torch-mlir/lib/Conversion/ATenToTCF/CoreOpConversionPatterns.cpp

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//===----------------------------------------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "npcomp/Conversion/ATenToTCF/Patterns.h"
#include "mlir/IR/MLIRContext.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/PatternMatch.h"
#include "npcomp/Dialect/ATen/IR/ATenDialect.h"
#include "npcomp/Dialect/TCF/IR/TCFOps.h"
using namespace mlir;
using namespace mlir::NPCOMP;
namespace {
/// The ATen AddOp actually has three arguments:
/// self, other, alpha
/// Alpha is an integer that is multiplied by 'other' prior to adding.
class ConvertATenAdd : public OpRewritePattern<aten::AddOp> {
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(aten::AddOp srcAddOp,
PatternRewriter &rewriter) const override {
// Special case: Match when alpha is constant 1, which is the default,
// quite common and maps directly to a TCF add. Note that regardless of
// the type of self/other (i.e. if they are float), alpha emits as an
// integer with value 1 when defaulted. It is this specific case that we
// are detecting (default value) and will leave all others to the fully
// generic conversion.
APInt alphaValue;
if (matchPattern(srcAddOp.alpha(), m_ConstantInt(&alphaValue)) &&
alphaValue.getZExtValue() == 1) {
rewriter.replaceOpWithNewOp<tcf::AddOp>(
srcAddOp, srcAddOp.getResult().getType(), srcAddOp.self(),
srcAddOp.other());
return success();
}
return rewriter.notifyMatchFailure(
srcAddOp, "aten.add to tcf.add currently only supports alpha == 1");
}
};
/// Common conversion template for true binary elementwise ops.
/// This does not apply to the handful of not-actually-binary PyTorch ops that
/// have broadcastable self/other operands but may have additional parameters.
template <typename SourceOp, typename TargetOp>
class ConvertBinaryElementwise : public OpRewritePattern<SourceOp> {
public:
using OpRewritePattern<SourceOp>::OpRewritePattern;
LogicalResult matchAndRewrite(SourceOp srcOp,
PatternRewriter &rewriter) const override {
auto operands = srcOp.getOperation()->getOperands();
auto results = srcOp.getOperation()->getResults();
assert(operands.size() == 2 && "expected true binary op");
assert(results.size() == 1 && "expected single result op");
Type resultType = results[0].getType();
rewriter.replaceOpWithNewOp<TargetOp>(
srcOp, resultType, srcOp.getOperand(0), srcOp.getOperand(1));
return success();
}
};
} // namespace
void mlir::NPCOMP::populateCoreATenToTCFPatterns(
MLIRContext *context, OwningRewritePatternList &patterns) {
patterns.insert<ConvertATenAdd>(context);
patterns.insert<ConvertBinaryElementwise<aten::MulOp, tcf::MulOp>>(context);
patterns.insert<ConvertBinaryElementwise<aten::MaximumOp, tcf::MaxOp>>(
context);
patterns.insert<ConvertBinaryElementwise<aten::MmOp, tcf::MatmulOp>>(context);
}