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llvm-project/mlir/unittests/Analysis/AffineStructuresTest.cpp

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//===- AffineStructuresTest.cpp - Tests for AffineStructures ----*- C++ -*-===//
//
// 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/Analysis/AffineStructures.h"
#include "mlir/IR/IntegerSet.h"
#include "mlir/IR/MLIRContext.h"
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include <numeric>
namespace mlir {
using testing::ElementsAre;
enum class TestFunction { Sample, Empty };
/// If fn is TestFunction::Sample (default):
/// If hasSample is true, check that findIntegerSample returns a valid sample
/// for the FlatAffineConstraints fac.
/// If hasSample is false, check that findIntegerSample returns None.
///
/// If fn is TestFunction::Empty, check that isIntegerEmpty returns the
/// opposite of hasSample.
static void checkSample(bool hasSample, const FlatAffineConstraints &fac,
TestFunction fn = TestFunction::Sample) {
Optional<SmallVector<int64_t, 8>> maybeSample;
switch (fn) {
case TestFunction::Sample:
maybeSample = fac.findIntegerSample();
if (!hasSample) {
EXPECT_FALSE(maybeSample.hasValue());
if (maybeSample.hasValue()) {
for (auto x : *maybeSample)
llvm::errs() << x << ' ';
llvm::errs() << '\n';
}
} else {
ASSERT_TRUE(maybeSample.hasValue());
EXPECT_TRUE(fac.containsPoint(*maybeSample));
}
break;
case TestFunction::Empty:
EXPECT_EQ(!hasSample, fac.isIntegerEmpty());
break;
}
}
/// Construct a FlatAffineConstraints from a set of inequality and
/// equality constraints.
static FlatAffineConstraints
makeFACFromConstraints(unsigned ids, ArrayRef<SmallVector<int64_t, 4>> ineqs,
ArrayRef<SmallVector<int64_t, 4>> eqs,
unsigned syms = 0) {
FlatAffineConstraints fac(ineqs.size(), eqs.size(), ids + 1, ids - syms, syms,
/*numLocals=*/0);
for (const auto &eq : eqs)
fac.addEquality(eq);
for (const auto &ineq : ineqs)
fac.addInequality(ineq);
return fac;
}
/// Check sampling for all the permutations of the dimensions for the given
/// constraint set. Since the GBR algorithm progresses dimension-wise, different
/// orderings may cause the algorithm to proceed differently. At least some of
///.these permutations should make it past the heuristics and test the
/// implementation of the GBR algorithm itself.
/// Use TestFunction fn to test.
static void checkPermutationsSample(bool hasSample, unsigned nDim,
ArrayRef<SmallVector<int64_t, 4>> ineqs,
ArrayRef<SmallVector<int64_t, 4>> eqs,
TestFunction fn = TestFunction::Sample) {
SmallVector<unsigned, 4> perm(nDim);
std::iota(perm.begin(), perm.end(), 0);
auto permute = [&perm](ArrayRef<int64_t> coeffs) {
SmallVector<int64_t, 4> permuted;
for (unsigned id : perm)
permuted.push_back(coeffs[id]);
permuted.push_back(coeffs.back());
return permuted;
};
do {
SmallVector<SmallVector<int64_t, 4>, 4> permutedIneqs, permutedEqs;
for (const auto &ineq : ineqs)
permutedIneqs.push_back(permute(ineq));
for (const auto &eq : eqs)
permutedEqs.push_back(permute(eq));
checkSample(hasSample,
makeFACFromConstraints(nDim, permutedIneqs, permutedEqs), fn);
} while (std::next_permutation(perm.begin(), perm.end()));
}
TEST(FlatAffineConstraintsTest, FindSampleTest) {
// Bounded sets with only inequalities.
// 0 <= 7x <= 5
checkSample(true, makeFACFromConstraints(1, {{7, 0}, {-7, 5}}, {}));
// 1 <= 5x and 5x <= 4 (no solution).
checkSample(false, makeFACFromConstraints(1, {{5, -1}, {-5, 4}}, {}));
// 1 <= 5x and 5x <= 9 (solution: x = 1).
checkSample(true, makeFACFromConstraints(1, {{5, -1}, {-5, 9}}, {}));
// Bounded sets with equalities.
