FailedPreconditionError while using tensorlfow.metrics.recal

Question

我正在尝试使用tensorlfow.metrics.recall和tensorlfow.metrics.precision但张量流引发了FailedPreconditionError。请注意，我使用了sess.run(tf.global_variables_initializer())

代码如下：

import numpy as np
import tensorflow as tf
y_true = np.array([[1, 1, 0], [0, 1, 1], [0, 0, 1]])
y_pred = np.array([[1, 0, 0], [1, 0, 1], [0, 0, 1]])
predictions = tf.placeholder(tf.int64, shape=[3, 3])
labels = tf.placeholder(tf.int64, shape=[3, 3])
prec = tf.metrics.precision(labels, predictions)
rec = tf.metrics.recall(labels, predictions)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
p, r = sess.run([prec, rec], feed_dict={predictions: y_pred, labels: y_true})
print("precision: {}, recall: {}".format(p, r))

• 张量流版本：1.2.1
• 蟒蛇版本：3.5.2

Answer 1

tf.metrics.precision和tf.metrics.recall内部创建local variable(使用collections=[tf.GraphKeys.LOCAL_VARIABLES]创建的变量(。所以你需要做：sess.run(tf.local_variables_initializer())也是。