How can I use GPU acceleration in PyTorch?

How can I use GPU acceleration in PyTorch?

To use GPU acceleration in PyTorch, you need to ensure that you have a compatible GPU and the CUDA toolkit installed. You can then move your tensors and models to the GPU using the .to('cuda') method.

What if I don't have a GPU? Can I still use PyTorch?

Yes, you can still use PyTorch on a CPU. It will be slower than using a GPU, but all functionalities are available. Just make sure to keep your tensors on the CPU.

How do I check if PyTorch is using the GPU?

You can check if PyTorch is using the GPU by running torch.cuda.is_available(). If it returns True, then your setup is correct.

Can I run multiple models on the GPU simultaneously?

Yes, you can run multiple models on the GPU, but be mindful of the GPU memory usage. You may need to manage memory allocation carefully.