// x >= 8 and 40 >= y and x = y.
checkSample(
true, makeFACFromConstraints(2, {{1, 0, -8}, {0, -1, 40}}, {{1, -1, 0}}));
// x <= 10 and y <= 10 and 10 <= z and x + 2y = 3z.
// solution: x = y = z = 10.
checkSample(true, makeFACFromConstraints(
3, {{-1, 0, 0, 10}, {0, -1, 0, 10}, {0, 0, 1, -10}},
{{1, 2, -3, 0}}));
// x <= 10 and y <= 10 and 11 <= z and x + 2y = 3z.
// This implies x + 2y >= 33 and x + 2y <= 30, which has no solution.
checkSample(false, makeFACFromConstraints(
3, {{-1, 0, 0, 10}, {0, -1, 0, 10}, {0, 0, 1, -11}},
{{1, 2, -3, 0}}));
// 0 <= r and r <= 3 and 4q + r = 7.
// Solution: q = 1, r = 3.
checkSample(true,
makeFACFromConstraints(2, {{0, 1, 0}, {0, -1, 3}}, {{4, 1, -7}}));
// 4q + r = 7 and r = 0.
// Solution: q = 1, r = 3.
checkSample(false, makeFACFromConstraints(2, {}, {{4, 1, -7}, {0, 1, 0}}));
// The next two sets are large sets that should take a long time to sample
// with a naive branch and bound algorithm but can be sampled efficiently with
// the GBR algorithm.
//
// This is a triangle with vertices at (1/3, 0), (2/3, 0) and (10000, 10000).
checkSample(
true,
makeFACFromConstraints(
2, {{0, 1, 0}, {300000, -299999, -100000}, {-300000, 299998, 200000}},
{}));
// This is a tetrahedron with vertices at
// (1/3, 0, 0), (2/3, 0, 0), (2/3, 0, 10000), and (10000, 10000, 10000).
// The first three points form a triangular base on the xz plane with the
// apex at the fourth point, which is the only integer point.
checkPermutationsSample(
true, 3,
{
{0, 1, 0, 0}, // y >= 0
{0, -1, 1, 0}, // z >= y
{300000, -299998, -1,
-100000}, // -300000x + 299998y + 100000 + z <= 0.
{-150000, 149999, 0, 100000}, // -150000x + 149999y + 100000 >= 0.
},
{});
// Same thing with some spurious extra dimensions equated to constants.
checkSample(true,
makeFACFromConstraints(
5,
{
{0, 1, 0, 1, -1, 0},
{0, -1, 1, -1, 1, 0},
{300000, -299998, -1, -9, 21, -112000},
{-150000, 149999, 0, -15, 47, 68000},
},
{{0, 0, 0, 1, -1, 0}, // p = q.
{0, 0, 0, 1, 1, -2000}})); // p + q = 20000 => p = q = 10000.
// This is a tetrahedron with vertices at
// (1/3, 0, 0), (2/3, 0, 0), (2/3, 0, 100), (100, 100 - 1/3, 100).
checkPermutationsSample(false, 3,
{
{0, 1, 0, 0},
{0, -300, 299, 0},
{300 * 299, -89400, -299, -100 * 299},
{-897, 894, 0, 598},
},
{});
// Two tests involving equalities that are integer empty but not rational
// empty.
// This is a line segment from (0, 1/3) to (100, 100 + 1/3).
checkSample(false, makeFACFromConstraints(
2,
{
{1, 0, 0}, // x >= 0.
{-1, 0, 100} // -x + 100 >= 0, i.e., x <= 100.
},
{
{3, -3, 1} // 3x - 3y + 1 = 0, i.e., y = x + 1/3.
}));
// A thin parallelogram. 0 <= x <= 100 and x + 1/3 <= y <= x + 2/3.
checkSample(false, makeFACFromConstraints(2,
{
{1, 0, 0}, // x >= 0.
{-1, 0, 100}, // x <= 100.
{3, -3, 2}, // 3x - 3y >= -2.
