Add a constant folding hook to ExtractElementOp to fold extracting the element of a constant. This also adds a 'getValue' function to DenseElementsAttr and SparseElementsAttr to get the element at a constant index.

PiperOrigin-RevId: 230098938

mlir/include/mlir/IR/Attributes.h

@@ -348,6 +348,10 @@ public:
   static DenseElementsAttr get(VectorOrTensorType type,
                                ArrayRef<Attribute> values);
 
+  /// Return the value at the given index. If index does not refer to a valid
+  /// element, then a null attribute is returned.
+  Attribute getValue(ArrayRef<uint64_t> index) const;
+
   void getValues(SmallVectorImpl<Attribute> &values) const;
 
   ArrayRef<char> getRawData() const;
@@ -427,10 +431,11 @@ public:
 /// This class uses COO (coordinate list) encoding to represent the sparse
 /// elements in an element attribute. Specifically, the sparse vector/tensor
 /// stores the indices and values as two separate dense elements attributes. The
-/// dense elements attribute indices is a 2-D tensor with shape [N, ndims],
+/// dense elements attribute indices is a 2-D tensor of 64-bit integer elements
-/// which specifies the indices of the elements in the sparse tensor that
+/// with shape [N, ndims], which specifies the indices of the elements in the
-/// contains nonzero values. The dense elements attribute values is a 1-D tensor
+/// sparse tensor that contains nonzero values. The dense elements attribute
-/// with shape [N], and it supplies the corresponding values for the indices.
+/// values is a 1-D tensor with shape [N], and it supplies the corresponding
+/// values for the indices.
 ///
 /// For example,
 /// `sparse<tensor<3x4xi32>, [[0, 0], [1, 2]], [1, 5]>` represents tensor
@@ -450,8 +455,8 @@ public:
 
   DenseElementsAttr getValues() const;
 
-  /// Return the value at the given index.
+  /// Return the value of the element at the given index.
-  Attribute getValue(ArrayRef<unsigned> index) const;
+  Attribute getValue(ArrayRef<uint64_t> index) const;
 
   /// Method for support type inquiry through isa, cast and dyn_cast.
   static bool kindof(Kind kind) { return kind == Kind::SparseElements; }

mlir/include/mlir/StandardOps/StandardOps.h

@@ -523,6 +523,8 @@ public:
   bool verify() const;
   static bool parse(OpAsmParser *parser, OperationState *result);
   void print(OpAsmPrinter *p) const;
+  Attribute constantFold(ArrayRef<Attribute> operands,
+                         MLIRContext *context) const;
 
 private:
   friend class OperationInst;

mlir/lib/IR/Attributes.cpp

@@ -149,6 +149,53 @@ Attribute SplatElementsAttr::getValue() const {
 
 /// DenseElementsAttr
 
+/// Return the value at the given index. If index does not refer to a valid
+/// element, then a null attribute is returned.
+Attribute DenseElementsAttr::getValue(ArrayRef<uint64_t> index) const {
+  auto type = getType();
+
+  // Verify that the rank of the indices matches the held type.
+  auto rank = type.getRank();
+  if (rank != index.size())
+    return Attribute();
+
+  // Verify that all of the indices are within the shape dimensions.
+  auto shape = type.getShape();
+  for (unsigned i = 0; i != rank; ++i)
+    if (shape[i] <= index[i])
+      return Attribute();
+
+  // Reduce the provided multidimensional index into a 1D index.
+  uint64_t valueIndex = 0;
+  uint64_t dimMultiplier = 1;
+  for (int i = rank - 1; i >= 0; --i) {
+    valueIndex += index[i] * dimMultiplier;
+    dimMultiplier *= shape[i];
+  }
+
+  // Return the element stored at the 1D index.
+
+  // FIXME(b/121118307): using 64 bits for BF16 because it is currently stored
+  // with double semantics.
+  auto elementType = getType().getElementType();
+  size_t bitWidth =
+      elementType.isBF16() ? 64 : elementType.getIntOrFloatBitWidth();
+  APInt rawValueData =
+      readBits(getRawData().data(), valueIndex * bitWidth, bitWidth);
+
+  // Convert the raw value data to an attribute value.
+  switch (getKind()) {
+  case Attribute::Kind::DenseIntElements:
+    return IntegerAttr::get(elementType, rawValueData);
+  case Attribute::Kind::DenseFPElements:
+    return FloatAttr::get(
+        elementType, APFloat(elementType.cast<FloatType>().getFloatSemantics(),
+                             rawValueData));
+  default:
+    llvm_unreachable("unexpected element type");
+  }
+}
+
 void DenseElementsAttr::getValues(SmallVectorImpl<Attribute> &values) const {
   auto elementType = getType().getElementType();
   switch (getKind()) {
@@ -188,8 +235,8 @@ void DenseElementsAttr::getRawValues(SmallVectorImpl<APInt> &values) const {
   auto elementNum = getType().getNumElements();
   values.reserve(elementNum);
 
