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Commit 10933808 authored by Nicolas Vasilache's avatar Nicolas Vasilache Committed by A. Unique TensorFlower
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Relax restriction on affine_apply dim and symbol operands

The affine_apply operation is currently "doubly" affine and conflates two things:
1. it applies an affine map to a list of values of type `index` that are defined as either dim or symbol
2. it restricts (and propagates constraints on) the provenance of dims and symbols to a small subset of ops for which more restrictive polyhedral constraints apply.

Point 2. is related to the ability to form so-called static control parts and is related to dependence analysis and legality of transformations.

Point 1. however is completely independent, the only local implication of dims and symbol for affine_apply is that dims compose while symbols concatenate as well as the structural constraint that dims may not be multiplied.

The properties of composition and canonicalization in affine_apply are more generally useful. This CL relaxes the verifier on affine_apply so it can be used more generally.

The relevant affine.for/if/load/store op verifiers already implement the dim and symbol checking.

See this thread for the related discussion: https://groups.google.com/a/tensorflow.org/g/mlir/c/HkwCbV8D9N0/m/8srUNrX6CAAJ

PiperOrigin-RevId: 282562517
parent a50f871e
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