[Mlir-commits] [mlir] 66ae1d6 - [mlir][sparse] fix windows build error
Peiming Liu
llvmlistbot at llvm.org
Wed Jul 6 14:16:10 PDT 2022
Author: Peiming Liu
Date: 2022-07-06T21:16:05Z
New Revision: 66ae1d60bb278793fd651cece264699d522bab84
URL: https://github.com/llvm/llvm-project/commit/66ae1d60bb278793fd651cece264699d522bab84
DIFF: https://github.com/llvm/llvm-project/commit/66ae1d60bb278793fd651cece264699d522bab84.diff
LOG: [mlir][sparse] fix windows build error
Silence warning from MSVC when handling ##__VA_ARGS
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D129227
Added:
Modified:
mlir/unittests/Dialect/SparseTensor/MergerTest.cpp
Removed:
################################################################################
diff --git a/mlir/unittests/Dialect/SparseTensor/MergerTest.cpp b/mlir/unittests/Dialect/SparseTensor/MergerTest.cpp
index f64251953c9f5..621e50247f871 100644
--- a/mlir/unittests/Dialect/SparseTensor/MergerTest.cpp
+++ b/mlir/unittests/Dialect/SparseTensor/MergerTest.cpp
@@ -1,4 +1,5 @@
#include "mlir/Dialect/SparseTensor/Utils/Merger.h"
+#include "llvm/Support/Compiler.h"
#include "gmock/gmock.h"
#include "gtest/gtest.h"
#include <memory>
@@ -6,8 +7,79 @@
using namespace mlir;
using namespace mlir::sparse_tensor;
+// Silence 'warning C4002: 'too many arguments for function-liked macro
+// invocation'
+// as MSVC handles ##__VA_ARGS__
diff erently as gcc/clang
+
+#if defined(_MSC_VER) && !defined(__clang__)
+#pragma warning(push)
+#pragma warning(disable : 4002)
+#endif
+
namespace {
+///
+/// Defines macros to iterate binary and the combination of binary operations.
+///
+
+#define FOREVERY_BINOP(DO) \
+ DO(mulf, Kind::kMulF) \
+ DO(mulc, Kind::kMulC) \
+ DO(muli, Kind::kMulI) \
+ DO(addf, Kind::kAddF) \
+ DO(addc, Kind::kAddC) \
+ DO(addi, Kind::kAddI) \
+ DO(subf, Kind::kSubF) \
+ DO(subc, Kind::kSubC) \
+ DO(subi, Kind::kSubI) \
+ DO(andi, Kind::kAndI) \
+ DO(xori, Kind::kXorI) \
+ DO(ori, Kind::kOrI)
+
+// TODO: Disjunctive binary operations that need special handling are not
+// included, e.g., Division are not tested (for now) as it need a constant
+// non-zero dividend.
+// ##__VA_ARGS__ handles cases when __VA_ARGS__ is empty.
+#define FOREVERY_COMMON_DISJ_BINOP(TEST, ...) \
+ TEST(addf, ##__VA_ARGS__) \
+ TEST(addc, ##__VA_ARGS__) \
+ TEST(addi, ##__VA_ARGS__) \
+ TEST(xori, ##__VA_ARGS__) \
+ TEST(ori, ##__VA_ARGS__)
+
+// TODO: Conjunctive binary operations that need special handling are not
+// included, e.g., substraction yields a
diff erent pattern as it is mapped to
+// negate operation.
+#define FOREVERY_COMMON_CONJ_BINOP(TEST, ...) \
+ TEST(mulf, ##__VA_ARGS__) \
+ TEST(mulc, ##__VA_ARGS__) \
+ TEST(muli, ##__VA_ARGS__) \
+ TEST(andi, ##__VA_ARGS__)
+
+#define FOREVERY_PAIR_OF_COMMON_CONJ_DISJ_BINOP(TEST) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, addf) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, addc) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, addi) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, xori) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, ori)
+
+#define FOREVERY_PAIR_OF_COMMON_CONJ_CONJ_BINOP(TEST) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, mulf) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, mulc) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, muli) \
+ FOREVERY_COMMON_CONJ_BINOP(TEST, andi)
+
+#define FOREVERY_PAIR_OF_COMMON_DISJ_DISJ_BINOP(TEST) \
+ FOREVERY_COMMON_DISJ_BINOP(TEST, addf) \
+ FOREVERY_COMMON_DISJ_BINOP(TEST, addc) \
+ FOREVERY_COMMON_DISJ_BINOP(TEST, addi) \
+ FOREVERY_COMMON_DISJ_BINOP(TEST, ori) \
+ FOREVERY_COMMON_DISJ_BINOP(TEST, xori)
+
+///
+/// Helper classes/functions for testing Merger.
