(Libtorch)How to use packed_accessor64 to access tensor elements in CUDA?

The tutorial gives an example about using packed_accessor64 to access tensor elements efficiently as follows. However, I still do not know how to use packed_accessor64. Can anyone give me a more specific example? Thanks.

__global__ void packed_accessor_kernel(
    PackedTensorAccessor64<float, 2> foo,
    float* trace) {
  int i=threadIdx.x
  gpuAtomicAdd(trace, foo[i][i])
}
 
torch::Tensor foo = torch::rand({12, 12});
 
// assert foo is 2-dimensional and holds floats.
auto foo_a = foo.packed_accessor64<float,2>();
float trace = 0;
 
packed_accessor_kernel<<<1, 12>>>(foo_a, &trace);

cc @sekyondaMeta @svekars @carljparker @NicolasHug @kit1980 @subramen

Start with the CUDA accessors section of the linked tensor basics tutorial and review the packed_accessor64 example shown in the issue. Determine what a more specific LibTorch usage example should cover, then update the tutorial so the intended usage is clear and verify the example is correct.