Hi,

why isnt this included by default if torch recognizes GPU computations?

Because the deterministic algorithms are significantly slower than non-deterministic ones.

Is there a way to use pytorch on the GPU and not use CuDNN as well?

You can set torch.backends.cudnn.enabled = False. pytorch has all the necessary cuda kernels to run without cudnn. The big advantage of cudnn is that it has a collection of algorithms for tasks like convolutions and will choose the most suited one for the given input/weight size.

And what would be the consequences if I dont include these lines?

If you don’t include these lines, you will get the fastest algorithms but potentially non-deterministic behaviour.
Keep in mind that non-deterministic here means that both results are correct (in the sense of float operations can have multiple correct output like a + b != b + a, or an argmax can return any index of the elements achieving the max value) but which of these correct results is returned can vary from one run to the other.