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[circle-mlir/dialect] Enable AddOp IR #14748

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Feb 26, 2025
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38 changes: 38 additions & 0 deletions circle-mlir/circle-mlir/lib/dialect/mlir/CircleOps.td
Original file line number Diff line number Diff line change
Expand Up @@ -296,6 +296,44 @@ class CIR_ConvOp<string mnemonic, string opSummary,
//===----------------------------------------------------------------------===//
// CIR op definitions.
//===----------------------------------------------------------------------===//
def CIR_AddOp : CIR_Op<"add", [
CIR_RuntimePredOpTrait<"Operands do not have valid shapes",
CPred<"Circle::VerifyAddOpShapeConstraints(llvm::cast<AddOp>($_op))">>,
ResultsBroadcastableShape,
DeclareOpInterfaceMethods<CIR_ShapeInferenceOpInterface>,
Pure,
Commutative,
// TODO enable QuantizableResult,
]> {
let summary = "Addition operator";

let description = [{
Element-wise addition operation.
}];

let arguments = (
// TODO add more dtypes
ins CIR_TensorOf<[F32, I32, I64]>:$lhs,
CIR_TensorOf<[F32, I32, I64]>:$rhs,
Comment on lines +316 to +317
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The reason why there's no Q8 or Q16 dtype here is because current circle-mlir focus on fake-quantized or float models?

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Yes...
But the actual reason is that quantize related codes are linked to TensorFlow that are too huge to import as of now.

CIR_AFAttr:$fused_activation_function);

let results = (outs CIR_TensorOf<[F32, I32, I64]>:$output);

let hasFolder = 1;

let hasCustomAssemblyFormat = 1;

let extraClassDefinition = [{
ParseResult $cppClass::parse(OpAsmParser &parser, OperationState &result) {
return parseOneResultSameOperandTypeOp(parser, result);
}
void $cppClass::print(OpAsmPrinter &p) {
return printOneResultOp(getOperation(), p);
}
}];

let hasOptions = 1;
}

def CIR_ConstOp : Op<CIR_Dialect, "pseudo_const", [ConstantLike, Pure,
FirstAttrDerivedResultType,
Expand Down
2 changes: 1 addition & 1 deletion circle-mlir/circle-mlir/lib/dialect/src/CircleDialect.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -442,7 +442,7 @@ void ConstBytesAttr::print(mlir::AsmPrinter &printer) const
} // namespace Circle
} // namespace mlir

// TODO add AddOp
#include "ops/AddOp.h"
#include "ops/ConstOp.h"
#include "ops/CustomOp.h"
#include "ops/NoValueOp.h"
Expand Down
17 changes: 16 additions & 1 deletion circle-mlir/circle-mlir/lib/dialect/src/ShapeInference.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,22 @@ template <typename BINOP> bool inferBinShapes(BINOP &op, SmallVector<int64_t, 4>

} // namespace

// TODO add AddOp
//===----------------------------------------------------------------------===//
// AddOp
//===----------------------------------------------------------------------===//

void AddOp::inferShapes()
{
AddOp op = *this;
SmallVector<int64_t, 4> inferred;
if (!inferBinShapes<AddOp>(op, inferred))
return;

auto input0_op = getOperand(0);
auto input0_type = input0_op.getType().cast<TensorType>();
RankedTensorType inferred_type = RankedTensorType::get(inferred, input0_type.getElementType());
getResult().setType(inferred_type);
}

//===----------------------------------------------------------------------===//
// CustomOp
Expand Down
66 changes: 66 additions & 0 deletions circle-mlir/circle-mlir/lib/dialect/src/ops/AddOp.h
Original file line number Diff line number Diff line change
@@ -0,0 +1,66 @@
/*
* Copyright (c) 2025 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

// from tensorflow/compiler/mlir/lite/ir/tfl_ops.cc

#ifndef __CIRCLE_MLIR_DIALECT_OPS_ADD_OP_H__
#define __CIRCLE_MLIR_DIALECT_OPS_ADD_OP_H__

#include "circle-mlir/dialect/CircleDialect.h"

namespace mlir
{
namespace Circle
{

// Return true if the given Add operation has the CPU kernel supported shapes.
bool VerifyAddOpShapeConstraints(AddOp op)
{
auto element_type = getElementTypeOrSelf(op.getOutput().getType());

// Allows F32 and I32 outputs when the operands have valid shapes,
// which are broadcastable shapes up to four dimensions or have same shapes.
// TODO support Quantized Type
if (element_type.isF32() || IsI32Type(element_type) || IsI64Type(element_type))
{
return VerifyOperandsHaveSameShapesOrBroadcastableShape(
/*op=*/op.getOperation(), /*indices=*/ArrayRef<unsigned>{0, 1},
/*max_bcast_rank=*/4);
}

return false;
}

//===----------------------------------------------------------------------===//
// AddOp
//===----------------------------------------------------------------------===//

OpFoldResult AddOp::fold(FoldAdaptor adaptor)
{
auto operands = adaptor.getOperands();
// TODO(b/142478136): Handle fused ops.
if (getFusedActivationFunction() != "NONE")
return {};
return ConstFoldBinaryOp(
getType(), operands, [](APFloat a, APFloat b) { return a + b; },
[](APInt a, APInt b) { return a + b; });
}

} // namespace Circle
} // namespace mlir

#endif // __CIRCLE_MLIR_DIALECT_OPS_ADD_OP_H__
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