scalars, strings, lists, numpy ndarrays, or TensorHandles.For reference, the tensor object was Tensor("batch:0", shape=(32, 50000, 32, 32, 3), dtype=uint8) which was passed to the feed with key Tensor("Placeholder:0", shape=(?, 1024), dtype=float32).

---

我做错了什么？我不确定错误是什么。

image\u batch

和

label\u batch

是tf.tensor（不是numpy数组）。使用

feed\u dict

馈送数据时，只能馈送numpy数组/列表。非常感谢！然而，使用tf.train.batch时，我总是会得到张量，我看不到一种将它们转换为numpy数组的简单方法。你有什么建议吗？看来我需要开个会？有没有更好的方法来获取批处理，那么我想知道，如果你看到它将被弃用。所以我建议您使用，

tf.data

。