llvm-project/mlir/lib/Conversion/LinalgToStandard/LinalgToStandard.cpp

Ignoring revisions in .git-blame-ignore-revs. Click here to bypass and see the normal blame view.

231 lines
8.9 KiB
C++
Raw Normal View History

//===- LinalgToStandard.cpp - conversion from Linalg to Standard 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/LinalgToStandard/LinalgToStandard.h"
#include "../PassDetail.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Linalg/IR/LinalgOps.h"
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/SCF.h"
#include "mlir/Dialect/StandardOps/IR/Ops.h"
using namespace mlir;
using namespace mlir::linalg;
/// Helper function to extract the operand types that are passed to the
/// generated CallOp. MemRefTypes have their layout canonicalized since the
/// information is not used in signature generation.
/// Note that static size information is not modified.
static SmallVector<Type, 4> extractOperandTypes(Operation *op) {
SmallVector<Type, 4> result;
result.reserve(op->getNumOperands());
if (auto indexedGenericOp = dyn_cast<IndexedGenericOp>(op)) {
auto *ctx = op->getContext();
auto numLoops = indexedGenericOp.getNumLoops();
result.reserve(op->getNumOperands() + numLoops);
result.assign(numLoops, IndexType::get(ctx));
}
for (auto type : op->getOperandTypes()) {
// The underlying descriptor type (e.g. LLVM) does not have layout
// information. Canonicalizing the type at the level of std when going into
// a library call avoids needing to introduce DialectCastOp.
if (auto memrefType = type.dyn_cast<MemRefType>())
result.push_back(eraseStridedLayout(memrefType));
else
result.push_back(type);
}
return result;
}
// Get a SymbolRefAttr containing the library function name for the LinalgOp.
// If the library function does not exist, insert a declaration.
static FlatSymbolRefAttr getLibraryCallSymbolRef(Operation *op,
PatternRewriter &rewriter) {
auto linalgOp = cast<LinalgOp>(op);
auto fnName = linalgOp.getLibraryCallName();
if (fnName.empty()) {
op->emitWarning("No library call defined for: ") << *op;
return {};
}
// fnName is a dynamic std::string, unique it via a SymbolRefAttr.
FlatSymbolRefAttr fnNameAttr = rewriter.getSymbolRefAttr(fnName);
auto module = op->getParentOfType<ModuleOp>();
if (module.lookupSymbol(fnName)) {
return fnNameAttr;
}
SmallVector<Type, 4> inputTypes(extractOperandTypes(op));
assert(op->getNumResults() == 0 &&
"Library call for linalg operation can be generated only for ops that "
"have void return types");
auto libFnType = rewriter.getFunctionType(inputTypes, {});
OpBuilder::InsertionGuard guard(rewriter);
// Insert before module terminator.
rewriter.setInsertionPoint(module.getBody(),
std::prev(module.getBody()->end()));
FuncOp funcOp =
rewriter.create<FuncOp>(op->getLoc(), fnNameAttr.getValue(), libFnType);
// Insert a function attribute that will trigger the emission of the
// corresponding `_mlir_ciface_xxx` interface so that external libraries see
// a normalized ABI. This interface is added during std to llvm conversion.
funcOp->setAttr("llvm.emit_c_interface", UnitAttr::get(op->getContext()));
funcOp.setPrivate();
return fnNameAttr;
}
static SmallVector<Value, 4>
createTypeCanonicalizedMemRefOperands(OpBuilder &b, Location loc,
ValueRange operands) {
SmallVector<Value, 4> res;
res.reserve(operands.size());
for (auto op : operands) {
auto memrefType = op.getType().dyn_cast<MemRefType>();
if (!memrefType) {
res.push_back(op);
continue;
}
Value cast =
b.create<memref::CastOp>(loc, eraseStridedLayout(memrefType), op);
res.push_back(cast);
}
return res;
}
LogicalResult mlir::linalg::LinalgOpToLibraryCallRewrite::matchAndRewrite(
Operation *op, PatternRewriter &rewriter) const {
// Only LinalgOp for which there is no specialized pattern go through this.
if (!isa<LinalgOp>(op) || isa<CopyOp>(op) || isa<IndexedGenericOp>(op))
return failure();
auto libraryCallName = getLibraryCallSymbolRef(op, rewriter);
if (!libraryCallName)
return failure();
rewriter.replaceOpWithNewOp<mlir::CallOp>(
op, libraryCallName.getValue(), TypeRange(),
