//===- 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 #include #include namespace mlir { /// If 'hasValue' is true, check that findIntegerSample returns a valid sample /// for the FlatAffineConstraints fac. /// /// If hasValue is false, check that findIntegerSample does not return None. static void checkSample(bool hasValue, const FlatAffineConstraints &fac) { Optional> maybeSample = fac.findIntegerSample(); if (!hasValue) { 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)); } } /// Construct a FlatAffineConstraints from a set of inequality and /// equality constraints. static FlatAffineConstraints makeFACFromConstraints(unsigned dims, ArrayRef> ineqs, ArrayRef> eqs) { FlatAffineConstraints fac(ineqs.size(), eqs.size(), dims + 1, dims); 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. static void checkPermutationsSample(bool hasValue, unsigned nDim, ArrayRef> ineqs, ArrayRef> eqs) { SmallVector perm(nDim); std::iota(perm.begin(), perm.end(), 0); auto permute = [&perm](ArrayRef coeffs) { SmallVector permuted; for (unsigned id : perm) permuted.push_back(coeffs[id]); permuted.push_back(coeffs.back()); return permuted; }; do { SmallVector, 4> permutedIneqs, permutedEqs; for (const auto &ineq : ineqs) permutedIneqs.push_back(permute(ineq)); for (const auto &eq : eqs) permutedEqs.push_back(permute(eq)); checkSample(hasValue, makeFACFromConstraints(nDim, permutedIneqs, permutedEqs)); } 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. }, {})); } 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()); // An unbounded set, which isIntegerEmpty should detect as unbounded and // return without calling findIntegerSample. EXPECT_FALSE(makeFACFromConstraints(3, { {2, 0, 0, -1}, {-2, 0, 0, 1}, {0, 2, 0, -1}, {0, -2, 0, 1}, {0, 0, 2, -1}, }, {}) .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()); } 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), testing::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 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(redundantConstraint)); } } } // namespace mlir