diff --git a/mlir/lib/Dialect/AMX/IR/AMXDialect.cpp b/mlir/lib/Dialect/AMX/IR/AMXDialect.cpp
index 748ff1edbfeb2..6f3110cdf00ef 100644
--- a/mlir/lib/Dialect/AMX/IR/AMXDialect.cpp
+++ b/mlir/lib/Dialect/AMX/IR/AMXDialect.cpp
@@ -96,9 +96,8 @@ static Value getStride(Location loc, MemRefType mType, Value base,
     MemRefDescriptor memrefDescriptor(base);
     auto attr = rewriter.getI64IntegerAttr(bytes);
     Value scale = LLVM::ConstantOp::create(rewriter, loc, llvmInt64Type, attr);
-    return rewriter
-        .create<LLVM::MulOp>(loc, llvmInt64Type, scale,
-                             memrefDescriptor.stride(rewriter, loc, preLast))
+    return LLVM::MulOp::create(rewriter, loc, llvmInt64Type, scale,
+                               memrefDescriptor.stride(rewriter, loc, preLast))
         .getResult();
   }
   // Use direct constant for static stride.
diff --git a/mlir/lib/Dialect/Bufferization/IR/BufferizableOpInterface.cpp b/mlir/lib/Dialect/Bufferization/IR/BufferizableOpInterface.cpp
index 994d48505d24f..f7b0b87085f3d 100644
--- a/mlir/lib/Dialect/Bufferization/IR/BufferizableOpInterface.cpp
+++ b/mlir/lib/Dialect/Bufferization/IR/BufferizableOpInterface.cpp
@@ -688,8 +688,8 @@ FailureOr<Value> bufferization::getBuffer(RewriterBase &rewriter, Value value,
   if (failed(bufferType))
     return failure();
   ensureToBufferOpIsValid(value, *bufferType);
-  return rewriter
-      .create<bufferization::ToBufferOp>(value.getLoc(), *bufferType, value)
+  return bufferization::ToBufferOp::create(rewriter, value.getLoc(),
+                                           *bufferType, value)
       .getResult();
 }
 
@@ -772,9 +772,8 @@ FailureOr<Value> BufferizationOptions::createAlloc(OpBuilder &b, Location loc,
 
   // Default bufferallocation via AllocOp.
   if (bufferAlignment != 0)
-    return b
-        .create<memref::AllocOp>(loc, type, dynShape,
-                                 b.getI64IntegerAttr(bufferAlignment))
+    return memref::AllocOp::create(b, loc, type, dynShape,
+                                   b.getI64IntegerAttr(bufferAlignment))
         .getResult();
   return memref::AllocOp::create(b, loc, type, dynShape).getResult();
 }
diff --git a/mlir/lib/Dialect/Bufferization/Transforms/LowerDeallocations.cpp b/mlir/lib/Dialect/Bufferization/Transforms/LowerDeallocations.cpp
index f0d65b04ee447..e9ad13f7ebfc6 100644
--- a/mlir/lib/Dialect/Bufferization/Transforms/LowerDeallocations.cpp
+++ b/mlir/lib/Dialect/Bufferization/Transforms/LowerDeallocations.cpp
@@ -482,10 +482,10 @@ func::FuncOp mlir::bufferization::buildDeallocationLibraryFunction(
 
         // Build the first for loop that computes aliasing with retained
         // memrefs.
-        Value noRetainAlias =
-            builder
-                .create<scf::ForOp>(
-                    loc, c0, toRetainSize, c1, trueValue,
+        Value
+            noRetainAlias =
+                scf::ForOp::create(
+                    builder, loc, c0, toRetainSize, c1, trueValue,
                     [&](OpBuilder &builder, Location loc, Value i,
                         ValueRange iterArgs) {
                       Value retainValue = memref::LoadOp::create(
@@ -512,14 +512,14 @@ func::FuncOp mlir::bufferization::buildDeallocationLibraryFunction(
                           builder, loc, iterArgs[0], doesntAlias);
                       scf::YieldOp::create(builder, loc, yieldValue);
                     })
-                .getResult(0);
+                    .getResult(0);
 
