Cantech Knowledge Base

Your Go-To Hosting Resource

  1. Linux
  2. How to Install PyTorch on Ubuntu 22.04?

How to Install PyTorch on Ubuntu 22.04?

If you take deep learning, AI, or data science seriously, PyTorch is one essential tech in your stack you must have. That sounds a bit off, huh? Fear not! Though installing PyTorch on Ubuntu 22.04 might sound like a daunting task for some, it’s not rocket science for those who have been through all this. A comprehensive stepwise guide, with appropriate ease, is presented here to assist you through everything in this article.

But first things first: if you are genuinely serious about AI and machine-learning stuff, it is the perfect time for you to have some power and reliability for hosting your models. Cantech provides reliable and fast Linux VPS Hosting, Dedicated Servers, and Cloud Hosting services – all optimized for AI workloads. We will make sure you maintain uninterrupted operations for, whether you are trying to train models, running experiments, deploying AI applications, or whatever you may be doing with a hosting platform with the right infrastructure and support.

Why Use PyTorch?

Let’s take a quick look at why PyTorch has become one of the most popular deep learning frameworks used by the AI community in the world. It offers everything from building neural networks, training models using large datasets and experimentation with reinforcement learning. It certainly provides enough flexibility and power.

Dynamic Computation Graphs – PyTorch features dynamic computation graphs that let you build models dynamically. You can modify the structure on the fly without restarting the process, which is extremely useful when debugging to prototype new AI architectures efficiently.

Seamless GPU Acceleration – PyTorch integrates easily with CUDA, enabling you to offload computations with NVIDIA GPUs. Thus, it increases the processing speed by orders of magnitude compared with a CPU, allowing you to process massive datasets and complex deep-learning models faster.

Strong Open-Source Community – PyTorch is backed by Facebook AI Research and is supplemented with a large, active global community contributing to its ecosystem. So what does that mean to you? You can expect regular updates, great documentation, and a ton of third-party extensions.

Intuitive & Pythonic – PyTorch is kept only for Python developers. It just feels normal and intuitive if you are used to programming in Python, thereby reducing the learning curve.

Powerful Libraries & Ecosystem – PyTorch works well with libraries like TorchVision (for computer vision), TorchText (for NLP), and torchaudio (for speech processing), making it a great versatile choice for AI applications in different domains.

When deep learning on a cloud machine is the norm for you, having a wholesome and good solution for hosting is very important. Cantech provides AI-optimized Linux VPS Hosting that helps you in all tasks from model training to proper execution and to work swiftly on computation. Be it any training job, or a deployment of machine-learning models in action, or a real-time AI workload, the power of hosting solutions from Cantech will consistently deliver!

Prerequisites

Before you install PyTorch, you require to have the following:

  • Ubuntu 22.04 LTS
  • Python 3.6+
  • pip or Conda installed
  • NVIDIA GPU (optional but recommended for AI/ML tasks)
  • CUDA (if using a GPU)

Need a high-performance server for deep learning? Check out Cantech’s Dedicated Servers and Cloud GPU Servers.

Step 1: Update Your System

You can begin by updating and upgrading your Ubuntu system to ensure you have installed the latest packages into the system.

sudo apt update && sudo apt upgrade -y

Step 2: Install Python & Pip

Make sure Python and pip are installed:

sudo apt install python3 python3-pip -y

Check the installed versions:

python3 --version
pip3 --version

If you prefer using Anaconda, download and install it from Anaconda’s official site.

Step 3: Install PyTorch (CPU Version)

For systems without GPU, a CPU-only version can be installed of PyTorch using pip as follows:

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu

For Conda users:

conda install pytorch torchvision torchaudio cpuonly -c pytorch

Step 4: Install PyTorch (GPU Version)

If you have an NVIDIA GPU, install CUDA and cuDNN first.
Check if your system has a supported GPU:

nvidia-smi

Now, install PyTorch with GPU support:

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

For Conda users:

conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

Step 5: Verify Installation

To see if the installed version of PyTorch works, open Python and run:

import torch
print(torch.__version__)
print(torch.cuda.is_available()) # Should return True if CUDA is enabled

If you see the version of PyTorch and a message about the GPU being available, you’ve installed PyTorch on Ubuntu 22.04!

Step 6: Running a Test Script

To ensure everything works fine, run a simple PyTorch script:

import torch
x = torch.rand(3, 3)
print(x)

If this runs without errors, PyTorch is ready to use!

Best Hosting for AI & ML Workloads

When running AI models, the right hosting solution is critical. Cantech offers high-performance hosting tailored for deep learning and machine learning needs:

Conclusion

To install PyTorch on Ubuntu 22.04, follow the necessary steps and you will find it easy. You can install either with pip or Conda, along with the necessary requirements. If you’re using a GPU, install the appropriate CUDA version for maximum performance.
And if you are looking for a future proof hosting solution that would take care of all your deep learning models, Cantech hosts AI and ML infrastructure, from VPS Hosting to Dedicated Servers.

FAQs

What are the uses of PyTorch?
PyTorch is one of the main deep learning frameworks used in many AI, machine learning, and data science domains. The library is used for developing neural networks, computer vision models, NLP’s and many other applications.

Can I install PyTorch with/without a GPU?
Yes! PyTorch works perfectly fine on the CPU. However, if you are working with large datasets and complicated models, the training time would be reduced significantly with a GPU optimized server like the ones from Cantech.

How do I check if PyTorch is using my GPU?
Following the successful installation of PyTorch, if you open a Python terminal, you can type in these lines

import torch
print(torch.cuda.is_available())

If the result is True, then it implies that PyTorch is utilizing your GPU. That means PyTorch is using your GPU.

What’s the difference between using pip and Conda to install PyTorch?
pip is the best option to operate in a virtual environment with a lightweight structure. Conda is the best option to manage dependencies, particularly if you are working on multiple projects.

Do I require CUDA for PyTorch?
CUDA is required only if you are going to use a GPU. If you are using PyTorch on a CPU, you will not need to install CUDA.

Can I install PyTorch inside a Docker container?
You can install PyTorch in a Docker container! Just remember, you must pull the right PyTorch Docker Image from the PyTorch official Docker Hub. Cantech’s Dedicated Servers for high-performance computing are great options for dedicated AI-optimized servers.

June 5, 2025