Specifying memory destination when copy tensor to cpu, just like numpy `out=`

is there any way to specify memory location when copy a cuda tensor to cpu? In numpy we can specify out=destination for some functions, is there similar functionality for pytorch, maybe like:

destination = np.empty(shape=(...very_large_n...)

I’v tried

destination[some_slice] = cuda_tensor.cpu().data.numpy()

found that is used twice time as purely tensor.cpu().data.numpy(), so I suggest it copied two times.