-  // FIXME: using 64 bits for BF16 because it is currently stored with double
+  // FIXME(b/121118307): using 64 bits for BF16 because it is currently stored
-  // semantics.
+  // with double semantics.
   size_t bitWidth =
       elementType.isBF16() ? 64 : elementType.getIntOrFloatBitWidth();
   const auto *rawData = getRawData().data();
@@ -281,3 +328,40 @@ DenseIntElementsAttr SparseElementsAttr::getIndices() const {
 DenseElementsAttr SparseElementsAttr::getValues() const {
   return static_cast<ImplType *>(attr)->values;
 }
+
+/// Return the value of the element at the given index.
+Attribute SparseElementsAttr::getValue(ArrayRef<uint64_t> index) const {
+  auto type = getType();
+
+  // Verify that the rank of the indices matches the held type.
+  auto rank = type.getRank();
+  if (rank != index.size())
+    return Attribute();
+
+  // The sparse indices are 64-bit integers, so we can reinterpret the raw data
+  // as a 1-D index array.
+  auto sparseIndices = getIndices();
+  const uint64_t *sparseIndexValues =
+      reinterpret_cast<const uint64_t *>(sparseIndices.getRawData().data());
+
+  // Build a mapping between known indices and the offset of the stored element.
+  llvm::SmallDenseMap<llvm::ArrayRef<uint64_t>, size_t> mappedIndices;
+  size_t numSparseIndices = sparseIndices.getType().getDimSize(0);
+  for (size_t i = 0, e = numSparseIndices; i != e; ++i)
+    mappedIndices.try_emplace(
+        {sparseIndexValues + (i * rank), static_cast<size_t>(rank)}, i);
+
+  // Look for the provided index key within the mapped indices. If the provided
+  // index is not found, then return a zero attribute.
+  auto it = mappedIndices.find(index);
+  if (it == mappedIndices.end()) {
+    auto eltType = type.getElementType();
+    if (eltType.isa<FloatType>())
+      return FloatAttr::get(eltType, 0);
+    assert(eltType.isa<IntegerType>() && "unexpected element type");
+    return IntegerAttr::get(eltType, 0);
+  }
+
+  // Otherwise, return the held sparse value element.
+  return getValues().getValue(it->second);
+}

mlir/lib/IR/MLIRContext.cpp

@@ -1074,8 +1074,8 @@ DenseElementsAttr DenseElementsAttr::get(VectorOrTensorType type,
   assert(values.size() == type.getNumElements() &&
          "expected 'values' to contain the same number of elements as 'type'");
 
-  // FIXME: using 64 bits for BF16 because it is currently stored with double
+  // FIXME(b/121118307): using 64 bits for BF16 because it is currently stored
-  // semantics.
+  // with double semantics.
   auto eltType = type.getElementType();
   size_t bitWidth = eltType.isBF16() ? 64 : eltType.getIntOrFloatBitWidth();
 
@@ -1136,6 +1136,9 @@ OpaqueElementsAttr OpaqueElementsAttr::get(VectorOrTensorType type,
 SparseElementsAttr SparseElementsAttr::get(VectorOrTensorType type,
                                            DenseIntElementsAttr indices,
                                            DenseElementsAttr values) {
+  assert(indices.getType().getElementType().isInteger(64) &&
+         "expected sparse indices to be 64-bit integer values");
+
   auto &impl = type.getContext()->getImpl();
 
   // Look to see if we already have this.

mlir/lib/Parser/Parser.cpp

@@ -1076,7 +1076,7 @@ Attribute Parser::parseAttribute(Type type) {
     switch (getToken().getKind()) {
     case Token::l_square: {
       /// Parse indices
-      auto indicesEltType = builder.getIntegerType(32);
+      auto indicesEltType = builder.getIntegerType(64);
       auto indices =
           parseDenseElementsAttr(indicesEltType, type.isa<VectorType>());
       if (!indices)

mlir/lib/StandardOps/StandardOps.cpp

@@ -1136,6 +1136,41 @@ bool ExtractElementOp::verify() const {
   return false;
 }
 