         // Build the second for loop that adds aliasing with previously
         // deallocated memrefs.
-        Value noAlias =
-            builder
-                .create<scf::ForOp>(
-                    loc, c0, outerIter, c1, noRetainAlias,
+        Value
+            noAlias =
+                scf::ForOp::create(
+                    builder, loc, c0, outerIter, c1, noRetainAlias,
                     [&](OpBuilder &builder, Location loc, Value i,
                         ValueRange iterArgs) {
                       Value prevDeallocValue = memref::LoadOp::create(
@@ -531,7 +531,7 @@ func::FuncOp mlir::bufferization::buildDeallocationLibraryFunction(
                           builder, loc, iterArgs[0], doesntAlias);
                       scf::YieldOp::create(builder, loc, yieldValue);
                     })
-                .getResult(0);
+                    .getResult(0);
 
         Value shouldDealoc = arith::AndIOp::create(builder, loc, noAlias, cond);
         memref::StoreOp::create(builder, loc, shouldDealoc, deallocCondsMemref,
diff --git a/mlir/lib/Dialect/Bufferization/Transforms/OwnershipBasedBufferDeallocation.cpp b/mlir/lib/Dialect/Bufferization/Transforms/OwnershipBasedBufferDeallocation.cpp
index 64c178dfe76d8..725fa2429ce5b 100644
--- a/mlir/lib/Dialect/Bufferization/Transforms/OwnershipBasedBufferDeallocation.cpp
+++ b/mlir/lib/Dialect/Bufferization/Transforms/OwnershipBasedBufferDeallocation.cpp
@@ -750,17 +750,16 @@ Value BufferDeallocation::materializeMemrefWithGuaranteedOwnership(
 
   // Insert a runtime check and only clone if we still don't have ownership at
   // runtime.
-  Value maybeClone = builder
-                         .create<scf::IfOp>(
-                             memref.getLoc(), condition,
-                             [&](OpBuilder &builder, Location loc) {
-                               scf::YieldOp::create(builder, loc, newMemref);
-                             },
-                             [&](OpBuilder &builder, Location loc) {
-                               Value clone = bufferization::CloneOp::create(
-                                   builder, loc, newMemref);
-                               scf::YieldOp::create(builder, loc, clone);
-                             })
+  Value maybeClone = scf::IfOp::create(
+                         builder, memref.getLoc(), condition,
+                         [&](OpBuilder &builder, Location loc) {
+                           scf::YieldOp::create(builder, loc, newMemref);
+                         },
+                         [&](OpBuilder &builder, Location loc) {
+                           Value clone = bufferization::CloneOp::create(
+                               builder, loc, newMemref);
+                           scf::YieldOp::create(builder, loc, clone);
+                         })
                          .getResult(0);
   Value trueVal = buildBoolValue(builder, memref.getLoc(), true);
   state.updateOwnership(maybeClone, trueVal);
diff --git a/mlir/lib/Dialect/GPU/Transforms/ShuffleRewriter.cpp b/mlir/lib/Dialect/GPU/Transforms/ShuffleRewriter.cpp
index d88f4d56d9009..8e05436155b4c 100644
--- a/mlir/lib/Dialect/GPU/Transforms/ShuffleRewriter.cpp
+++ b/mlir/lib/Dialect/GPU/Transforms/ShuffleRewriter.cpp
@@ -60,14 +60,12 @@ struct GpuShuffleRewriter : public OpRewritePattern<gpu::ShuffleOp> {
 
     // Shuffle the values.
     ValueRange loRes =
-        rewriter
-            .create<gpu::ShuffleOp>(op.getLoc(), lo, op.getOffset(),
-                                    op.getWidth(), op.getMode())
+        gpu::ShuffleOp::create(rewriter, op.getLoc(), lo, op.getOffset(),
+                               op.getWidth(), op.getMode())
             .getResults();
     ValueRange hiRes =
-        rewriter
-            .create<gpu::ShuffleOp>(op.getLoc(), hi, op.getOffset(),
-                                    op.getWidth(), op.getMode())
+        gpu::ShuffleOp::create(rewriter, op.getLoc(), hi, op.getOffset(),
+                               op.getWidth(), op.getMode())
             .getResults();
 
