这是重复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的玩具代码。
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)
跟踪看起来像:
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)]]
最佳答案
这是由生成器的错误实例化引起的。
该错误是由于 makeRand() 耗尽了要产生的元素而引起的。通过将其更改为以下内容可以解决此问题:
def makeRand():
while True:
yield np.random.rand(1)
关于python - TensorFlow 数据集 API from_generator 序列结束错误,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/47519104/