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