+Attribute ExtractElementOp::constantFold(ArrayRef<Attribute> operands,
+                                         MLIRContext *context) const {
+  assert(operands.size() > 1 && "extract_element takes atleast one operands");
+
+  // The aggregate operand must be a known constant.
+  Attribute aggregate = operands.front();
+  if (!aggregate)
+    return Attribute();
+
+  // If this is a splat elements attribute, simply return the value. All of the
+  // elements of a splat attribute are the same.
+  if (auto splatAggregate = aggregate.dyn_cast<SplatElementsAttr>())
+    return splatAggregate.getValue();
+
+  // Otherwise, collect the constant indices into the aggregate.
+  SmallVector<uint64_t, 8> indices;
+  for (Attribute indice : llvm::drop_begin(operands, 1)) {
+    if (!indice || !indice.isa<IntegerAttr>())
+      return Attribute();
+    indices.push_back(indice.cast<IntegerAttr>().getInt());
+  }
+
+  // Get the element value of the aggregate attribute with the given constant
+  // indices.
+  switch (aggregate.getKind()) {
+  case Attribute::Kind::DenseFPElements:
+  case Attribute::Kind::DenseIntElements:
+    return aggregate.cast<DenseElementsAttr>().getValue(indices);
+  case Attribute::Kind::SparseElements:
+    return aggregate.cast<SparseElementsAttr>().getValue(indices);
+  default:
+    return Attribute();
+  }
+}
+
 //===----------------------------------------------------------------------===//
 // LoadOp
 //===----------------------------------------------------------------------===//

mlir/test/Transforms/constant-fold.mlir

@@ -320,6 +320,36 @@ func @cmpi() -> (i1, i1, i1, i1, i1, i1, i1, i1, i1, i1) {
   return %0, %1, %2, %3, %4, %5, %6, %7, %8, %9 : i1, i1, i1, i1, i1, i1, i1, i1, i1, i1
 }
 
+// CHECK-LABEL: func @fold_extract_element
+func @fold_extract_element(%arg0 : index) -> (f32, f16, f16, i32) {
+  %const_0 = constant 0 : index
+  %const_1 = constant 1 : index
+  %const_3 = constant 3 : index
+
+  // Fold an extract into a splat.
+  // CHECK-NEXT: {{.*}} = constant 4.500000e+00 : f32
+  %0 = constant splat<tensor<4xf32>, 4.5> : tensor<4xf32>
+  %ext_1 = extract_element %0[%arg0] : tensor<4xf32>
+
+  // Fold an extract into a sparse with a sparse index.
+  // CHECK-NEXT: {{.*}} = constant -2.000000e+00 : f16
+  %1 = constant sparse<vector<1x1x1xf16>, [[0, 0, 0], [1, 1, 1]],  [-5.0, -2.0]> : vector<1x1x1xf16>
+  %ext_2 = extract_element %1[%const_1, %const_1, %const_1] : vector<1x1x1xf16>
+
+  // Fold an extract into a sparse with a non sparse index.
+  // CHECK-NEXT: {{.*}} = constant 0.000000e+00 : f16
+  %2 = constant sparse<vector<1x1x1xf16>, [[1, 1, 1]],  [-2.0]> : vector<1x1x1xf16>
+  %ext_3 = extract_element %2[%const_0, %const_0, %const_0] : vector<1x1x1xf16>
+
+  // Fold an extract into a dense tensor.
+  // CHECK-NEXT: {{.*}} = constant 64 : i32
+  %3 = constant dense<tensor<2x1x4xi32>, [[[1, -2, 1, 36]], [[0, 2, -1, 64]]]> : tensor<2x1x4xi32>
+  %ext_4 = extract_element %3[%const_1, %const_0, %const_3] : tensor<2x1x4xi32>
+
+  // CHECK-NEXT: return
+  return %ext_1, %ext_2, %ext_3, %ext_4 : f32, f16, f16, i32
+}
+
 // --------------------------------------------------------------------------//
 // IMPORTANT NOTE: the operations in this test are exactly those produced by
 // lowering affine_apply (i) -> (i mod 42) to standard operations.  Please only