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//===- AffineExprTest.cpp - unit tests for affine expression API ----------===//
//
// 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 <cstdint>
#include <limits>
#include "mlir/IR/AffineExpr.h"
#include "mlir/IR/Builders.h"
#include "gtest/gtest.h"
using namespace mlir;
static std::string toString(AffineExpr expr) {
std::string s;
llvm::raw_string_ostream ss(s);
ss << expr;
return s;
}
// Test creating AffineExprs using the overloaded binary operators.
TEST(AffineExprTest, constructFromBinaryOperators) {
MLIRContext ctx;
OpBuilder b(&ctx);
auto d0 = b.getAffineDimExpr(0);
auto d1 = b.getAffineDimExpr(1);
auto sum = d0 + d1;
auto difference = d0 - d1;
auto product = d0 * d1;
auto remainder = d0 % d1;
ASSERT_EQ(sum.getKind(), AffineExprKind::Add);
ASSERT_EQ(difference.getKind(), AffineExprKind::Add);
ASSERT_EQ(product.getKind(), AffineExprKind::Mul);
ASSERT_EQ(remainder.getKind(), AffineExprKind::Mod);
}
TEST(AffineExprTest, constantFolding) {
MLIRContext ctx;
OpBuilder b(&ctx);
auto cn1 = b.getAffineConstantExpr(-1);
auto c0 = b.getAffineConstantExpr(0);
auto c1 = b.getAffineConstantExpr(1);
auto c2 = b.getAffineConstantExpr(2);
auto c3 = b.getAffineConstantExpr(3);
auto c6 = b.getAffineConstantExpr(6);
auto cmax = b.getAffineConstantExpr(std::numeric_limits<int64_t>::max());
auto cmin = b.getAffineConstantExpr(std::numeric_limits<int64_t>::min());
ASSERT_EQ(getAffineBinaryOpExpr(AffineExprKind::Add, c1, c2), c3);
ASSERT_EQ(getAffineBinaryOpExpr(AffineExprKind::Mul, c2, c3), c6);
ASSERT_EQ(getAffineBinaryOpExpr(AffineExprKind::FloorDiv, c3, c2), c1);
ASSERT_EQ(getAffineBinaryOpExpr(AffineExprKind::CeilDiv, c3, c2), c2);
// Test division by zero:
auto c3ceildivc0 = getAffineBinaryOpExpr(AffineExprKind::CeilDiv, c3, c0);
ASSERT_EQ(c3ceildivc0.getKind(), AffineExprKind::CeilDiv);
auto c3floordivc0 = getAffineBinaryOpExpr(AffineExprKind::FloorDiv, c3, c0);
ASSERT_EQ(c3floordivc0.getKind(), AffineExprKind::FloorDiv);
auto c3modc0 = getAffineBinaryOpExpr(AffineExprKind::Mod, c3, c0);
ASSERT_EQ(c3modc0.getKind(), AffineExprKind::Mod);
// Test overflow:
auto cmaxplusc1 = getAffineBinaryOpExpr(AffineExprKind::Add, cmax, c1);
ASSERT_EQ(cmaxplusc1.getKind(), AffineExprKind::Add);
auto cmaxtimesc2 = getAffineBinaryOpExpr(AffineExprKind::Mul, cmax, c2);
ASSERT_EQ(cmaxtimesc2.getKind(), AffineExprKind::Mul);
auto cminceildivcn1 =
getAffineBinaryOpExpr(AffineExprKind::CeilDiv, cmin, cn1);
ASSERT_EQ(cminceildivcn1.getKind(), AffineExprKind::CeilDiv);
auto cminfloordivcn1 =
getAffineBinaryOpExpr(AffineExprKind::FloorDiv, cmin, cn1);
ASSERT_EQ(cminfloordivcn1.getKind(), AffineExprKind::FloorDiv);
