[ADT][mlir][NFCI] Do not use non-const lvalue-refs with enumerate

[kuhar]

Summary

Replace references to enumerate results with either result_pairs
(reference wrapper type) or structured bindings. I did not use
structured bindings everywhere as it wasn't clear to me it would
improve readability.

This is in preparation to the switch to zip semantics which won't
support non-const lvalue reference to elements:
https://reviews.llvm.org/D144503.

I chose to use values instead of const lvalue-refs because MLIR is
biased towards avoiding const local variables. This won't degrade
performance because currently result_pair is cheap to copy (size_t
+ iterator), and in the future, the enumerator iterator dereference
will return temporaries anyway.

[dblaikie]

Looks good, thanks!

mlir/lib/Analysis/DataFlow/SparseAnalysis.cpp

for (Block::pred_iterator it = block->pred_begin(), e = block->pred_end();
     if (!edgeExecutable->isLive())
       continue;
 
     // Check if we can reason about the data-flow from the predecessor.
     if (auto branch =
             dyn_cast<BranchOpInterface>(predecessor->getTerminator())) {
       SuccessorOperands operands =
           branch.getSuccessorOperands(it.getSuccessorIndex());
-      for (auto &it : llvm::enumerate(argLattices)) {
-        if (Value operand = operands[it.index()]) {
-          join(it.value(), *getLatticeElementFor(block, operand));
+      for (auto [idx, lattice] : llvm::enumerate(argLattices)) {
+        if (Value operand = operands[idx]) {
+          join(lattice, *getLatticeElementFor(block, operand));
         } else {
           // Conservatively consider internally produced arguments as entry
           // points.
-          setAllToEntryStates(it.value());
+          setAllToEntryStates(lattice);
         }
       }
     } else {
       return setAllToEntryStates(argLattices);
     }
   }
 }
 

mlir/lib/Bytecode/Writer/IRNumbering.cpp

for (unsigned i = 1; i < 9; ++i) {
     dialectToOrderFirst = byteSubRange.back()->dialect->number;
 
     // If the data range is now empty, we are done.
     if (iterRange.empty())
       break;
   }
 
   // Assign the entry numbers based on the sort order.
-  for (auto &entry : llvm::enumerate(range))
-    entry.value()->number = entry.index();
+  for (auto [idx, value] : llvm::enumerate(range))
+    value->number = idx;
 }
 
 IRNumberingState::IRNumberingState(Operation *op) {
   // Number the root operation.
   number(*op);
 
   // Push all of the regions of the root operation onto the worklist.
   SmallVector<std::pair<Region *, unsigned>, 8> numberContext;
for (Operation &op : region->getOps()) {
         numberContext.emplace_back(&region, opFirstValueID);
     }
   }
 
   // Number each of the dialects. For now this is just in the order they were
   // found, given that the number of dialects on average is small enough to fit
   // within a singly byte (128). If we ever have real world use cases that have
   // a huge number of dialects, this could be made more intelligent.
-  for (auto &it : llvm::enumerate(dialects))
-    it.value().second->number = it.index();
+  for (auto [idx, dialect] : llvm::enumerate(dialects))
+    dialect.second->number = idx;
 
   // Number each of the recorded components within each dialect.
 
   // First sort by ref count so that the most referenced elements are first. We
   // try to bias more heavily used elements to the front. This allows for more
   // frequently referenced things to be encoded using smaller varints.
   auto sortByRefCountFn = [](const auto &lhs, const auto &rhs) {
     return lhs->refCount > rhs->refCount;

 
 void IRNumberingState::number(Region &region) {
   if (region.empty())
     return;
   size_t firstValueID = nextValueID;
 
   // Number the blocks within this region.
   size_t blockCount = 0;
-  for (auto &it : llvm::enumerate(region)) {
+  for (auto it : llvm::enumerate(region)) {
     blockIDs.try_emplace(&it.value(), it.index());
     number(it.value());
     ++blockCount;
   }
 
   // Remember the number of blocks and values in this region.
   regionBlockValueCounts.try_emplace(&region, blockCount,
                                      nextValueID - firstValueID);

mlir/lib/Conversion/AMDGPUToROCDL/AMDGPUToROCDL.cpp

matchAndRewrite(GpuOp gpuOp, typename GpuOp::Adaptor adaptor,
     Value word3Const = createI32Constant(rewriter, loc, word3);
     resource = rewriter.create<LLVM::InsertElementOp>(
         loc, llvm4xI32, resource, word3Const,
         this->createIndexConstant(rewriter, loc, 3));
     args.push_back(resource);
 
     // Indexing (voffset)
     Value voffset;
-    for (auto &pair : llvm::enumerate(adaptor.getIndices())) {
+    for (auto pair : llvm::enumerate(adaptor.getIndices())) {
       size_t i = pair.index();
       Value index = pair.value();
       Value strideOp;
       if (ShapedType::isDynamic(strides[i])) {
         strideOp = rewriter.create<LLVM::MulOp>(
             loc, memrefDescriptor.stride(rewriter, loc, i), byteWidthConst);
       } else {
         strideOp =

mlir/lib/Conversion/FuncToLLVM/FuncToLLVM.cpp

auto wrapperFuncOp = rewriter.create<LLVM::LLVMFuncOp>(
       wrapperFuncType, LLVM::Linkage::External, /*dsoLocal*/ false,
       /*cconv*/ LLVM::CConv::C, attributes);
 
   OpBuilder::InsertionGuard guard(rewriter);
   rewriter.setInsertionPointToStart(wrapperFuncOp.addEntryBlock());
 