+///
+
/// Simple recursive data structure used to match expressions in Mergers.
struct Pattern {
Kind kind;
@@ -40,17 +112,16 @@ static std::shared_ptr<Pattern> tensorPattern(unsigned tensorNum) {
return std::make_shared<Pattern>(tensorNum);
}
-static std::shared_ptr<Pattern>
-addfPattern(const std::shared_ptr<Pattern> &e0,
- const std::shared_ptr<Pattern> &e1) {
- return std::make_shared<Pattern>(Kind::kAddF, e0, e1);
-}
+#define IMPL_BINOP_PATTERN(OP, KIND) \
+ LLVM_ATTRIBUTE_UNUSED static std::shared_ptr<Pattern> OP##Pattern( \
+ const std::shared_ptr<Pattern> &e0, \
+ const std::shared_ptr<Pattern> &e1) { \
+ return std::make_shared<Pattern>(KIND, e0, e1); \
+ }
-static std::shared_ptr<Pattern>
-mulfPattern(const std::shared_ptr<Pattern> &e0,
- const std::shared_ptr<Pattern> &e1) {
- return std::make_shared<Pattern>(Kind::kMulF, e0, e1);
-}
+FOREVERY_BINOP(IMPL_BINOP_PATTERN)
+
+#undef IMPL_BINOP_PATTERN
class MergerTestBase : public ::testing::Test {
protected:
@@ -66,13 +137,14 @@ class MergerTestBase : public ::testing::Test {
return merger.addExp(Kind::kTensor, tensor);
}
- unsigned addf(unsigned e0, unsigned e1) {
- return merger.addExp(Kind::kAddF, e0, e1);
+#define IMPL_BINOP_EXPR(OP, KIND) \
+ LLVM_ATTRIBUTE_UNUSED unsigned OP##Expr(unsigned e0, unsigned e1) { \
+ return merger.addExp(KIND, e0, e1); \
}
- unsigned mulf(unsigned e0, unsigned e1) {
- return merger.addExp(Kind::kMulF, e0, e1);
- }
+ FOREVERY_BINOP(IMPL_BINOP_EXPR)
+
+#undef IMPL_BINOP_EXPR
///
/// Comparison helpers.
@@ -87,12 +159,14 @@ class MergerTestBase : public ::testing::Test {
/// constraints between lattice points. We generally know how contiguous
/// groups of lattice points should be ordered with respect to other groups,
/// but there is no required ordering within groups.
+ /// If simple is true, then compare the lat.simple field instead to test the
+ /// result after optimization
bool latPointWithinRange(unsigned s, unsigned p, unsigned n,
const std::shared_ptr<Pattern> &pattern,
- const BitVector &bits) {
+ const BitVector &bits, bool simple) {
for (unsigned i = p; i < p + n; ++i) {
if (compareExpression(merger.lat(merger.set(s)[i]).exp, pattern) &&
- compareBits(s, i, bits))
+ compareBits(s, i, bits, simple))
return true;
}
return false;
@@ -101,15 +175,15 @@ class MergerTestBase : public ::testing::Test {
/// Wrapper over latPointWithinRange for readability of tests.
void expectLatPointWithinRange(unsigned s, unsigned p, unsigned n,
const std::shared_ptr<Pattern> &pattern,
- const BitVector &bits) {
- EXPECT_TRUE(latPointWithinRange(s, p, n, pattern, bits));
+ const BitVector &bits, bool simple = false) {
+ EXPECT_TRUE(latPointWithinRange(s, p, n, pattern, bits, simple));
}
/// Wrapper over expectLatPointWithinRange for a single lat point.
void expectLatPoint(unsigned s, unsigned p,
const std::shared_ptr<Pattern> &pattern,
- const BitVector &bits) {
- EXPECT_TRUE(latPointWithinRange(s, p, 1, pattern, bits));
+ const BitVector &bits, bool simple = false) {
+ EXPECT_TRUE(latPointWithinRange(s, p, 1, pattern, bits, simple));
}
/// Converts a vector of (loop, tensor) pairs to a bitvector with the
@@ -126,7 +200,11 @@ class MergerTestBase : public ::testing::Test {
}
/// Returns true if the bits of lattice point p in set s match the given bits.
