- Make rank1.mlir be the new "basic.mlir", as it is really the simplest
case.
- Move basic.mlir to mixed-ranks.mlir
- Delete starting-from-linalg.mlir, it wasn't really useful anymore.
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.
This also adds a small pass to clean up the `dim` ops that linalg
introduces. For now, it only has a trivial pattern that looks for a
`tcp.alloc_memref(%shape)` op to get the shape as we currently have an
invariant that all memrefs are the result of such ops.
But eventually this will need to look through view ops and any other
shape-ish stuff that linalg introduces as it lowers to loops, along with
any slicing ops introduced by buffer allocation.
There's a lot of details to flesh out here, but the basic approach seems
promising (see comments in createE2ELoweringPipeline).
This approach will be put to the test when we try to do our first
fusions since that tickles some of the nasty phase ordering issues
involved here.
But we're not there yet.
This makes sure we stay resonably canonically using the shape machinery.
(In fact, DimOp should probably be in the shape dialect since it hides a
`shape.shape_of` call)
We should look into having a `ninja check-npcomp` that runs everything
with lit so that we get decent test multithreading.
We can look to how LLVM does its gtest tests ("unittests") for
inspiration.
* This suppresses a warning that arises from using "-m" to launch a module contained in a package that arranges modules via __init__.py. It seems irrelevant to the use case of running doctests.
* This is intended to provide low-level modeling for built-in objects.
* It is now possible to trace slice tuples (which are tuples of NoneType|EllipsisType|SlotObjectType<slice, ...>).
* Creates an abstraction/registry around emitters (intended to generalize to AST compilation as well).
* Reworks ufuncs to use the same mechanism as array funcs.
* Adds the numpy.dot op.
Sean Silva
Stella Laurenzo