问题描述
Session.run(fetches, feed_dict)是否保证按顺序执行其fetches自变量?
Is Session.run(fetches, feed_dict) guaranteed to execute its fetches arguments in-order?
文档似乎没有提及它.
例如，如果您运行
sess.run([accuracy, train_op], feed_dict=feed_dict)
执行顺序很重要:train_op将更新影响accuracy的参数.
the order of execution matters: train_op will update parameters affecting accuracy.
推荐答案
否.默认情况下，Tensorflow可以自由评估任何顺序的运算符.由于并发性，该顺序甚至在两次运行之间可能会发生变化.这通常是一件好事，因为这意味着Tensorflow可能会充分利用可用的硬件.如果您的代码突变状态(例如变量)，则可能会出现问题.
No. By default, Tensorflow is free to evaluate operators in any order. Because of concurrency, that order may even change between runs. This is usually a good thing because it means that Tensorflow may make optimal use of the available hardware. It can be problematic if your code mutates state such as Variables.
但是，如果出于某种原因您希望控制评估的顺序，通常可以使用控件依赖项来强制运算符之间的顺序.控件依赖项记录在这里:
However, if for some reason you do wish to control the order of evaluation, in general you can use control dependencies to enforce an order between operators. Control dependencies are documented here:
https://www.tensorflow.org/api_docs/python/tf/Graph#control_dependencies
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