[Mlir-commits] [mlir] [MLIR][XeGPU] refine verifier for TensorDescType (PR #137226)

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``````````bash
git-clang-format --diff HEAD~1 HEAD --extensions cpp,h -- mlir/include/mlir/Dialect/XeGPU/IR/XeGPU.h mlir/lib/Dialect/XeGPU/IR/XeGPUDialect.cpp mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp
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View the diff from clang-format here.
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``````````diff
diff --git a/mlir/lib/Dialect/XeGPU/IR/XeGPUDialect.cpp b/mlir/lib/Dialect/XeGPU/IR/XeGPUDialect.cpp
index 35a3eb058..f5fe959a2 100644
--- a/mlir/lib/Dialect/XeGPU/IR/XeGPUDialect.cpp
+++ b/mlir/lib/Dialect/XeGPU/IR/XeGPUDialect.cpp
@@ -37,18 +37,19 @@ bool XeGPUDialect::isEvenlyDistributable(llvm::ArrayRef<int64_t> shape,
                                          xegpu::LayoutAttr attr) {
   assert(attr && "Layout attribute is missing.");
 
-  // Checks whether the given shape can be evenly distributed using the specified
-  // layout and data attributes. If successful, it returns the work size for each
-  // compute unit; otherwise, it returns `std::nullopt`. The work size per compute
-  // unit is calculated as follows:
+  // Checks whether the given shape can be evenly distributed using the
+  // specified layout and data attributes. If successful, it returns the work
+  // size for each compute unit; otherwise, it returns `std::nullopt`. The work
+  // size per compute unit is calculated as follows:
   //   - If `data` is null: newShape[i] = shape[i] / layout[i]
   //   - If `data` is not null: newShape[i] = data[i]
-  // When round-robin distribution (`use_rr`) is enabled, `shape[i]` can be smaller
-  // than `layout[i] * data[i]`, allowing multiple compute units to share the data.
-  auto tryDistribute =
-      [&](llvm::ArrayRef<int64_t> shape, DenseI32ArrayAttr layout,
-          DenseI32ArrayAttr data,
-          bool use_rr = true) -> std::optional<SmallVector<int64_t>> {
+  // When round-robin distribution (`use_rr`) is enabled, `shape[i]` can be
+  // smaller than `layout[i] * data[i]`, allowing multiple compute units to
+  // share the data.
+  auto tryDistribute = [&](llvm::ArrayRef<int64_t> shape,
+                           DenseI32ArrayAttr layout, DenseI32ArrayAttr data,
+                           bool use_rr =
+                               true) -> std::optional<SmallVector<int64_t>> {
     llvm::SmallVector<int64_t> newShape(shape);
     if (layout) {
       auto vec = llvm::to_vector_of<int64_t>(layout.asArrayRef());
@@ -91,8 +92,8 @@ bool XeGPUDialect::isEvenlyDistributable(llvm::ArrayRef<int64_t> shape,
   auto instShape = maybeInstShape.value();
 
   // check LaneLayout and LaneData
-  auto maybeLaneShape = tryDistribute(instShape, attr.getLaneLayout(),
-                                          attr.getLaneData(), false);
+  auto maybeLaneShape =
+      tryDistribute(instShape, attr.getLaneLayout(), attr.getLaneData(), false);
   return maybeLaneShape.has_value();
 }
 

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https://github.com/llvm/llvm-project/pull/137226