   SmallVector<Value, 8> args;
   size_t argOffset = resultStructType ? 1 : 0;
-  for (auto &[index, argType] : llvm::enumerate(type.getInputs())) {
+  for (auto [index, argType] : llvm::enumerate(type.getInputs())) {
     Value arg = wrapperFuncOp.getArgument(index + argOffset);
     if (auto memrefType = argType.dyn_cast<MemRefType>()) {
       Value loaded = rewriter.create<LLVM::LoadOp>(
           loc, typeConverter.convertType(memrefType), arg);
       MemRefDescriptor::unpack(rewriter, loc, loaded, memrefType, args);
       continue;
     }
     if (argType.isa<UnrankedMemRefType>()) {
Value one = builder.create<LLVM::ConstantOp>(
         builder.getIntegerAttr(builder.getIndexType(), 1));
     Value result =
         builder.create<LLVM::AllocaOp>(loc, resultType, resultStructType, one);
     args.push_back(result);
   }
 
   // Iterate over the inputs of the original function and pack values into
   // memref descriptors if the original type is a memref.
-  for (auto &en : llvm::enumerate(type.getInputs())) {
+  for (Type input : type.getInputs()) {
     Value arg;
     int numToDrop = 1;
-    auto memRefType = en.value().dyn_cast<MemRefType>();
-    auto unrankedMemRefType = en.value().dyn_cast<UnrankedMemRefType>();
+    auto memRefType = input.dyn_cast<MemRefType>();
+    auto unrankedMemRefType = input.dyn_cast<UnrankedMemRefType>();
     if (memRefType || unrankedMemRefType) {
       numToDrop = memRefType
                       ? MemRefDescriptor::getNumUnpackedValues(memRefType)
                       : UnrankedMemRefDescriptor::getNumUnpackedValues();
       Value packed =
           memRefType
               ? MemRefDescriptor::pack(builder, loc, typeConverter, memRefType,
                                        wrapperArgsRange.take_front(numToDrop))
matchAndRewrite(func::ReturnOp op, OpAdaptor adaptor,
     }
 
     // Otherwise, we need to pack the arguments into an LLVM struct type before
     // returning.
     auto packedType =
         getTypeConverter()->packFunctionResults(op.getOperandTypes());
 
     Value packed = rewriter.create<LLVM::UndefOp>(loc, packedType);
-    for (auto &it : llvm::enumerate(updatedOperands)) {
-      packed = rewriter.create<LLVM::InsertValueOp>(loc, packed, it.value(),
-                                                    it.index());
+    for (auto [idx, operand] : llvm::enumerate(updatedOperands)) {
+      packed = rewriter.create<LLVM::InsertValueOp>(loc, packed, operand, idx);
     }
     rewriter.replaceOpWithNewOp<LLVM::ReturnOp>(op, TypeRange(), packed,
                                                 op->getAttrs());
     return success();
   }
 };
 } // namespace
 

mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp

 Type LLVMTypeConverter::convertFunctionSignature(
     FunctionType funcTy, bool isVariadic,
     LLVMTypeConverter::SignatureConversion &result) {
   // Select the argument converter depending on the calling convention.
   auto funcArgConverter = options.useBarePtrCallConv
                               ? barePtrFuncArgTypeConverter
                               : structFuncArgTypeConverter;
   // Convert argument types one by one and check for errors.
-  for (auto &en : llvm::enumerate(funcTy.getInputs())) {
-    Type type = en.value();
+  for (auto [idx, type] : llvm::enumerate(funcTy.getInputs())) {
     SmallVector<Type, 8> converted;
     if (failed(funcArgConverter(*this, type, converted)))
       return {};
-    result.addInputs(en.index(), converted);
+    result.addInputs(idx, converted);
   }
 
   // If function does not return anything, create the void result type,
   // if it returns on element, convert it, otherwise pack the result types into
   // a struct.
   Type resultType = funcTy.getNumResults() == 0
                         ? LLVM::LLVMVoidType::get(&getContext())
                         : packFunctionResults(funcTy.getResults());

mlir/lib/Conversion/PDLToPDLInterp/PredicateTree.cpp

for (const auto &operandIt : llvm::enumerate(operands)) {
               : builder.getOperand(opPos, operandIt.index());
       getTreePredicates(predList, operandIt.value(), builder, inputs, pos);
     }
   }
   /// Results.
   if (types.size() == 1 && types[0].getType().isa<pdl::RangeType>()) {
     getTreePredicates(predList, types.front(), builder, inputs,
                       builder.getType(builder.getAllResults(opPos)));
-  } else {
-    bool foundVariableLength = false;
-    for (auto &resultIt : llvm::enumerate(types)) {
-      bool isVariadic = resultIt.value().getType().isa<pdl::RangeType>();
-      foundVariableLength |= isVariadic;
+    return;
+  }
+
+  for (auto [idx, typeValue] : llvm::enumerate(types)) {
+    bool isVariadic = typeValue.getType().isa<pdl::RangeType>();
 
