How to tell if tensorflow is using gpu acceleration from inside python shell?

Question

I have installed tensorflow in my ubuntu 16.04 using the second answer here with ubuntu's builtin apt cuda installation.

Now my question is how can I test if tensorflow is really using gpu? I have a gtx 960m gpu. When I import tensorflow this is the output

I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally

Is this output enough to check if tensorflow is using gpu ?

Answer 1

No, I don't think "open CUDA library" is enough to tell, because different nodes of the graph may be on different devices.

To find out which device is used, you can enable log device placement like this:

sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))

Check your console for this type of output.