python - Is it thread-safe when using tf.Session in inference service?

Question

Now we have used TensorFlow to train and export an model. We can implement the inference service with this model just like how tensorflow/serving does.

I have a question about whether the tf.Session object is thread-safe or not. If it's true, we may initialize the object after starting and use the singleton object to process the concurrent requests.

Answer 1

The tf.Session object is thread-safe for Session.run() calls from multiple threads.

Before TensorFlow 0.10 graph modification was not thread-safe. This was fixed in the 0.10 release, so you can add nodes to the graph concurrently with Session.run() calls, although this is not advised for performance reasons; instead, it is recommended to call sess.graph.finalize() before using the session from multiple threads, to prevent accidental memory leaks.