-      auto *resultPos =
-          foundVariableLength
-              ? builder.getResultGroup(pos, resultIt.index(), isVariadic)
-              : builder.getResult(pos, resultIt.index());
-      predList.emplace_back(resultPos, builder.getIsNotNull());
-      getTreePredicates(predList, resultIt.value(), builder, inputs,
-                        builder.getType(resultPos));
-    }
-  }
-}
+    auto *resultPos = foundVariableLength
+                          ? builder.getResultGroup(pos, idx, isVariadic)
+                          : builder.getResult(pos, idx);
+    getTreePredicates(predList, typeValue, builder, inputs,
 
 static void getTreePredicates(std::vector<PositionalPredicate> &predList,
                               Value val, PredicateBuilder &builder,
                               DenseMap<Value, Position *> &inputs,
                               TypePosition *pos) {
   // Check for a constraint on a constant type.
   if (pdl::TypeOp typeOp = val.getDefiningOp<pdl::TypeOp>()) {
     if (Attribute type = typeOp.getConstantTypeAttr())

mlir/lib/Dialect/Affine/Analysis/Utils.cpp

 }
 
 void ComputationSliceState::dump() const {
   llvm::errs() << "\tIVs:\n";
   for (Value iv : ivs)
     llvm::errs() << "\t\t" << iv << "\n";
 
   llvm::errs() << "\tLBs:\n";
-  for (auto &en : llvm::enumerate(lbs)) {
+  for (auto en : llvm::enumerate(lbs)) {
     llvm::errs() << "\t\t" << en.value() << "\n";
     llvm::errs() << "\t\tOperands:\n";
     for (Value lbOp : lbOperands[en.index()])
       llvm::errs() << "\t\t\t" << lbOp << "\n";
   }
 
   llvm::errs() << "\tUBs:\n";
-  for (auto &en : llvm::enumerate(ubs)) {
+  for (auto en : llvm::enumerate(ubs)) {
     llvm::errs() << "\t\t" << en.value() << "\n";
     llvm::errs() << "\t\tOperands:\n";
     for (Value ubOp : ubOperands[en.index()])
       llvm::errs() << "\t\t\t" << ubOp << "\n";
   }
 }
 
 /// Fast check to determine if the computation slice is maximal. Returns true if

mlir/lib/Dialect/LLVMIR/IR/LLVMDialect.cpp

OpFoldResult LLVM::GEPOp::fold(FoldAdaptor adaptor) {
   if (getBase().getType() == getType() && indices.size() == 1)
     if (auto integer = indices[0].dyn_cast_or_null<IntegerAttr>())
       if (integer.getValue().isZero())
         return getBase();
 
   // Canonicalize any dynamic indices of constant value to constant indices.
   bool changed = false;
   SmallVector<GEPArg> gepArgs;
-  for (auto &iter : llvm::enumerate(indices)) {
+  for (auto iter : llvm::enumerate(indices)) {
     auto integer = iter.value().dyn_cast_or_null<IntegerAttr>();
     // Constant indices can only be int32_t, so if integer does not fit we
     // are forced to keep it dynamic, despite being a constant.
     if (!indices.isDynamicIndex(iter.index()) || !integer ||
         !integer.getValue().isSignedIntN(kGEPConstantBitWidth)) {
 
       PointerUnion<IntegerAttr, Value> existing = getIndices()[iter.index()];
       if (Value val = existing.dyn_cast<Value>())

mlir/lib/Dialect/Linalg/TransformOps/LinalgTransformOps.cpp

for (Operation *op : dynamicSizeProducers.back()) {
       diag.attachNote(transformValue.getLoc()) << "for this handle";
       return diag;
     }
   }
 
   SmallVector<Operation *> tiled;
   SmallVector<SmallVector<Operation *, 4>, 4> loops;
   loops.resize(getLoops().size());
-  for (auto &[i, op] : llvm::enumerate(targets)) {
+  for (auto [i, op] : llvm::enumerate(targets)) {
     auto tilingInterface = dyn_cast<TilingInterface>(op);
     auto dpsInterface = dyn_cast<DestinationStyleOpInterface>(op);
     if (!tilingInterface || !dpsInterface) {
       DiagnosedSilenceableFailure diag =
           emitSilenceableError() << "only ops implementing TilingInterface and "
                                     "DestinationStyleOpInterface are supported";
       diag.attachNote(op->getLoc()) << "target op";
       return diag;
for (Operation *op : dynamicSizeProducers.back()) {
       diag.attachNote(dynamicSizeProducerHandle.getLoc()) << "for this handle";
       return diag;
     }
   }
 
   SmallVector<Operation *> tiled;
   SmallVector<SmallVector<Operation *, 4>, 4> loops;
   loops.resize(getLoops().size());
-  for (auto &en : llvm::enumerate(targets)) {
+  for (auto en : llvm::enumerate(targets)) {
     auto tilingInterfaceOp = dyn_cast<TilingInterface>(en.value());
     if (!tilingInterfaceOp) {
       DiagnosedSilenceableFailure diag =
           emitSilenceableError() << "only TilingInterface ops are supported";
       diag.attachNote(en.value()->getLoc()) << "target op";
       return diag;
     }
 

mlir/lib/Dialect/Linalg/Transforms/SplitReduction.cpp

FailureOr<SplitReductionResult> mlir::linalg::splitReduction(
   Value constantOp = b.create<arith::ConstantOp>(loc, *identity);
   Value identityTensor =
       b.create<linalg::FillOp>(op->getLoc(), constantOp, emptyOrAllocTensor)
           .getResult(0);
 
   newMaps.push_back(AffineMap::get(oldOutputMap.getNumDims() + 1, 0, outputExpr,
                                    op.getContext()));
   SmallVector<utils::IteratorType> newIteratorTypes;
-  for (auto &it : llvm::enumerate(op.getIteratorTypesArray())) {
-    if (insertSplitDimension == it.index())
+  for (auto [index, iteratorType] :
+       llvm::enumerate(op.getIteratorTypesArray())) {
+    if (insertSplitDimension == index)
       newIteratorTypes.push_back(utils::IteratorType::parallel);
-    newIteratorTypes.push_back(it.value());
+    newIteratorTypes.push_back(iteratorType);
   }
   if (insertSplitDimension == op.getIteratorTypesArray().size()) {
     newIteratorTypes.push_back(utils::IteratorType::parallel);
   }
   // Create the new op matching the original op with an extra parallel
   // dimension.
   GenericOp genericOp = b.create<GenericOp>(
       loc, TypeRange({emptyOrAllocTensor.getType()}), newInputs,

mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp

for (unsigned idx = 0, e = tileSizes.size(); idx < e; ++idx)
     res.push_back(Range{b.getIndexAttr(0), shapeSizes[idx], tileSizes[idx]});
   return std::make_tuple(res, loopIndexToRangeIndex);
 }
 
 void mlir::linalg::transformIndexOps(
     RewriterBase &b, LinalgOp op, SmallVectorImpl<Value> &ivs,
     const LoopIndexToRangeIndexMap &loopIndexToRangeIndex) {
   SmallVector<Value> allIvs(op.getNumLoops(), nullptr);
-  for (auto &en : enumerate(allIvs)) {
+  for (auto en : enumerate(allIvs)) {
     auto rangeIndex = loopIndexToRangeIndex.find(en.index());
     if (rangeIndex == loopIndexToRangeIndex.end())
       continue;
     en.value() = ivs[rangeIndex->second];
   }
   offsetIndices(b, op, getAsOpFoldResult(allIvs));
 }
 

mlir/lib/Dialect/Linalg/Transforms/TilingInterfaceImpl.cpp

Operation *tileToPartialReduction(Operation *op, OpBuilder &b, Location loc,
     auto linalgOp = cast<LinalgOp>(op);
     assert(reductionDims.size() == 1 &&
            "only support single reduction right now.");
     int64_t insertSplitDimension = reductionDims[0];
 
     AffineMap oldOutputMap =
         linalgOp.getMatchingIndexingMap(linalgOp.getDpsInitOperand(0));
     SmallVector<AffineExpr> outputExpr;
-    for (auto &[idx, expr] : llvm::enumerate(oldOutputMap.getResults())) {
+    for (auto [idx, expr] : llvm::enumerate(oldOutputMap.getResults())) {
       if (static_cast<int64_t>(idx) == insertSplitDimension) {
         outputExpr.push_back(b.getAffineDimExpr(reductionDims[0]));
       }
       outputExpr.push_back(expr);
     }
     if (insertSplitDimension == oldOutputMap.getNumResults())
       outputExpr.push_back(b.getAffineDimExpr(reductionDims[0]));
 

mlir/lib/Dialect/SCF/IR/SCF.cpp

for (auto [idx, result, operand] :
                  .attachNote(yield.getLoc())
              << name << " returns " << operand << " here";
     }
     return success();
   };
 
   if (failed(verifyRegion(getDefaultRegion(), "default region")))
     return failure();
-  for (auto &[idx, caseRegion] : llvm::enumerate(getCaseRegions()))
+  for (auto [idx, caseRegion] : llvm::enumerate(getCaseRegions()))
     if (failed(verifyRegion(caseRegion, "case region #" + Twine(idx))))
       return failure();
 
   return success();
 }
 
 unsigned scf::IndexSwitchOp::getNumCases() { return getCases().size(); }
 

mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp

LogicalResult matchAndRewrite(ReshapeOp op,
     SmallVector<Value> dstDynSizes;
     if (dstTp.hasStaticShape()) {
       for (auto d : dstTp.getShape())
         dstSizes.push_back(constantIndex(rewriter, loc, d));
     } else {
       ArrayRef<int64_t> dstShape = dstTp.getShape();
       genReshapeDstShape(loc, rewriter, dstSizes, srcSizes, dstShape,
                          op.getReassociationIndices());
-      for (auto &d : llvm::enumerate(dstShape)) {
-        if (d.value() == ShapedType::kDynamic)
-          dstDynSizes.push_back(dstSizes[d.index()]);
+      for (auto [idx, shape] : llvm::enumerate(dstShape)) {
+        if (shape == ShapedType::kDynamic)
+          dstDynSizes.push_back(dstSizes[idx]);
       }
     }
 
     // Implement the sparse2sparse reshape as follows:
     //   %tmp = bufferization.alloc_tensor : unordered COO
     //   foreach srcCoords %srcTensor
     //     insert reshapeCvs(srcCoords), %tmp
     //   %t = sparse_tensor.cast %tmp

mlir/lib/Dialect/Tensor/IR/TensorOps.cpp

LogicalResult matchAndRewrite(PadOp padOp,
     }
 
     // 6) Combine the offsets of the two tensor::ExtractSliceOps. Find the
     // zero-offset and zero-padding tensor::ExtractSliceOp, tensor::PadOp pair
     // for every dimension, and use the offset the other pair. Fail if no
     // zero-offset and zero-padding tensor::ExtractSliceOp, tensor::PadOp pair
     // exists.
     SmallVector<OpFoldResult> newOffsets(rank, rewriter.getIndexAttr(0));
-    for (auto &en : enumerate(newOffsets)) {
+    for (auto en : enumerate(newOffsets)) {
       OpFoldResult innerOffset = innerSliceOp.getMixedOffsets()[en.index()];
       OpFoldResult outerOffset = outerSliceOp.getMixedOffsets()[en.index()];
       if (!innerDims.test(en.index()) &&
           (getConstantIntValue(innerOffset) == static_cast<int64_t>(0))) {
         en.value() = outerOffset;
         continue;
       }
       if (!outerDims.test(en.index()) &&
           (getConstantIntValue(outerOffset) == static_cast<int64_t>(0))) {
         en.value() = innerOffset;
         continue;
       }
       return rewriter.notifyMatchFailure(
           padOp, "cannot find zero-offset and zero-padding pair");
     }
 