{-3, 3, -1}, // 3x - 3y <= -1.
},
{}));
checkSample(true, makeFACFromConstraints(2,
{
{2, 0, 0}, // 2x >= 1.
{-2, 0, 99}, // 2x <= 99.
{0, 2, 0}, // 2y >= 0.
{0, -2, 99}, // 2y <= 99.
},
{}));
// 2D cone with apex at (10000, 10000) and
// edges passing through (1/3, 0) and (2/3, 0).
checkSample(
true,
makeFACFromConstraints(
2, {{300000, -299999, -100000}, {-300000, 299998, 200000}}, {}));
// Cartesian product of a tetrahedron and a 2D cone.
// The tetrahedron has vertices at
// (1/3, 0, 0), (2/3, 0, 0), (2/3, 0, 10000), and (10000, 10000, 10000).
// The first three points form a triangular base on the xz plane with the
// apex at the fourth point, which is the only integer point.
// The cone has apex at (10000, 10000) and
// edges passing through (1/3, 0) and (2/3, 0).
checkPermutationsSample(
true /* not empty */, 5,
{
// Tetrahedron contraints:
{0, 1, 0, 0, 0, 0}, // y >= 0
{0, -1, 1, 0, 0, 0}, // z >= y
// -300000x + 299998y + 100000 + z <= 0.
{300000, -299998, -1, 0, 0, -100000},
// -150000x + 149999y + 100000 >= 0.
{-150000, 149999, 0, 0, 0, 100000},
// Triangle constraints:
// 300000p - 299999q >= 100000
{0, 0, 0, 300000, -299999, -100000},
// -300000p + 299998q + 200000 >= 0
{0, 0, 0, -300000, 299998, 200000},
},
{});
// Cartesian product of same tetrahedron as above and {(p, q) : 1/3 <= p <=
// 2/3}. Since the second set is empty, the whole set is too.
checkPermutationsSample(
false /* empty */, 5,
{
// Tetrahedron contraints:
{0, 1, 0, 0, 0, 0}, // y >= 0
{0, -1, 1, 0, 0, 0}, // z >= y
// -300000x + 299998y + 100000 + z <= 0.
{300000, -299998, -1, 0, 0, -100000},
// -150000x + 149999y + 100000 >= 0.
{-150000, 149999, 0, 0, 0, 100000},
// Second set constraints:
// 3p >= 1
{0, 0, 0, 3, 0, -1},
// 3p <= 2
{0, 0, 0, -3, 0, 2},
},
{});
// Cartesian product of same tetrahedron as above and
// {(p, q, r) : 1 <= p <= 2 and p = 3q + 3r}.
// Since the second set is empty, the whole set is too.
checkPermutationsSample(
false /* empty */, 5,
{
// Tetrahedron contraints:
{0, 1, 0, 0, 0, 0, 0}, // y >= 0
{0, -1, 1, 0, 0, 0, 0}, // z >= y
// -300000x + 299998y + 100000 + z <= 0.
{300000, -299998, -1, 0, 0, 0, -100000},
// -150000x + 149999y + 100000 >= 0.
{-150000, 149999, 0, 0, 0, 0, 100000},
// Second set constraints:
// p >= 1
{0, 0, 0, 1, 0, 0, -1},
// p <= 2
{0, 0, 0, -1, 0, 0, 2},
},
{
{0, 0, 0, 1, -3, -3, 0}, // p = 3q + 3r
});
// Cartesian product of a tetrahedron and a 2D cone.
// The tetrahedron is empty and has vertices at
// (1/3, 0, 0), (2/3, 0, 0), (2/3, 0, 100), and (100, 100 - 1/3, 100).
// The cone has apex at (10000, 10000) and
// edges passing through (1/3, 0) and (2/3, 0).
