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[mlir] Allow all shaped types for arith ops. #99028

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[mlir] Allow all shaped types for arith ops. #99028

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9 changes: 6 additions & 3 deletions mlir/include/mlir/IR/CommonTypeConstraints.td
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Original file line number Diff line number Diff line change
Expand Up @@ -636,6 +636,10 @@ def AnyScalableVector : ScalableVectorOf<[AnyType]>;

// Shaped types.

class ShapedTypeOf<list<Type> allowedTypes> :
ShapedContainerType<allowedTypes, IsShapedTypePred, "shaped",
"::mlir::ShapedType">;
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@matthias-springer matthias-springer Jul 17, 2024 •
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One problem with this is that memrefs could now be passed because they are shaped types. E.g.:

// Should arith.addf allocate a new buffer?
%0 = arith.addf %a, %b : memref<?xf32>

I think we should allow only immutable types. Whether they are shaped types or not may not even be that important.

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Being a value type is not sufficient (e.g. we shouldn't allow adding tuples or structs). So scalar or shaped value type is probably the most useful/accurate definition.


def AnyShaped: ShapedContainerType<[AnyType], IsShapedTypePred, "shaped",
"::mlir::ShapedType">;

Expand Down Expand Up @@ -842,10 +846,9 @@ class NestedTupleOf<list<Type> allowedTypes> :
// Common type constraints
//===----------------------------------------------------------------------===//
// Type constraint for types that are "like" some type or set of types T, that is
// they're either a T, a vector of Ts, or a tensor of Ts
// they're either a T or a shaped type of Ts
class TypeOrContainer<Type allowedType, string name> : TypeConstraint<Or<[
allowedType.predicate, VectorOf<[allowedType]>.predicate,
TensorOf<[allowedType]>.predicate]>,
allowedType.predicate, ShapedTypeOf<[allowedType]>.predicate]>,
name>;

// Temporary constraint to allow gradual transition to supporting 0-D vectors.
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6 changes: 6 additions & 0 deletions mlir/test/Dialect/Arith/ops.mlir
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Expand Up @@ -13,6 +13,12 @@ func.func @test_addi_tensor(%arg0 : tensor<8x8xi64>, %arg1 : tensor<8x8xi64>) ->
return %0 : tensor<8x8xi64>
}

// CHECK-LABEL: test_addi_unranked_tensor
func.func @test_addi_unranked_tensor(%arg0 : tensor<*xi32>, %arg1 : tensor<*xi32>) -> tensor<*xi32> {
%0 = arith.addi %arg0, %arg1 : tensor<*xi32>
return %0 : tensor<*xi32>
}

// CHECK-LABEL: test_addi_vector
func.func @test_addi_vector(%arg0 : vector<8xi64>, %arg1 : vector<8xi64>) -> vector<8xi64> {
%0 = arith.addi %arg0, %arg1 : vector<8xi64>
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