tensorflow


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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