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[mlir][sparse] Add optional start_value to sparse_tensor.init
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Authored by jim22k on May 24 2022, 2:58 PM.

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aartbik
Summary

The start value will be used during reductions instead of assuming that
the initial value is zero, allowing e.g. multiplication during
a reduction which needs 1.0 as the starting value rather than 0.0.

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jim22k created this revision.May 24 2022, 2:58 PM
jim22k requested review of this revision.May 24 2022, 2:58 PM

I plan to add custom reduction using sparse_tensor.binary later. This PR will focus solely on explicit starting values for non-custom reductions.

mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td
77

I am unhappy with the need to specify the type of startValue. It should always be the same as the result's element type. However, I tried several iterations of TypesMatchWith trait and custom builders and couldn't get it to work. I think it is because startValue is optional, so the inferring of type is tricky.

Requiring the type to be specified works, but if someone knows how to eliminate this, I think it would look better.

aartbik added inline comments.May 26 2022, 5:17 PM
mlir/include/mlir/Dialect/SparseTensor/IR/SparseTensorOps.td
64

replace "the" before unitialized with "an"

66

Perhaps give a small motivation for this

77

I can't think of an easy way around either (others?).

But I think it is okay, MLIR is not really a programming language in the sense that our syntax needs to be as concise as possible. Sometimes we over state the types.

mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
236

this will need an invalid.mlir case

also, the new syntax needs an roundtrip.mlir

Note that there is this parallel effort to unify our tensor initialization ops (see https://reviews.llvm.org/D126180).
So let's brainstorm offline to come up with another solution.

jim22k abandoned this revision.Thu, Jun 2, 10:19 AM

With the removal of sparse_tensor.init operation, this change no longer makes sense.

@aartbik and I discussed an alternative to create a new sparse_tensor.reduce operation which will accept a start value.