- bool compareBits(unsigned s, unsigned p, const BitVector &bits) {
+ /// If simple is true, then compare the lat.simple field instead to test the
+ /// result after optimization
+ bool compareBits(unsigned s, unsigned p, const BitVector &bits, bool simple) {
+ if (simple)
+ return merger.lat(merger.set(s)[p]).simple == bits;
return merger.lat(merger.set(s)[p]).bits == bits;
}
@@ -215,6 +293,10 @@ class MergerTestBase : public ::testing::Test {
Merger merger;
};
+///
+/// Tests with all sparse inputs.
+///
+
class MergerTest3T1L : public MergerTestBase {
protected:
// Our three tensors (two inputs, one output).
@@ -238,9 +320,63 @@ class MergerTest3T1L : public MergerTestBase {
}
};
+class MergerTest4T1L : public MergerTestBase {
+protected:
+ // Our four tensors (three inputs, one output).
+ const unsigned t0 = 0, t1 = 1, t2 = 2, t3 = 3;
+
+ // Our single loop.
+ const unsigned l0 = 0;
+
+ MergerTest4T1L() : MergerTestBase(4, 1) {
+ // Tensor 0: sparse input vector.
+ merger.addExp(Kind::kTensor, t0, -1u);
+ merger.setDim(t0, l0, Dim::kSparse);
+
+ // Tensor 1: sparse input vector.
+ merger.addExp(Kind::kTensor, t1, -1u);
+ merger.setDim(t1, l0, Dim::kSparse);
+
+ // Tensor 2: sparse input vector
+ merger.addExp(Kind::kTensor, t2, -1u);
+ merger.setDim(t2, l0, Dim::kSparse);
+
+ // Tensor 3: dense output vector
+ merger.addExp(Kind::kTensor, t3, -1u);
+ merger.setDim(t3, l0, Dim::kDense);
+ }
+};
+
+///
+/// Tests with both sparse and dense input.
+///
+
+class MergerTest3T1LD : public MergerTestBase {
+protected:
+ // Our three tensors (two inputs, one output).
+ const unsigned t0 = 0, t1 = 1, t2 = 2;
+
+ // Our single loop.
+ const unsigned l0 = 0;
+
+ MergerTest3T1LD() : MergerTestBase(3, 1) {
+ // Tensor 0: sparse input vector.
+ merger.addExp(Kind::kTensor, t0, -1u);
+ merger.setDim(t0, l0, Dim::kSparse);
+
+ // Tensor 1: dense input vector.
+ merger.addExp(Kind::kTensor, t1, -1u);
+ merger.setDim(t1, l0, Dim::kDense);
+
+ // Tensor 2: dense output vector.
+ merger.addExp(Kind::kTensor, t2, -1u);
+ merger.setDim(t2, l0, Dim::kDense);
+ }
+};
+
} // namespace
-/// Vector addition of 2 vectors, i.e.:
+/// Vector addition (disjunction) of 2 vectors. i.e.;
/// a(i) = b(i) + c(i)
/// which should form the 3 lattice points
/// {
@@ -248,55 +384,259 @@ class MergerTest3T1L : public MergerTestBase {
/// lat( i_00 / tensor_0 )
/// lat( i_01 / tensor_1 )
/// }
-/// and after optimization, will reduce to the 2 lattice points
+/// and after optimization, the lattice points do not change (as there is no
+/// duplicated point and all input vectors are sparse vector).
/// {
/// lat( i_00 i_01 / (tensor_0 + tensor_1) )
/// lat( i_00 / tensor_0 )
+/// lat( i_01 / tensor_1 )
/// }
-TEST_F(MergerTest3T1L, VectorAdd2) {
- // Construct expression.
- auto e = addf(tensor(t0), tensor(t1));
-
- // Build lattices and check.
- auto s = merger.buildLattices(e, l0);
- expectNumLatPoints(s, 3);
- expectLatPoint(s, lat(0), addfPattern(tensorPattern(t0), tensorPattern(t1)),
- loopsToBits({{l0, t0}, {l0, t1}}));
- expectLatPointWithinRange(s, lat(1), 2, tensorPattern(t0),
- loopsToBits({{l0, t0}}));
- expectLatPointWithinRange(s, lat(1), 2, tensorPattern(t1),
- loopsToBits({{l0, t1}}));
-
- // Optimize lattices and check.
