The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
565 lines
21 KiB
C++
565 lines
21 KiB
C++
//===- VectorToSPIRV.cpp - Vector 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 Vector dialect to SPIRV dialect.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Conversion/VectorToSPIRV/VectorToSPIRV.h"
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#include "mlir/Dialect/Arith/IR/Arith.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/IR/SPIRVTypes.h"
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#include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
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#include "mlir/Dialect/Vector/IR/VectorOps.h"
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#include "mlir/IR/BuiltinAttributes.h"
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#include "mlir/IR/BuiltinTypes.h"
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#include "mlir/IR/Matchers.h"
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#include "mlir/IR/PatternMatch.h"
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#include "mlir/IR/TypeUtilities.h"
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#include "mlir/Support/LogicalResult.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "llvm/ADT/ArrayRef.h"
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#include "llvm/ADT/STLExtras.h"
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#include "llvm/Support/FormatVariadic.h"
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#include <numeric>
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using namespace mlir;
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/// Gets the first integer value from `attr`, assuming it is an integer array
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/// attribute.
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static uint64_t getFirstIntValue(ArrayAttr attr) {
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return (*attr.getAsValueRange<IntegerAttr>().begin()).getZExtValue();
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}
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/// Returns the number of bits for the given scalar/vector type.
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static int getNumBits(Type type) {
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// TODO: This does not take into account any memory layout or widening
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// constraints. E.g., a vector<3xi57> may report to occupy 3x57=171 bit, even
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// though in practice it will likely be stored as in a 4xi64 vector register.
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if (auto vectorType = dyn_cast<VectorType>(type))
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return vectorType.getNumElements() * vectorType.getElementTypeBitWidth();
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return type.getIntOrFloatBitWidth();
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}
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namespace {
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struct VectorBitcastConvert final
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: public OpConversionPattern<vector::BitCastOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::BitCastOp bitcastOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type dstType = getTypeConverter()->convertType(bitcastOp.getType());
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if (!dstType)
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return failure();
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if (dstType == adaptor.getSource().getType()) {
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rewriter.replaceOp(bitcastOp, adaptor.getSource());
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return success();
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}
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// Check that the source and destination type have the same bitwidth.
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// Depending on the target environment, we may need to emulate certain
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// types, which can cause issue with bitcast.
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Type srcType = adaptor.getSource().getType();
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if (getNumBits(dstType) != getNumBits(srcType)) {
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return rewriter.notifyMatchFailure(
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bitcastOp,
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llvm::formatv("different source ({0}) and target ({1}) bitwidth",
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srcType, dstType));
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}
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rewriter.replaceOpWithNewOp<spirv::BitcastOp>(bitcastOp, dstType,
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adaptor.getSource());
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return success();
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}
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};
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struct VectorBroadcastConvert final
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: public OpConversionPattern<vector::BroadcastOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::BroadcastOp castOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type resultType =
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getTypeConverter()->convertType(castOp.getResultVectorType());
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if (!resultType)
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return failure();
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if (isa<spirv::ScalarType>(resultType)) {
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rewriter.replaceOp(castOp, adaptor.getSource());
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return success();
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}
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SmallVector<Value, 4> source(castOp.getResultVectorType().getNumElements(),
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adaptor.getSource());
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rewriter.replaceOpWithNewOp<spirv::CompositeConstructOp>(
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castOp, castOp.getResultVectorType(), source);
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return success();
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}
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};
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struct VectorExtractOpConvert final
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: public OpConversionPattern<vector::ExtractOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::ExtractOp extractOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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// Only support extracting a scalar value now.
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VectorType resultVectorType = dyn_cast<VectorType>(extractOp.getType());
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if (resultVectorType && resultVectorType.getNumElements() > 1)
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return failure();
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Type dstType = getTypeConverter()->convertType(extractOp.getType());
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if (!dstType)
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return failure();
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if (isa<spirv::ScalarType>(adaptor.getVector().getType())) {
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rewriter.replaceOp(extractOp, adaptor.getVector());
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return success();
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}
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int32_t id = getFirstIntValue(extractOp.getPosition());
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rewriter.replaceOpWithNewOp<spirv::CompositeExtractOp>(
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extractOp, adaptor.getVector(), id);
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return success();
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}
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};
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struct VectorExtractStridedSliceOpConvert final
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: public OpConversionPattern<vector::ExtractStridedSliceOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::ExtractStridedSliceOp extractOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type dstType = getTypeConverter()->convertType(extractOp.getType());
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if (!dstType)
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return failure();
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uint64_t offset = getFirstIntValue(extractOp.getOffsets());
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uint64_t size = getFirstIntValue(extractOp.getSizes());
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uint64_t stride = getFirstIntValue(extractOp.getStrides());
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if (stride != 1)
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return failure();
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Value srcVector = adaptor.getOperands().front();
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// Extract vector<1xT> case.
