![]() ![]() What is the difference between apt update and apt upgrade? “apt-get update” updates the package sources list to get the latest list of available packages in the repositories and “apt-get upgrade” updates all the packages presently installed in our Linux system to their latest versions. In this article, I have tried to explain what this command means from a beginner’s perspective avoiding unnecessary “technical terms” and I have tried to keep this article concise so that you can get through the entire article in about 10 to 20 mins max!įor those of you in a hurry here is the short version of the answer! The Short Version of the Answer Let’s see the difference between these 2 commands and what happens internally once you execute these commands. ![]() In plain English, update and upgrade have almost the same meanings, so it can get confusing for a beginner to understand what these commands actually do. I guess to beginners, it just feels like a magic spell to get something installed!Īs time went on, so many of my google searches led to using very similar patterns of “apt update” and “apt upgrade” commands to install stuff. Feel free to test more complex programs to make sure everything is running smoothly.I was just happy that I was able to type something in the Terminal and it actually worked! I did not pay much attention to what I actually typed in. Print(_available()) # should print TrueĪlso, try creating a random tensor: t = torch.rand(10, 10).cuda()Īnd there you have it! Now, you're all set to run GPU-accelerated machine learning or deep learning tasks. Open Python in your terminal and run the following: import torch Within the virtual environment, install PyTorch and its friends: pip3 install torch torchvision torchaudio ![]() Now, create and activate your virtual environment: virtualenv -p p圓.10 venv Sudo apt install libcudnn8-samples Testing CUDA with PyTorchįirst, install pip3 and virtualenv: sudo apt-get install python3-pip ![]() If your cuDNN version is 8 (it could differ), then do: sudo apt update Sudo cp /var/cudnn-.gpg /usr/share/keyrings/ Navigate to your download directory and run: sudo apt install. Note: you'll need an Nvidia account for this. Head over to the Nvidia website and download the cuDNN. Time to install the CUDA toolkit: sudo apt install nvidia-cuda-toolkitĬheck if CUDA is installed by running: nvcc -version Installing cuDNN Yes, another update check to keep things smooth: sudo apt update & sudo apt upgrade If it works, you're good to go! Installing CUDA If the recommended version is 525 (it might differ for you), then run: sudo apt install nvidia-driver-525Īfter rebooting, run the following to ensure the driver installed correctly: nvidia-smi Now, install those recommended drivers automatically: sudo ubuntu-drivers autoinstall Look for the driver version tagged as "recommended". Use this command to see which drivers Ubuntu recommends: ubuntu-drivers devices If you've tried to install NVIDIA drivers before, let's clean that up: sudo apt autoremove nvidia* -purge Installing NVIDIA Drivers Let's make sure your system is up to date: sudo apt update & sudo apt upgrade Update Your Package List and Existing Software This tutorial focuses on Ubuntu 22.04, so make sure that's what you're running before we get started. But don't worry, I'll guide you through it step-by-step. Setting up CUDA and cuDNN can be a bit tricky, especially if you're not familiar with the command line. ![]()
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