     // Convert lo back to i64.
diff --git a/mlir/lib/Dialect/GPU/Transforms/SubgroupReduceLowering.cpp b/mlir/lib/Dialect/GPU/Transforms/SubgroupReduceLowering.cpp
index b9e2dd5b19a6f..b45fdf34e78e1 100644
--- a/mlir/lib/Dialect/GPU/Transforms/SubgroupReduceLowering.cpp
+++ b/mlir/lib/Dialect/GPU/Transforms/SubgroupReduceLowering.cpp
@@ -197,10 +197,9 @@ Value createSubgroupShuffleReduction(OpBuilder &builder, Location loc,
   // Parallel reduction using butterfly shuffles.
   for (unsigned i = ci.clusterStride; i < ci.clusterStride * ci.clusterSize;
        i <<= 1) {
-    Value shuffled = builder
-                         .create<gpu::ShuffleOp>(loc, packFn(laneVal), i,
-                                                 /*width=*/ci.subgroupSize,
-                                                 /*mode=*/gpu::ShuffleMode::XOR)
+    Value shuffled = gpu::ShuffleOp::create(builder, loc, packFn(laneVal), i,
+                                            /*width=*/ci.subgroupSize,
+                                            /*mode=*/gpu::ShuffleMode::XOR)
                          .getShuffleResult();
     laneVal = vector::makeArithReduction(builder, loc,
                                          gpu::convertReductionKind(mode),
diff --git a/mlir/lib/Dialect/MemRef/Transforms/IndependenceTransforms.cpp b/mlir/lib/Dialect/MemRef/Transforms/IndependenceTransforms.cpp
index 66c1aa6bf3fe1..d5e2b97e501e6 100644
--- a/mlir/lib/Dialect/MemRef/Transforms/IndependenceTransforms.cpp
+++ b/mlir/lib/Dialect/MemRef/Transforms/IndependenceTransforms.cpp
@@ -56,9 +56,8 @@ FailureOr<Value> memref::buildIndependentOp(OpBuilder &b,
   // Create a memref::SubViewOp.
   SmallVector<OpFoldResult> offsets(newSizes.size(), b.getIndexAttr(0));
   SmallVector<OpFoldResult> strides(newSizes.size(), b.getIndexAttr(1));
-  return b
-      .create<SubViewOp>(loc, newAllocaOp, offsets, allocaOp.getMixedSizes(),
-                         strides)
+  return SubViewOp::create(b, loc, newAllocaOp, offsets,
+                           allocaOp.getMixedSizes(), strides)
       .getResult();
 }
 
diff --git a/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp b/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
index 1f03e9ae8d6a1..d3a77c026379e 100644
--- a/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
+++ b/mlir/lib/Dialect/MemRef/Transforms/RuntimeOpVerification.cpp
@@ -185,9 +185,8 @@ struct CopyOpInterface
                             int64_t dim) -> Value {
         return type.isDynamicDim(dim)
                    ? DimOp::create(builder, loc, memRef, dim).getResult()
-                   : builder
-                         .create<arith::ConstantIndexOp>(loc,
-                                                         type.getDimSize(dim))
+                   : arith::ConstantIndexOp::create(builder, loc,
+                                                    type.getDimSize(dim))
                          .getResult();
       };
       Value sourceDim = getDimSize(copyOp.getSource(), rankedSourceType, i);
diff --git a/mlir/lib/Dialect/Quant/Transforms/LowerQuantOps.cpp b/mlir/lib/Dialect/Quant/Transforms/LowerQuantOps.cpp
index 58cd160948f7f..9e37bc5163f71 100644
--- a/mlir/lib/Dialect/Quant/Transforms/LowerQuantOps.cpp
+++ b/mlir/lib/Dialect/Quant/Transforms/LowerQuantOps.cpp
@@ -148,16 +148,14 @@ flattenUnrankedTensorAroundAxis(OpBuilder &builder, Location loc, Value input,
   auto axisValue = arith::ConstantIndexOp::create(builder, loc, axis);
   auto axisNextValue = arith::ConstantIndexOp::create(builder, loc, axis + 1);
   auto shapeLeft =
-      builder
-          .create<shape::SplitAtOp>(loc, TypeRange{shapeType, shapeType},
-                                    inputShape, axisValue)
+      shape::SplitAtOp::create(builder, loc, TypeRange{shapeType, shapeType},
+                               inputShape, axisValue)
           .getResult(0);
   auto sizeLeft =
       shape::NumElementsOp::create(builder, loc, indexType, shapeLeft);
   auto shapeRight =
-      builder
-          .create<shape::SplitAtOp>(loc, TypeRange{shapeType, shapeType},
-                                    inputShape, axisNextValue)
+      shape::SplitAtOp::create(builder, loc, TypeRange{shapeType, shapeType},
+                               inputShape, axisNextValue)
           .getResult(1);
   auto sizeRight =
       shape::NumElementsOp::create(builder, loc, indexType, shapeRight);
@@ -557,25 +555,24 @@ Value convertPerChannelRanked(OpBuilder &builder, Location loc, Operation *op,
   SmallVector<AffineMap> indexingMaps{
       builder.getMultiDimIdentityMap(inputRank), channelAxisAffineMap,
       channelAxisAffineMap, builder.getMultiDimIdentityMap(inputRank)};
-  auto result = builder
-                    .create<linalg::GenericOp>(
-                        loc,
-                        init.getType(),                        // resultType
-                        ValueRange{input, scales, zeroPoints}, // inputs
-                        ValueRange{init},                      // outputs
-                        indexingMaps, iteratorTypes,
-                        [&](OpBuilder &builder, Location loc, ValueRange args) {
-                          assert(args.size() == 4);
-                          auto input = args[0];
-                          auto scale = args[1];
-                          auto zeroPoint = args[2];
-
-                          auto result =
-                              convertRanked(builder, loc, op, input, {}, scale,
-                                            zeroPoint, quantizedType);
-
-                          linalg::YieldOp::create(builder, loc, result);
-                        })
+  auto result = linalg::GenericOp::create(
+                    builder, loc,
+                    init.getType(),                        // resultType
+                    ValueRange{input, scales, zeroPoints}, // inputs
+                    ValueRange{init},                      // outputs
+                    indexingMaps, iteratorTypes,
+                    [&](OpBuilder &builder, Location loc, ValueRange args) {
+                      assert(args.size() == 4);
+                      auto input = args[0];
+                      auto scale = args[1];
+                      auto zeroPoint = args[2];
+
+                      auto result =
+                          convertRanked(builder, loc, op, input, {}, scale,
+                                        zeroPoint, quantizedType);
+
+                      linalg::YieldOp::create(builder, loc, result);
+                    })
                     .getResult(0);
 