// Since the tetrahedron is empty, the Cartesian product is too.
checkPermutationsSample(false /* empty */, 5,
{
// Tetrahedron contraints:
{0, 1, 0, 0, 0, 0},
{0, -300, 299, 0, 0, 0},
{300 * 299, -89400, -299, 0, 0, -100 * 299},
{-897, 894, 0, 0, 0, 598},
// Triangle constraints:
// 300000p - 299999q >= 100000
{0, 0, 0, 300000, -299999, -100000},
// -300000p + 299998q + 200000 >= 0
{0, 0, 0, -300000, 299998, 200000},
},
{});
// Cartesian product of same tetrahedron as above and
// {(p, q) : 1/3 <= p <= 2/3}.
checkPermutationsSample(false /* empty */, 5,
{
// Tetrahedron contraints:
{0, 1, 0, 0, 0, 0},
{0, -300, 299, 0, 0, 0},
{300 * 299, -89400, -299, 0, 0, -100 * 299},
{-897, 894, 0, 0, 0, 598},
// Second set constraints:
// 3p >= 1
{0, 0, 0, 3, 0, -1},
// 3p <= 2
{0, 0, 0, -3, 0, 2},
},
{});
checkSample(true, makeFACFromConstraints(3,
{
{2, 0, 0, -1}, // 2x >= 1
},
{{
{1, -1, 0, -1}, // y = x - 1
{0, 1, -1, 0}, // z = y
}}));
}
TEST(FlatAffineConstraintsTest, IsIntegerEmptyTest) {
// 1 <= 5x and 5x <= 4 (no solution).
EXPECT_TRUE(
makeFACFromConstraints(1, {{5, -1}, {-5, 4}}, {}).isIntegerEmpty());
// 1 <= 5x and 5x <= 9 (solution: x = 1).
EXPECT_FALSE(
makeFACFromConstraints(1, {{5, -1}, {-5, 9}}, {}).isIntegerEmpty());
// Unbounded sets.
EXPECT_TRUE(makeFACFromConstraints(3,
{
{0, 2, 0, -1}, // 2y >= 1
{0, -2, 0, 1}, // 2y <= 1
{0, 0, 2, -1}, // 2z >= 1
},
{{2, 0, 0, -1}} // 2x = 1
)
.isIntegerEmpty());
EXPECT_FALSE(makeFACFromConstraints(3,
{
{2, 0, 0, -1}, // 2x >= 1
{-3, 0, 0, 3}, // 3x <= 3
{0, 0, 5, -6}, // 5z >= 6
{0, 0, -7, 17}, // 7z <= 17
{0, 3, 0, -2}, // 3y >= 2
},
{})
.isIntegerEmpty());
EXPECT_FALSE(makeFACFromConstraints(3,
{
{2, 0, 0, -1}, // 2x >= 1
},
{{
{1, -1, 0, -1}, // y = x - 1
{0, 1, -1, 0}, // z = y
}})
.isIntegerEmpty());
// FlatAffineConstraints::isEmpty() does not detect the following sets to be
// empty.
// 3x + 7y = 1 and 0 <= x, y <= 10.
// Since x and y are non-negative, 3x + 7y can never be 1.
EXPECT_TRUE(
makeFACFromConstraints(
2, {{1, 0, 0}, {-1, 0, 10}, {0, 1, 0}, {0, -1, 10}}, {{3, 7, -1}})
.isIntegerEmpty());
// 2x = 3y and y = x - 1 and x + y = 6z + 2 and 0 <= x, y <= 100.
// Substituting y = x - 1 in 3y = 2x, we obtain x = 3 and hence y = 2.
// Since x + y = 5 cannot be equal to 6z + 2 for any z, the set is empty.
EXPECT_TRUE(
makeFACFromConstraints(3,
{
{1, 0, 0, 0},
{-1, 0, 0, 100},
{0, 1, 0, 0},
{0, -1, 0, 100},
},
{{2, -3, 0, 0}, {1, -1, 0, -1}, {1, 1, -6, -2}})
.isIntegerEmpty());
// 2x = 3y and y = x - 1 + 6z and x + y = 6q + 2 and 0 <= x, y <= 100.
// 2x = 3y implies x is a multiple of 3 and y is even.
// Now y = x - 1 + 6z implies y = 2 mod 3. In fact, since y is even, we have
// y = 2 mod 6. Then since x = y + 1 + 6z, we have x = 3 mod 6, implying
// x + y = 5 mod 6, which contradicts x + y = 6q + 2, so the set is empty.