     // 7) Combine the sizes of the two tensor::ExtractSliceOps. Take the size
     // of the outer tensor::ExtractSliceOp for the dimensions padded by the
     // outer tensor::PadOp and fail if the size of the inner
     // tensor::ExtractSliceOp does not match the size of the padded dimension.
     // Otherwise, take the size of the inner tensor::ExtractSliceOp.
     SmallVector<OpFoldResult> newSizes = innerSliceOp.getMixedSizes();
-    for (auto &en : enumerate(newSizes)) {
+    for (auto en : enumerate(newSizes)) {
       if (!outerDims.test(en.index()))
         continue;
       OpFoldResult sliceSize = innerSliceOp.getMixedSizes()[en.index()];
       int64_t sourceSize = innerSliceOp.getSourceType().getShape()[en.index()];
       assert(!ShapedType::isDynamic(sourceSize) &&
              "expected padded dimension to have a static size");
       if (getConstantIntValue(sliceSize) != sourceSize) {
         return rewriter.notifyMatchFailure(
             padOp, "cannot fold since the inner ExtractSliceOp size does not "
                    "match the size of the outer padding");
       }
       en.value() = outerSliceOp.getMixedSizes()[en.index()];
     }
 
     // Combine the high paddings of the two tensor::PadOps.
     SmallVector<OpFoldResult> newHighPad(rank, rewriter.getIndexAttr(0));
-    for (auto &en : enumerate(newHighPad)) {
+    for (auto en : enumerate(newHighPad)) {
       if (innerDims.test(en.index()))
         newHighPad[en.index()] = padOp.getMixedHighPad()[en.index()];
       if (outerDims.test(en.index()))
         newHighPad[en.index()] = outerPadOp.getMixedHighPad()[en.index()];
     }
 
     // Create a new tensor::ExtractSliceOp, tensor::PadOp pair that performs
     // the two paddings in one step.

mlir/lib/Dialect/Transform/IR/TransformInterfaces.cpp

void transform::detail::setApplyToOneResults(
   SmallVector<SmallVector<MappedValue>> transposed;
   transposed.resize(transformOp->getNumResults());
   for (const ApplyToEachResultList &partialResults : results) {
     if (llvm::any_of(partialResults,
                      [](MappedValue value) { return value.isNull(); }))
       continue;
     assert(transformOp->getNumResults() == partialResults.size() &&
            "expected as many partial results as op as results");
-    for (auto &[i, value] : llvm::enumerate(partialResults))
+    for (auto [i, value] : llvm::enumerate(partialResults))
       transposed[i].push_back(value);
   }
 
   for (OpResult r : transformOp->getResults()) {
     unsigned position = r.getResultNumber();
     if (r.getType().isa<TransformParamTypeInterface>()) {
       transformResults.setParams(r,
                                  castVector<Attribute>(transposed[position]));

mlir/lib/Dialect/Vector/Transforms/VectorDistribute.cpp

static WarpExecuteOnLane0Op moveRegionToNewWarpOpAndAppendReturns(
   llvm::SmallSetVector<Value, 32> yieldValues(yield.getOperands().begin(),
                                               yield.getOperands().end());
   for (auto newRet : llvm::zip(newYieldedValues, newReturnTypes)) {
     if (yieldValues.insert(std::get<0>(newRet))) {
       types.push_back(std::get<1>(newRet));
       indices.push_back(yieldValues.size() - 1);
     } else {
       // If the value already exit the region don't create a new output.
-      for (auto &yieldOperand : llvm::enumerate(yieldValues.getArrayRef())) {
-        if (yieldOperand.value() == std::get<0>(newRet)) {
-          indices.push_back(yieldOperand.index());
+      for (auto [idx, yieldOperand] :
+           llvm::enumerate(yieldValues.getArrayRef())) {
+        if (yieldOperand == std::get<0>(newRet)) {
+          indices.push_back(idx);
           break;
         }
       }
     }
   }
   yieldValues.insert(newYieldedValues.begin(), newYieldedValues.end());
   WarpExecuteOnLane0Op newWarpOp = moveRegionToNewWarpOpAndReplaceReturns(
       rewriter, warpOp, yieldValues.getArrayRef(), types);

mlir/lib/Dialect/Vector/Transforms/VectorUnroll.cpp

LogicalResult matchAndRewrite(vector::TransposeOp transposeOp,
     // of multiples of the targetShape.
     auto ratioStrides = computeStrides(ratio);
     for (int64_t i = 0; i < sliceCount; i++) {
       SmallVector<int64_t> elementOffsets =
           getVectorOffset(ratioStrides, i, *targetShape);
       SmallVector<int64_t> permutedOffsets(elementOffsets.size());
       SmallVector<int64_t> permutedShape(elementOffsets.size());
       // Compute the source offsets and shape.
-      for (auto &indices : llvm::enumerate(permutation)) {
+      for (auto indices : llvm::enumerate(permutation)) {
         permutedOffsets[indices.value()] = elementOffsets[indices.index()];
         permutedShape[indices.value()] = (*targetShape)[indices.index()];
       }
       Value slicedOperand = rewriter.create<vector::ExtractStridedSliceOp>(
           loc, transposeOp.getVector(), permutedOffsets, permutedShape,
           strides);
       Value transposedSlice =
           rewriter.create<vector::TransposeOp>(loc, slicedOperand, permutation);

mlir/lib/Dialect/X86Vector/Transforms/AVXTranspose.cpp

LogicalResult matchAndRewrite(vector::TransposeOp op,
 
     // Check if the source vector type is supported. AVX2 patterns can only be
     // applied to f32 vector types with two dimensions greater than one.
     VectorType srcType = op.getSourceVectorType();
     if (!srcType.getElementType().isF32())
       return rewriter.notifyMatchFailure(op, "Unsupported vector element type");
 