   return result;
@@ -660,25 +657,24 @@ Value convertSubChannel(OpBuilder &builder, Location loc, Operation *op,
   SmallVector<AffineMap> indexingMaps{
       builder.getMultiDimIdentityMap(inputRank), affineMap, affineMap,
       builder.getMultiDimIdentityMap(inputRank)};
-  auto result = builder
-                    .create<linalg::GenericOp>(
-                        loc,
-                        init.getType(),                        // resultType
-                        ValueRange{input, scales, zeroPoints}, // inputs
-                        ValueRange{init},                      // outputs
-                        indexingMaps, iteratorTypes,
-                        [&](OpBuilder &builder, Location loc, ValueRange args) {
-                          assert(args.size() == 4);
-                          auto input = args[0];
-                          auto scale = args[1];
-                          auto zeroPoint = args[2];
-
-                          auto result =
-                              convertRanked(builder, loc, op, input, {}, scale,
-                                            zeroPoint, quantizedType);
-
-                          linalg::YieldOp::create(builder, loc, result);
-                        })
+  auto result = linalg::GenericOp::create(
+                    builder, loc,
+                    init.getType(),                        // resultType
+                    ValueRange{input, scales, zeroPoints}, // inputs
+                    ValueRange{init},                      // outputs
+                    indexingMaps, iteratorTypes,
+                    [&](OpBuilder &builder, Location loc, ValueRange args) {
+                      assert(args.size() == 4);
+                      auto input = args[0];
+                      auto scale = args[1];
+                      auto zeroPoint = args[2];
+
+                      auto result =
+                          convertRanked(builder, loc, op, input, {}, scale,
+                                        zeroPoint, quantizedType);
+
+                      linalg::YieldOp::create(builder, loc, result);
+                    })
                     .getResult(0);
 
