np.where prevents CUDA Tensors from compressing

[dakami]

https://github.com/rballester/tntorch/blob/master/tntorch/round.py#L139

    where = np.where((torch.cumsum(S[reverse], dim=0).detach().cpu() <= delta**2))[0]

If S is located on the device, np.where causes a cpu/gpu conflict.

Replacing np.where with torch.where and removing the cpu() call allows both CPU and GPU compressed tensors to work. Unclear if detach is necessary or if it causes resource leaks.

Cool code!