Lunderberg opened a new pull request, #16589:
URL: https://github.com/apache/tvm/pull/16589

   When determining whether to evaluate matrix multiplications as `(A*B)*C` or 
as `A*(B*C)`, dynamic shapes may occur (e.g. a dynamic LoRA rank).  This commit 
tests for these cases, and improves the arithmetic bounds used to prove which 
order of evaluation is preferred.
   
   As part of the implementation, this commit also adds a utility 
`CollectNonNegativeExpressions`, exposed to the python API as 
`relax.analysis.collect_non_negative_expresisons`.  This utility collects 
expressions within a `StructInfo` which must be non-negative, based on the 
location where they appear.  For example, the size of a tensor along each 
dimension must be non-negative.  Unlike the existing 
`defineable_tir_vars_in_struct_info`, this will include the `N-2` expression in 
`R.Tensor([N-2])`.


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