Files
clang-p2996/mlir/test/lib/Transforms/TestLinalgTransforms.cpp
Nicolas Vasilache 8dbbb22383 [mlir][Linalg] NFC - Refactor and simplify Promotion
Summary: This revision introduces LinalgPromotionOptions to more easily control the application of promotion patterns. It also simplifies the different entry points into Promotion in preparation for some behavior change in subsequent revisions.

Differential Revision: https://reviews.llvm.org/D79489
2020-05-11 10:44:45 -04:00

153 lines
6.1 KiB
C++

//===- TestLinalgTransforms.cpp - Test Linalg transformation patterns -----===//
//
// 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 logic for testing Linalg transformations.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Linalg/IR/LinalgOps.h"
#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
#include "mlir/Dialect/Linalg/Utils/Utils.h"
#include "mlir/IR/PatternMatch.h"
#include "mlir/Pass/Pass.h"
#include "llvm/ADT/SetVector.h"
using namespace mlir;
using namespace mlir::linalg;
namespace {
struct TestLinalgTransforms
: public PassWrapper<TestLinalgTransforms, FunctionPass> {
TestLinalgTransforms() = default;
TestLinalgTransforms(const TestLinalgTransforms &pass) {}
void runOnFunction() override;
Option<bool> testPatterns{*this, "test-patterns",
llvm::cl::desc("Test a mixed set of patterns"),
llvm::cl::init(false)};
};
} // end anonymous namespace
static void applyPatterns(FuncOp funcOp) {
MLIRContext *ctx = funcOp.getContext();
OwningRewritePatternList patterns;
//===--------------------------------------------------------------------===//
// Linalg tiling patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({2000, 3000, 4000}),
LinalgMarker({"MEM", {}}, "L3"));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({200, 300, 400}),
LinalgMarker({"L3"}, "L2"));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({20, 30, 40}),
LinalgMarker({"L2"}, "L1"));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({2, 3, 4}),
LinalgMarker({"L1"}, "REG"));
patterns.insert<LinalgTilingPattern<MatvecOp>>(
ctx,
LinalgTilingOptions().setTileSizes({5, 6}).setLoopType(
LinalgTilingLoopType::ParallelLoops),
LinalgMarker({}, "L1"));
patterns.insert<LinalgTilingPattern<DotOp>>(
ctx, LinalgTilingOptions().setTileSizes(8000),
LinalgMarker({"MEM", "L3", "L2", {}}, "REG"));
//===--------------------------------------------------------------------===//
// Linalg tiling and permutation patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx,
LinalgTilingOptions()
.setTileSizes({2000, 3000, 4000})
.setInterchange({1, 2, 0}),
LinalgMarker({"__with_perm__"}, "L2__with_perm__"));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx,
LinalgTilingOptions()
.setTileSizes({200, 300, 400})
.setInterchange({1, 0, 2}),
LinalgMarker({"L2__with_perm__"}, "L1__with_perm__"));
patterns.insert<LinalgTilingPattern<MatmulOp>>(
ctx, LinalgTilingOptions().setTileSizes({20, 30, 40}),
LinalgMarker({"L1__with_perm__"}, "REG__with_perm__"));
patterns.insert<LinalgTilingPattern<MatvecOp>>(
ctx, LinalgTilingOptions().setTileSizes({5, 6}).setInterchange({1, 0}),
LinalgMarker({"__with_perm__"}, "L1__with_perm__"));
//===--------------------------------------------------------------------===//
// Linalg to loops patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgLoweringPattern<DotOp>>(
ctx,
/*loweringType=*/LinalgLoweringType::Loops, LinalgMarker({"REG"}));
//===--------------------------------------------------------------------===//
// Linalg to vector contraction patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgVectorizationPattern<MatmulOp>,
LinalgVectorizationPattern<FillOp>,
LinalgVectorizationPattern<GenericOp>>(
ctx, LinalgMarker({"VECTORIZE"}));
//===--------------------------------------------------------------------===//
// Linalg generic permutation patterns.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgInterchangePattern<GenericOp>>(
ctx,
/*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
LinalgMarker({}, "PERMUTED"));
patterns.insert<LinalgInterchangePattern<IndexedGenericOp>>(
ctx,
/*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0},
LinalgMarker({}, "PERMUTED"));
//===--------------------------------------------------------------------===//
// Linalg subview operands promotion.
//===--------------------------------------------------------------------===//
patterns.insert<LinalgPromotionPattern<MatmulOp>>(
ctx, LinalgPromotionOptions(),
LinalgMarker({"_promote_views_"}, "_views_promoted_"));
patterns.insert<LinalgPromotionPattern<MatmulOp>>(
ctx, LinalgPromotionOptions().setOperandsToPromote({0}),
LinalgMarker({"_promote_first_view_"}, "_first_view_promoted_"));
patterns.insert<LinalgPromotionPattern<FillOp>>(
ctx, LinalgPromotionOptions().setOperandsToPromote({0}).setAlignment(32),
LinalgMarker({"_promote_views_aligned_"}, "_views_aligned_promoted_"));
applyPatternsAndFoldGreedily(funcOp, patterns);
// Drop the marker.
funcOp.walk([](LinalgOp op) {
op.removeAttr(LinalgTransforms::kLinalgTransformMarker);
});
}
/// Apply transformations specified as patterns.
void TestLinalgTransforms::runOnFunction() {
if (testPatterns)
return applyPatterns(getFunction());
}
namespace mlir {
void registerTestLinalgTransforms() {
PassRegistration<TestLinalgTransforms> testTransformPatternsPass(
"test-linalg-transform-patterns",
"Test Linalg transformation patterns by applying them greedily.");
}
} // namespace mlir