Oh, I just realized you might mean a CPU-only distribution of PyTorch? I’m using a CUDA-enabled version, but with a CPU device. I haven’t tried with a CPU-only version of PyTorch because I do train on a GPU occasionally, though if this bug (if it is a bug) isn’t on a CPU only version of PyTorch, I can definitely switch to that for the actual deployment.