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=Tensorflow 1.9.0 with GPU Installation Log=
'''Important note:'''<br>
Install the version of software/packages strictly according to the instructions provided by Tensorflow. A different version of software, for example CUDA toolkit 9.2 instead of 9.0, might lead to failure in tensorflow. When upgrading tensorflow, do it very carefully. As of July 2018, Tensorflow is [https://github.com/tensorflow/tensorflow/issues/17629 notoriously easy to break] with careless installation. DO NOT attempt to install Tensorflow under your user account. Tensorflow has been installed for all users, and a new local install will interfere with it.
==Synopsis==
Tensorflow was previously installed. In 2018 Summer, a new piece of graphics card was installed on DB Server. Wei and Minh hence-force installed and configured '''tensorflow-gpu 1.9.0 for Python3.6''' for all users of DB Server.
 
===Using Tensorflow===
It is important to know that, on DB Server, Tensorflow-gpu 1.9.0 is installed for ''python3.6'', instead of either the default ''python3'' which is Python 3.5, or the default ''python'' which is Python 2.7 . In case that the system default ''python3'' might be changed, type to find out:
which python3
and
which python3.6
 
A quick test of whether tensorflow-gpu is working for ''python3.6'', type the following into a terminal:"
python3.6 -c "import tensorflow as tf; sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))"
 
This will report back which CPU and GPU devices the tensorflow is using. If there is no information for the GPU device, there is something wrong.
==NVIDIA configuration==

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