遍历tf.data.Dataset的高效方法

import tensorflow as tf

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3, 4, 5])
iterator = dataset.make_one_shot_iterator()
next_element = iterator.get_next()

with tf.Session() as sess:
    try:
        while True:
            value = sess.run(next_element)
            print(value)
    except tf.errors.OutOfRangeError:
        pass

import tensorflow as tf

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3, 4, 5])
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()

with tf.Session() as sess:
    sess.run(iterator.initializer)
    try:
        while True:
            value = sess.run(next_element)
            print(value)
    except tf.errors.OutOfRangeError:
        pass

import tensorflow as tf

dataset1 = tf.data.Dataset.from_tensor_slices([1, 2, 3, 4, 5])
dataset2 = tf.data.Dataset.from_tensor_slices([6, 7, 8, 9, 10])
combined_dataset = tf.data.experimental.sample_from_datasets([dataset1, dataset2])
iterator = combined_dataset.make_initializable_iterator()
next_element = iterator.get_next()

with tf.Session() as sess:
    # 遍历dataset1
    sess.run(iterator.initializer)
    try:
        while True:
            value = sess.run(next_element)
            print(value)
    except tf.errors.OutOfRangeError:
        pass

    # 遍历dataset2
    sess.run(iterator.initializer)
    try:
        while True:
            value = sess.run(next_element)
            print(value)
    except tf.errors.OutOfRangeError:
        pass