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if (isa<spirv::ScalarType>(dstType)) {
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rewriter.replaceOpWithNewOp<spirv::CompositeExtractOp>(extractOp,
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srcVector, offset);
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return success();
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}
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SmallVector<int32_t, 2> indices(size);
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std::iota(indices.begin(), indices.end(), offset);
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rewriter.replaceOpWithNewOp<spirv::VectorShuffleOp>(
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extractOp, dstType, srcVector, srcVector,
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rewriter.getI32ArrayAttr(indices));
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return success();
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}
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};
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template <class SPIRVFMAOp>
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struct VectorFmaOpConvert final : public OpConversionPattern<vector::FMAOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::FMAOp fmaOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type dstType = getTypeConverter()->convertType(fmaOp.getType());
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if (!dstType)
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return failure();
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rewriter.replaceOpWithNewOp<SPIRVFMAOp>(fmaOp, dstType, adaptor.getLhs(),
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adaptor.getRhs(), adaptor.getAcc());
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return success();
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}
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};
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struct VectorInsertOpConvert final
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: public OpConversionPattern<vector::InsertOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::InsertOp insertOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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// Special case for inserting scalar values into size-1 vectors.
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if (insertOp.getSourceType().isIntOrFloat() &&
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insertOp.getDestVectorType().getNumElements() == 1) {
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rewriter.replaceOp(insertOp, adaptor.getSource());
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return success();
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}
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if (isa<VectorType>(insertOp.getSourceType()) ||
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!spirv::CompositeType::isValid(insertOp.getDestVectorType()))
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return failure();
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int32_t id = getFirstIntValue(insertOp.getPosition());
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rewriter.replaceOpWithNewOp<spirv::CompositeInsertOp>(
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insertOp, adaptor.getSource(), adaptor.getDest(), id);
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return success();
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}
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};
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struct VectorExtractElementOpConvert final
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: public OpConversionPattern<vector::ExtractElementOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::ExtractElementOp extractOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type resultType = getTypeConverter()->convertType(extractOp.getType());
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if (!resultType)
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return failure();
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if (isa<spirv::ScalarType>(adaptor.getVector().getType())) {
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rewriter.replaceOp(extractOp, adaptor.getVector());
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return success();
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}
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APInt cstPos;
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if (matchPattern(adaptor.getPosition(), m_ConstantInt(&cstPos)))
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rewriter.replaceOpWithNewOp<spirv::CompositeExtractOp>(
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extractOp, resultType, adaptor.getVector(),
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rewriter.getI32ArrayAttr({static_cast<int>(cstPos.getSExtValue())}));
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else
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rewriter.replaceOpWithNewOp<spirv::VectorExtractDynamicOp>(
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extractOp, resultType, adaptor.getVector(), adaptor.getPosition());
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return success();
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}
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};
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struct VectorInsertElementOpConvert final
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: public OpConversionPattern<vector::InsertElementOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::InsertElementOp insertOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type vectorType = getTypeConverter()->convertType(insertOp.getType());
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if (!vectorType)
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return failure();
