Add getNonSplatRawData method to DenseIntOrFPElementsAttr for fas…

…t retrieval of internal data (#78)
Xilinx · Sep 12, 2023 · faf28e5 · faf28e5
1 parent 22a1f58
commit faf28e5
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Showing 3 changed files with 74 additions and 4 deletions.
diff --git a/mlir/include/mlir/IR/BuiltinAttributes.td b/mlir/include/mlir/IR/BuiltinAttributes.td
@@ -348,6 +348,24 @@ def Builtin_DenseIntOrFPElementsAttr : Builtin_Attr<
                                               int64_t dataEltSize, bool isInt,
                                               bool isSigned);
   public:
+    /// Returns the internal buffer of a non-splatted DenseIntOrFPElementAttr.
+    /// Provided storage_t must be unsigned integer and match the bit-width of
+    /// the element type of the DenseIntOrFPElementAttr. \returns an
+    /// ArrayRef<storage_t> over the internal data
+    template <typename storage_t>
+    llvm::ArrayRef<storage_t> getNonSplatRawData() const {
+      assert(!isSplat() && "DenseElementAttr must not be splatted");
+      assert(getElementType().getIntOrFloatBitWidth() ==
+             sizeof(storage_t) * /*bits per byte*/ 8);
+
+      static_assert(std::numeric_limits<storage_t>::is_integer &&
+                        !std::numeric_limits<storage_t>::is_signed,
+                    "storage type must be integer and unsigned");
+
+      return llvm::ArrayRef<storage_t>(
+          reinterpret_cast<const storage_t *>(getRawData().data()),
+          getNumElements());
+    }
   }];
   let genAccessors = 0;
   let genStorageClass = 0;

diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaFolders.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaFolders.cpp
@@ -225,10 +225,8 @@ template <typename BaseType>
 DenseElementsAttr transposeTypeRaw(DenseElementsAttr attr, ShapedType inputType,
                                    ShapedType outputType,
                                    llvm::ArrayRef<int64_t> permValues) {
-
-  ArrayRef inputValues(
-      reinterpret_cast<const BaseType *>(attr.getRawData().data()),
-      attr.getNumElements());
+  ArrayRef<BaseType> inputValues =
+      cast<DenseIntOrFPElementsAttr>(attr).getNonSplatRawData<BaseType>();
 
   SmallVector<BaseType> outputValues;
   outputValues.resize_for_overwrite(inputType.getNumElements());

diff --git a/mlir/unittests/IR/AttributeTest.cpp b/mlir/unittests/IR/AttributeTest.cpp
@@ -446,3 +446,57 @@ TEST(SubElementTest, Nested) {
                 {strAttr, trueAttr, falseAttr, boolArrayAttr, dictAttr}));
 }
 } // namespace
+
+//===----------------------------------------------------------------------===//
+// NonSplattedDenseElementAttr
+//===----------------------------------------------------------------------===//
+
+namespace {
+TEST(NonSplattedDenseElementAttrTest, GetNonSplatRawDataF32) {
+  constexpr std::size_t numberOfElements = 6;
+  static constexpr std::array<float, numberOfElements> rawValues = {
+      0., 2., 4., 8., 3.1, 10.4};
+
+  mlir::MLIRContext context;
+  mlir::OpBuilder b(&context);
+
+  llvm::SmallVector<mlir::Attribute> mlirValues;
+  llvm::transform(rawValues, std::back_inserter(mlirValues),
+                  [&](float v) { return b.getFloatAttr(b.getF32Type(), v); });
+
+  llvm::ArrayRef<uint32_t> expected(
+      reinterpret_cast<const uint32_t *>(rawValues.data()), rawValues.size());
+
+  auto values = mlir::DenseElementsAttr::get(
+      mlir::RankedTensorType::get({numberOfElements}, b.getF32Type()),
+      mlirValues);
+
+  EXPECT_EQ(mlir::cast<mlir::DenseIntOrFPElementsAttr>(values)
+                .getNonSplatRawData<uint32_t>(),
+            expected);
+}
+
+TEST(NonSplattedDenseElementAttrTest, GetNonSplatRawDataI16) {
+  constexpr std::size_t numberOfElements = 6;
+  static constexpr std::array<int16_t, numberOfElements> rawValues = {
+      12, 5723, 23, 2, 634, 321};
+
+  mlir::MLIRContext context;
+  mlir::OpBuilder b(&context);
+
+  llvm::SmallVector<mlir::Attribute> mlirValues;
+  llvm::transform(rawValues, std::back_inserter(mlirValues),
+                  [&](int16_t v) { return b.getI16IntegerAttr(v); });
+
+  llvm::ArrayRef<uint16_t> expected(
+      reinterpret_cast<const uint16_t *>(rawValues.data()), rawValues.size());
+
+  auto values = mlir::DenseElementsAttr::get(
+      mlir::RankedTensorType::get({numberOfElements}, b.getI16Type()),
+      mlirValues);
+
+  EXPECT_EQ(mlir::cast<mlir::DenseIntOrFPElementsAttr>(values)
+                .getNonSplatRawData<uint16_t>(),
+            expected);
+}
+} // namespace