GPU is not used for calculations despite tensorflow-gpu installed
My computer has the following software installed: Anaconda (3), TensorFlow (GPU), and Keras. There are two Anaconda virtual environments - one with TensorFlow for Python 2.7 and one for 3.5, both GPU version, installed according to the TF instructions. (I had a CPU version of TensorFlow installed previously in a separate environment, but I've deleted it.) When I run the following: source activate tensorflow-gpu-3.5 python code.py and check nvidia-smi it shows only 3MiB GPU Memory Usage by Python, so it looks like GPU is not used for calculations. (code.py is a simple deep Q-learning algorithm implemented with Keras) Any ideas what can be going wrong?
A good way to debug these problems is to check which operations have been allocated to which devices. You can check this by passing a configuration parameter to the session: session = tf.Session(config=tf.ConfigProto(log_device_placement=True)) When you run your app, you will see some output indicating which devices are being used. You can find more information here: https://www.tensorflow.org/tutorials/using_gpu
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