[mlir][linalg] Remove duplicate methods (NFC).

Remove duplicate methods used to check iterator types.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D108102

mlir/include/mlir/Dialect/Linalg/Utils/Utils.h

@@ -56,19 +56,6 @@ SmallVector<Value, 4> getDynOperands(Location loc, Value val, OpBuilder &b);
 /// Otherwise return nullptr.
 IntegerAttr getSmallestBoundingIndex(Value size);
 
-//===----------------------------------------------------------------------===//
-// Iterator type utilities
-//===----------------------------------------------------------------------===//
-
-/// Checks if an iterator_type attribute is parallel.
-bool isParallelIteratorType(Attribute attr);
-
-/// Checks if an iterator_type attribute is parallel.
-bool isReductionIteratorType(Attribute attr);
-
-/// Checks if an iterator_type attribute is parallel.
-bool isWindowIteratorType(Attribute attr);
-
 //===----------------------------------------------------------------------===//
 // Fusion utilities
 //===----------------------------------------------------------------------===//

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

@@ -53,7 +53,7 @@ struct DistributeTiledLoopPattern
       if (procInfoCallback == options.procInfoMap.end())
         continue;
 
-      if (!isParallelIteratorType(op.iterator_types()[i])) {
+      if (!isParallelIterator(op.iterator_types()[i])) {
         op.emitOpError("only support for parallel loops is implemented");
         return failure();
       }

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

@@ -210,7 +210,7 @@ static Value reduceIfNeeded(OpBuilder &b, VectorType targetVectorType,
   unsigned idx = 0;
   SmallVector<bool> reductionMask(linalgOp.iterator_types().size(), false);
   for (auto attr : linalgOp.iterator_types()) {
-    if (isReductionIteratorType(attr))
+    if (isReductionIterator(attr))
       reductionMask[idx] = true;
     ++idx;
   }
@@ -615,7 +615,7 @@ static bool allIndexingsAreProjectedPermutation(LinalgOp op) {
 // TODO: probably need some extra checks for reduction followed by consumer
 // ops that may not commute (e.g. linear reduction + non-linear instructions).
 static LogicalResult reductionPreconditions(LinalgOp op) {
-  if (llvm::none_of(op.iterator_types(), isReductionIteratorType))
+  if (llvm::none_of(op.iterator_types(), isReductionIterator))
     return failure();
   for (OpOperand *opOperand : op.getOutputOperands()) {
     Operation *reductionOp = getSingleBinaryOpAssumedReduction(opOperand);

mlir/lib/Dialect/Linalg/Utils/Utils.cpp

@@ -116,27 +116,6 @@ RegionMatcher::matchAsScalarBinaryOp(GenericOp op) {
   return llvm::None;
 }
 
-bool mlir::linalg::isParallelIteratorType(Attribute attr) {
-  if (auto strAttr = attr.dyn_cast<StringAttr>()) {
-    return strAttr.getValue() == getParallelIteratorTypeName();
-  }
-  return false;
-}
-
-bool mlir::linalg::isReductionIteratorType(Attribute attr) {
-  if (auto strAttr = attr.dyn_cast<StringAttr>()) {
-    return strAttr.getValue() == getReductionIteratorTypeName();
-  }
-  return false;
-}
-
-bool mlir::linalg::isWindowIteratorType(Attribute attr) {
-  if (auto strAttr = attr.dyn_cast<StringAttr>()) {
-    return strAttr.getValue() == getWindowIteratorTypeName();
-  }
-  return false;
-}
-
 /// Explicit instantiation of loop nest generator for different loop types.
 template struct mlir::linalg::GenerateLoopNest<scf::ForOp>;
 template struct mlir::linalg::GenerateLoopNest<scf::ParallelOp>;
@@ -233,7 +212,7 @@ void GenerateLoopNest<scf::ForOp>::doit(
     // Collect loop ranges for parallel dimensions.
     SmallVector<Range, 2> parallelLoopRanges;
     for (auto iteratorType : enumerate(iteratorTypes))
-      if (isParallelIteratorType(iteratorType.value()))
+      if (isParallelIterator(iteratorType.value()))
         parallelLoopRanges.push_back(loopRanges[iteratorType.index()]);
 
     // Get their distribution schemes.
@@ -254,7 +233,7 @@ void GenerateLoopNest<scf::ForOp>::doit(
   // Filter out scf.for loops that were created out of parallel dimensions.
   SmallVector<scf::ForOp, 4> loops;
   for (auto iteratorType : enumerate(iteratorTypes))
-    if (isParallelIteratorType(iteratorType.value()))
+    if (isParallelIterator(iteratorType.value()))
       loops.push_back(loopNest.loops[iteratorType.index()]);
 
   // Distribute - only supports cyclic distribution for now.
@@ -375,7 +354,7 @@ static void generateParallelLoopNest(
   // Find the outermost parallel loops and drop their types from the list.
   unsigned nLoops = iteratorTypes.size();
   unsigned nOuterPar =
-      nLoops - iteratorTypes.drop_while(isParallelIteratorType).size();
+      nLoops - iteratorTypes.drop_while(isParallelIterator).size();
 
   // If there are no outer parallel loops, generate one sequential loop and
   // recurse. Note that we wouldn't have dropped anything from `iteratorTypes`
@@ -502,7 +481,7 @@ void GenerateLoopNest<scf::ParallelOp>::doit(
                               distributionOptions->distributionMethod.end());
     SmallVector<Range, 2> parallelLoopRanges;
     for (auto iteratorType : enumerate(iteratorTypes)) {
-      if (isParallelIteratorType(iteratorType.value()))
+      if (isParallelIterator(iteratorType.value()))
         parallelLoopRanges.push_back(loopRanges[iteratorType.index()]);
     }
     if (distributionMethod.size() < parallelLoopRanges.size())
@@ -513,7 +492,7 @@ void GenerateLoopNest<scf::ParallelOp>::doit(
     for (auto iteratorType : enumerate(iteratorTypes)) {
       if (index >= procInfo.size())
         break;
-      if (isParallelIteratorType(iteratorType.value())) {
+      if (isParallelIterator(iteratorType.value())) {
         unsigned i = iteratorType.index();
         updateBoundsForCyclicDistribution(b, loc, procInfo[index].procId,
                                           procInfo[index].nprocs, lbsStorage[i],

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

@@ -743,7 +743,7 @@ static Operation *genFor(Merger &merger, CodeGen &codegen,
   unsigned tensor = merger.tensor(fb);
   assert(idx == merger.index(fb));
   auto iteratorTypes = op.iterator_types().getValue();
-  bool isReduction = linalg::isReductionIteratorType(iteratorTypes[idx]);
+  bool isReduction = isReductionIterator(iteratorTypes[idx]);
   bool isSparse = merger.isDim(fb, Dim::kSparse);
   bool isVector = isVectorFor(codegen, isInner, isSparse) &&
                   denseUnitStrides(merger, op, idx);