a54f4eae0e
Precursor: https://reviews.llvm.org/D110200 Removed redundant ops from the standard dialect that were moved to the `arith` or `math` dialects. Renamed all instances of operations in the codebase and in tests. Reviewed By: rriddle, jpienaar Differential Revision: https://reviews.llvm.org/D110797
81 lines
3.3 KiB
C++
81 lines
3.3 KiB
C++
//===- MathToSPIRV.cpp - Math to SPIR-V Patterns --------------------------===//
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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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//
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// This file implements patterns to convert Math dialect to SPIR-V dialect.
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//
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//===----------------------------------------------------------------------===//
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#include "../SPIRVCommon/Pattern.h"
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#include "mlir/Dialect/Math/IR/Math.h"
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#include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
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#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
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#include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
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#include "llvm/Support/Debug.h"
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#define DEBUG_TYPE "math-to-spirv-pattern"
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using namespace mlir;
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//===----------------------------------------------------------------------===//
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// Operation conversion
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//===----------------------------------------------------------------------===//
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// Note that DRR cannot be used for the patterns in this file: we may need to
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// convert type along the way, which requires ConversionPattern. DRR generates
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// normal RewritePattern.
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namespace {
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/// Converts math.log1p to SPIR-V ops.
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///
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/// SPIR-V does not have a direct operations for log(1+x). Explicitly lower to
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/// these operations.
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class Log1pOpPattern final : public OpConversionPattern<math::Log1pOp> {
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public:
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using OpConversionPattern<math::Log1pOp>::OpConversionPattern;
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LogicalResult
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matchAndRewrite(math::Log1pOp operation, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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assert(adaptor.getOperands().size() == 1);
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Location loc = operation.getLoc();
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auto type =
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this->getTypeConverter()->convertType(operation.operand().getType());
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auto one = spirv::ConstantOp::getOne(type, operation.getLoc(), rewriter);
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auto onePlus =
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rewriter.create<spirv::FAddOp>(loc, one, adaptor.getOperands()[0]);
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rewriter.replaceOpWithNewOp<spirv::GLSLLogOp>(operation, type, onePlus);
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return success();
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}
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};
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} // namespace
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//===----------------------------------------------------------------------===//
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// Pattern population
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//===----------------------------------------------------------------------===//
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namespace mlir {
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void populateMathToSPIRVPatterns(SPIRVTypeConverter &typeConverter,
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RewritePatternSet &patterns) {
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patterns.add<
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Log1pOpPattern,
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spirv::UnaryAndBinaryOpPattern<math::AbsOp, spirv::GLSLFAbsOp>,
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spirv::UnaryAndBinaryOpPattern<math::CeilOp, spirv::GLSLCeilOp>,
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spirv::UnaryAndBinaryOpPattern<math::CosOp, spirv::GLSLCosOp>,
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spirv::UnaryAndBinaryOpPattern<math::ExpOp, spirv::GLSLExpOp>,
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spirv::UnaryAndBinaryOpPattern<math::FloorOp, spirv::GLSLFloorOp>,
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spirv::UnaryAndBinaryOpPattern<math::LogOp, spirv::GLSLLogOp>,
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spirv::UnaryAndBinaryOpPattern<math::PowFOp, spirv::GLSLPowOp>,
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spirv::UnaryAndBinaryOpPattern<math::RsqrtOp, spirv::GLSLInverseSqrtOp>,
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spirv::UnaryAndBinaryOpPattern<math::SinOp, spirv::GLSLSinOp>,
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spirv::UnaryAndBinaryOpPattern<math::SqrtOp, spirv::GLSLSqrtOp>,
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spirv::UnaryAndBinaryOpPattern<math::TanhOp, spirv::GLSLTanhOp>>(
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typeConverter, patterns.getContext());
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}
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} // namespace mlir
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