Hi everyone, I’m new to deep learning libraries, so apologies in advance if this is something I’m already supposed to know.
I’ve used Theano before but guides for setting up the GPU there were very straightforward, also I was doing this using a WinPy instance on Windows. I come from a MATLAB background where I’m used to being able to play around with the variables and initialize things quickly, so naturally I felt like PyTorch may have more to offer.
But there isn’t that much documentation on how to set things up from scratch with PyTorch. I have Anaconda installed on Ubuntu and have tried the basic functionality of PyTorch that way, but I’m not sure how to get it working with CUDA. Any advice would be appreciated!
Hi, welcome to PyTorch world. Tensorflow’s installation guide’s NVIDIA requirements to run TensorFlow with GPU support would be helpful. It tells you how to install CUDA etc. Edited by moderator, pytorch does not need manual CUDA install
if you want to use pytorch with an NVIDIA GPU, all you need to do is install pytorch binaries and start using it. We ship with everything in-built (pytorch binaries include CUDA, CuDNN, NCCL, MKL, etc.).
@smth thank you for your moderation. I used Tensorflow before installing PyTorch, so I misunderstood that they are needed.
These installations are complicated so PyTorch’s everything-in-build is cool.
@smth Thanks for the reply! Is installing from the binaries the same as following the instructions on the front page? Because I’ve done this but I get a CUDA library error when running
a = torch.randn(10).cuda()
Just to make sure, I updated Pytorch with my Anaconda installation via the following
Hi, this could be a very naive question because I am new to this.
So if I install PyTorch first, I wouldn’t have to manually install the NVIDIA software for TensorFlow later. Correct?