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if (isa<spirv::ScalarType>(vectorType)) {
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rewriter.replaceOp(insertOp, adaptor.getSource());
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return success();
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}
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APInt cstPos;
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if (matchPattern(adaptor.getPosition(), m_ConstantInt(&cstPos)))
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rewriter.replaceOpWithNewOp<spirv::CompositeInsertOp>(
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insertOp, adaptor.getSource(), adaptor.getDest(),
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cstPos.getSExtValue());
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else
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rewriter.replaceOpWithNewOp<spirv::VectorInsertDynamicOp>(
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insertOp, vectorType, insertOp.getDest(), adaptor.getSource(),
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adaptor.getPosition());
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return success();
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}
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};
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struct VectorInsertStridedSliceOpConvert final
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: public OpConversionPattern<vector::InsertStridedSliceOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::InsertStridedSliceOp insertOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Value srcVector = adaptor.getOperands().front();
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Value dstVector = adaptor.getOperands().back();
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uint64_t stride = getFirstIntValue(insertOp.getStrides());
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if (stride != 1)
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return failure();
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uint64_t offset = getFirstIntValue(insertOp.getOffsets());
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if (isa<spirv::ScalarType>(srcVector.getType())) {
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assert(!isa<spirv::ScalarType>(dstVector.getType()));
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rewriter.replaceOpWithNewOp<spirv::CompositeInsertOp>(
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insertOp, dstVector.getType(), srcVector, dstVector,
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rewriter.getI32ArrayAttr(offset));
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return success();
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}
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uint64_t totalSize = cast<VectorType>(dstVector.getType()).getNumElements();
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uint64_t insertSize =
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cast<VectorType>(srcVector.getType()).getNumElements();
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SmallVector<int32_t, 2> indices(totalSize);
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std::iota(indices.begin(), indices.end(), 0);
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std::iota(indices.begin() + offset, indices.begin() + offset + insertSize,
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totalSize);
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rewriter.replaceOpWithNewOp<spirv::VectorShuffleOp>(
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insertOp, dstVector.getType(), dstVector, srcVector,
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rewriter.getI32ArrayAttr(indices));
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return success();
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}
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};
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template <class SPIRVFMaxOp, class SPIRVFMinOp, class SPIRVUMaxOp,
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class SPIRVUMinOp, class SPIRVSMaxOp, class SPIRVSMinOp>
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struct VectorReductionPattern final
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: public OpConversionPattern<vector::ReductionOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::ReductionOp reduceOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type resultType = typeConverter->convertType(reduceOp.getType());
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if (!resultType)
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return failure();
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auto srcVectorType = dyn_cast<VectorType>(adaptor.getVector().getType());
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if (!srcVectorType || srcVectorType.getRank() != 1)
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return rewriter.notifyMatchFailure(reduceOp, "not 1-D vector source");
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// Extract all elements.
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int numElements = srcVectorType.getDimSize(0);
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SmallVector<Value, 4> values;
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values.reserve(numElements + (adaptor.getAcc() != nullptr));
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Location loc = reduceOp.getLoc();
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for (int i = 0; i < numElements; ++i) {
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values.push_back(rewriter.create<spirv::CompositeExtractOp>(
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loc, srcVectorType.getElementType(), adaptor.getVector(),
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rewriter.getI32ArrayAttr({i})));