     SmallVector<int64_t> srcGtOneDims;
-    for (auto &en : llvm::enumerate(srcType.getShape()))
-      if (en.value() > 1)
-        srcGtOneDims.push_back(en.index());
+    for (auto [index, size] : llvm::enumerate(srcType.getShape()))
+      if (size > 1)
+        srcGtOneDims.push_back(index);
 
     if (srcGtOneDims.size() != 2)
       return rewriter.notifyMatchFailure(op, "Unsupported vector type");
 
     SmallVector<int64_t, 4> transp;
     for (auto attr : op.getTransp())
       transp.push_back(attr.cast<IntegerAttr>().getInt());
 

mlir/lib/ExecutionEngine/ExecutionEngine.cpp

for (auto &func : module->getFunctionList()) {
     // Extract the arguments from the type-erased argument list and cast them to
     // the proper types.
     auto *bb = llvm::BasicBlock::Create(ctx);
     bb->insertInto(interfaceFunc);
     builder.SetInsertPoint(bb);
     llvm::Value *argList = interfaceFunc->arg_begin();
     SmallVector<llvm::Value *, 8> args;
     args.reserve(llvm::size(func.args()));
-    for (auto &indexedArg : llvm::enumerate(func.args())) {
+    for (auto [index, arg] : llvm::enumerate(func.args())) {
       llvm::Value *argIndex = llvm::Constant::getIntegerValue(
-          builder.getInt64Ty(), APInt(64, indexedArg.index()));
+          builder.getInt64Ty(), APInt(64, index));
       llvm::Value *argPtrPtr =
           builder.CreateGEP(builder.getInt8PtrTy(), argList, argIndex);
       llvm::Value *argPtr =
           builder.CreateLoad(builder.getInt8PtrTy(), argPtrPtr);
-      llvm::Type *argTy = indexedArg.value().getType();
+      llvm::Type *argTy = arg.getType();
       argPtr = builder.CreateBitCast(argPtr, argTy->getPointerTo());
-      llvm::Value *arg = builder.CreateLoad(argTy, argPtr);
-      args.push_back(arg);
+      llvm::Value *load = builder.CreateLoad(argTy, argPtr);
+      args.push_back(load);
     }
 
     // Call the implementation function with the extracted arguments.
     llvm::Value *result = builder.CreateCall(&func, args);
 
     // Assuming the result is one value, potentially of type `void`.
     if (!result->getType()->isVoidTy()) {
       llvm::Value *retIndex = llvm::Constant::getIntegerValue(

mlir/lib/IR/AsmPrinter.cpp

 
 void OperationPrinter::printValueUsers(Value value) {
   if (value.use_empty())
     os << "unused";
 
   // One value might be used as the operand of an operation more than once.
   // Only print the operations results once in that case.
   SmallPtrSet<Operation *, 1> userSet;
-  for (auto &indexedUser : enumerate(value.getUsers())) {
-    if (userSet.insert(indexedUser.value()).second)
-      printUserIDs(indexedUser.value(), indexedUser.index());
+  for (auto [index, user] : enumerate(value.getUsers())) {
+    if (userSet.insert(user).second)
+      printUserIDs(user, index);
   }
 }
 
 void OperationPrinter::printUserIDs(Operation *user, bool prefixComma) {
   if (prefixComma)
     os << ", ";
 
   if (!user->getNumResults()) {

mlir/lib/Pass/PassStatistics.cpp

#if LLVM_ENABLE_STATS
       if (statistics.empty())
         return;
 
       auto &passEntry = mergedStats[pass->getName()];
       if (passEntry.empty()) {
         for (Pass::Statistic *it : pass->getStatistics())
           passEntry.push_back({it->getName(), it->getDesc(), it->getValue()});
       } else {
-        for (auto &it : llvm::enumerate(pass->getStatistics()))
-          passEntry[it.index()].value += it.value()->getValue();
+        for (auto [idx, statistic] : llvm::enumerate(pass->getStatistics()))
+          passEntry[idx].value += statistic->getValue();
       }
 #endif
       return;
     }
 
     // Otherwise, recursively add each of the children.
     for (auto &mgr : adaptor->getPassManagers())
       for (Pass &pass : mgr.getPasses())

mlir/lib/TableGen/Operator.cpp

void Operator::populateTypeInferenceInfo(
   };
 
   // This vector represents the type inference graph, with one node for each
   // operation result. The nth element is the node for the nth result.
   SmallVector<ResultTypeInference> inference(getNumResults(), {});
 
   // For all results whose types are buildable, initialize their type inference
   // nodes with an edge to themselves. Mark those nodes are fully-inferred.
-  for (auto &[idx, infer] : llvm::enumerate(inference)) {
+  for (auto [idx, infer] : llvm::enumerate(inference)) {
     if (getResult(idx).constraint.getBuilderCall()) {
       infer.sources.emplace_back(InferredResultType::mapResultIndex(idx),
                                  "$_self");
       infer.inferred = true;
     }
   }
 
