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[mlir][vector][nfc] Replace failure() with notifyMatchFailure() #129278

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Merged
merged 2 commits into from
Mar 6, 2025
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[mlir][vector][nfc] Replace failure() with notifyMatchFailure() #129278

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1da3e18
[mlir][vector][nfc] Replace `failure()` with `notifyMatchFailure()`
banach-space Feb 28, 2025
68aa29d
fixup! [mlir][vector][nfc] Replace `failure()` with `notifyMatchFailu…
banach-space Mar 6, 2025
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44 changes: 25 additions & 19 deletions mlir/lib/Conversion/VectorToSCF/VectorToSCF.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -549,22 +549,26 @@ struct Strategy<TransferWriteOp> {
};

template <typename OpTy>
LogicalResult checkPrepareXferOp(OpTy xferOp,
VectorTransferToSCFOptions options) {
static LogicalResult checkPrepareXferOp(OpTy xferOp, PatternRewriter &rewriter,
VectorTransferToSCFOptions options) {
if (xferOp->hasAttr(kPassLabel))
return failure();
return rewriter.notifyMatchFailure(
xferOp, "kPassLabel is present (vector-to-scf lowering in progress)");
if (xferOp.getVectorType().getRank() <= options.targetRank)
return failure();
// Currently the unpacking of the leading dimension into the memref is not
// supported for scalable dimensions.
return rewriter.notifyMatchFailure(
xferOp, "xferOp vector rank <= transformation target rank");
if (xferOp.getVectorType().getScalableDims().front())
return failure();
return rewriter.notifyMatchFailure(
xferOp, "Unpacking of the leading dimension into the memref is not yet "
"supported for scalable dims");
if (isTensorOp(xferOp) && !options.lowerTensors)
return failure();
// Transfer ops that modify the element type are not supported atm.
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Should we retain this comment if it gives additional info?

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Oh, I just moved the comment inside rewriter.notifyMatchFailure (with some tweaks):

// BEFORE
// Transfer ops that modify the element type are not supported atm.
  if (xferOp.getVectorType().getElementType() !=
      xferOp.getShapedType().getElementType())
    return failure();
// AFTER
  if (xferOp.getVectorType().getElementType() !=
      xferOp.getShapedType().getElementType())
    return rewriter.notifyMatchFailure(
        xferOp, "Mismatching source and destination element types.");

return rewriter.notifyMatchFailure(
xferOp, "Unpacking for tensors has been disabled.");
if (xferOp.getVectorType().getElementType() !=
xferOp.getShapedType().getElementType())
return failure();
return rewriter.notifyMatchFailure(
xferOp, "Mismatching source and destination element types.");

return success();
}

Expand Down Expand Up @@ -597,8 +601,9 @@ struct PrepareTransferReadConversion

LogicalResult matchAndRewrite(TransferReadOp xferOp,
PatternRewriter &rewriter) const override {
if (checkPrepareXferOp(xferOp, options).failed())
return failure();
if (checkPrepareXferOp(xferOp, rewriter, options).failed())
return rewriter.notifyMatchFailure(
xferOp, "checkPrepareXferOp conditions not met!");

auto buffers = allocBuffers(rewriter, xferOp);
auto *newXfer = rewriter.clone(*xferOp.getOperation());
Expand Down Expand Up @@ -646,8 +651,9 @@ struct PrepareTransferWriteConversion

LogicalResult matchAndRewrite(TransferWriteOp xferOp,
PatternRewriter &rewriter) const override {
if (checkPrepareXferOp(xferOp, options).failed())
return failure();
if (checkPrepareXferOp(xferOp, rewriter, options).failed())
return rewriter.notifyMatchFailure(
xferOp, "checkPrepareXferOp conditions not met!");

Location loc = xferOp.getLoc();
auto buffers = allocBuffers(rewriter, xferOp);
Expand Down Expand Up @@ -903,15 +909,17 @@ struct TransferOpConversion : public VectorToSCFPattern<OpTy> {
LogicalResult matchAndRewrite(OpTy xferOp,
PatternRewriter &rewriter) const override {
if (!xferOp->hasAttr(kPassLabel))
return failure();
return rewriter.notifyMatchFailure(
xferOp, "kPassLabel is present (progressing lowering in progress)");

// Find and cast data buffer. How the buffer can be found depends on OpTy.
ImplicitLocOpBuilder locB(xferOp.getLoc(), rewriter);
Value dataBuffer = Strategy<OpTy>::getBuffer(xferOp);
auto dataBufferType = dyn_cast<MemRefType>(dataBuffer.getType());
FailureOr<MemRefType> castedDataType = unpackOneDim(dataBufferType);
if (failed(castedDataType))
return failure();
return rewriter.notifyMatchFailure(xferOp,
"Failed to unpack one vector dim.");

auto castedDataBuffer =
locB.create<vector::TypeCastOp>(*castedDataType, dataBuffer);
Expand Down Expand Up @@ -1294,16 +1302,14 @@ struct UnrollTransferReadConversion
xferOp, "vector rank is less or equal to target rank");
if (failed(checkLowerTensors(xferOp, rewriter)))
return failure();
// Transfer ops that modify the element type are not supported atm.
if (xferOp.getVectorType().getElementType() !=
xferOp.getShapedType().getElementType())
return rewriter.notifyMatchFailure(
xferOp, "not yet supported: element type mismatch");
auto xferVecType = xferOp.getVectorType();
if (xferVecType.getScalableDims()[0]) {
// Cannot unroll a scalable dimension at compile time.
return rewriter.notifyMatchFailure(
xferOp, "scalable dimensions cannot be unrolled");
xferOp, "scalable dimensions cannot be unrolled at compile time");
}

auto insertOp = getInsertOp(xferOp);
Expand Down