NFC: add indexing operator for ArrayAttr

[bondhugula]

Summary

• add ArrayAttr::operator[](unsigned idx)

[mehdi_amini]

Seems like you don't use arc to create revisions? I think it is needed to have the CI running

[rriddle]

mlir/test/lib/TestDialect/TestOps.td

613

Could we merge these lines now? (here and below)

[bondhugula]

In D74663#1877591, @mehdi_amini wrote:

Seems like you don't use arc to create revisions? I think it is needed to have the CI running

I normally just use the web interface: https://llvm.org/docs/Phabricator.html#id4

[bondhugula]

merge lines in testops.td

[bondhugula]

switching to arc

[bondhugula]

@rriddle could you please commit this for me? (the revision has been switched to arc)

[rriddle]

Closed by: https://github.com/llvm/llvm-project/commit/2101590a78b7189f89aa06513eeea2dee6a3c45a

mlir/docs/DeclarativeRewrites.md

 which is a subclass of `mlir::Builder`) to the C++ helper function to use the
 handy methods on `mlir::Builder`.
 
 `$_self` is useful when we want to write something in the form of
 `NativeCodeCall<"...">:$symbol`. For example, if we want to reverse the previous
 example and decompose the array attribute into two attributes:
 
 ```tablegen
-class getNthAttr<int n> : NativeCodeCall<"$_self.getValue()[" # n # "]">;
+class getNthAttr<int n> : NativeCodeCall<"$_self[" # n # "]">;
 
 def : Pat<(OneAttrOp $attr),
           (TwoAttrOp (getNthAttr<0>:$attr), (getNthAttr<1>:$attr)>;
 ```
 
 In the above, `$_self` is substituted by the attribute bound by `$attr`, which
 is `OnAttrOp`'s array attribute.
 

mlir/docs/Tutorials/Toy/Ch-7.md

 
 /// Fold simple struct access operations that access into a constant.
 OpFoldResult StructAccessOp::fold(ArrayRef<Attribute> operands) {
   auto structAttr = operands.front().dyn_cast_or_null<mlir::ArrayAttr>();
   if (!structAttr)
     return nullptr;
 
