Could you check if detaching the tensor if you are not using the computation graph or calling backward before calling copy_ (similar to as described here `copy_` operations get repeated in autograd computation graph) helps?
Alternatively, if you know that gradients are not needed anywhere, you could try using the no_grad guard as well:
Typedef torch::NoGradGuard — PyTorch master documentation
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