这是我的代码。
import tensorflow as tf
a=tf.Variable(tf.constant([0,1,2],dtype=tf.int32))
b=tf.Variable(tf.constant([1,1,1],dtype=tf.int32))
recall=tf.metrics.recall(b,a)
init=tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
rec=sess.run(recall)
print(rec)
我尝试测试tf.metrics.precision并收到以下错误消息。
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value recall/true_positives/count
[[Node: recall/true_positives/count/read = Identity[T=DT_FLOAT, _class=["loc:@recall/true_positives/count"], _device="/job:localhost/replica:0/task:0/gpu:0"](recall/true_positives/count)]]
[[Node: recall/value/_15 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_73_recall/value", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
您还需要初始化隐藏在tf.metrics.recall方法中的局部变量。
例如，这段代码可以工作：
init_g = tf.global_variables_initializer()
init_l = tf.local_variables_initializer()
with tf.Session() as sess:
sess.run(init_g)
sess.run(init_l)
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我来说两句