Fix refcount handling for dtype, layout and memory format (#125271)

Finish fixing https://github.com/pytorch/pytorch/issues/124868
re-use our wrap() utils as much as possible and NewRef in other places.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125271
Approved by: https://github.com/colesbury

torch/csrc/profiler/python/init.cpp

@@ -440,8 +440,7 @@ void initPythonBindings(PyObject* module) {
           "dtype",
           [](const TensorMetadata& metadata) {
             return py::reinterpret_borrow<py::object>(
-                torch::autograd::utils::wrap(
-                    torch::getTHPDtype(metadata.dtype_)));
+                torch::autograd::utils::wrap(metadata.dtype_));
           })
       .def_readonly("dim", &TensorMetadata::dim_)
       .def_readonly("sizes", &TensorMetadata::sizes_)