   return result;
diff --git a/mlir/lib/Dialect/SCF/Transforms/BufferizableOpInterfaceImpl.cpp b/mlir/lib/Dialect/SCF/Transforms/BufferizableOpInterfaceImpl.cpp
index 64c4d607e3fb9..f8799c52e8797 100644
--- a/mlir/lib/Dialect/SCF/Transforms/BufferizableOpInterfaceImpl.cpp
+++ b/mlir/lib/Dialect/SCF/Transforms/BufferizableOpInterfaceImpl.cpp
@@ -497,10 +497,10 @@ getBbArgReplacements(RewriterBase &rewriter, Block::BlockArgListType bbArgs,
     size_t idx = it.index();
     Value val = it.value();
     if (tensorIndices.contains(idx)) {
-      result.push_back(rewriter
-                           .create<bufferization::ToTensorOp>(
-                               val.getLoc(), oldBbArgs[idx].getType(), val)
-                           .getResult());
+      result.push_back(
+          bufferization::ToTensorOp::create(rewriter, val.getLoc(),
+                                            oldBbArgs[idx].getType(), val)
+              .getResult());
     } else {
       result.push_back(val);
     }
diff --git a/mlir/lib/Dialect/SCF/Utils/Utils.cpp b/mlir/lib/Dialect/SCF/Utils/Utils.cpp
index 5b0c60415a6c4..57317951d609c 100644
--- a/mlir/lib/Dialect/SCF/Utils/Utils.cpp
+++ b/mlir/lib/Dialect/SCF/Utils/Utils.cpp
@@ -827,9 +827,8 @@ static Value getProductOfIntsOrIndexes(RewriterBase &rewriter, Location loc,
       productOf = v;
   }
   if (!productOf) {
-    productOf = rewriter
-                    .create<arith::ConstantOp>(
-                        loc, rewriter.getOneAttr(getType(values.front())))
+    productOf = arith::ConstantOp::create(
+                    rewriter, loc, rewriter.getOneAttr(getType(values.front())))
                     .getResult();
   }
   return productOf.value();
diff --git a/mlir/lib/Dialect/Shape/IR/Shape.cpp b/mlir/lib/Dialect/Shape/IR/Shape.cpp
index e24f0f87e781d..5ba828918c22a 100644
--- a/mlir/lib/Dialect/Shape/IR/Shape.cpp
+++ b/mlir/lib/Dialect/Shape/IR/Shape.cpp
@@ -1702,9 +1702,8 @@ struct ShapeOfOpToConstShapeOp : public OpRewritePattern<shape::ShapeOfOp> {
       return failure();
     Location loc = op.getLoc();
     Value constShape =
-        rewriter
-            .create<ConstShapeOp>(loc,
-                                  rewriter.getIndexTensorAttr(type.getShape()))
+        ConstShapeOp::create(rewriter, loc,
+                             rewriter.getIndexTensorAttr(type.getShape()))
             .getResult();
     if (constShape.getType() != op.getResult().getType())
       constShape = tensor::CastOp::create(rewriter, loc,
diff --git a/mlir/lib/Dialect/Shard/Transforms/Partition.cpp b/mlir/lib/Dialect/Shard/Transforms/Partition.cpp
index 5fe55669c90db..3e3d4768853e5 100644
--- a/mlir/lib/Dialect/Shard/Transforms/Partition.cpp
+++ b/mlir/lib/Dialect/Shard/Transforms/Partition.cpp
@@ -70,10 +70,8 @@ splitLastAxisInResharding(ImplicitLocOpBuilder &builder,
                           TypedValue<ShapedType> sourceShard, GridOp grid,
                           int64_t splitTensorAxis, GridAxis splitGridAxis) {
   TypedValue<ShapedType> targetShard = cast<TypedValue<ShapedType>>(
-      builder
-          .create<AllSliceOp>(sourceShard, grid,
-                              ArrayRef<GridAxis>(splitGridAxis),
-                              splitTensorAxis)
+      AllSliceOp::create(builder, sourceShard, grid,
+                         ArrayRef<GridAxis>(splitGridAxis), splitTensorAxis)
           .getResult());
   Sharding targetSharding = targetShardingInSplitLastAxis(
       builder.getContext(), sourceSharding, splitTensorAxis, splitGridAxis);
@@ -420,16 +418,15 @@ tryUpdateHaloInResharding(ImplicitLocOpBuilder &builder, GridOp grid,
 