}
TEST(AffineExprTest, commutative) {
MLIRContext ctx;
OpBuilder b(&ctx);
auto c2 = b.getAffineConstantExpr(1);
auto d0 = b.getAffineDimExpr(0);
auto d1 = b.getAffineDimExpr(1);
auto s0 = b.getAffineSymbolExpr(0);
auto s1 = b.getAffineSymbolExpr(1);
ASSERT_EQ(d0 * d1, d1 * d0);
ASSERT_EQ(s0 + s1, s1 + s0);
ASSERT_EQ(s0 * c2, c2 * s0);
}
TEST(AffineExprTest, divisionSimplification) {
MLIRContext ctx;
OpBuilder b(&ctx);
auto cn6 = b.getAffineConstantExpr(-6);
auto c6 = b.getAffineConstantExpr(6);
auto d0 = b.getAffineDimExpr(0);
auto d1 = b.getAffineDimExpr(1);
ASSERT_EQ(c6.floorDiv(-1), cn6);
ASSERT_EQ((d0 * 6).floorDiv(2), d0 * 3);
ASSERT_EQ((d0 * 6).floorDiv(4).getKind(), AffineExprKind::FloorDiv);
ASSERT_EQ((d0 * 6).floorDiv(-2), d0 * -3);
ASSERT_EQ((d0 * 6 + d1).floorDiv(2), d0 * 3 + d1.floorDiv(2));
ASSERT_EQ((d0 * 6 + d1).floorDiv(-2), d0 * -3 + d1.floorDiv(-2));
ASSERT_EQ((d0 * 6 + d1).floorDiv(4).getKind(), AffineExprKind::FloorDiv);
ASSERT_EQ(c6.ceilDiv(-1), cn6);
ASSERT_EQ((d0 * 6).ceilDiv(2), d0 * 3);
ASSERT_EQ((d0 * 6).ceilDiv(4).getKind(), AffineExprKind::CeilDiv);
ASSERT_EQ((d0 * 6).ceilDiv(-2), d0 * -3);
}
TEST(AffineExprTest, modSimplificationRegression) {
MLIRContext ctx;
OpBuilder b(&ctx);
auto d0 = b.getAffineDimExpr(0);
auto sum = d0 + d0.floorDiv(3).floorDiv(-3);
ASSERT_EQ(sum.getKind(), AffineExprKind::Add);
}
TEST(AffineExprTest, divisorOfNegativeFloorDiv) {
MLIRContext ctx;
OpBuilder b(&ctx);
ASSERT_EQ(b.getAffineDimExpr(0).floorDiv(-1).getLargestKnownDivisor(), 1);
}
TEST(AffineExprTest, d0PlusD0FloorDivNeg2) {
// Regression test for a bug where this was rewritten to d0 mod -2. We do not
// support a negative RHS for mod in LowerAffinePass.
MLIRContext ctx;
OpBuilder b(&ctx);
auto d0 = b.getAffineDimExpr(0);
auto sum = d0 + d0.floorDiv(-2) * 2;
ASSERT_EQ(toString(sum), "d0 + (d0 floordiv -2) * 2");
}
TEST(AffineExprTest, simpleAffineExprFlattenerRegression) {
// Regression test for a bug where mod simplification was not handled
// properly when `lhs % rhs` was happened to have the property that `lhs
// floordiv rhs = lhs`.
MLIRContext ctx;
OpBuilder b(&ctx);
auto d0 = b.getAffineDimExpr(0);
// Manually replace variables by constants to avoid constant folding.
AffineExpr expr = (d0 - (d0 + 2)).floorDiv(8) % 8;
AffineExpr result = mlir::simplifyAffineExpr(expr, 1, 0);
ASSERT_TRUE(isa<AffineConstantExpr>(result));
ASSERT_EQ(cast<AffineConstantExpr>(result).getValue(), 7);
}
TEST(AffineExprTest, simplifyCommutative) {
MLIRContext ctx;
OpBuilder b(&ctx);
auto s0 = b.getAffineSymbolExpr(0);
auto s1 = b.getAffineSymbolExpr(1);
ASSERT_EQ(s0 * s1 - s1 * s0 + 1, 1);
}