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
Change-Id: Ie165275f134beaebbff2992e62442ce590dd6b36
diff --git a/third_party/mlir/lib/Dialect/AffineOps/AffineOps.cpp b/third_party/mlir/lib/Dialect/AffineOps/AffineOps.cpp
index ae219c7..2cd357f 100644
--- a/third_party/mlir/lib/Dialect/AffineOps/AffineOps.cpp
+++ b/third_party/mlir/lib/Dialect/AffineOps/AffineOps.cpp
@@ -285,11 +285,6 @@
if (!getResult()->getType().isIndex())
return emitOpError("result must be of type 'index'");
- // Verify that the operands are valid dimension and symbol identifiers.
- if (failed(verifyDimAndSymbolIdentifiers(*this, getOperands(),
- map.getNumDims())))
- return failure();
-
// Verify that the map only produces one result.
if (map.getNumResults() != 1)
return emitOpError("mapping must produce one value");
