[mlir][ods] Populate properties in generated builder

mlir/include/mlir/Dialect/LLVMIR/LLVMOps.td

@@ -65,13 +65,13 @@ class LLVM_IntArithmeticOpWithOverflowFlag<string mnemonic, string instName,
   let builders = [
     OpBuilder<(ins "Type":$type, "Value":$lhs, "Value":$rhs,
                    "IntegerOverflowFlags":$overflowFlags), [{
-      build($_builder, $_state, type, lhs, rhs);
       $_state.getOrAddProperties<Properties>().overflowFlags = overflowFlags;
+      build($_builder, $_state, type, lhs, rhs);
     }]>,
     OpBuilder<(ins "Value":$lhs, "Value":$rhs,
                    "IntegerOverflowFlags":$overflowFlags), [{
-      build($_builder, $_state, lhs, rhs);
       $_state.getOrAddProperties<Properties>().overflowFlags = overflowFlags;
+      build($_builder, $_state, lhs, rhs);
     }]>
   ];
 

mlir/include/mlir/Dialect/MemRef/IR/MemRefOps.td

@@ -1764,9 +1764,9 @@ def MemRef_CollapseShapeOp : MemRef_ReassociativeReshapeOp<"collapse_shape", [
       "ArrayRef<ReassociationIndices>":$reassociation,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs),
     [{
-      build($_builder, $_state, resultType, src, attrs);
       $_state.addAttribute("reassociation",
                           getReassociationIndicesAttribute($_builder, reassociation));
+      build($_builder, $_state, resultType, src, attrs);
     }]>,
     OpBuilder<(ins "Type":$resultType, "Value":$src,
       "ArrayRef<ReassociationExprs>":$reassociation,

mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td

@@ -1216,9 +1216,9 @@ def Tensor_CollapseShapeOp : Tensor_ReassociativeReshapeOp<"collapse_shape"> {
       "ArrayRef<ReassociationIndices>":$reassociation,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs),
     [{
-      build($_builder, $_state, resultType, src, attrs);
       $_state.addAttribute("reassociation",
           getReassociationIndicesAttribute($_builder, reassociation));
+      build($_builder, $_state, resultType, src, attrs);
     }]>,
     OpBuilder<(ins "Type":$resultType, "Value":$src,
       "ArrayRef<ReassociationExprs>":$reassociation,

mlir/include/mlir/IR/Operation.h

@@ -916,11 +916,12 @@ class alignas(8) Operation final
   /// operation. Returns an empty attribute if no properties are present.
   Attribute getPropertiesAsAttribute();
 
-  /// Set the properties from the provided  attribute.
+  /// Set the properties from the provided attribute.
   /// This is an expensive operation that can fail if the attribute is not
   /// matching the expectations of the properties for this operation. This is
   /// mostly useful for unregistered operations or used when parsing the
-  /// generic format. An optional diagnostic can be passed in for richer errors.
+  /// generic format. An optional diagnostic emitter can be passed in for richer
+  /// errors, if none is passed then behavior is undefined in error case.
   LogicalResult
   setPropertiesFromAttribute(Attribute attr,
                              function_ref<InFlightDiagnostic()> emitError);

mlir/lib/Dialect/Func/Transforms/OneToNFuncConversions.cpp

@@ -40,9 +40,9 @@ class ConvertTypesInFuncCallOp : public OneToNOpConversionPattern<CallOp> {
       return failure();
 
     // Create new CallOp.
-    auto newOp = rewriter.create<CallOp>(loc, resultMapping.getConvertedTypes(),
-                                         adaptor.getFlatOperands());
-    newOp->setAttrs(op->getAttrs());
+    auto newOp =
+        rewriter.create<CallOp>(loc, resultMapping.getConvertedTypes(),
+                                adaptor.getFlatOperands(), op->getAttrs());
 
     rewriter.replaceOp(op, newOp->getResults(), resultMapping);
     return success();

mlir/lib/Dialect/MemRef/IR/MemRefOps.cpp

@@ -1806,11 +1806,11 @@ void ReinterpretCastOp::build(OpBuilder &b, OperationState &result,
   dispatchIndexOpFoldResults(offset, dynamicOffsets, staticOffsets);
   dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
   dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
+  result.addAttributes(attrs);
   build(b, result, resultType, source, dynamicOffsets, dynamicSizes,
         dynamicStrides, b.getDenseI64ArrayAttr(staticOffsets),
         b.getDenseI64ArrayAttr(staticSizes),
         b.getDenseI64ArrayAttr(staticStrides));
-  result.addAttributes(attrs);
 }
 
