TensorFlow is a free, open-source machine learning and deep learning framework that can work on almost all operating systems. Due to its multi-purpose utilities and ease of compatibility, developers prefer to use this framework for developing and training ML algorithms. This tutorial will give you a quick walkthrough of installing TensorFlow in Windows, Linux, and Mac operating systems.
TensorFlow Installation Types
When installing TensorFlow, there are two options: either choose only the CPU or GPU-supported version. Install the CPU version to design and train simple machine learning models and install the GPU-supported versions for complex graphical tasks such as image processing.
The GPU-supported TensorFlow is compatible with NVIDIA GPU cards with CUDA Compute 3.5 or higher; it requires some libraries and drivers.
- NVIDIA GPU drivers
- CUDA Toolkit (CUDA 9.0)
- NCCL 2.2 (optional)
- cuDNN SDK (7.2 or higher)
- TensorRT (To improve latency and throughput).
The first thing you need in your system is a Python interpreter. You can go with 3.4 or above, as it is the best version to start working with TensorFlow. To install TensorFlow, you also need a pip package manager for Python. Usually, pip comes as a built-in tool, and it gets installed together with Python.
To check the version of pip installed on your system, type:
pip3 --version in the command prompt (in
TensorFlow Installation Process on Windows
Setting up TensorFlow Using PIP
The following command installs TensorFlow via the pip package manager:
pip3 install --upgrade tensorflow
The command may take some time to execute and install TensorFlow. The following command installs GPU-supported TensorFlow:
pip3 install tensorflow-gpu
Setting up TensorFlow Using Anaconda
Anaconda does not come with Python as a built-in tool. You have to download it from its official site and install the package manually. After installation, you can search for "Anaconda Prompt" on the Windows Start Menu.
If you want to see the details of the conda package, at the prompt, you must type the following command:
$ conda info
It's good practice to create a different work environment for each project so you can work with a specific version of varying Python libraries without affecting other Python projects.
To create a virtual environment for TensorFlow, execute the following conda command:
conda create -n [environment-name]
The following command activates the environment:
The following command installs TensorFlow via Anaconda:
$ conda install tensorflow
TensorFlow Installation Process on Linux
The TensorFlow installation process is straightforward in Linux; You need to execute the following commands below.
First, a virtual environment needs to be created for the Python venv model using the following command:
sudo apt install python3-venv python3-dev
Next, to create and activate a Python 3 virtual environment:
mkdir tensor cd tensor/ python3 -m venv [environment-name] source [environment-name]/bin/activate
Now check your pip version using the following command:
Check for the latest pip version and if it does not match, use the following command to upgrade your pip to the latest version:
pip install --upgrade pip
Now, install TensorFlow using the following command:
pip install --upgrade tensorflow
Now execute these two lines of code (saving as .py files) to check whether TensorFlow got installed or not.
import tensorflow as tf print(tf.__version__);
TensorFlow Installation Process on Mac
First, you'll need to download and install Python on your Mac OS if it's not already installed.
Verify the Python version by executing the following command in the terminal:
Now, check whether the brew is installed on your system:
Now, Create a virtual environment with the following command:
brew install virtualenv
Now create a directory to hold the environment:
virtualenv --system-site-packages -p python3 ./pythonenv
Go inside the ./pythonenv directory.
Activate the virtual environment:
Once you go inside the directory and activate the virtual environment, it is time to install the TensorFlow.
brew install tensorflow
It might take some time. Once it gets installed completely, you are good to go and use TensorFlow in your Python program.