   size_t elementIndex = index().getZExtValue();
-  return structAttr.getValue()[elementIndex];
+  return structAttr[elementIndex];
 }
 ```
 
 To ensure that MLIR generates the proper constant operations when folding our
 `Toy` operations, i.e. `ConstantOp` for `TensorType` and `StructConstant` for
 `StructType`, we will need to provide an override for the dialect hook
 `materializeConstant`. This allows for generic MLIR operations to create
 constants for the `Toy` dialect when necessary.

mlir/examples/toy/Ch7/mlir/ToyCombine.cpp

 
 /// Fold simple struct access operations that access into a constant.
 OpFoldResult StructAccessOp::fold(ArrayRef<Attribute> operands) {
   auto structAttr = operands.front().dyn_cast_or_null<mlir::ArrayAttr>();
   if (!structAttr)
     return nullptr;
 
   size_t elementIndex = index().getZExtValue();
-  return structAttr.getValue()[elementIndex];
+  return structAttr[elementIndex];
 }
 
 /// This is an example of a c++ rewrite pattern for the TransposeOp. It
 /// optimizes the following scenario: transpose(transpose(x)) -> transpose(x)
 struct SimplifyRedundantTranspose : public mlir::OpRewritePattern<TransposeOp> {
   /// We register this pattern to match every toy.transpose in the IR.
   /// The "benefit" is used by the framework to order the patterns and process
   /// them in order of profitability.

mlir/include/mlir/IR/Attributes.h

class ArrayAttr : public Attribute::AttrBase<ArrayAttr, Attribute,
                                              detail::ArrayAttributeStorage> {
 public:
   using Base::Base;
   using ValueType = ArrayRef<Attribute>;
 
   static ArrayAttr get(ArrayRef<Attribute> value, MLIRContext *context);
 
   ArrayRef<Attribute> getValue() const;
+  Attribute operator[](unsigned idx) const;
 
   /// Support range iteration.
   using iterator = llvm::ArrayRef<Attribute>::iterator;
   iterator begin() const { return getValue().begin(); }
   iterator end() const { return getValue().end(); }
   size_t size() const { return getValue().size(); }
 
   /// Methods for support type inquiry through isa, cast, and dyn_cast.

mlir/include/mlir/IR/OpBase.td

 
 class ArrayCount<int n> : AttrConstraint<
     CPred<"$_self.cast<ArrayAttr>().size() == " #n>,
     "with exactly " # n # " elements">;
 
 class IntArrayNthElemEq<int index, int value> : AttrConstraint<
     And<[
       CPred<"$_self.cast<ArrayAttr>().size() > " # index>,
-      CPred<"$_self.cast<ArrayAttr>().getValue()[" # index # "]"
+      CPred<"$_self.cast<ArrayAttr>()[" # index # "]"
         ".cast<IntegerAttr>().getInt() == " # value>
        ]>,
     "whose " # index # "-th element must be " # value>;
 
 class IntArrayNthElemMinValue<int index, int min> : AttrConstraint<
     And<[
       CPred<"$_self.cast<ArrayAttr>().size() > " # index>,
-      CPred<"$_self.cast<ArrayAttr>().getValue()[" # index # "]"
+      CPred<"$_self.cast<ArrayAttr>()[" # index # "]"
         ".cast<IntegerAttr>().getInt() >= " # min>
         ]>,
     "whose " # index # "-th element must be at least " # min>;
 
 def IsNullAttr : AttrConstraint<
     CPred<"!$_self">, "empty attribute (for optional attributes)">;
 
 // An attribute constraint on FlatSymbolRefAttr that requires that the

mlir/lib/Dialect/VectorOps/VectorOps.cpp

 static Type inferStridedSliceOpResultType(VectorType vectorType,
                                           ArrayAttr offsets, ArrayAttr sizes,
                                           ArrayAttr strides) {
   assert(offsets.size() == sizes.size() && offsets.size() == strides.size());
   SmallVector<int64_t, 4> shape;
   shape.reserve(vectorType.getRank());
   unsigned idx = 0;
   for (unsigned e = offsets.size(); idx < e; ++idx)
-    shape.push_back(sizes.getValue()[idx].cast<IntegerAttr>().getInt());
+    shape.push_back(sizes[idx].cast<IntegerAttr>().getInt());
   for (unsigned e = vectorType.getShape().size(); idx < e; ++idx)
     shape.push_back(vectorType.getShape()[idx]);
 
   return VectorType::get(shape, vectorType.getElementType());
 }
 
 void StridedSliceOp::build(Builder *builder, OperationState &result,
                            Value source, ArrayRef<int64_t> offsets,

mlir/lib/IR/Attributes.cpp

