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[mlir][tosa] Avoid requirement to specify enum name for enum attributes #155695

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merged 2 commits into from
Aug 29, 2025
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[mlir][tosa] Avoid requirement to specify enum name for enum attributes #155695

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57abfe1
Use `Tosa_I32EnumAttr` instead of `StringBasedAttr` to represent Tosa…
AnnuCode Aug 9, 2025
8e8b3fe
[mlir][tosa] Avoid requirement to specify enum name for enum attributes
Tai78641 Aug 9, 2025
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23 changes: 8 additions & 15 deletions mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td
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Original file line number Diff line number Diff line change
Expand Up @@ -391,22 +391,22 @@ def Tosa_RESIZE_BILINEAR : I32EnumAttrCase<"BILINEAR", 2>;

def Tosa_ResizeModeAttr
: Tosa_I32EnumAttr<"ResizeMode", "Supported resize/upsampling strategies", "resize_mode",
[Tosa_RESIZE_NEAREST_NEIGHBOR, Tosa_RESIZE_BILINEAR]>;
[Tosa_RESIZE_NEAREST_NEIGHBOR, Tosa_RESIZE_BILINEAR]>;

def Tosa_NANPROPAGATION_PROPAGATE : I32EnumAttrCase<"PROPAGATE", 1>;
def Tosa_NANPROPAGATION_IGNORE : I32EnumAttrCase<"IGNORE", 2>;

def Tosa_NanPropagationModeAttr
: Tosa_I32EnumAttr<"NanPropagationMode", "Supported NaN propagation strategies", "nan_mode",
[Tosa_NANPROPAGATION_PROPAGATE, Tosa_NANPROPAGATION_IGNORE]>;
[Tosa_NANPROPAGATION_PROPAGATE, Tosa_NANPROPAGATION_IGNORE]>;

def Tosa_ROUNDING_SINGLE_ROUND : I32EnumAttrCase<"SINGLE_ROUND", 1>;
def Tosa_ROUNDING_INEXACT_ROUND : I32EnumAttrCase<"INEXACT_ROUND", 2>;
def Tosa_ROUNDING_DOUBLE_ROUND : I32EnumAttrCase<"DOUBLE_ROUND", 3>;

def Tosa_RoundingModeAttr
: Tosa_I32EnumAttr<"RoundingMode", "Supported rounding modes", "rounding_mode",
[Tosa_ROUNDING_SINGLE_ROUND, Tosa_ROUNDING_INEXACT_ROUND, Tosa_ROUNDING_DOUBLE_ROUND]>;
[Tosa_ROUNDING_SINGLE_ROUND, Tosa_ROUNDING_INEXACT_ROUND, Tosa_ROUNDING_DOUBLE_ROUND]>;


//===----------------------------------------------------------------------===//
Expand Down Expand Up @@ -472,33 +472,26 @@ class Tosa_ElementwiseOp<string mnemonic, list<Trait> traits = []> :
ResultsBroadcastableShape,
TosaElementwiseOperator,
SameOperandsAndResultRank,
Pure])> {
let assemblyFormat =
"operands attr-dict `:` functional-type(operands, results)";
}
Pure])> {}

class Tosa_ElementwiseUnaryOp<string mnemonic, list<Trait> traits = []> :
Tosa_ElementwiseOp<mnemonic, !listconcat(traits, [
SameOperandsAndResultShape,
SameOperandsAndResultElementType])> {}

class Tosa_InferTensorTypeOp<string mnemonic, list<Trait> traits = []>
: Tosa_Op<mnemonic, !listconcat(traits, [InferTensorTypeAdaptor, Pure])> {
let assemblyFormat =
"operands attr-dict `:` functional-type(operands, results)";
}
: Tosa_Op<mnemonic, !listconcat(traits, [InferTensorTypeAdaptor, Pure])> {}

class Tosa_InferShapedTypeOp<string mnemonic, list<Trait> traits = []>
: Tosa_Op<mnemonic, !listconcat(traits, [InferShapedTypeOpAdaptor, Pure])> {
let assemblyFormat =
"operands attr-dict `:` functional-type(operands, results)";
}
: Tosa_Op<mnemonic, !listconcat(traits, [InferShapedTypeOpAdaptor, Pure])> {}

// The "SameVariadicOperandSize" trait allows us to pass optional arguments
// for multiple zero points in convolution ops.
class Tosa_ConvOp<string mnemonic, list<Trait> traits = []>
: Tosa_InferShapedTypeOp<mnemonic, !listconcat(traits,
[SameVariadicOperandSize])> {
let assemblyFormat =
"operands attr-dict `:` functional-type(operands, results)";
}

#endif // TOSA_OP_BASE
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