EXPECT_TRUE(makeFACFromConstraints(
4,
{
{1, 0, 0, 0, 0},
{-1, 0, 0, 0, 100},
{0, 1, 0, 0, 0},
{0, -1, 0, 0, 100},
},
{{2, -3, 0, 0, 0}, {1, -1, 6, 0, -1}, {1, 1, 0, -6, -2}})
.isIntegerEmpty());
// Set with symbols.
FlatAffineConstraints fac6 = makeFACFromConstraints(2,
{
{1, 1, 0},
},
{
{1, -1, 0},
},
1);
EXPECT_FALSE(fac6.isIntegerEmpty());
}
TEST(FlatAffineConstraintsTest, removeRedundantConstraintsTest) {
FlatAffineConstraints fac = makeFACFromConstraints(1,
{
{1, -2}, // x >= 2.
{-1, 2} // x <= 2.
},
{{1, -2}}); // x == 2.
fac.removeRedundantConstraints();
// Both inequalities are redundant given the equality. Both have been removed.
EXPECT_EQ(fac.getNumInequalities(), 0u);
EXPECT_EQ(fac.getNumEqualities(), 1u);
FlatAffineConstraints fac2 =
makeFACFromConstraints(2,
{
{1, 0, -3}, // x >= 3.
{0, 1, -2} // y >= 2 (redundant).
},
{{1, -1, 0}}); // x == y.
fac2.removeRedundantConstraints();
// The second inequality is redundant and should have been removed. The
// remaining inequality should be the first one.
EXPECT_EQ(fac2.getNumInequalities(), 1u);
EXPECT_THAT(fac2.getInequality(0), ElementsAre(1, 0, -3));
EXPECT_EQ(fac2.getNumEqualities(), 1u);
FlatAffineConstraints fac3 =
makeFACFromConstraints(3, {},
{{1, -1, 0, 0}, // x == y.
{1, 0, -1, 0}, // x == z.
{0, 1, -1, 0}}); // y == z.
fac3.removeRedundantConstraints();
// One of the three equalities can be removed.
EXPECT_EQ(fac3.getNumInequalities(), 0u);
EXPECT_EQ(fac3.getNumEqualities(), 2u);
FlatAffineConstraints fac4 = makeFACFromConstraints(
17,
{{0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1},
{0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 500},
{0, 0, 0, -16, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1},
{0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 998},
{0, 0, 0, 16, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 15},
{0, 0, 0, 0, -16, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1},
{0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 998},
{0, 0, 0, 0, 16, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 15},
{0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, -1},
{0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 500},
{0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 15},
{0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, -16, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -16, 0, 1, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, -1},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 998},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 0, -1, 0, 0, 15},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 1},
{0, 0, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, -1, 8, 8},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, -8, -1},
{0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, -8, -1},
{0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, -10},
{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 10},
{0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -13},
{0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 13},
{0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10},
{0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10},
{1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -13},
{-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 13}},
{});
// The above is a large set of constraints without any redundant constraints,
// as verified by the Fourier-Motzkin based removeRedundantInequalities.
unsigned nIneq = fac4.getNumInequalities();
unsigned nEq = fac4.getNumEqualities();
fac4.removeRedundantInequalities();
ASSERT_EQ(fac4.getNumInequalities(), nIneq);
ASSERT_EQ(fac4.getNumEqualities(), nEq);
// Now we test that removeRedundantConstraints does not find any constraints
// to be redundant either.
fac4.removeRedundantConstraints();
EXPECT_EQ(fac4.getNumInequalities(), nIneq);
EXPECT_EQ(fac4.getNumEqualities(), nEq);
FlatAffineConstraints fac5 =
makeFACFromConstraints(2,
{
{128, 0, 127}, // [0]: 128x >= -127.
{-1, 0, 7}, // [1]: x <= 7.
{-128, 1, 0}, // [2]: y >= 128x.
{0, 1, 0} // [3]: y >= 0.
},
{});
// [0] implies that 128x >= 0, since x has to be an integer. (This should be
// caught by GCDTightenInqualities().)
