What’s the appropriate way to create a copy of a tensor, where the copy requires grad when the original tensor did not in 0.4?

Previously, I was using something like `Variable(original_tensor, requires_grad=True)`

. However, this was in 0.3 where `original_tensor`

was only a tensor (and not a variable). `Variable()`

seems to be on the way out, and I’d like to replace it with the appropriate approach in the new version. Should I be using some sort of `clone`

? Or will this result in the original also being updated to require grad as well? Or would something like `torch.tensor(original_tensor, requires_grad=True)`

(note, using new `tensor`

not `Tensor`

) create a new tensor based off the old one but which is it’s own tensor and will not change the grad requirements of the original? Or would a different approach be recommended? Thank you!