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[mlir][transform] Emit error message with emitSilenceableFailure (#86146)

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The previous implementation used a `notifyMatchFailure` to emit failure
message inappropriately and then used the
`emitDefaultSilenceableFailure`. This patch changes this to use the more
appropriate `emitSilenceableFailure` with error message. Additionally a
failure test has been added.
This commit is contained in:
srcarroll 2024-03-22 12:37:39 -05:00 committed by GitHub
parent 36a6afdd2c
commit bbcfe6f431
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GPG Key ID: B5690EEEBB952194
2 changed files with 41 additions and 6 deletions
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14
mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp
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@ -3269,22 +3269,24 @@ DiagnosedSilenceableFailure transform::FlattenElementwiseLinalgOp::applyToOne(
transform::ApplyToEachResultList &results,
transform::TransformState &state) {
rewriter.setInsertionPoint(target);
if (!isElementwise(target)) {
failed(rewriter.notifyMatchFailure(
target, "only elementwise flattening is supported"));
return emitDefaultSilenceableFailure(target);
}
if (!isElementwise(target))
return mlir::emitSilenceableFailure(target->getLoc())
<< "only elementwise flattening is supported";
// If rank <= 1, do nothing
if (target.getNumLoops() <= 1) {
results.push_back(target);
return DiagnosedSilenceableFailure::success();
}
// Attempt to flatten all dims to one.
ReassociationIndices reassociation(target.getNumLoops());
std::iota(reassociation.begin(), reassociation.end(), 0);
auto maybeFlattened =
collapseOpIterationDims(target, reassociation, rewriter);
if (failed(maybeFlattened))
return emitDefaultSilenceableFailure(target);
return mlir::emitSilenceableFailure(target->getLoc())
<< "attempted to flatten, but failed";
results.push_back(maybeFlattened->collapsedOp);
rewriter.replaceOp(target, maybeFlattened->results);
return DiagnosedSilenceableFailure::success();

33
mlir/test/Dialect/Linalg/flatten-unsupported.mlir Normal file
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@ -0,0 +1,33 @@
// RUN: mlir-opt %s -transform-interpreter -split-input-file -verify-diagnostics
func.func @non_elementwise(%arg0: memref<2x3xf32>, %arg1: memref<3x4xf32>, %arg2: memref<2x4xf32>) {
// expected-error @below {{only elementwise flattening is supported}}
linalg.matmul ins(%arg0, %arg1 : memref<2x3xf32>, memref<3x4xf32>) outs(%arg2: memref<2x4xf32>)
return
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op
%flattened = transform.structured.flatten_elementwise %0
: (!transform.any_op) -> !transform.any_op
transform.yield
}
}
// -----
func.func @unsupported_memref(%arg0: memref<32x7xf32, strided<[7, 2]>>, %arg1: memref<32x7xf32, strided<[7, 2]>>, %arg2: memref<32x7xf32, strided<[7, 2]>>) {
// expected-error @below {{attempted to flatten, but failed}}
linalg.map {arith.addf} ins(%arg0, %arg1: memref<32x7xf32, strided<[7, 2]>>, memref<32x7xf32, strided<[7, 2]>>) outs(%arg2: memref<32x7xf32, strided<[7, 2]>>)
return
}
module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
%0 = transform.structured.match interface{LinalgOp} in %arg1 : (!transform.any_op) -> !transform.any_op
%flattened = transform.structured.flatten_elementwise %0
: (!transform.any_op) -> !transform.any_op
transform.yield
}
}