Running torch.cummax
on HPU seems to fail. I can run the snippet below on CPU, and it works fine. But when I run on HPU it fails.
torch.cummax(torch.range(10,0,-1)[None,:].repeat(5,1).to('hpu'), dim=1)
*** RuntimeError: vector::_M_range_check: __n (which is 0) >= this->size() (which is 0)
On CPU i get the expected results.
torch.cummax(torch.range(10,0,-1)[None,:].repeat(5,1).to('cpu'), dim=1)
torch.return_types.cummax(
values=tensor([[10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 10.],
[10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 10.],
[10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 10.],
[10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 10.],
[10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 10.]]),
indices=tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]))
I’m running this on an AWS DL1 Instance with the Habana Gaudi AMI. I’ve also manually installed torch_hpu from GitHub - HabanaAI/Setup_and_Install: Setup and Installation Instructions for Habana binaries, docker image creation