createTypeCanonicalizedMemRefOperands(rewriter, op->getLoc(),
op->getOperands()));
return success();
}
LogicalResult mlir::linalg::CopyOpToLibraryCallRewrite::matchAndRewrite(
CopyOp op, PatternRewriter &rewriter) const {
auto inputPerm = op.inputPermutation();
if (inputPerm.hasValue() && !inputPerm->isIdentity())
return failure();
auto outputPerm = op.outputPermutation();
if (outputPerm.hasValue() && !outputPerm->isIdentity())
return failure();
auto libraryCallName = getLibraryCallSymbolRef(op, rewriter);
if (!libraryCallName)
return failure();
rewriter.replaceOpWithNewOp<mlir::CallOp>(
op, libraryCallName.getValue(), TypeRange(),
createTypeCanonicalizedMemRefOperands(rewriter, op.getLoc(),
op.getOperands()));
return success();
}
LogicalResult mlir::linalg::CopyTransposeRewrite::matchAndRewrite(
CopyOp op, PatternRewriter &rewriter) const {
Value in = op.input(), out = op.output();
// If either inputPerm or outputPerm are non-identities, insert transposes.
auto inputPerm = op.inputPermutation();
if (inputPerm.hasValue() && !inputPerm->isIdentity())
in = rewriter.create<memref::TransposeOp>(op.getLoc(), in,
AffineMapAttr::get(*inputPerm));
auto outputPerm = op.outputPermutation();
if (outputPerm.hasValue() && !outputPerm->isIdentity())
out = rewriter.create<memref::TransposeOp>(op.getLoc(), out,
AffineMapAttr::get(*outputPerm));
// If nothing was transposed, fail and let the conversion kick in.
if (in == op.input() && out == op.output())
return failure();
auto libraryCallName = getLibraryCallSymbolRef(op, rewriter);
if (!libraryCallName)
return failure();
rewriter.replaceOpWithNewOp<mlir::CallOp>(
op, libraryCallName.getValue(), TypeRange(),
createTypeCanonicalizedMemRefOperands(rewriter, op.getLoc(), {in, out}));
return success();
}
LogicalResult
mlir::linalg::IndexedGenericOpToLibraryCallRewrite::matchAndRewrite(
IndexedGenericOp op, PatternRewriter &rewriter) const {
auto libraryCallName = getLibraryCallSymbolRef(op, rewriter);
if (!libraryCallName)
return failure();
// TODO: Use induction variables values instead of zeros, when
// IndexedGenericOp is tiled.
auto zero = rewriter.create<mlir::ConstantOp>(
op.getLoc(), rewriter.getIntegerAttr(rewriter.getIndexType(), 0));
auto indexedGenericOp = cast<IndexedGenericOp>(op);
auto numLoops = indexedGenericOp.getNumLoops();
SmallVector<Value, 4> operands;
operands.reserve(numLoops + op.getNumOperands());
for (unsigned i = 0; i < numLoops; ++i)
operands.push_back(zero);
for (auto operand : op.getOperands())
operands.push_back(operand);
rewriter.replaceOpWithNewOp<mlir::CallOp>(
op, libraryCallName.getValue(), TypeRange(),
createTypeCanonicalizedMemRefOperands(rewriter, op.getLoc(), operands));
return success();
}
/// Populate the given list with patterns that convert from Linalg to Standard.
void mlir::linalg::populateLinalgToStandardConversionPatterns(
OwningRewritePatternList &patterns) {
// TODO: ConvOp conversion needs to export a descriptor with relevant
// attribute values such as kernel striding and dilation.
// clang-format off
patterns.insert<
CopyOpToLibraryCallRewrite,
CopyTransposeRewrite,
IndexedGenericOpToLibraryCallRewrite>(patterns.getContext());
patterns.insert<LinalgOpToLibraryCallRewrite>();
// clang-format on
}
namespace {
struct ConvertLinalgToStandardPass
: public ConvertLinalgToStandardBase<ConvertLinalgToStandardPass> {
void runOnOperation() override;
};
} // namespace
void ConvertLinalgToStandardPass::runOnOperation() {
auto module = getOperation();
ConversionTarget target(getContext());
target.addLegalDialect<AffineDialect, memref::MemRefDialect, scf::SCFDialect,
StandardOpsDialect>();
target.addLegalOp<ModuleOp, FuncOp, ModuleTerminatorOp, ReturnOp>();
target.addLegalOp<linalg::ReshapeOp, linalg::RangeOp>();
OwningRewritePatternList patterns(&getContext());
populateLinalgToStandardConversionPatterns(patterns);
if (failed(applyFullConversion(module, target, std::move(patterns))))
signalPassFailure();
}
std::unique_ptr<OperationPass<ModuleOp>>
mlir::createConvertLinalgToStandardPass() {
return std::make_unique<ConvertLinalgToStandardPass>();
}