   // Finally update the halo.
   auto updateHaloResult =
-      builder
-          .create<UpdateHaloOp>(
-              sourceShard.getLoc(),
-              RankedTensorType::get(outShape,
-                                    sourceShard.getType().getElementType()),
-              initOprnd, grid.getSymName(),
-              GridAxesArrayAttr::get(builder.getContext(),
-                                     sourceSharding.getSplitAxes()),
-              targetSharding.getDynamicHaloSizes(),
-              targetSharding.getStaticHaloSizes())
+      UpdateHaloOp::create(
+          builder, sourceShard.getLoc(),
+          RankedTensorType::get(outShape,
+                                sourceShard.getType().getElementType()),
+          initOprnd, grid.getSymName(),
+          GridAxesArrayAttr::get(builder.getContext(),
+                                 sourceSharding.getSplitAxes()),
+          targetSharding.getDynamicHaloSizes(),
+          targetSharding.getStaticHaloSizes())
           .getResult();
   return std::make_tuple(cast<TypedValue<ShapedType>>(updateHaloResult),
                          targetSharding);
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseBufferRewriting.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseBufferRewriting.cpp
index a52872dd093d8..3b4140edd1641 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseBufferRewriting.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseBufferRewriting.cpp
@@ -931,10 +931,9 @@ createQuickSort(OpBuilder &builder, ModuleOp module, func::FuncOp func,
   FlatSymbolRefAttr partitionFunc = getMangledSortHelperFunc(
       builder, func, {IndexType::get(context)}, kPartitionFuncNamePrefix, xPerm,
       ny, args.drop_back(nTrailingP), createPartitionFunc);
-  Value p = builder
-                .create<func::CallOp>(loc, partitionFunc,
-                                      TypeRange{IndexType::get(context)},
-                                      args.drop_back(nTrailingP))
+  Value p = func::CallOp::create(builder, loc, partitionFunc,
+                                 TypeRange{IndexType::get(context)},
+                                 args.drop_back(nTrailingP))
                 .getResult(0);
 
   Value lenLow = arith::SubIOp::create(builder, loc, p, lo);
@@ -1028,9 +1027,8 @@ static void createSortStableFunc(OpBuilder &builder, ModuleOp module,
   FlatSymbolRefAttr searchFunc = getMangledSortHelperFunc(
       builder, func, {IndexType::get(context)}, kBinarySearchFuncNamePrefix,
       xPerm, ny, operands, createBinarySearchFunc);
-  Value p = builder
-                .create<func::CallOp>(loc, searchFunc, TypeRange{c1.getType()},
-                                      operands)
+  Value p = func::CallOp::create(builder, loc, searchFunc,
+                                 TypeRange{c1.getType()}, operands)
                 .getResult(0);
 
   // Move the value at data[i] to a temporary location.
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseGPUCodegen.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseGPUCodegen.cpp
index a317abd6c560b..0bd1d34c3504b 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseGPUCodegen.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseGPUCodegen.cpp
@@ -98,10 +98,10 @@ static Value genLaunchGPUFunc(OpBuilder &builder, gpu::GPUFuncOp gpuFunc,
   Value numT = constantIndex(builder, loc, numThreads);
   gpu::KernelDim3 gridSize = {one, one, one};
   gpu::KernelDim3 blckSize = {numT, one, one};
-  return builder
-      .create<gpu::LaunchFuncOp>(loc, gpuFunc, gridSize, blckSize,
-                                 /*dynSharedMemSz*/ none, args,
-                                 builder.getType<gpu::AsyncTokenType>(), tokens)
+  return gpu::LaunchFuncOp::create(builder, loc, gpuFunc, gridSize, blckSize,
+                                   /*dynSharedMemSz*/ none, args,
+                                   builder.getType<gpu::AsyncTokenType>(),
+                                   tokens)
       .getAsyncToken();
 }
 
@@ -1168,7 +1168,7 @@ struct ForallRewriter : public OpRewritePattern<scf::ParallelOp> {
   using OpRewritePattern<scf::ParallelOp>::OpRewritePattern;
 
   ForallRewriter(MLIRContext *context, unsigned nT)
-      : OpRewritePattern(context), numThreads(nT){};
+      : OpRewritePattern(context), numThreads(nT) {};
 
   LogicalResult matchAndRewrite(scf::ParallelOp forallOp,
                                 PatternRewriter &rewriter) const override {
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp
index dfb127444e281..9cd489653a0f3 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseIterationToScf.cpp
@@ -443,8 +443,8 @@ mlir::SparseIterationTypeConverter::SparseIterationTypeConverter() {
 
