cyx-6 commented on PR #593:
URL: https://github.com/apache/tvm-ffi/pull/593#issuecomment-4978725670

   some other questions:
   
   > Trying to understand this - it means id-consistency is not guaranteed for 
tensors?
   
   `Tensors` deliberately don't bind as canonical (a chandle may be wrapped 
more than once per arg-setter), so is identity isn't guaranteed for them; FFI 
returns still route through `make_ret_object`.
   
   > A quick question: what objects will use the builtin allocator defined in 
C++? If we use import tvm_ffi, what objects do not have the desired property 
(i.e., created before we register the python custom allocator for tvm-ffi).
   
   Any object whose wrapper class derives from `CObject` and is registered via 
`@register_object` / `@c_class` / `@py_class` gets it — that's the sole gate in 
`_update_registry`. Since `core.pyx` registers the Python allocator at `import 
tvm_ffi` before any type is registered, effectively all Python-visible FFI 
objects qualify; the builtin C++ allocator only backs objects created during 
C++ static init or by non-Python frontends (plus `String/Bytes/Shape/Tensor`, 
which intentionally don't tie).


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