Difference between revisions of "TensorFlow 2016"
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== Introduction == | == Introduction == | ||
TensorFlow™ is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. | |||
== Installed version == | == Installed version == | ||
The currently installed versions are | The currently installed versions are | ||
''on the environment '''hpc-env/8.3''''' | |||
'''TensorFlow/1.13.1-fosscuda-2019b-Python-3.7.4''' | |||
'''TensorFlow/2.1.0-fosscuda-2019b-Python-3.7.4''' | |||
'''TensorFlow/2.3.1-fosscuda-2019b-Python-3.7.4''' | |||
''on the environment '''hpc-env/6.4''''' | ''on the environment '''hpc-env/6.4''''' | ||
'''TensorFlow/1.7.0-intel-2018a-Python-3.6.3''' | '''TensorFlow/1.7.0-intel-2018a-Python-3.6.3''' | ||
'''TensorFlow/1.8.0-intel-2018a-Python-3.6.3''' | '''TensorFlow/1.8.0-intel-2018a-Python-3.6.3''' | ||
'''TensorFlow/1.13.1-foss-2017b-Python-3.6.3''' (Not built with GPU support!) | |||
''on the environment '''hpc-uniol-env''''' | ''on the environment '''hpc-uniol-env''''' | ||
'''Tensorflow/1.4.0-intel-2016b-Python-2.7.12''' | '''Tensorflow/1.4.0-intel-2016b-Python-2.7.12''' | ||
| Line 20: | Line 28: | ||
This will show you basic informations e.g. a short description and the currently installed version. | This will show you basic informations e.g. a short description and the currently installed version. | ||
To load the desired version, you must load the module as well as the environment: | To load the desired version (e.g. 1.8), you must load the module as well as the environment: | ||
module load hpc-env/6.4 | module load hpc-env/6.4 | ||
module load TensorFlow | module load TensorFlow/1.8.0 | ||
== Documentation == | == Documentation == | ||
Latest revision as of 09:21, 21 October 2020
Introduction
TensorFlow™ is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
Installed version
The currently installed versions are
on the environment hpc-env/8.3
TensorFlow/1.13.1-fosscuda-2019b-Python-3.7.4 TensorFlow/2.1.0-fosscuda-2019b-Python-3.7.4 TensorFlow/2.3.1-fosscuda-2019b-Python-3.7.4
on the environment hpc-env/6.4
TensorFlow/1.7.0-intel-2018a-Python-3.6.3 TensorFlow/1.8.0-intel-2018a-Python-3.6.3 TensorFlow/1.13.1-foss-2017b-Python-3.6.3 (Not built with GPU support!)
on the environment hpc-uniol-env
Tensorflow/1.4.0-intel-2016b-Python-2.7.12
Using TensorFlow
If you want to find out more about Tensorflow on the HPC Cluster, you can use the command
module spider TensorFlow
This will show you basic informations e.g. a short description and the currently installed version.
To load the desired version (e.g. 1.8), you must load the module as well as the environment:
module load hpc-env/6.4 module load TensorFlow/1.8.0
Documentation
For more information about how to use TensorFlow, you can take a look at the tutorial.
Further information are also available on the homepage
