====== TensorFlow ======
[[https://www.tensorflow.org|TensorFlow]] is a open-source machine learning framework mainly developed by Google. It can be used for verious machine learning tasks, e.g. deep learning. TensorFlow provides a high level API in python and other languages and is can run on CPUs as well as GPUs.

==== Installing TensorFlow ====
It is recommended to use Anaconda to create a virtual python environment and install the desired version of tensorflow within that environment.
<code bash>
module load anaconda3
source $ANACONDA3_ROOT/etc/profile.d/conda.sh
conda create -n myenv python=3.8.8
conda activate myenv
conda install tensorflow-gpu==2.2.0
</code>
If you do not want to use GPUs simply replace the last line with <code bash>conda install tensorflow==2.2.0</code>

==== Testing the installation ====
To run TensorFlow on GPUs, load the correct modules and submit a job to the gpu partition.
<file bash jobscript.sh>
#!/bin/bash
#SBATCH -p gpu
#SBATCH -t 1
#SBATCH --gpus-per-node 1

module load anaconda3

source $ANACONDA3_ROOT/etc/profile.d/conda.sh
conda activate myenv
 
python tftest.py
</file>

<file python tftest.py>
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
hello = tf.constant('Hello, TensorFlow!')
sess = tf.compat.v1.Session()
print(sess.run(hello))
</file>
And then submit the job using Slurm: <code bash>
sbatch jobscript.sh</code>

The output file should contain
<code>
The output (if any) follows:

b'Hello, TensorFlow!'</code>
and also information about the GPUs selected.

=== Testing CPU only installation ===
If you want to test a CPU only installation, you can just run the tftest.py on a login node.

==== Using TensorFlow ====
You can now use TensorFlow in your python scripts. Please read [[en:services:application_services:high_performance_computing:running_jobs_slurm#gpu_selection]] for more information about GPU usage.