 //===----------------------------------------------------------------------===//
 
 ArrayAttr ArrayAttr::get(ArrayRef<Attribute> value, MLIRContext *context) {
   return Base::get(context, StandardAttributes::Array, value);
 }
 
 ArrayRef<Attribute> ArrayAttr::getValue() const { return getImpl()->value; }
 
+Attribute ArrayAttr::operator[](unsigned idx) const {
+  assert(idx < size() && "index out of bounds");
+  return getValue()[idx];
+}
+
 //===----------------------------------------------------------------------===//
 // BoolAttr
 //===----------------------------------------------------------------------===//
 
 bool BoolAttr::getValue() const { return getImpl()->value; }
 
 //===----------------------------------------------------------------------===//
 // DictionaryAttr

mlir/test/lib/TestDialect/TestDialect.cpp

void getAsmBlockArgumentNames(Block *block,
                                 OpAsmSetValueNameFn setNameFn) const final {
     auto op = block->getParentOp();
     auto arrayAttr = op->getAttrOfType<ArrayAttr>("arg_names");
     if (!arrayAttr)
       return;
     auto args = block->getArguments();
     auto e = std::min(arrayAttr.size(), args.size());
     for (unsigned i = 0; i < e; ++i) {
-      if (auto strAttr = arrayAttr.getValue()[i].dyn_cast<StringAttr>())
+      if (auto strAttr = arrayAttr[i].dyn_cast<StringAttr>())
         setNameFn(args[i], strAttr.getValue());
     }
   }
 };
 
 struct TestOpFolderDialectInterface : public OpFolderDialectInterface {
   using OpFolderDialectInterface::OpFolderDialectInterface;
 

mlir/test/lib/TestDialect/TestOps.td

def OpAllAttrConstraint1 : TEST_Op<"all_attr_constraint_of1"> {
   let arguments = (ins I64ArrayAttr:$attr);
   let results = (outs I32);
 }
 def OpAllAttrConstraint2 : TEST_Op<"all_attr_constraint_of2"> {
   let arguments = (ins I64ArrayAttr:$attr);
   let results = (outs I32);
 }
 def Constraint0 : AttrConstraint<
-    CPred<"$_self.cast<ArrayAttr>().getValue()[0]."
+    CPred<"$_self.cast<ArrayAttr>()[0]."
           "cast<IntegerAttr>().getInt() == 0">,
     "[0] == 0">;
 def Constraint1 : AttrConstraint<
-    CPred<"$_self.cast<ArrayAttr>().getValue()[1]."
+    CPred<"$_self.cast<ArrayAttr>()[1]."
           "cast<IntegerAttr>().getInt() == 1">,
     "[1] == 1">;
 def : Pat<(OpAllAttrConstraint1
             AllAttrConstraintsOf<[Constraint0, Constraint1]>:$attr),
           (OpAllAttrConstraint2 $attr)>;
 
 // Op for testing RewritePattern removing op with inner ops.
 def TestOpWithRegionPattern : TEST_Op<"op_with_region_pattern"> {

mlir/test/mlir-tblgen/predicate.td

 // CHECK:       (tblgen_attr.cast<ArrayAttr>().size() >= 8)
 // CHECK-SAME:    return emitOpError("attribute 'attr' failed to satisfy constraint: array attribute with at least 8 elements");
 
 def OpH : NS_Op<"op_for_arr_value_at_index", []> {
   let arguments = (ins Confined<ArrayAttr, [IntArrayNthElemEq<0, 8>]>:$attr);
 }
 
 // CHECK-LABEL: OpH::verify()
-// CHECK: (((tblgen_attr.cast<ArrayAttr>().size() > 0)) && ((tblgen_attr.cast<ArrayAttr>().getValue()[0].cast<IntegerAttr>().getInt() == 8)))))
+// CHECK: (((tblgen_attr.cast<ArrayAttr>().size() > 0)) && ((tblgen_attr.cast<ArrayAttr>()[0].cast<IntegerAttr>().getInt() == 8)))))
 // CHECK-SAME:    return emitOpError("attribute 'attr' failed to satisfy constraint: array attribute whose 0-th element must be 8");
 
 def OpI: NS_Op<"op_for_arr_min_value_at_index", []> {
   let arguments = (ins Confined<ArrayAttr, [IntArrayNthElemMinValue<0, 8>]>:$attr);
 }
 
 // CHECK-LABEL: OpI::verify()
-// CHECK: (((tblgen_attr.cast<ArrayAttr>().size() > 0)) && ((tblgen_attr.cast<ArrayAttr>().getValue()[0].cast<IntegerAttr>().getInt() >= 8)))))
+// CHECK: (((tblgen_attr.cast<ArrayAttr>().size() > 0)) && ((tblgen_attr.cast<ArrayAttr>()[0].cast<IntegerAttr>().getInt() >= 8)))))
 // CHECK-SAME:    return emitOpError("attribute 'attr' failed to satisfy constraint: array attribute whose 0-th element must be at least 8");
 
 def OpJ: NS_Op<"op_for_TCopVTEtAreSameAt", [
                 PredOpTrait<"operands indexed at 0, 2, 3 should all have "
                  "the same type", TCopVTEtAreSameAt<[0, 2, 3]>>]> {
   let arguments = (ins
     AnyTensor:$a,
     AnyTensor:$b,