vinx13 commented on pull request #39:
URL: https://github.com/apache/tvm-rfcs/pull/39#issuecomment-936668384


   One way to represent the layout mapping in TIR is to introduce different 
storage scopes and have a registry of pre-defined layout mapping (for example, 
we already did similar thing for [`wmma` 
fragments](https://github.com/apache/tvm/blob/813136401a11a49d6c15e6013c34dd822a5c4ff6/python/tvm/topi/cuda/tensor_intrin.py#L94-L101),
 a special data structure for tensor core input). The cons is that the TIR 
itself doesn't contain the mapping, the meaning of TIR depends on the contents 
in the registry. If we can have a few pre-defined mapping that is general to be 
used in different operators, this might be fine. A possible way to embed the 
mapping inside TIR is to build the `PrimExpr` from the mapping function, which 
is similar to what we did for 
[te.compute](https://github.com/apache/tvm/blob/main/python/tvm/te/operation.py#L106)


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