Tensorflow Amd Cpu Support CentOS 7/8 Installation

Installing

3. 3. Installing Dependencies

   Then to Install Required Python Software
   Run one by one:

   pip install --upgrade pyparsing

   pip install --upgrade appdirs

   pip install --upgrade --no-deps --force-reinstall --no-cache-dir numpy==1.24.0 absl-py

   pip install -U pip six wheel importlib-metadata setuptools mock future

   pip install -U keras_applications --no-deps

   pip install -U keras_preprocessing --no-deps

   Possibly take into account to Amend also the Numpy Version cause there is a recommended one for every Python Release. As for Python 3.7 it was “1.21.6”.

4. 4. Downloading ZenDNN Library

   Download ZenDNN Library for CentOS GNU/Linux

   ZenDDN Tensorflow .Zip Library for CentOS

   Downloading ZenDNN Library for CentOS

   Grab the Tensorflow supporting Library.

5. 5. Extracting ZenDNN Library

   Then Extract Tensorflow ZenDNN Library into /tmp Directory
   First, if needed to Install Unzip:

   sudo yum install unzip

   Then if it does Not Open automatically then Double-Click/Right-Click to Open with Archive Manager:
   
   Or from Command Line:

   unzip -d ~ ~/Downloads/*ZenDNN*.zip

   Finally, if yuo are in Trouble to Find Out it on Terminal See: How to Access Downloads Folder from Browser.

6. 6. Installing ZenDNN Library

   Then to Install Tensorflow ZenDNN Library
   To Setup the TensorFlow wheel Package.
   Access the Target:

   cd ~/TF*ZenDNN*

   And run:

   source ./scripts/TF_ZenDNN_setup_release.sh

   

7. 7. Amending User’s Env Vars

   (Optional) In case of Issue in Benchmark Testing
   You may be needed to Set the Environment Variables indicated in the Setup Output.
   For further insight you should see the Official TensorFlow ZenDNN Docs.
   First, you may try some TensorFlow Benchmark Testing.
   In case to find out the Number of CPUs Cores in your System:

   nproc --all

   And consequently you may then Set the Variable:

   echo "export GOMP_CPU_AFFINITY=0-[CPUSNUM]" >> ~/.bashrc

   Replace [CPUSNUM] with the Output of the previous Command in the above.
   Last, to Reload the Path simply:

   bash

8. 8. TensorFlow Getting-Started Guide

   Getting-Started with TensorFlow on CentOS GNU/Linux

   TensorFlow Quick Start Guide

   Getting-Started with TensorFlow in CentOS