This tutorial will show you how to install TensorFlow on Debian 11. According to their site, TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
Install TensorFlow on Debian 11
There are various ways in which TensorFlow can be installed on Debian Linux;
- Install using Python PIP
- Install via Docker
- Build and install from the source.
We will only discuss the PIP installation method in this guide. For other methods refer to the documentation.
Before you can proceed with installation, be sure to check on hardware, system and software requirements.
Use Python PIP to Install TensorFlow
- Install Python 3.x
TensorFlow requires Python 3.7-3.10. Fortunately, Debian 11 ships with Python 3.9;
python3 -VSample output;
Python 3.9.2- Install PIP on Debian 11
pip version 19.0 or higher is required. You can install PIP on Debian 11 using the command below;
sudo apt updatesudo apt install python3-pip- Install Required Python Libraries and Virtual Environment
Run the command below to install required Python libraries and virtual environment.
sudo apt install python3-{venv,dev}- Create TensorFlow Virtual Environment
Next, run the command below to install TensorFlow;
mkdir ~/tensorflow && cd ~/tensorflowCreate virtual environment, in this case we called our virtual environment, tensorflow_venv. You can use any name!
python3 -m venv tensorflow_venvActivate the virtual environment created;
source ./tensorflow_venv/bin/activateYou will see the shell prompt change;
(tensorflow_venv) kifarunix@debian11:~/tensorflow$- Upgrade PIP;
pip install --upgrade pipVerify installed PIP version;
pip --versionpip 22.1.1 from /home/kifarunix/tensorflow/tensorflow_venv/lib/python3.9/site-packages/pip (python 3.9)- Install TensorFlow using PIP
Within the virtual environment, run the command below to install TensorFlow using PIP.
pip install --upgrade tensorflowSample installation output;
Requirement already satisfied: pip in ./tensorflow_venv/lib/python3.9/site-packages (20.3.4)
Collecting pip
Downloading pip-22.1.1-py3-none-any.whl (2.1 MB)
|████████████████████████████████| 2.1 MB 821 kB/s
Installing collected packages: pip
Attempting uninstall: pip
Found existing installation: pip 20.3.4
Uninstalling pip-20.3.4:
Successfully uninstalled pip-20.3.4
Successfully installed pip-22.1.1
(tensorflow_venv) kifarunix@debian11:~/tensorflow$ pip3 --version
pip 22.1.1 from /home/kifarunix/tensorflow/tensorflow_venv/lib/python3.9/site-packages/pip (python 3.9)
(tensorflow_venv) kifarunix@debian11:~/tensorflow$ pip install --upgrade tensorflow
Collecting tensorflow
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Using legacy 'setup.py install' for termcolor, since package 'wheel' is not installed.
Installing collected packages: termcolor, tensorboard-plugin-wit, pyasn1, libclang, keras, flatbuffers, zipp, wrapt, wheel, werkzeug, urllib3, typing-extensions, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, six, rsa, pyparsing, pyasn1-modules, protobuf, oauthlib, numpy, idna, gast, charset-normalizer, certifi, cachetools, requests, packaging, opt-einsum, keras-preprocessing, importlib-metadata, h5py, grpcio, google-pasta, google-auth, astunparse, absl-py, requests-oauthlib, markdown, google-auth-oauthlib, tensorboard, tensorflow
Running setup.py install for termcolor ... done
Successfully installed absl-py-1.0.0 astunparse-1.6.3 cachetools-5.1.0 certifi-2022.5.18.1 charset-normalizer-2.0.12 flatbuffers-1.12 gast-0.4.0 google-auth-2.6.6 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.46.3 h5py-3.7.0 idna-3.3 importlib-metadata-4.11.4 keras-2.9.0 keras-preprocessing-1.1.2 libclang-14.0.1 markdown-3.3.7 numpy-1.22.4 oauthlib-3.2.0 opt-einsum-3.3.0 packaging-21.3 protobuf-3.19.4 pyasn1-0.4.8 pyasn1-modules-0.2.8 pyparsing-3.0.9 requests-2.27.1 requests-oauthlib-1.3.1 rsa-4.8 six-1.16.0 tensorboard-2.9.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.9.1 tensorflow-estimator-2.9.0 tensorflow-io-gcs-filesystem-0.26.0 termcolor-1.1.0 typing-extensions-4.2.0 urllib3-1.26.9 werkzeug-2.1.2 wheel-0.37.1 wrapt-1.14.1 zipp-3.8.0
Check installed version of TensorFlow;
python3 -c 'import tensorflow as tf;print(tf.version.VERSION)'Sample output;
2.9.1You can now use TensorFlow. Refer to the documentation for more information.
You can deactivate the virtual environment using the command;
deactivateYou should see the shell prompt change.
