Files
clang-p2996/mlir/lib/Conversion/LLVMCommon/VectorPattern.cpp
Tres Popp 5550c82189 [mlir] Move casting calls from methods to function calls
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
2023-05-12 11:21:25 +02:00

132 lines
5.3 KiB
C++

//===- VectorPattern.cpp - Vector conversion pattern to the LLVM dialect --===//
//
// 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 "mlir/Conversion/LLVMCommon/VectorPattern.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
using namespace mlir;
// For >1-D vector types, extracts the necessary information to iterate over all
// 1-D subvectors in the underlying llrepresentation of the n-D vector
// Iterates on the llvm array type until we hit a non-array type (which is
// asserted to be an llvm vector type).
LLVM::detail::NDVectorTypeInfo
LLVM::detail::extractNDVectorTypeInfo(VectorType vectorType,
LLVMTypeConverter &converter) {
assert(vectorType.getRank() > 1 && "expected >1D vector type");
NDVectorTypeInfo info;
info.llvmNDVectorTy = converter.convertType(vectorType);
if (!info.llvmNDVectorTy || !LLVM::isCompatibleType(info.llvmNDVectorTy)) {
info.llvmNDVectorTy = nullptr;
return info;
}
info.arraySizes.reserve(vectorType.getRank() - 1);
auto llvmTy = info.llvmNDVectorTy;
while (isa<LLVM::LLVMArrayType>(llvmTy)) {
info.arraySizes.push_back(
cast<LLVM::LLVMArrayType>(llvmTy).getNumElements());
llvmTy = cast<LLVM::LLVMArrayType>(llvmTy).getElementType();
}
if (!LLVM::isCompatibleVectorType(llvmTy))
return info;
info.llvm1DVectorTy = llvmTy;
return info;
}
// Express `linearIndex` in terms of coordinates of `basis`.
// Returns the empty vector when linearIndex is out of the range [0, P] where
// P is the product of all the basis coordinates.
//
// Prerequisites:
// Basis is an array of nonnegative integers (signed type inherited from
// vector shape type).
SmallVector<int64_t, 4> LLVM::detail::getCoordinates(ArrayRef<int64_t> basis,
unsigned linearIndex) {
SmallVector<int64_t, 4> res;
res.reserve(basis.size());
for (unsigned basisElement : llvm::reverse(basis)) {
res.push_back(linearIndex % basisElement);
linearIndex = linearIndex / basisElement;
}
if (linearIndex > 0)
return {};
std::reverse(res.begin(), res.end());
return res;
}
// Iterate of linear index, convert to coords space and insert splatted 1-D
// vector in each position.
void LLVM::detail::nDVectorIterate(const LLVM::detail::NDVectorTypeInfo &info,
OpBuilder &builder,
function_ref<void(ArrayRef<int64_t>)> fun) {
unsigned ub = 1;
for (auto s : info.arraySizes)
ub *= s;
for (unsigned linearIndex = 0; linearIndex < ub; ++linearIndex) {
auto coords = getCoordinates(info.arraySizes, linearIndex);
// Linear index is out of bounds, we are done.
if (coords.empty())
break;
assert(coords.size() == info.arraySizes.size());
fun(coords);
}
}
LogicalResult LLVM::detail::handleMultidimensionalVectors(
Operation *op, ValueRange operands, LLVMTypeConverter &typeConverter,
std::function<Value(Type, ValueRange)> createOperand,
ConversionPatternRewriter &rewriter) {
auto resultNDVectorType = cast<VectorType>(op->getResult(0).getType());
auto resultTypeInfo =
extractNDVectorTypeInfo(resultNDVectorType, typeConverter);
auto result1DVectorTy = resultTypeInfo.llvm1DVectorTy;
auto resultNDVectoryTy = resultTypeInfo.llvmNDVectorTy;
auto loc = op->getLoc();
Value desc = rewriter.create<LLVM::UndefOp>(loc, resultNDVectoryTy);
nDVectorIterate(resultTypeInfo, rewriter, [&](ArrayRef<int64_t> position) {
// For this unrolled `position` corresponding to the `linearIndex`^th
// element, extract operand vectors
SmallVector<Value, 4> extractedOperands;
for (const auto &operand : llvm::enumerate(operands)) {
extractedOperands.push_back(rewriter.create<LLVM::ExtractValueOp>(
loc, operand.value(), position));
}
Value newVal = createOperand(result1DVectorTy, extractedOperands);
desc = rewriter.create<LLVM::InsertValueOp>(loc, desc, newVal, position);
});
rewriter.replaceOp(op, desc);
return success();
}
LogicalResult LLVM::detail::vectorOneToOneRewrite(
Operation *op, StringRef targetOp, ValueRange operands,
ArrayRef<NamedAttribute> targetAttrs, LLVMTypeConverter &typeConverter,
ConversionPatternRewriter &rewriter) {
assert(!operands.empty());
// Cannot convert ops if their operands are not of LLVM type.
if (!llvm::all_of(operands.getTypes(), isCompatibleType))
return failure();
auto llvmNDVectorTy = operands[0].getType();
if (!isa<LLVM::LLVMArrayType>(llvmNDVectorTy))
return oneToOneRewrite(op, targetOp, operands, targetAttrs, typeConverter,
rewriter);
auto callback = [op, targetOp, targetAttrs, &rewriter](Type llvm1DVectorTy,
ValueRange operands) {
return rewriter
.create(op->getLoc(), rewriter.getStringAttr(targetOp), operands,
llvm1DVectorTy, targetAttrs)
->getResult(0);
};
return handleMultidimensionalVectors(op, operands, typeConverter, callback,
rewriter);
}