Files
clang-p2996/mlir/lib/Dialect/Vector/Transforms/LowerVectorBroadcast.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

157 lines
5.8 KiB
C++

//===- LowerVectorBroadcast.cpp - Lower 'vector.broadcast' operation ------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements target-independent rewrites and utilities to lower the
// 'vector.broadcast' operation.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
#include "mlir/Dialect/Linalg/IR/Linalg.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/Tensor/IR/Tensor.h"
#include "mlir/Dialect/Utils/IndexingUtils.h"
#include "mlir/Dialect/Utils/StructuredOpsUtils.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
#include "mlir/Dialect/Vector/Transforms/VectorRewritePatterns.h"
#include "mlir/Dialect/Vector/Utils/VectorUtils.h"
#include "mlir/IR/BuiltinAttributeInterfaces.h"
#include "mlir/IR/BuiltinTypes.h"
#include "mlir/IR/ImplicitLocOpBuilder.h"
#include "mlir/IR/Location.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/IR/TypeUtilities.h"
#include "mlir/Interfaces/VectorInterfaces.h"
#include "mlir/Support/LogicalResult.h"
#define DEBUG_TYPE "vector-broadcast-lowering"
using namespace mlir;
using namespace mlir::vector;
namespace {
/// Progressive lowering of BroadcastOp.
class BroadcastOpLowering : public OpRewritePattern<vector::BroadcastOp> {
public:
using OpRewritePattern::OpRewritePattern;
LogicalResult matchAndRewrite(vector::BroadcastOp op,
PatternRewriter &rewriter) const override {
auto loc = op.getLoc();
VectorType dstType = op.getResultVectorType();
VectorType srcType = dyn_cast<VectorType>(op.getSourceType());
Type eltType = dstType.getElementType();
// Scalar to any vector can use splat.
if (!srcType) {
rewriter.replaceOpWithNewOp<vector::SplatOp>(op, dstType, op.getSource());
return success();
}
// Determine rank of source and destination.
int64_t srcRank = srcType.getRank();
int64_t dstRank = dstType.getRank();
// Stretching scalar inside vector (e.g. vector<1xf32>) can use splat.
if (srcRank <= 1 && dstRank == 1) {
Value ext;
if (srcRank == 0)
ext = rewriter.create<vector::ExtractElementOp>(loc, op.getSource());
else
ext = rewriter.create<vector::ExtractOp>(loc, op.getSource(), 0);
rewriter.replaceOpWithNewOp<vector::SplatOp>(op, dstType, ext);
return success();
}
// Duplicate this rank.
// For example:
// %x = broadcast %y : k-D to n-D, k < n
// becomes:
// %b = broadcast %y : k-D to (n-1)-D
// %x = [%b,%b,%b,%b] : n-D
// becomes:
// %b = [%y,%y] : (n-1)-D
// %x = [%b,%b,%b,%b] : n-D
if (srcRank < dstRank) {
// Duplication.
VectorType resType =
VectorType::get(dstType.getShape().drop_front(), eltType);
Value bcst =
rewriter.create<vector::BroadcastOp>(loc, resType, op.getSource());
Value result = rewriter.create<arith::ConstantOp>(
loc, dstType, rewriter.getZeroAttr(dstType));
for (int64_t d = 0, dim = dstType.getDimSize(0); d < dim; ++d)
result = rewriter.create<vector::InsertOp>(loc, bcst, result, d);
rewriter.replaceOp(op, result);
return success();
}
// Find non-matching dimension, if any.
assert(srcRank == dstRank);
int64_t m = -1;
for (int64_t r = 0; r < dstRank; r++)
if (srcType.getDimSize(r) != dstType.getDimSize(r)) {
m = r;
break;
}
// All trailing dimensions are the same. Simply pass through.
if (m == -1) {
rewriter.replaceOp(op, op.getSource());
return success();
}
// Any non-matching dimension forces a stretch along this rank.
// For example:
// %x = broadcast %y : vector<4x1x2xf32> to vector<4x2x2xf32>
// becomes:
// %a = broadcast %y[0] : vector<1x2xf32> to vector<2x2xf32>
// %b = broadcast %y[1] : vector<1x2xf32> to vector<2x2xf32>
// %c = broadcast %y[2] : vector<1x2xf32> to vector<2x2xf32>
// %d = broadcast %y[3] : vector<1x2xf32> to vector<2x2xf32>
// %x = [%a,%b,%c,%d]
// becomes:
// %u = broadcast %y[0][0] : vector<2xf32> to vector <2x2xf32>
// %v = broadcast %y[1][0] : vector<2xf32> to vector <2x2xf32>
// %a = [%u, %v]
// ..
// %x = [%a,%b,%c,%d]
VectorType resType =
VectorType::get(dstType.getShape().drop_front(), eltType);
Value result = rewriter.create<arith::ConstantOp>(
loc, dstType, rewriter.getZeroAttr(dstType));
if (m == 0) {
// Stetch at start.
Value ext = rewriter.create<vector::ExtractOp>(loc, op.getSource(), 0);
Value bcst = rewriter.create<vector::BroadcastOp>(loc, resType, ext);
for (int64_t d = 0, dim = dstType.getDimSize(0); d < dim; ++d)
result = rewriter.create<vector::InsertOp>(loc, bcst, result, d);
} else {
// Stetch not at start.
for (int64_t d = 0, dim = dstType.getDimSize(0); d < dim; ++d) {
Value ext = rewriter.create<vector::ExtractOp>(loc, op.getSource(), d);
Value bcst = rewriter.create<vector::BroadcastOp>(loc, resType, ext);
result = rewriter.create<vector::InsertOp>(loc, bcst, result, d);
}
}
rewriter.replaceOp(op, result);
return success();
}
};
} // namespace
void mlir::vector::populateVectorBroadcastLoweringPatterns(
RewritePatternSet &patterns, PatternBenefit benefit) {
patterns.add<BroadcastOpLowering>(patterns.getContext(), benefit);
}