   addSourceMaterialization([](OpBuilder &builder, IterSpaceType spTp,
                               ValueRange inputs, Location loc) -> Value {
-    return builder
-        .create<UnrealizedConversionCastOp>(loc, TypeRange(spTp), inputs)
+    return UnrealizedConversionCastOp::create(builder, loc, TypeRange(spTp),
+                                              inputs)
         .getResult(0);
   });
 }
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
index 70795e2eb211b..7a26cd301eb99 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorCodegen.cpp
@@ -412,13 +412,13 @@ static Value genSliceToSize(OpBuilder &builder, Location loc, Value mem,
   if (memTp.getRank() > 1)
     return mem;
   // Truncate linear memrefs to given size.
-  return builder
-      .create<memref::SubViewOp>(
-          loc, MemRefType::get({ShapedType::kDynamic}, memTp.getElementType()),
-          mem, ValueRange{}, ValueRange{sz}, ValueRange{},
-          ArrayRef<int64_t>{0},                    // static offset
-          ArrayRef<int64_t>{ShapedType::kDynamic}, // dynamic size
-          ArrayRef<int64_t>{1})                    // static stride
+  return memref::SubViewOp::create(
+             builder, loc,
+             MemRefType::get({ShapedType::kDynamic}, memTp.getElementType()),
+             mem, ValueRange{}, ValueRange{sz}, ValueRange{},
+             ArrayRef<int64_t>{0},                    // static offset
+             ArrayRef<int64_t>{ShapedType::kDynamic}, // dynamic size
+             ArrayRef<int64_t>{1})                    // static stride
       .getResult();
 }
 
@@ -449,7 +449,7 @@ class SparseInsertGenerator
 public:
   SparseInsertGenerator(TensorType rtp, TypeRange retTypes, ValueRange params,
                         bool genCall)
-      : FuncCallOrInlineGenerator(retTypes, params, genCall), rtp(rtp){};
+      : FuncCallOrInlineGenerator(retTypes, params, genCall), rtp(rtp) {};
 
   /// Generates code along an insertion path without the need for a "cursor".
   /// This current insertion strategy comes at the expense of some testing
diff --git a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp
index b444ac5ba1285..79f4e7f67ab9d 100644
--- a/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp
+++ b/mlir/lib/Dialect/SparseTensor/Transforms/SparseTensorRewriting.cpp
@@ -904,9 +904,8 @@ struct TensorReshapeRewriter : public OpRewritePattern<tensor::ReshapeOp> {
         dstTp->withoutDimToLvl(),
         !srcTp->isAllOrdered() || !srcTp->isIdentity() || !dstTp->isIdentity());
     SmallVector<Value> dynSizes;
-    Value buffer = rewriter
-                       .create<AllocTensorOp>(loc, bufferTp, dynSizes, Value(),
-                                              nnz, Attribute())
+    Value buffer = AllocTensorOp::create(rewriter, loc, bufferTp, dynSizes,
+                                         Value(), nnz, Attribute())
                        .getResult();
 
     // Convert src coordinates to dst coordinates by first collapsing it to 1D
@@ -1013,9 +1012,8 @@ struct Sparse2SparseReshapeRewriter : public OpRewritePattern<ReshapeOp> {
         !srcTp.isAllOrdered() || !srcTp.isIdentity() || !dstTp.isIdentity());
 
     Value buffer =
-        rewriter
-            .create<AllocTensorOp>(loc, bufferTp, dstDynSizes, Value(),
-                                   /*sizeHint=*/nnz, Attribute())
+        AllocTensorOp::create(rewriter, loc, bufferTp, dstDynSizes, Value(),
+                              /*sizeHint=*/nnz, Attribute())
             .getResult();
 
     // Implement the sparse2sparse reshape as follows:
diff --git a/mlir/lib/Dialect/Tensor/Transforms/BufferizableOpInterfaceImpl.cpp b/mlir/lib/Dialect/Tensor/Transforms/BufferizableOpInterfaceImpl.cpp
index bc11e567fa2d8..c3356c1e4b9d8 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/BufferizableOpInterfaceImpl.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/BufferizableOpInterfaceImpl.cpp
@@ -784,8 +784,8 @@ struct PadOpInterface
     auto toValue = [&](OpFoldResult ofr) {
       if (auto value = dyn_cast<Value>(ofr))
         return value;
-      return rewriter
-          .create<arith::ConstantIndexOp>(loc, *getConstantIntValue(ofr))
+      return arith::ConstantIndexOp::create(rewriter, loc,
+                                            *getConstantIntValue(ofr))
           .getResult();
     };
 
