llvm-project/mlir/test/lib/Dialect/Affine/TestAffineDataCopy.cpp
River Riddle 3655069234 [mlir] Move the Builtin FuncOp to the Func dialect
This commit moves FuncOp out of the builtin dialect, and into the Func
dialect. This move has been planned in some capacity from the moment
we made FuncOp an operation (years ago). This commit handles the
functional aspects of the move, but various aspects are left untouched
to ease migration: func::FuncOp is re-exported into mlir to reduce
the actual API churn, the assembly format still accepts the unqualified
`func`. These temporary measures will remain for a little while to
simplify migration before being removed.

Differential Revision: https://reviews.llvm.org/D121266
2022-03-16 17:07:03 -07:00

141 lines
4.9 KiB
C++

//===- TestAffineDataCopy.cpp - Test affine data copy utility -------------===//
//
// 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 a pass to test affine data copy utility functions and
// options.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/Analysis/Utils.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Affine/LoopUtils.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
#include "mlir/Transforms/Passes.h"
#define PASS_NAME "test-affine-data-copy"
using namespace mlir;
namespace {
struct TestAffineDataCopy
: public PassWrapper<TestAffineDataCopy, OperationPass<FuncOp>> {
StringRef getArgument() const final { return PASS_NAME; }
StringRef getDescription() const final {
return "Tests affine data copy utility functions.";
}
TestAffineDataCopy() = default;
TestAffineDataCopy(const TestAffineDataCopy &pass) : PassWrapper(pass){};
void getDependentDialects(DialectRegistry &registry) const override {
registry.insert<memref::MemRefDialect>();
}
void runOnOperation() override;
private:
Option<bool> clMemRefFilter{
*this, "memref-filter",
llvm::cl::desc(
"Enable memref filter testing in affine data copy optimization"),
llvm::cl::init(false)};
Option<bool> clTestGenerateCopyForMemRegion{
*this, "for-memref-region",
llvm::cl::desc("Test copy generation for a single memref region"),
llvm::cl::init(false)};
};
} // namespace
void TestAffineDataCopy::runOnOperation() {
// Gather all AffineForOps by loop depth.
std::vector<SmallVector<AffineForOp, 2>> depthToLoops;
gatherLoops(getOperation(), depthToLoops);
assert(!depthToLoops.empty() && "Loop nest not found");
// Only support tests with a single loop nest and a single innermost loop
// for now.
unsigned innermostLoopIdx = depthToLoops.size() - 1;
if (depthToLoops[0].size() != 1 || depthToLoops[innermostLoopIdx].size() != 1)
return;
auto loopNest = depthToLoops[0][0];
auto innermostLoop = depthToLoops[innermostLoopIdx][0];
AffineLoadOp load;
if (clMemRefFilter || clTestGenerateCopyForMemRegion) {
// Gather MemRef filter. For simplicity, we use the first loaded memref
// found in the innermost loop.
for (auto &op : *innermostLoop.getBody()) {
if (auto ld = dyn_cast<AffineLoadOp>(op)) {
load = ld;
break;
}
}
}
if (!load)
return;
AffineCopyOptions copyOptions = {/*generateDma=*/false,
/*slowMemorySpace=*/0,
/*fastMemorySpace=*/0,
/*tagMemorySpace=*/0,
/*fastMemCapacityBytes=*/32 * 1024 * 1024UL};
DenseSet<Operation *> copyNests;
if (clMemRefFilter) {
if (failed(affineDataCopyGenerate(loopNest, copyOptions, load.getMemRef(),
copyNests)))
return;
} else if (clTestGenerateCopyForMemRegion) {
CopyGenerateResult result;
MemRefRegion region(loopNest.getLoc());
if (failed(region.compute(load, /*loopDepth=*/0)))
return;
if (failed(generateCopyForMemRegion(region, loopNest, copyOptions, result)))
return;
}
// Promote any single iteration loops in the copy nests and simplify
// load/stores.
SmallVector<Operation *, 4> copyOps;
for (Operation *nest : copyNests) {
// With a post order walk, the erasure of loops does not affect
// continuation of the walk or the collection of load/store ops.
nest->walk([&](Operation *op) {
if (auto forOp = dyn_cast<AffineForOp>(op))
(void)promoteIfSingleIteration(forOp);
else if (auto loadOp = dyn_cast<AffineLoadOp>(op))
copyOps.push_back(loadOp);
else if (auto storeOp = dyn_cast<AffineStoreOp>(op))
copyOps.push_back(storeOp);
});
}
// Promoting single iteration loops could lead to simplification of
// generated load's/store's, and the latter could anyway also be
// canonicalized.
RewritePatternSet patterns(&getContext());
for (Operation *op : copyOps) {
patterns.clear();
if (isa<AffineLoadOp>(op)) {
AffineLoadOp::getCanonicalizationPatterns(patterns, &getContext());
} else {
assert(isa<AffineStoreOp>(op) && "expected affine store op");
AffineStoreOp::getCanonicalizationPatterns(patterns, &getContext());
}
}
(void)applyOpPatternsAndFold(copyOps, std::move(patterns), /*strict=*/true);
}
namespace mlir {
void registerTestAffineDataCopyPass() {
PassRegistration<TestAffineDataCopy>();
}
} // namespace mlir