Specifically, we use unranked memrefs which get passed as a fixed-size
set of arguments/returns. One big caveat about this is that returning
results isn't going to work. See TODO in LowerTensorLoadOp.
This is far from enough runtime-wise, but it starts to demarcate a
plausible layering. Notice for example how this removes the
runtime-dependence from LowerRankedShapes.
Eventually, we want to have an `npcomp_rt` or `npcomp_hal` dialect with
its own set of runtime types that will supercede this.
See comments in LowerTensorLoadOp for more direction about where this is
going to evolve.
This uses an approach inspired by what is done in IREE. See comments on
LowerRankedShapes.cpp for how it works.
The basic gist is that we have an op that creates a !shape.shape from a
set of SSA values representing the extents, and then iteratively replace
any op producing a !shape.shape with instances of that op.
Sean Silva