   // Use `AllTypesMatch` and `TypesMatchWith` operation traits to build the

mlir/lib/Target/LLVMIR/ModuleTranslation.cpp

void mlir::LLVM::detail::connectPHINodes(Region &region,
                                          const ModuleTranslation &state) {
   // Skip the first block, it cannot be branched to and its arguments correspond
   // to the arguments of the LLVM function.
   for (Block &bb : llvm::drop_begin(region)) {
     llvm::BasicBlock *llvmBB = state.lookupBlock(&bb);
     auto phis = llvmBB->phis();
     auto numArguments = bb.getNumArguments();
     assert(numArguments == std::distance(phis.begin(), phis.end()));
-    for (auto &numberedPhiNode : llvm::enumerate(phis)) {
-      auto &phiNode = numberedPhiNode.value();
-      unsigned index = numberedPhiNode.index();
+    for (auto [index, phiNode] : llvm::enumerate(phis)) {
       for (auto *pred : bb.getPredecessors()) {
         // Find the LLVM IR block that contains the converted terminator
         // instruction and use it in the PHI node. Note that this block is not
         // necessarily the same as state.lookupBlock(pred), some operations
         // (in particular, OpenMP operations using OpenMPIRBuilder) may have
         // split the blocks.
         llvm::Instruction *terminator =
             state.lookupBranch(pred->getTerminator());

mlir/lib/Transforms/TopologicalSort.cpp

 using namespace mlir;
 
 namespace {
 struct TopologicalSortPass
     : public impl::TopologicalSortBase<TopologicalSortPass> {
   void runOnOperation() override {
     // Topologically sort the regions of the operation without SSA dominance.
     getOperation()->walk([](RegionKindInterface op) {
-      for (auto &it : llvm::enumerate(op->getRegions())) {
+      for (auto it : llvm::enumerate(op->getRegions())) {
         if (op.hasSSADominance(it.index()))
           continue;
         for (Block &block : it.value())
           sortTopologically(&block);
       }
     });
   }
 };
 } // end anonymous namespace
 
 std::unique_ptr<Pass> mlir::createTopologicalSortPass() {
   return std::make_unique<TopologicalSortPass>();
 }

mlir/lib/Transforms/Utils/ControlFlowSinkUtils.cpp

size_t mlir::controlFlowSink(
   return Sinker(shouldMoveIntoRegion, moveIntoRegion, domInfo)
       .sinkRegions(regions);
 }
 
 void mlir::getSinglyExecutedRegionsToSink(RegionBranchOpInterface branch,
                                           SmallVectorImpl<Region *> &regions) {
   // Collect constant operands.
   SmallVector<Attribute> operands(branch->getNumOperands(), Attribute());
-  for (auto &it : llvm::enumerate(branch->getOperands()))
-    (void)matchPattern(it.value(), m_Constant(&operands[it.index()]));
+  for (auto [idx, operand] : llvm::enumerate(branch->getOperands()))
+    (void)matchPattern(operand, m_Constant(&operands[idx]));
 
   // Get the invocation bounds.
   SmallVector<InvocationBounds> bounds;
   branch.getRegionInvocationBounds(operands, bounds);
 
   // For a simple control-flow sink, only consider regions that are executed at
   // most once.
   for (auto it : llvm::zip(branch->getRegions(), bounds)) {
     const InvocationBounds &bound = std::get<1>(it);
     if (bound.getUpperBound() && *bound.getUpperBound() <= 1)
       regions.push_back(&std::get<0>(it));
   }
 }

mlir/test/lib/Analysis/DataFlow/TestDenseDataFlowAnalysis.cpp

void runOnOperation() override {
     op->walk([&](Operation *op) {
       auto tag = op->getAttrOfType<StringAttr>("tag");
       if (!tag)
         return;
       os << "test_tag: " << tag.getValue() << ":\n";
       const LastModification *lastMods =
           solver.lookupState<LastModification>(op);
       assert(lastMods && "expected a dense lattice");
-      for (auto &it : llvm::enumerate(op->getOperands())) {
-        os << " operand #" << it.index() << "\n";
-        Value value = getMostUnderlyingValue(it.value(), [&](Value value) {
+      for (auto [index, operand] : llvm::enumerate(op->getOperands())) {
+        os << " operand #" << index << "\n";
+        Value value = getMostUnderlyingValue(operand, [&](Value value) {
           return solver.lookupState<UnderlyingValueLattice>(value);
         });
         assert(value && "expected an underlying value");
         if (std::optional<ArrayRef<Operation *>> lastMod =
                 lastMods->getLastModifiers(value)) {
           for (Operation *lastModifier : *lastMod) {
             if (auto tagName =
                     lastModifier->getAttrOfType<StringAttr>("tag_name")) {

mlir/tools/mlir-tblgen/AttrOrTypeFormatGen.cpp

private:
   /// Seen attribute or type parameters.
   BitVector seenParams;
 };
 } // namespace
 
 LogicalResult DefFormatParser::verify(SMLoc loc,
                                       ArrayRef<FormatElement *> elements) {
   // Check that all parameters are referenced in the format.
-  for (auto &it : llvm::enumerate(def.getParameters())) {
-    if (it.value().isOptional())
+  for (auto [index, param] : llvm::enumerate(def.getParameters())) {
+    if (param.isOptional())
       continue;
-    if (!seenParams.test(it.index())) {
-      if (isa<AttributeSelfTypeParameter>(it.value()))
+    if (!seenParams.test(index)) {
+      if (isa<AttributeSelfTypeParameter>(param))
         continue;
       return emitError(loc, "format is missing reference to parameter: " +
-                                it.value().getName());
+                                param.getName());
     }
-    if (isa<AttributeSelfTypeParameter>(it.value())) {
+    if (isa<AttributeSelfTypeParameter>(param)) {
       return emitError(loc,
                        "unexpected self type parameter in assembly format");
     }
   }
   if (elements.empty())
     return success();
   // A `struct` directive that contains optional parameters cannot be followed
   // by a comma literal, which is ambiguous.