 void ReinterpretCastOp::build(OpBuilder &b, OperationState &result,
@@ -2483,9 +2483,9 @@ void CollapseShapeOp::build(OpBuilder &b, OperationState &result, Value src,
   auto srcType = llvm::cast<MemRefType>(src.getType());
   MemRefType resultType =
       CollapseShapeOp::computeCollapsedType(srcType, reassociation);
-  build(b, result, resultType, src, attrs);
   result.addAttribute(::mlir::getReassociationAttrName(),
                       getReassociationIndicesAttribute(b, reassociation));
+  build(b, result, resultType, src, attrs);
 }
 
 LogicalResult CollapseShapeOp::verify() {
@@ -2781,11 +2781,11 @@ void SubViewOp::build(OpBuilder &b, OperationState &result,
     resultType = llvm::cast<MemRefType>(SubViewOp::inferResultType(
         sourceMemRefType, staticOffsets, staticSizes, staticStrides));
   }
+  result.addAttributes(attrs);
   build(b, result, resultType, source, dynamicOffsets, dynamicSizes,
         dynamicStrides, b.getDenseI64ArrayAttr(staticOffsets),
         b.getDenseI64ArrayAttr(staticSizes),
         b.getDenseI64ArrayAttr(staticStrides));
-  result.addAttributes(attrs);
 }
 
 // Build a SubViewOp with mixed static and dynamic entries and inferred result
@@ -3320,8 +3320,8 @@ void TransposeOp::build(OpBuilder &b, OperationState &result, Value in,
   // Compute result type.
   MemRefType resultType = inferTransposeResultType(memRefType, permutationMap);
 
-  build(b, result, resultType, in, attrs);
   result.addAttribute(TransposeOp::getPermutationAttrStrName(), permutation);
+  build(b, result, resultType, in, attrs);
 }
 
 // transpose $in $permutation attr-dict : type($in) `to` type(results)

mlir/lib/Dialect/Tensor/IR/TensorOps.cpp

@@ -1743,9 +1743,9 @@ void CollapseShapeOp::build(OpBuilder &b, OperationState &result, Value src,
       llvm::cast<RankedTensorType>(src.getType()),
       getSymbolLessAffineMaps(
           convertReassociationIndicesToExprs(b.getContext(), reassociation)));
-  build(b, result, resultType, src, attrs);
   result.addAttribute(getReassociationAttrStrName(),
                       getReassociationIndicesAttribute(b, reassociation));
+  build(b, result, resultType, src, attrs);
 }
 
 template <typename TensorReshapeOp, bool isExpansion = std::is_same<
@@ -2100,11 +2100,11 @@ void ExtractSliceOp::build(OpBuilder &b, OperationState &result,
     resultType = llvm::cast<RankedTensorType>(ExtractSliceOp::inferResultType(
         sourceRankedTensorType, staticOffsets, staticSizes, staticStrides));
   }
+  result.addAttributes(attrs);
   build(b, result, resultType, source, dynamicOffsets, dynamicSizes,
         dynamicStrides, b.getDenseI64ArrayAttr(staticOffsets),
         b.getDenseI64ArrayAttr(staticSizes),
         b.getDenseI64ArrayAttr(staticStrides));
-  result.addAttributes(attrs);
 }
 
 /// Build an ExtractSliceOp with mixed static and dynamic entries and inferred
@@ -2499,11 +2499,11 @@ void InsertSliceOp::build(OpBuilder &b, OperationState &result, Value source,
   dispatchIndexOpFoldResults(offsets, dynamicOffsets, staticOffsets);
   dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
   dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
+  result.addAttributes(attrs);
   build(b, result, dest.getType(), source, dest, dynamicOffsets, dynamicSizes,
         dynamicStrides, b.getDenseI64ArrayAttr(staticOffsets),
         b.getDenseI64ArrayAttr(staticSizes),
         b.getDenseI64ArrayAttr(staticStrides));
-  result.addAttributes(attrs);
 }
 
