PyTorch Tutorial 01 - Installation

hi everybody welcome to a new tutorial series in this series we are going to learn how to work with PI torch high torch is one of the most popular machine learning and deep learning frameworks it's really fun to work with it and develop cool applications so I hope you watch the serious and learn all about the necessary basics for this framework so in this first video I show you how we install PI torch so let's start and for this we go to the official website PI torch org then click on get started then select the newest PI touch build right now this is version 1.3 then select your operating system so in my case it's a Mac then select the package manager with which you want to install PI torch so I highly recommend to use anaconda and if you haven't installed anaconda yet and don't know how to use it then please watch my other tutorial about anaconda so I will put the link in the description below and then select the newest python version so here i select python 3.7 and unfortunately on the mac you can only install the CPU version right now but if you are on linux or windows and want to have GPU support and then you can also install or have to install the cuda toolkit first so the CUDA toolkit is a development environment for creating high-performance cheap you accelerated applications for this you need an NVIDIA GPU in your machine and if you have that then you can go to the website developer dot and video comm slash CUDA - downloads and then we have to be careful because right now the newest supported cuda version by pi torch is cuda 10.1 so we have to get this version so right now the newest version is 10.2 so we have to go to legacy releases then selecting newest CUDA toolkit 10.1 then select your operating system so for example Windows Windows 10 then download the installer and follow the instructions and this will also check if your system is suitable for the CUDA toolkit so if this is successful then we can go back to the pie charts site and copy this command so in my case on the Mac now I need this command so let's copy this and now let's open up a terminal and first of all we want to create a virtual environment with Conda in which we want to install all of our packages and install pie charts so let's create a environment let's say Conda create - N and now give it a name so I call this pie torch simply pie touch and then also specify the Python version so let's say python equals 3.7 and then hit enter now this will create your virtual environment with python 3.7 let's hit enter again to proceed and this will take a while and now it's done so now we can activate this environment with Conda activate PI torch and now we are inside of this environment and we can see this because here in the beginning we have PI touch in parentheses so this is the name of the environment and now let's paste our installation command from the website so this will install pi torch and all the necessary packages so this will also take a couple of seconds now again let's hit enter to proceed and now it's done so now we have installed PI torch and we can very by that by starting Python inside this environment so let's say no type Python and enter and now we have Python the running and now we can import the torch module so if the installation was not correct and right now you would get a module not found error but in this case it is correct and now we can for example create a torch tensor so let's say x equals torch dot R and and of size 3 and now we want to print our tensor so this also works and now we can also check if CUDA is available so we can say tour torch dot CUDA dot is underscore available so in my case it says false but if you've installed the CUDA toolkit and also the GPU supported PI touch packages then this should say true so yeah so now we have installed in our PI torch and can get started working with it so I hope you enjoyed this and see you in the next tutorial bye

Channel: Patrick Loeber

Views: 385,531

Keywords: Python, Machine Learning, ML, PyTorch, Deep Learning, DL, Python DL Tutorial, PyTorch Tutorial, PyTorch Course, Neural Net, PyTorch Training, PyTorch Installation

Id: EMXfZB8FVUA

Length: 5min 45sec (345 seconds)

Published: Fri Dec 13 2019