I tried to train a model using PyTorch on my Macbook pro. It uses the new generation apple M1 CPU. However, PyTorch couldn't recognize my GPUs.
GPU available: False, used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
Does anyone know any solution?
I have updated all the libraries to the latest versions.
It looks like PyTorch support for the M1 GPU is in the works, but is not yet complete.
From @soumith on GitHub:
So, here's an update. We plan to get the M1 GPU supported. @albanD, @ezyang and a few core-devs have been looking into it. I can't confirm/deny the involvement of any other folks right now.
So, what we have so far is that we had a prototype that was just about okay. We took the wrong approach (more graph-matching-ish), and the user-experience wasn't great -- some operations were really fast, some were really slow, there wasn't a smooth experience overall. One had to guess-work which of their workflows would be fast.
So, we're completely re-writing it using a new approach, which I think is a lot closer to your good ole PyTorch, but it is going to take some time. I don't think we're going to hit a public alpha in the next ~4 months.
We will open up development of this backend as soon as we can.
That post: https://github.com/pytorch/pytorch/issues/47702#issuecomment-965625139
TL;DR: a public beta is at least 4 months out.
PyTorch added support for M1 GPU as of 2022-05-18 in the Nightly version. Read more about it in their blog post.
Simply install nightly:
conda install pytorch -c pytorch-nightly --force-reinstall
To use (source):
mps_device = torch.device("mps")
# Create a Tensor directly on the mps device
x = torch.ones(5, device=mps_device)
# Or
x = torch.ones(5, device="mps")
# Any operation happens on the GPU
y = x * 2
# Move your model to mps just like any other device
model = YourFavoriteNet()
model.to(mps_device)
# Now every call runs on the GPU
pred = model(x)
For those who couldn't install using conda like me use pip as following:-
pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
Update:
No need of nightly version. Pytorch version 1.12 now supports GPU acceleration in apple silicon. Simply install using following command:-
pip3 install torch torchvision torchaudioYou may follow other instructions for using pytorch in apple silicon and getting your benchmark.
Make sure you use mps as your device as following:
device = torch.device('mps')
# Send you tensor to GPU
my_tensor = my_tensor.to(device)
Without using GPU
Using GPU (5x faster)