 /// Build an InsertSliceOp with mixed static and dynamic entries packed into a
@@ -2967,10 +2967,10 @@ void PadOp::build(OpBuilder &b, OperationState &result, Type resultType,
   auto sourceType = llvm::cast<RankedTensorType>(source.getType());
   if (!resultType)
     resultType = inferResultType(sourceType, staticLow, staticHigh);
+  result.addAttributes(attrs);
   build(b, result, resultType, source, low, high,
         b.getDenseI64ArrayAttr(staticLow), b.getDenseI64ArrayAttr(staticHigh),
         nofold ? b.getUnitAttr() : UnitAttr());
-  result.addAttributes(attrs);
 }
 
 void PadOp::build(OpBuilder &b, OperationState &result, Type resultType,
@@ -3000,10 +3000,10 @@ void PadOp::build(OpBuilder &b, OperationState &result, Type resultType,
     resultType = PadOp::inferResultType(sourceType, staticLow, staticHigh);
   }
   assert(llvm::isa<RankedTensorType>(resultType));
+  result.addAttributes(attrs);
   build(b, result, resultType, source, dynamicLow, dynamicHigh,
         b.getDenseI64ArrayAttr(staticLow), b.getDenseI64ArrayAttr(staticHigh),
         nofold ? b.getUnitAttr() : UnitAttr());
-  result.addAttributes(attrs);
 }
 
 void PadOp::build(OpBuilder &b, OperationState &result, Type resultType,
@@ -3447,11 +3447,11 @@ void ParallelInsertSliceOp::build(OpBuilder &b, OperationState &result,
   dispatchIndexOpFoldResults(offsets, dynamicOffsets, staticOffsets);
   dispatchIndexOpFoldResults(sizes, dynamicSizes, staticSizes);
   dispatchIndexOpFoldResults(strides, dynamicStrides, staticStrides);
+  result.addAttributes(attrs);
   build(b, result, {}, source, dest, dynamicOffsets, dynamicSizes,
         dynamicStrides, b.getDenseI64ArrayAttr(staticOffsets),
         b.getDenseI64ArrayAttr(staticSizes),
         b.getDenseI64ArrayAttr(staticStrides));
-  result.addAttributes(attrs);
 }
 
 /// Build an ParallelInsertSliceOp with mixed static and dynamic entries

mlir/test/Dialect/OpenMP/invalid.mlir

@@ -2113,23 +2113,23 @@ func.func @omp_distribute_allocate(%data_var : memref<i32>) -> () {
 
 func.func @omp_distribute_wrapper() -> () {
   // expected-error @below {{op must be a loop wrapper}}
-  "omp.distribute"() ({
+  omp.distribute {
       %0 = arith.constant 0 : i32
       "omp.terminator"() : () -> ()
-    }) : () -> ()
+  }
 }
 
 // -----
 
 func.func @omp_distribute_nested_wrapper(%data_var : memref<i32>) -> () {
   // expected-error @below {{only supported nested wrappers are 'omp.parallel' and 'omp.simd'}}
-  "omp.distribute"() ({
-      "omp.wsloop"() ({
-        %0 = arith.constant 0 : i32
-        "omp.terminator"() : () -> ()
-      }) : () -> ()
+  omp.distribute {
+    "omp.wsloop"() ({
+      %0 = arith.constant 0 : i32
       "omp.terminator"() : () -> ()
     }) : () -> ()
+    "omp.terminator"() : () -> ()
+  }
 }
 
 // -----

mlir/test/Dialect/OpenMP/ops.mlir

@@ -521,13 +521,13 @@ func.func @omp_wsloop_pretty(%lb : index, %ub : index, %step : index, %data_var
 // CHECK-LABEL: omp_simd
 func.func @omp_simd(%lb : index, %ub : index, %step : index) -> () {
   // CHECK: omp.simd
-  "omp.simd" () ({
+  omp.simd {
     "omp.loop_nest" (%lb, %ub, %step) ({
     ^bb1(%iv2: index):
       "omp.yield"() : () -> ()
     }) : (index, index, index) -> ()
     "omp.terminator"() : () -> ()
-  }) : () -> ()
+  }
 
   return
 }

mlir/test/lib/Dialect/Test/TestOps.td

@@ -2402,6 +2402,13 @@ def TableGenBuildOp5 : TableGenBuildInferReturnTypeBaseOp<
   let regions = (region AnyRegion:$body);
 }
 
+// Two variadic args, non variadic results, with AttrSizedOperandSegments
+// Test build method generation for property conversion & type inference.
+def TableGenBuildOp6 : TEST_Op<"tblgen_build_6", [AttrSizedOperandSegments]> {
+  let arguments = (ins Variadic<AnyType>:$a, Variadic<AnyType>:$b);
+  let results = (outs F32:$result);
+}
+
 //===----------------------------------------------------------------------===//
 // Test BufferPlacement
 //===----------------------------------------------------------------------===//