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}
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if (Value acc = adaptor.getAcc())
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values.push_back(acc);
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// Reduce them.
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Value result = values.front();
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for (Value next : llvm::ArrayRef(values).drop_front()) {
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switch (reduceOp.getKind()) {
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#define INT_AND_FLOAT_CASE(kind, iop, fop) \
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case vector::CombiningKind::kind: \
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if (resultType.isa<IntegerType>()) { \
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result = rewriter.create<spirv::iop>(loc, resultType, result, next); \
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} else { \
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assert(resultType.isa<FloatType>()); \
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result = rewriter.create<spirv::fop>(loc, resultType, result, next); \
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} \
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break
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#define INT_OR_FLOAT_CASE(kind, fop) \
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case vector::CombiningKind::kind: \
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result = rewriter.create<fop>(loc, resultType, result, next); \
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break
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INT_AND_FLOAT_CASE(ADD, IAddOp, FAddOp);
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INT_AND_FLOAT_CASE(MUL, IMulOp, FMulOp);
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INT_OR_FLOAT_CASE(MAXF, SPIRVFMaxOp);
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INT_OR_FLOAT_CASE(MINF, SPIRVFMinOp);
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INT_OR_FLOAT_CASE(MINUI, SPIRVUMinOp);
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INT_OR_FLOAT_CASE(MINSI, SPIRVSMinOp);
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INT_OR_FLOAT_CASE(MAXUI, SPIRVUMaxOp);
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INT_OR_FLOAT_CASE(MAXSI, SPIRVSMaxOp);
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case vector::CombiningKind::AND:
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case vector::CombiningKind::OR:
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case vector::CombiningKind::XOR:
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return rewriter.notifyMatchFailure(reduceOp, "unimplemented");
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}
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}
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rewriter.replaceOp(reduceOp, result);
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return success();
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}
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};
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class VectorSplatPattern final : public OpConversionPattern<vector::SplatOp> {
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public:
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using OpConversionPattern<vector::SplatOp>::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::SplatOp op, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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Type dstType = getTypeConverter()->convertType(op.getType());
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if (!dstType)
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return failure();
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if (isa<spirv::ScalarType>(dstType)) {
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rewriter.replaceOp(op, adaptor.getInput());
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} else {
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auto dstVecType = cast<VectorType>(dstType);
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SmallVector<Value, 4> source(dstVecType.getNumElements(),
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adaptor.getInput());
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rewriter.replaceOpWithNewOp<spirv::CompositeConstructOp>(op, dstType,
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source);
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}
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return success();
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}
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};
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struct VectorShuffleOpConvert final
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: public OpConversionPattern<vector::ShuffleOp> {
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using OpConversionPattern::OpConversionPattern;
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LogicalResult
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matchAndRewrite(vector::ShuffleOp shuffleOp, OpAdaptor adaptor,
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ConversionPatternRewriter &rewriter) const override {
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auto oldResultType = shuffleOp.getResultVectorType();
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if (!spirv::CompositeType::isValid(oldResultType))
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return failure();
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Type newResultType = getTypeConverter()->convertType(oldResultType);
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auto oldSourceType = shuffleOp.getV1VectorType();
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if (oldSourceType.getNumElements() > 1) {
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SmallVector<int32_t, 4> components = llvm::to_vector<4>(
