From 767f7529628e6fdea7c9d4bded4284a55e99f14e Mon Sep 17 00:00:00 2001
From: Natalie Breidenbach <natalie.breidenbach@tu-dresden.de>
Date: Tue, 28 Nov 2023 14:39:56 +0100
Subject: [PATCH] Update tensorflow.md
---
.../docs/software/tensorflow.md | 29 ++++++++++---------
1 file changed, 16 insertions(+), 13 deletions(-)
diff --git a/doc.zih.tu-dresden.de/docs/software/tensorflow.md b/doc.zih.tu-dresden.de/docs/software/tensorflow.md
index f11ecb3ac..06cf153f7 100644
--- a/doc.zih.tu-dresden.de/docs/software/tensorflow.md
+++ b/doc.zih.tu-dresden.de/docs/software/tensorflow.md
@@ -17,13 +17,16 @@ to find out, which TensorFlow modules are available on your partition.
On ZIH systems, TensorFlow 2 is the default module version. For compatibility hints between
TensorFlow 2 and TensorFlow 1, see the corresponding [section below](#compatibility-tf2-and-tf1).
-We recommend using partitions `alpha` and/or `ml` when working with machine learning workflows
+We recommend using the clusters `alpha` and/or `power` when working with machine learning workflows
and the TensorFlow library. You can find detailed hardware specification in our
[Hardware](../jobs_and_resources/hardware_overview.md) documentation.
## TensorFlow Console
-On the partition `alpha`, load the module environment:
+_The module environments /hiera, /scs5, /classic and /ml originated from the old taurus system are momentarily under construction. The script will be updated after completion of the redesign accordingly_
+
+
+On the cluster `alpha`, load the module environment:
```console
marie@alpha$ module load modenv/scs5
@@ -47,17 +50,17 @@ marie@alpha$ module avail TensorFlow
[...]
```
-On the partition `ml` load the module environment:
+On the cluster `power` load the module environment:
```console
-marie@ml$ module load modenv/ml
+marie@power$ module load modenv/ml
The following have been reloaded with a version change: 1) modenv/scs5 => modenv/ml
```
This example shows how to install and start working with TensorFlow using the modules system.
```console
-marie@ml$ module load TensorFlow
+marie@power$ module load TensorFlow
Module TensorFlow/2.3.1-fosscuda-2019b-Python-3.7.4 and 47 dependencies loaded.
```
@@ -68,16 +71,16 @@ import TensorFlow:
!!! example
```console
- marie@ml$ ws_allocate -F scratch python_virtual_environment 1
+ marie@power$ ws_allocate -F /data/horse python_virtual_environment 1
Info: creating workspace.
- /scratch/ws/1/python_virtual_environment
+ /data/horse/ws/1/python_virtual_environment
[...]
- marie@ml$ which python #check which python are you using
+ marie@power$ which python #check which python are you using
/sw/installed/Python/3.7.2-GCCcore-8.2.0
- marie@ml$ virtualenv --system-site-packages /scratch/ws/1/marie-python_virtual_environment/env
+ marie@power$ virtualenv --system-site-packages /data/horse/ws/1/marie-python_virtual_environment/env
[...]
- marie@ml$ source /scratch/ws/1/marie-python_virtual_environment/env/bin/activate
- marie@ml$ python -c "import tensorflow as tf; print(tf.__version__)"
+ marie@power$ source /data/horse/ws/1/marie-python_virtual_environment/env/bin/activate
+ marie@power$ python -c "import tensorflow as tf; print(tf.__version__)"
[...]
2.3.1
```
@@ -105,7 +108,7 @@ Another option to use TensorFlow are containers. In the HPC domain, the
following example, we use the tensorflow-test in a Singularity container:
```console
-marie@ml$ singularity shell --nv /scratch/singularity/powerai-1.5.3-all-ubuntu16.04-py3.img
+marie@power$ singularity shell --nv /data/horse/singularity/powerai-1.5.3-all-ubuntu16.04-py3.img
Singularity>$ export PATH=/opt/anaconda3/bin:$PATH
Singularity>$ source activate /opt/anaconda3 #activate conda environment
(base) Singularity>$ . /opt/DL/tensorflow/bin/tensorflow-activate
@@ -156,5 +159,5 @@ marie@compute$ module spider Keras
[...]
```
-to find out, which Keras modules are available on your partition. TensorFlow should be automatically
+to find out, which Keras modules are available on your cluster. TensorFlow should be automatically
loaded as a dependency. After loading the module, you can use Keras as usual.
--
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