// So [2] and [0] imply [3] since we have y >= 128x >= 0.
fac5.removeRedundantConstraints();
EXPECT_EQ(fac5.getNumInequalities(), 3u);
SmallVector<int64_t, 8> redundantConstraint = {0, 1, 0};
for (unsigned i = 0; i < 3; ++i) {
// Ensure that the removed constraint was the redundant constraint [3].
EXPECT_NE(fac5.getInequality(i), ArrayRef<int64_t>(redundantConstraint));
}
}
TEST(FlatAffineConstraintsTest, addConstantUpperBound) {
FlatAffineConstraints fac = makeFACFromConstraints(2, {}, {});
fac.addBound(FlatAffineConstraints::UB, 0, 1);
EXPECT_EQ(fac.atIneq(0, 0), -1);
EXPECT_EQ(fac.atIneq(0, 1), 0);
EXPECT_EQ(fac.atIneq(0, 2), 1);
fac.addBound(FlatAffineConstraints::UB, {1, 2, 3}, 1);
EXPECT_EQ(fac.atIneq(1, 0), -1);
EXPECT_EQ(fac.atIneq(1, 1), -2);
EXPECT_EQ(fac.atIneq(1, 2), -2);
}
TEST(FlatAffineConstraintsTest, addConstantLowerBound) {
FlatAffineConstraints fac = makeFACFromConstraints(2, {}, {});
fac.addBound(FlatAffineConstraints::LB, 0, 1);
EXPECT_EQ(fac.atIneq(0, 0), 1);
EXPECT_EQ(fac.atIneq(0, 1), 0);
EXPECT_EQ(fac.atIneq(0, 2), -1);
fac.addBound(FlatAffineConstraints::LB, {1, 2, 3}, 1);
EXPECT_EQ(fac.atIneq(1, 0), 1);
EXPECT_EQ(fac.atIneq(1, 1), 2);
EXPECT_EQ(fac.atIneq(1, 2), 2);
}
TEST(FlatAffineConstraintsTest, removeInequality) {
FlatAffineConstraints fac =
makeFACFromConstraints(1, {{0, 0}, {1, 1}, {2, 2}, {3, 3}, {4, 4}}, {});
fac.removeInequalityRange(0, 0);
EXPECT_EQ(fac.getNumInequalities(), 5u);
fac.removeInequalityRange(1, 3);
EXPECT_EQ(fac.getNumInequalities(), 3u);
EXPECT_THAT(fac.getInequality(0), ElementsAre(0, 0));
EXPECT_THAT(fac.getInequality(1), ElementsAre(3, 3));
EXPECT_THAT(fac.getInequality(2), ElementsAre(4, 4));
fac.removeInequality(1);
EXPECT_EQ(fac.getNumInequalities(), 2u);
EXPECT_THAT(fac.getInequality(0), ElementsAre(0, 0));
EXPECT_THAT(fac.getInequality(1), ElementsAre(4, 4));
}
TEST(FlatAffineConstraintsTest, removeEquality) {
FlatAffineConstraints fac =
makeFACFromConstraints(1, {}, {{0, 0}, {1, 1}, {2, 2}, {3, 3}, {4, 4}});
fac.removeEqualityRange(0, 0);
EXPECT_EQ(fac.getNumEqualities(), 5u);
fac.removeEqualityRange(1, 3);
EXPECT_EQ(fac.getNumEqualities(), 3u);
EXPECT_THAT(fac.getEquality(0), ElementsAre(0, 0));
EXPECT_THAT(fac.getEquality(1), ElementsAre(3, 3));
EXPECT_THAT(fac.getEquality(2), ElementsAre(4, 4));
fac.removeEquality(1);
EXPECT_EQ(fac.getNumEqualities(), 2u);
EXPECT_THAT(fac.getEquality(0), ElementsAre(0, 0));
EXPECT_THAT(fac.getEquality(1), ElementsAre(4, 4));
}
TEST(FlatAffineConstraintsTest, clearConstraints) {
FlatAffineConstraints fac = makeFACFromConstraints(1, {}, {});
fac.addInequality({1, 0});
EXPECT_EQ(fac.atIneq(0, 0), 1);
EXPECT_EQ(fac.atIneq(0, 1), 0);
fac.clearConstraints();
fac.addInequality({1, 0});
EXPECT_EQ(fac.atIneq(0, 0), 1);
EXPECT_EQ(fac.atIneq(0, 1), 0);
}
/// Check if the expected division representation of local variables matches the
/// computed representation. The expected division representation is given as
/// a vector of expressions set in `divisions` and the corressponding
/// denominator in `denoms`. If expected denominator for a variable is
/// non-positive, the local variable is expected to not have a computed
/// representation.
