How to Install PyTorch on AlmaLinux
Installing PyTorch on AlmaLinux is a straightforward process, though it does require some familiarity with the Linux command line and Python package management. In this guide, we’ll walk through the steps to get PyTorch running on an AlmaLinux machine. By the end of this tutorial, you will have PyTorch installed and ready to use for your machine learning or deep learning projects.
Prerequisites
Before starting the installation, ensure the following:
- You have AlmaLinux installed on your machine.
- You have sudo privileges.
- Python 3.8 or later is installed.
- pip is installed for managing Python packages.
If you don’t have Python or pip installed, you can install them using the following commands:
sudo dnf install python3-pip
Now, let’s proceed with installing PyTorch.
Step 1: Update System Packages
First, make sure your system packages are up to date to avoid compatibility issues during installation.
This command will update all installed packages to their latest versions.
Step 2: Install Python Development Tools
You need Python development tools and virtualenv to create an isolated Python environment for PyTorch.
sudo dnf install python3-devel
sudo pip3 install virtualenv
Step 3: Create a Virtual Environment (Optional)
Creating a virtual environment is optional but recommended. It helps keep your Python projects organized and avoids package conflicts.
cd pytorch_env
python3 -m venv venv
source venv/bin/activate
Now, your terminal should show that you are working inside the virtual environment ((venv) should appear before your prompt).
Step 4: Install PyTorch Using pip
To install PyTorch, you can use the official PyTorch installation command. Visit the PyTorch website and select the appropriate options (such as PyTorch build, OS, package manager, and CUDA version). Here, we will assume you want to install the latest stable version without GPU (CPU-only version):
If you have a CUDA-compatible GPU and want to leverage it for PyTorch, you need to install the version that matches your CUDA version. For example, if you have CUDA 11.7 installed:
Make sure you have installed the corresponding CUDA version on your AlmaLinux system before using this command.
Step 5: Verify the Installation
After the installation is complete, you can verify that PyTorch is correctly installed by launching Python and running a simple script.
Then, within the Python interactive shell, type:
print(torch.__version__)
print(torch.cuda.is_available())
The output should display the installed PyTorch version. If you installed a CUDA-compatible version and have a CUDA-capable GPU, torch.cuda.is_available() should return True.
Step 6: Deactivating the Virtual Environment (If Used)
Once you have verified the installation, you can deactivate the virtual environment:
To reactivate the environment in the future, navigate to the project directory and use:
Conclusion
You have successfully installed PyTorch on AlmaLinux! Now you can start building and running your deep learning models using PyTorch. By following this guide, you have also learned how to create a Python virtual environment, which is a useful skill for managing Python projects.
Happy coding with PyTorch! If you encounter any issues, be sure to check the PyTorch documentation for more detailed instructions and troubleshooting tips.