mlir/tools/mlir-tblgen/EnumsGen.cpp

os << "  return p << '\"' << valueStr << '\"';\n"
           "} // namespace llvm\n";
     return;
   }
 
   // If there are any cases that can't be used with a keyword, switch on the
   // case value to determine when to print in the string form.
   if (nonKeywordCases.any()) {
     os << "  switch (value) {\n";
-    for (auto &it : llvm::enumerate(cases)) {
+    for (auto it : llvm::enumerate(cases)) {
       if (nonKeywordCases.test(it.index()))
         continue;
       StringRef symbol = it.value().getSymbol();
       os << llvm::formatv("  case {0}::{1}:\n", qualName,
                           makeIdentifier(symbol));
     }
     os << "    break;\n"
           "  default:\n"

mlir/tools/mlir-tblgen/OpDefinitionsGen.cpp

void OpEmitter::genAttrNameGetters() {
   return name.getAttributeNames()[index];
 )";
     method->body() << formatv(getAttrName, attributes.size());
   }
 
   // Generate the <attr>AttrName methods, that expose the attribute names to
   // users.
   const char *attrNameMethodBody = "  return getAttributeNameForIndex({0});";
-  for (auto &attrIt : llvm::enumerate(llvm::make_first_range(attributes))) {
-    std::string name = op.getGetterName(attrIt.value());
+  for (auto [index, attr] :
+       llvm::enumerate(llvm::make_first_range(attributes))) {
+    std::string name = op.getGetterName(attr);
     std::string methodName = name + "AttrName";
 
     // Generate the non-static variant.
     {
       auto *method = opClass.addInlineMethod("::mlir::StringAttr", methodName);
       ERROR_IF_PRUNED(method, methodName, op);
-      method->body() << llvm::formatv(attrNameMethodBody, attrIt.index());
+      method->body() << llvm::formatv(attrNameMethodBody, index);
     }
 
     // Generate the static variant.
     {
       auto *method = opClass.addStaticInlineMethod(
           "::mlir::StringAttr", methodName,
           MethodParameter("::mlir::OperationName", "name"));
       ERROR_IF_PRUNED(method, methodName, op);
       method->body() << llvm::formatv(attrNameMethodBody,
-                                      "name, " + Twine(attrIt.index()));
+                                      "name, " + Twine(index));
     }
   }
 }
 
 // Emit the getter for an attribute with the return type specified.
 // It is templated to be shared between the Op and the adaptor class.
 template <typename OpClassOrAdaptor>
 static void emitAttrGetterWithReturnType(FmtContext &fctx,
const auto canSkip = [](const NamedSuccessor &successor) {
     return successor.constraint.getPredicate().isNull();
   };
   auto successors = op.getSuccessors();
   if (successors.empty() && llvm::all_of(successors, canSkip))
     return;
 
   body << "  {\n    unsigned index = 0; (void)index;\n";
 
-  for (auto &it : llvm::enumerate(successors)) {
+  for (auto it : llvm::enumerate(successors)) {
     const auto &successor = it.value();
     if (canSkip(successor))
       continue;
 
     auto getSuccessor =
         formatv(successor.isVariadic() ? "{0}()" : getSingleSuccessor,
                 successor.name, it.index())
             .str();

mlir/tools/mlir-tblgen/OpFormatGen.cpp

static void genEnumAttrPrinter(const NamedAttribute *var, const Operator &op,
   body << llvm::formatv(enumAttrBeginPrinterCode,
                         (var->attr.isOptional() ? "*" : "") +
                             op.getGetterName(var->name),
                         enumAttr.getSymbolToStringFnName());
 
   // Get a string containing all of the cases that can't be represented with a
   // keyword.
   BitVector nonKeywordCases(cases.size());
-  for (auto &it : llvm::enumerate(cases)) {
+  for (auto it : llvm::enumerate(cases)) {
     if (!canFormatStringAsKeyword(it.value().getStr()))
       nonKeywordCases.set(it.index());
   }
 
   // Otherwise if this is a bit enum attribute, don't allow cases that may
   // overlap with other cases. For simplicity sake, only allow cases with a
   // single bit value.
   if (enumAttr.isBitEnum()) {
-    for (auto &it : llvm::enumerate(cases)) {
+    for (auto it : llvm::enumerate(cases)) {
       int64_t value = it.value().getValue();
       if (value < 0 || !llvm::isPowerOf2_64(value))
         nonKeywordCases.set(it.index());
     }
   }
 
   // If there are any cases that can't be used with a keyword, switch on the
   // case value to determine when to print in the string form.
   if (nonKeywordCases.any()) {
     body << "    switch (caseValue) {\n";
     StringRef cppNamespace = enumAttr.getCppNamespace();
     StringRef enumName = enumAttr.getEnumClassName();
-    for (auto &it : llvm::enumerate(cases)) {
+    for (auto it : llvm::enumerate(cases)) {
       if (nonKeywordCases.test(it.index()))
         continue;
       StringRef symbol = it.value().getSymbol();
       body << llvm::formatv("    case {0}::{1}::{2}:\n", cppNamespace, enumName,
                             llvm::isDigit(symbol.front()) ? ("_" + symbol)
                                                           : symbol);
     }
     body << "      _odsPrinter << caseValueStr;\n"