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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.

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Why Use PyTorch?

Before we get started installing it, let’s dive a little bit into why PyTorch has become one of the most widely used deep-learning frameworks within the AI community. From building neural networks to training models with huge datasets, to experimentation with reinforcement learning, PyTorch has it all! 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.

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Prerequisites

Prerequisites
Before you install PyTorch, make sure you 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)
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Step 1: Update Your System

As a wise practice, 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:

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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

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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 it prints out the PyTorch version along with a message about GPU availability, congratulations, you’ve finished installing 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!

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Conclusion

Installing PyTorch on Ubuntu 22.04 is easy when you follow the right steps. Whether you choose pip or Conda, ensure your system meets the prerequisites. If you’re using a GPU, install the appropriate CUDA version for maximum performance.

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Happy coding!

FAQs

What is PyTorch used for?
PyTorch is among the main Deep learning frameworks leveraged in AI, machine learning, and data science areas. The library has its applications in developing neural networks, computer vision models, NLP, and more.

Can I install PyTorch with/without a GPU?
Yes! PyTorch runs just fine on the CPU. But if you are dealing with large datasets and complicated models, a GPU-optimized server such as the ones you will find at Cantech will boost training massively.

How do I check if PyTorch is using my GPU?

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

Following the successful installation of PyTorch, if you open a Python terminal, you can type in these lines

What’s the difference between using pip and Conda to install PyTorch?

  • pip: It is fantastic if you want to operate in a virtual environment and desire a lightweight architecture.
  • Conda: Best for managing dependencies, especially when working on multiple projects.

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Do I need CUDA for PyTorch?
CUDA is necessary only if you’re going to be using a GPU. For those running PyTorch on a CPU, there’s no need to install CUDA.

Can I install PyTorch inside a Docker container?
Absolutely! You can install PyTorch in a Docker container to ensure a reproducible environment. Just be sure to pull the appropriate PyTorch Docker Image from the official Docker Hub of PyTorch.

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April 10, 2025