automatic code reformat

src/PIM/Conversion/ONNXToSpatial/Common/ShapeTilingUtils.cpp

@@ -8,8 +8,8 @@
 #include <algorithm>
 #include <functional>
 
-#include "ShapeTilingUtils.hpp"
 #include "IndexingUtils.hpp"
+#include "ShapeTilingUtils.hpp"
 #include "src/Accelerators/PIM/Common/IR/ConstantUtils.hpp"
 #include "src/Accelerators/PIM/Compiler/PimCompilerOptions.hpp"
 #include "src/Accelerators/PIM/Conversion/ONNXToSpatial/Common/Common.hpp"
@@ -53,7 +53,9 @@ bool hasStaticPositiveShape(ArrayRef<int64_t> shape) {
   return llvm::all_of(shape, [](int64_t dim) { return dim > 0; });
 }
 
-bool hasStaticPositiveShape(RankedTensorType type) { return type.hasStaticShape() && hasStaticPositiveShape(type.getShape()); }
+bool hasStaticPositiveShape(RankedTensorType type) {
+  return type.hasStaticShape() && hasStaticPositiveShape(type.getShape());
+}
 
 int64_t getStaticShapeElementCount(ArrayRef<int64_t> shape) {
   return std::accumulate(shape.begin(), shape.end(), int64_t {1}, std::multiplies<int64_t> {});
@@ -98,11 +100,8 @@ FailureOr<SmallVector<int64_t>> getTransposePermutationChecked(std::optional<Arr
   return permutation;
 }
 
-Value transposeMaybeInCompute(Value value,
-                              RankedTensorType resultType,
-                              ArrayRef<int64_t> permutation,
-                              PatternRewriter& rewriter,
-                              Location loc) {
+Value transposeMaybeInCompute(
+  Value value, RankedTensorType resultType, ArrayRef<int64_t> permutation, PatternRewriter& rewriter, Location loc) {
   auto buildTranspose = [&](Value input) -> Value {
     return ONNXTransposeOp::create(rewriter, loc, resultType, input, rewriter.getI64ArrayAttr(permutation)).getResult();
   };
@@ -127,7 +126,8 @@ SmallVector<OpFoldResult> getStaticSizes(PatternRewriter& rewriter, ArrayRef<int
 
 static bool isContiguousTensorSlice(Value source, RankedTensorType resultType, ArrayRef<OpFoldResult> strides) {
   auto sourceType = dyn_cast<RankedTensorType>(source.getType());
-  if (!sourceType || !sourceType.hasStaticShape() || !resultType.hasStaticShape() || sourceType.getRank() != resultType.getRank())
+  if (!sourceType || !sourceType.hasStaticShape() || !resultType.hasStaticShape()
+      || sourceType.getRank() != resultType.getRank())
     return false;
 
   for (OpFoldResult stride : strides) {
@@ -290,7 +290,8 @@ Value materializeContiguousTensorSlice(Value source,
     }
 
     Value lower = zeroIndices[dim];
-    Value upper = getOrCreateIndexConstant(rewriter, rewriter.getInsertionBlock()->getParentOp(), resultType.getDimSize(dim));
+    Value upper =
+      getOrCreateIndexConstant(rewriter, rewriter.getInsertionBlock()->getParentOp(), resultType.getDimSize(dim));
     Value step = getOrCreateIndexConstant(rewriter, rewriter.getInsertionBlock()->getParentOp(), 1);
     auto loop = scf::ForOp::create(rewriter, loc, lower, upper, step, ValueRange {accumulator});
     rewriter.setInsertionPointToStart(loop.getBody());
@@ -316,7 +317,8 @@ Value extractAxisSlice(
   SmallVector<OpFoldResult> sizes = getStaticSizes(rewriter, sourceType.getShape());
   offsets[axis] = rewriter.getIndexAttr(offset);
   sizes[axis] = rewriter.getIndexAttr(size);
-  return tensor::ExtractSliceOp::create(rewriter, loc, resultType, source, offsets, sizes, getUnitStrides(rewriter, sourceType.getRank()))
+  return tensor::ExtractSliceOp::create(
+           rewriter, loc, resultType, source, offsets, sizes, getUnitStrides(rewriter, sourceType.getRank()))
     .getResult();
 }