@@ -919,9 +919,8 @@ struct ReshapeOpInterface
       auto memrefType = MemRefType::get(
           srcType.getShape(), srcType.getElementType(), AffineMap(),
           cast<BaseMemRefType>(srcBuffer->getType()).getMemorySpace());
-      srcBuffer = rewriter
-                      .create<bufferization::ToBufferOp>(
-                          op->getLoc(), memrefType, *tensorAlloc)
+      srcBuffer = bufferization::ToBufferOp::create(rewriter, op->getLoc(),
+                                                    memrefType, *tensorAlloc)
                       .getResult();
     }
 
diff --git a/mlir/lib/Dialect/Tensor/Transforms/IndependenceTransforms.cpp b/mlir/lib/Dialect/Tensor/Transforms/IndependenceTransforms.cpp
index 43d9d704a29ff..9fd27d328694e 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/IndependenceTransforms.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/IndependenceTransforms.cpp
@@ -130,8 +130,7 @@ FailureOr<Value> tensor::buildIndependentOp(OpBuilder &b,
   // Create a tensor::ExtractSliceOp.
   SmallVector<OpFoldResult> offsets(newSizes.size(), b.getIndexAttr(0));
   SmallVector<OpFoldResult> strides(newSizes.size(), b.getIndexAttr(1));
-  return b
-      .create<ExtractSliceOp>(loc, newEmptyOp, offsets, emptyOp.getMixedSizes(),
-                              strides)
+  return ExtractSliceOp::create(b, loc, newEmptyOp, offsets,
+                                emptyOp.getMixedSizes(), strides)
       .getResult();
 }
diff --git a/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp b/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
index e0af2f77d44b8..2ec23e1fb35ce 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/ReshapePatterns.cpp
@@ -385,10 +385,9 @@ struct BubbleUpExpandShapeThroughExtractSlice
             return getValueOrCreateConstantIndexOp(rewriter, loc, ofr);
           });
       OpFoldResult collapsedOffset =
-          rewriter
-              .create<affine::AffineLinearizeIndexOp>(loc, offsetVals,
-                                                      reassocGroupSizes,
-                                                      /*disjoint=*/true)
+          affine::AffineLinearizeIndexOp::create(rewriter, loc, offsetVals,
+                                                 reassocGroupSizes,
+                                                 /*disjoint=*/true)
               .getResult();
       collapsedOffsets.push_back(collapsedOffset);
       collapsedSizes.push_back(collapsedSize);
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
index 1ad2c806cc39e..6d2cbb5539e14 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
@@ -707,9 +707,8 @@ struct ConcatSliceOptimization : public OpRewritePattern<tosa::SliceOp> {
         auto size_op =
             getTosaConstShape(rewriter, sliceOp.getLoc(), sliceSizes);
         replaceWithSlice =
-            rewriter
-                .create<tosa::SliceOp>(sliceOp.getLoc(), sliceOp.getType(),
-                                       input, start_op, size_op)
+            tosa::SliceOp::create(rewriter, sliceOp.getLoc(), sliceOp.getType(),
+                                  input, start_op, size_op)
                 .getResult();
         break;
       }
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaDecomposeDepthwise.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaDecomposeDepthwise.cpp
index 9474299a39582..0bec0da3f4320 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/TosaDecomposeDepthwise.cpp
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaDecomposeDepthwise.cpp
@@ -81,9 +81,8 @@ struct DepthwiseConv2DIsMul : public OpRewritePattern<tosa::DepthwiseConv2DOp> {
         dyn_cast<RankedTensorType>(input.getType()).getElementType());
     auto revisedInputShapeValue =
         getTosaConstShape(rewriter, op.getLoc(), revisedInputShape);
-    input = rewriter
-                .create<tosa::ReshapeOp>(op.getLoc(), inputType, input,
-                                         revisedInputShapeValue)
+    input = tosa::ReshapeOp::create(rewriter, op.getLoc(), inputType, input,
+                                    revisedInputShapeValue)
                 .getResult();
 
     Type resultETy = resultType.getElementType();
@@ -162,9 +161,8 @@ struct DepthwiseConv2DIsMul : public OpRewritePattern<tosa::DepthwiseConv2DOp> {
         shiftType, rewriter.getIntegerAttr(shiftElementType, 0));
     Value constZero =
         tosa::ConstOp::create(rewriter, op.getLoc(), shiftType, shiftZeroAttr);
-    Value mulValue = rewriter
-                         .create<tosa::MulOp>(op.getLoc(), mulShapeType, input,
-                                              weight, constZero)
+    Value mulValue = tosa::MulOp::create(rewriter, op.getLoc(), mulShapeType,
+                                         input, weight, constZero)
                          .getResult();
 
     // Reshape output to [N, H, W, C * M].