以下是一个玩具代码，用于复制我在尝试使用生成器动态生成/提供训练数据时遇到的问题。

def makeRand():    yield np.random.rand(1)dataset = tf.data.Dataset.from_generator(makeRand, (tf.float32))iterator = tf.contrib.data.Iterator.from_structure(tf.float32, tf.TensorShape([]))next_x = iterator.get_next()init_op = iterator.make_initializer(dataset)with tf.Session() as sess:    sess.run(init_op)    a = sess.run(next_x)    print(a)    a = sess.run(next_x)    print(a)

错误追踪如下：

Traceback (most recent call last):  File “test_iterator_gen.py", line 31, in <module>    a = sess.run(next_x) tensorflow.python.framework.errors_impl.OutOfRangeError: End of sequence     [[Node: IteratorGetNext = IteratorGetNext[output_shapes=[[]], output_types=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](Iterator)]]Caused by op 'IteratorGetNext', defined at:  File "test_iterator_gen.py", line 23, in <module>    next_x = iterator.get_next()OutOfRangeError (see above for traceback): End of sequence     [[Node: IteratorGetNext = IteratorGetNext[output_shapes=[[]], output_types=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](Iterator)]]

回答：

这个问题是由生成器的错误实例化引起的。

错误是由 makeRand() 函数耗尽可yield元素引起的。通过将其更改为以下代码可以解决这个问题：

def makeRand():   while True:      yield np.random.rand(1)