static void checkDivisionRepresentation(
FlatAffineConstraints &fac,
const std::vector<SmallVector<int64_t, 8>> &divisions,
const SmallVector<int64_t, 8> &denoms) {
assert(divisions.size() == fac.getNumLocalIds() &&
"Size of expected divisions does not match number of local variables");
assert(
denoms.size() == fac.getNumLocalIds() &&
"Size of expected denominators does not match number of local variables");
std::vector<llvm::Optional<std::pair<unsigned, unsigned>>> res(
fac.getNumLocalIds(), llvm::None);
fac.getLocalReprLbUbPairs(res);
// Check if all expected divisions are computed.
for (unsigned i = 0, e = fac.getNumLocalIds(); i < e; ++i)
if (denoms[i] > 0)
EXPECT_TRUE(res[i].hasValue());
else
EXPECT_FALSE(res[i].hasValue());
unsigned divOffset = fac.getNumDimAndSymbolIds();
for (unsigned i = 0, e = fac.getNumLocalIds(); i < e; ++i) {
if (!res[i])
continue;
// Check if the bounds are of the form:
// 0 <= expr - divisor * id <= divisor - 1
// Rearranging, we have:
// divisor * id - expr + (divisor - 1) >= 0 <-- Lower bound for 'id'
// -divisor * id + expr >= 0 <-- Upper bound for 'id'
// where `id = expr floordiv divisor`.
unsigned ubPos = res[i]->first, lbPos = res[i]->second;
const SmallVector<int64_t, 8> &expr = divisions[i];
// Check if lower bound is of the correct form.
int64_t computedDivisorLb = fac.atIneq(lbPos, i + divOffset);
EXPECT_EQ(computedDivisorLb, denoms[i]);
for (unsigned c = 0, f = fac.getNumLocalIds(); c < f; ++c) {
if (c == i + divOffset)
continue;
EXPECT_EQ(fac.atIneq(lbPos, c), -expr[c]);
}
// Check if constant term of lower bound matches expected constant term.
EXPECT_EQ(fac.atIneq(lbPos, fac.getNumCols() - 1),
-expr.back() + (denoms[i] - 1));
// Check if upper bound is of the correct form.
int64_t computedDivisorUb = fac.atIneq(ubPos, i + divOffset);
EXPECT_EQ(computedDivisorUb, -denoms[i]);
for (unsigned c = 0, f = fac.getNumLocalIds(); c < f; ++c) {
if (c == i + divOffset)
continue;
EXPECT_EQ(fac.atIneq(ubPos, c), expr[c]);
}
// Check if constant term of upper bound matches expected constant term.
EXPECT_EQ(fac.atIneq(ubPos, fac.getNumCols() - 1), expr.back());
}
}
TEST(FlatAffineConstraintsTest, computeLocalReprSimple) {
FlatAffineConstraints fac = makeFACFromConstraints(1, {}, {});
fac.addLocalFloorDiv({1, 4}, 10);
fac.addLocalFloorDiv({1, 0, 100}, 10);
std::vector<SmallVector<int64_t, 8>> divisions = {{1, 0, 0, 4},
{1, 0, 0, 100}};
SmallVector<int64_t, 8> denoms = {10, 10};
// Check if floordivs can be computed when no other inequalities exist
// and floor divs do not depend on each other.