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llvm::map_range(shuffleOp.getMask(), [](Attribute attr) -> int32_t {
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return cast<IntegerAttr>(attr).getValue().getZExtValue();
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}));
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rewriter.replaceOpWithNewOp<spirv::VectorShuffleOp>(
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shuffleOp, newResultType, adaptor.getV1(), adaptor.getV2(),
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rewriter.getI32ArrayAttr(components));
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return success();
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}
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SmallVector<Value, 2> oldOperands = {adaptor.getV1(), adaptor.getV2()};
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SmallVector<Value, 4> newOperands;
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newOperands.reserve(oldResultType.getNumElements());
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for (const APInt &i : shuffleOp.getMask().getAsValueRange<IntegerAttr>()) {
|
|
newOperands.push_back(oldOperands[i.getZExtValue()]);
|
|
}
|
|
rewriter.replaceOpWithNewOp<spirv::CompositeConstructOp>(
|
|
shuffleOp, newResultType, newOperands);
|
|
|
|
return success();
|
|
}
|
|
};
|
|
|
|
struct VectorReductionToDotProd final : OpRewritePattern<vector::ReductionOp> {
|
|
using OpRewritePattern::OpRewritePattern;
|
|
|
|
LogicalResult matchAndRewrite(vector::ReductionOp op,
|
|
PatternRewriter &rewriter) const override {
|
|
if (op.getKind() != vector::CombiningKind::ADD)
|
|
return rewriter.notifyMatchFailure(op, "combining kind is not 'add'");
|
|
|
|
auto resultType = dyn_cast<IntegerType>(op.getType());
|
|
if (!resultType)
|
|
return rewriter.notifyMatchFailure(op, "result is not an integer");
|
|
|
|
int64_t resultBitwidth = resultType.getIntOrFloatBitWidth();
|
|
if (!llvm::is_contained({32, 64}, resultBitwidth))
|
|
return rewriter.notifyMatchFailure(op, "unsupported integer bitwidth");
|
|
|
|
VectorType inVecTy = op.getSourceVectorType();
|
|
if (!llvm::is_contained({4, 3}, inVecTy.getNumElements()) ||
|
|
inVecTy.getShape().size() != 1 || inVecTy.isScalable())
|
|
return rewriter.notifyMatchFailure(op, "unsupported vector shape");
|
|
|
|
auto mul = op.getVector().getDefiningOp<arith::MulIOp>();
|
|
if (!mul)
|
|
return rewriter.notifyMatchFailure(
|
|
op, "reduction operand is not 'arith.muli'");
|
|
|
|
if (succeeded(handleCase<arith::ExtSIOp, arith::ExtSIOp, spirv::SDotOp,
|
|
spirv::SDotAccSatOp, false>(op, mul, rewriter)))
|
|
return success();
|
|
|
|
if (succeeded(handleCase<arith::ExtUIOp, arith::ExtUIOp, spirv::UDotOp,
|
|
spirv::UDotAccSatOp, false>(op, mul, rewriter)))
|
|
return success();
|
|
|
|
if (succeeded(handleCase<arith::ExtSIOp, arith::ExtUIOp, spirv::SUDotOp,
|
|
spirv::SUDotAccSatOp, false>(op, mul, rewriter)))
|
|
return success();
|
|
|
|
if (succeeded(handleCase<arith::ExtUIOp, arith::ExtSIOp, spirv::SUDotOp,
|
|
spirv::SUDotAccSatOp, true>(op, mul, rewriter)))
|
|
return success();
|
|
|
|
return failure();
|
|
}
|
|
|
|
private:
|
|
template <typename LhsExtensionOp, typename RhsExtensionOp, typename DotOp,
|
|
typename DotAccOp, bool SwapOperands>
|
|
static LogicalResult handleCase(vector::ReductionOp op, arith::MulIOp mul,
|
|
PatternRewriter &rewriter) {
|
|
auto lhs = mul.getLhs().getDefiningOp<LhsExtensionOp>();
|
|
if (!lhs)
|
|
return failure();
|
|
Value lhsIn = lhs.getIn();
|
|
auto lhsInType = cast<VectorType>(lhsIn.getType());
|
|
if (!lhsInType.getElementType().isInteger(8))
|
|
return failure();
|
|
|
|
auto rhs = mul.getRhs().getDefiningOp<RhsExtensionOp>();
|
|
if (!rhs)
|
|
return failure();
|
|
Value rhsIn = rhs.getIn();
|
|
auto rhsInType = cast<VectorType>(rhsIn.getType());
|
|
if (!rhsInType.getElementType().isInteger(8))
|
|
return failure();
|
|
|
|
if (op.getSourceVectorType().getNumElements() == 3) {
|
|
IntegerType i8Type = rewriter.getI8Type();
|
|
auto v4i8Type = VectorType::get({4}, i8Type);
|
|
Location loc = op.getLoc();
|
|
Value zero = spirv::ConstantOp::getZero(i8Type, loc, rewriter);
|
|
lhsIn = rewriter.create<spirv::CompositeConstructOp>(
|
|
loc, v4i8Type, ValueRange{lhsIn, zero});
|
|
rhsIn = rewriter.create<spirv::CompositeConstructOp>(
|
|
loc, v4i8Type, ValueRange{rhsIn, zero});
|
|
}
|
|
|
|
// There's no variant of dot prod ops for unsigned LHS and signed RHS, so
|
|
// we have to swap operands instead in that case.
|
|
if (SwapOperands)
|
|
std::swap(lhsIn, rhsIn);
|
|
|
|
if (Value acc = op.getAcc()) {
|
|
rewriter.replaceOpWithNewOp<DotAccOp>(op, op.getType(), lhsIn, rhsIn, acc,
|
|
nullptr);
|
|
} else {
|
|
rewriter.replaceOpWithNewOp<DotOp>(op, op.getType(), lhsIn, rhsIn,
|
|
nullptr);
|
|
}
|
|
|
|
return success();
|
|
}
|
|
};
|
|
|
|
} // namespace
|
|
#define CL_MAX_MIN_OPS \
|
|
spirv::CLFMaxOp, spirv::CLFMinOp, spirv::CLUMaxOp, spirv::CLUMinOp, \
|
|
spirv::CLSMaxOp, spirv::CLSMinOp
|
|
|
|
#define GL_MAX_MIN_OPS \
|
|
spirv::GLFMaxOp, spirv::GLFMinOp, spirv::GLUMaxOp, spirv::GLUMinOp, \
|
|
spirv::GLSMaxOp, spirv::GLSMinOp
|
|
|
|
void mlir::populateVectorToSPIRVPatterns(SPIRVTypeConverter &typeConverter,
|
|
RewritePatternSet &patterns) {
|
|
patterns.add<
|
|
VectorBitcastConvert, VectorBroadcastConvert,
|
|
VectorExtractElementOpConvert, VectorExtractOpConvert,
|
|
VectorExtractStridedSliceOpConvert, VectorFmaOpConvert<spirv::GLFmaOp>,
|
|
VectorFmaOpConvert<spirv::CLFmaOp>, VectorInsertElementOpConvert,
|
|
VectorInsertOpConvert, VectorReductionPattern<GL_MAX_MIN_OPS>,
|
|
VectorReductionPattern<CL_MAX_MIN_OPS>, VectorInsertStridedSliceOpConvert,
|
|
VectorShuffleOpConvert, VectorSplatPattern>(typeConverter,
|
|
patterns.getContext());
|
|
}
|
|
|
|
void mlir::populateVectorReductionToSPIRVDotProductPatterns(
|
|
RewritePatternSet &patterns) {
|
|
patterns.add<VectorReductionToDotProd>(patterns.getContext());
|
|
}
|