Formating

Author: umangyadav

mlir/lib/Conversion/TosaToRock/TosaToRock.cpp

@@ -1715,8 +1715,8 @@ struct AttentionRewritePattern : public OpRewritePattern<tosa::MatMulOp> {
       RankedTensorType resTensorType = cast<RankedTensorType>(res.getType());
       MemRefType resMemRefType = MemRefType::get(
           resTensorType.getShape(), resTensorType.getElementType());
-      Value resMemref =
-          rewriter.create<bufferization::ToBufferOp>(loc, cast<bufferization::BufferLikeType>(resMemRefType), res);
+      Value resMemref = rewriter.create<bufferization::ToBufferOp>(
+          loc, cast<bufferization::BufferLikeType>(resMemRefType), res);
       Value outMemref =
           preSoftmaxElemwiseBlock->addArgument(resMemRefType, loc);
       rewriter.create<memref::CopyOp>(loc, resMemref, outMemref);

mlir/tools/rocmlir-gen/rocmlir-gen.cpp

@@ -3284,7 +3284,9 @@ createCpuConvElementwiseGemmKernelWithMlir(ModuleOp module,
                                           bool isWritable = false) {
     constexpr bool isRestrict{true};
     Value flatTensor = builder.create<bufferization::ToTensorOp>(
-        loc, memref::getTensorTypeFromMemRefType(block->getArgument(blockArgIndex).getType()),
+        loc,
+        memref::getTensorTypeFromMemRefType(
+            block->getArgument(blockArgIndex).getType()),
         block->getArgument(blockArgIndex), isRestrict, isWritable);
     ArrayRef<int64_t> origShape =
         cast<ShapedType>(argTypes[blockArgIndex]).getShape();
@@ -3464,7 +3466,9 @@ createCpuGemmElementwiseGemmKernelWithMlir(ModuleOp module,
                                           bool isWritable = false) {
     constexpr bool isRestrict{true};
     Value flatTensor = builder.create<bufferization::ToTensorOp>(
-        loc, memref::getTensorTypeFromMemRefType(block->getArgument(blockArgIndex).getType()),
+        loc,
+        memref::getTensorTypeFromMemRefType(
+            block->getArgument(blockArgIndex).getType()),
         block->getArgument(blockArgIndex), isRestrict, isWritable);
     ArrayRef<int64_t> origShape =
         cast<ShapedType>(argTypes[blockArgIndex]).getShape();
@@ -3580,7 +3584,9 @@ static func::FuncOp createCpuAttentionKernelWithMlir(ModuleOp module,
                                           bool isWritable = false) {
     constexpr bool isRestrict{true};
     Value flatTensor = builder.create<bufferization::ToTensorOp>(
-        loc, memref::getTensorTypeFromMemRefType(block->getArgument(blockArgIndex).getType()),
+        loc,
+        memref::getTensorTypeFromMemRefType(
+            block->getArgument(blockArgIndex).getType()),
         block->getArgument(blockArgIndex), isRestrict, isWritable);
     ArrayRef<int64_t> origShape =
         cast<ShapedType>(argTypes[blockArgIndex]).getShape();