• numpy
• scipy
• pandas
• matplotlib
• seaborn
• tensorflow
• sklearn
• pillow
• wave

Preparing the PC for Tensorflow

Setting up a virtual Python environment

The procedure is described in https://www.freecodecamp.org/news/virtualenv-with-virtualenvwrapper-on-ubuntu-18-04.

Once his is done you can create a new virtual environment with:

mkvirtualenv name_of_env (e.g. mkvirtualenv AI)

switch to a virtual environment with the "workon" command:

e.g. workon AI

Setting up the GPU

When trying my first simple TensorFlow program I saw this warning:

My PC, being a "gaming machine", uses an nVIDIA GeForce GTX 950M graphics card whose GPU (Graphics Processing Unit) can be used by TensorFlow to speed up number crunching.

TensorFlow relies on the cuda toolkit and on the NVidia display driver. I had difficulties to install these with the .deb files but succeeded to do so using the .run file.

To run the installer script I had to boot into single user mode, avoiding to start the desktop system. This can be done typing "e" at the boot screen and adding "single" to the boot command.

In the "Additional Drivers" tab of the Software & Updates program you see that we are using the manually installed NVidia driver:

When trying a very simple TensorFlow program: #!/usr/bin/python3
import tensorflow as tf
import numpy as np
from tensorflow import keras
model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])])

I get:

-- Uli Raich - 2022-01-31

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