The Tensor is now going to "view" the same storage than the given tensor. As the result, any modification in the elements of the Tensor will have a impact on the elements of the given tensor, and vice-versa. This is an efficient method, as there is no memory copy! 

> x = torch.Tensor(2,5):fill(3.14)
> print(x)

 3.1400  3.1400  3.1400  3.1400  3.1400
 3.1400  3.1400  3.1400  3.1400  3.1400
[torch.Tensor of dimension 2x5]

> y = torch.Tensor():set(x)
> print(y)

 3.1400  3.1400  3.1400  3.1400  3.1400
 3.1400  3.1400  3.1400  3.1400  3.1400
[torch.Tensor of dimension 2x5]

> y:zero()
> print(x) -- elements of x are the same than y!

0 0 0 0 0
0 0 0 0 0
[torch.Tensor of dimension 2x5]