In case you have a series of tensor operation let say you have these dummy operations
a=Operation (t1) ====> on cuda
b= Operation (a) ====> on cuda
c= Operation (b)====> on cuda
d= Operation (removing tensor c to cpu)
convert d to cuda again
.
.
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Does this style break the computation graph, I’m assuming it doesn’t, not sure though?
If it does is there any workaround ?
The reason why I’m asking because I have a problem with this Pytorch Function
torch.Tensor.svd(X_bar.cpu().T, some=True,compute_uv=True)
or
torch.svd(X_bar.cpu().T, some=True,compute_uv=True)
It always throws an error as below every a couple of Epochs.
svd_cpu: the updating process of SBDSDC did not converge (error: 17)