checkDivisionRepresentation(fac, divisions, denoms);
}
TEST(FlatAffineConstraintsTest, computeLocalReprConstantFloorDiv) {
FlatAffineConstraints fac = makeFACFromConstraints(4, {}, {});
fac.addInequality({1, 0, 3, 1, 2});
fac.addInequality({1, 2, -8, 1, 10});
fac.addEquality({1, 2, -4, 1, 10});
fac.addLocalFloorDiv({0, 0, 0, 0, 10}, 30);
fac.addLocalFloorDiv({0, 0, 0, 0, 0, 99}, 101);
std::vector<SmallVector<int64_t, 8>> divisions = {{0, 0, 0, 0, 0, 0, 10},
{0, 0, 0, 0, 0, 0, 99}};
SmallVector<int64_t, 8> denoms = {30, 101};
// Check if floordivs with constant numerator can be computed.
checkDivisionRepresentation(fac, divisions, denoms);
}
TEST(FlatAffineConstraintsTest, computeLocalReprRecursive) {
FlatAffineConstraints fac = makeFACFromConstraints(4, {}, {});
fac.addInequality({1, 0, 3, 1, 2});
fac.addInequality({1, 2, -8, 1, 10});
fac.addEquality({1, 2, -4, 1, 10});
fac.addLocalFloorDiv({0, -2, 7, 2, 10}, 3);
fac.addLocalFloorDiv({3, 0, 9, 2, 2, 10}, 5);
fac.addLocalFloorDiv({0, 1, -123, 2, 0, -4, 10}, 3);
fac.addInequality({1, 2, -2, 1, -5, 0, 6, 100});
fac.addInequality({1, 2, -8, 1, 3, 7, 0, -9});
std::vector<SmallVector<int64_t, 8>> divisions = {{0, -2, 7, 2, 0, 0, 0, 10},
{3, 0, 9, 2, 2, 0, 0, 10},
{0, 1, -123, 2, 0, -4, 10}};
SmallVector<int64_t, 8> denoms = {3, 5, 3};
// Check if floordivs which may depend on other floordivs can be computed.
checkDivisionRepresentation(fac, divisions, denoms);
}
TEST(FlatAffineConstraintsTest, removeIdRange) {
FlatAffineConstraints fac(3, 2, 1);
fac.addInequality({10, 11, 12, 20, 21, 30, 40});
fac.removeId(FlatAffineConstraints::IdKind::Symbol, 1);
EXPECT_THAT(fac.getInequality(0),
testing::ElementsAre(10, 11, 12, 20, 30, 40));
fac.removeIdRange(FlatAffineConstraints::IdKind::Dimension, 0, 2);
EXPECT_THAT(fac.getInequality(0), testing::ElementsAre(12, 20, 30, 40));
fac.removeIdRange(FlatAffineConstraints::IdKind::Local, 1, 1);
EXPECT_THAT(fac.getInequality(0), testing::ElementsAre(12, 20, 30, 40));
fac.removeIdRange(FlatAffineConstraints::IdKind::Local, 0, 1);
EXPECT_THAT(fac.getInequality(0), testing::ElementsAre(12, 20, 40));
}
TEST(FlatAffineConstraintsTest, simplifyLocalsTest) {
// (x) : (exists y: 2x + y = 1 and y = 2).
FlatAffineConstraints fac(1, 0, 1);
fac.addEquality({2, 1, -1});
fac.addEquality({0, 1, -2});
EXPECT_TRUE(fac.isEmpty());
// (x) : (exists y, z, w: 3x + y = 1 and 2y = z and 3y = w and z = w).
FlatAffineConstraints fac2(1, 0, 3);
fac2.addEquality({3, 1, 0, 0, -1});
fac2.addEquality({0, 2, -1, 0, 0});
fac2.addEquality({0, 3, 0, -1, 0});
fac2.addEquality({0, 0, 1, -1, 0});
EXPECT_TRUE(fac2.isEmpty());
// (x) : (exists y: x >= y + 1 and 2x + y = 0 and y >= -1).
FlatAffineConstraints fac3(1, 0, 1);
fac3.addInequality({1, -1, -1});
fac3.addInequality({0, 1, 1});
fac3.addEquality({2, 1, 0});
EXPECT_TRUE(fac3.isEmpty());
}
} // namespace mlir
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