- s = merger.optimizeSet(s);
- expectNumLatPoints(s, 3);
- expectLatPoint(s, lat(0), addfPattern(tensorPattern(t0), tensorPattern(t1)),
- loopsToBits({{l0, t0}, {l0, t1}}));
- expectLatPointWithinRange(s, lat(1), 2, tensorPattern(t0),
- loopsToBits({{l0, t0}}));
- expectLatPointWithinRange(s, lat(1), 2, tensorPattern(t1),
- loopsToBits({{l0, t1}}));
-}
+#define IMPL_MERGER_TEST_DISJ(OP) \
+ TEST_F(MergerTest3T1L, vector_##OP) { \
+ auto e = OP##Expr(tensor(t0), tensor(t1)); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto s = merger.buildLattices(e, l0); \
+ \
+ expectNumLatPoints(s, 3); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 2, p0, loopsToBits({{l0, t0}})); \
+ expectLatPointWithinRange(s, lat(1), 2, p1, loopsToBits({{l0, t1}})); \
+ \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 3); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}}), true); \
+ expectLatPointWithinRange(s, lat(1), 2, p0, loopsToBits({{l0, t0}}), \
+ true); \
+ expectLatPointWithinRange(s, lat(1), 2, p1, loopsToBits({{l0, t1}}), \
+ true); \
+ }
+
+FOREVERY_COMMON_DISJ_BINOP(IMPL_MERGER_TEST_DISJ)
-/// Vector multiplication of 2 vectors, i.e.:
+#undef IMPL_MERGER_TEST_DISJ
+
+/// Vector multiplication (conjunction) of 2 vectors, i.e.;
/// a(i) = b(i) * c(i)
/// which should form the single lattice point
/// {
/// lat( i_00 i_01 / (tensor_0 * tensor_1) )
/// }
-TEST_F(MergerTest3T1L, VectorMul2) {
- // Construct expression.
- auto e = mulf(t0, t1);
-
- // Build lattices and check.
- auto s = merger.buildLattices(e, l0);
- expectNumLatPoints(s, 1);
- expectLatPoint(s, lat(0), mulfPattern(tensorPattern(t0), tensorPattern(t1)),
- loopsToBits({{l0, t0}, {l0, t1}}));
-
- // Optimize lattices and check.
- s = merger.optimizeSet(s);
- expectNumLatPoints(s, 1);
- expectLatPoint(s, lat(0), mulfPattern(tensorPattern(t0), tensorPattern(t1)),
- loopsToBits({{l0, t0}, {l0, t1}}));
-}
+#define IMPL_MERGER_TEST_CONJ(OP) \
+ TEST_F(MergerTest3T1L, vector_##OP) { \
+ auto e = OP##Expr(t0, t1); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto s = merger.buildLattices(e, l0); \
+ \
+ expectNumLatPoints(s, 1); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 1); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}}), true); \
+ }
+
+FOREVERY_COMMON_CONJ_BINOP(IMPL_MERGER_TEST_CONJ)
+
+#undef IMPL_MERGER_TEST_CONJ
+
+/// Vector multiplication (conjunction) then addition (disjunction), i.e.;
+/// a(i) = b(i) * c(i) + d(i);
+/// which should form
+/// {
+/// lat( i_00 i_01 i_02 / (tensor_0 * tensor_1) + tensor_2 )
+/// lat( i_00 i_01 / tensor_0 * tensor_1
+/// lat( i_02 / tensor_2 )
+/// }
+#define IMPL_MERGER_TEST_CONJ_DISJ(CONJ, DISJ) \
+ TEST_F(MergerTest4T1L, vector_##CONJ##_##DISJ) { \
+ auto em = CONJ##Expr(t0, t1); \
+ auto e = DISJ##Expr(em, t2); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto p2 = tensorPattern(t2); \
+ auto s = merger.buildLattices(e, l0); \
+ \
+ expectNumLatPoints(s, 3); \
+ expectLatPoint(s, lat(0), DISJ##Pattern(CONJ##Pattern(p0, p1), p2), \
+ loopsToBits({{l0, t0}, {l0, t1}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 2, CONJ##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 2, p2, loopsToBits({{l0, t2}})); \
+ \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 3); \
+ expectLatPoint(s, lat(0), DISJ##Pattern(CONJ##Pattern(p0, p1), p2), \
+ loopsToBits({{l0, t0}, {l0, t1}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 2, CONJ##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 2, p2, loopsToBits({{l0, t2}})); \
+ }
+
+FOREVERY_PAIR_OF_COMMON_CONJ_DISJ_BINOP(IMPL_MERGER_TEST_CONJ_DISJ)
+
+#undef IMPL_MERGER_TEST_CONJ_DISJ
+
+/// Vector addition (disjunction) then addition (disjunction), i.e.;
+/// a(i) = b(i) + c(i) + d(i)
+/// which should form
+/// {
+/// lat( i_00 i_01 i_02 / (tensor_0 + tensor_1) + tensor_2 )
+/// lat( i_02 i_01 / tensor_2 + tensor_1 )
+/// lat( i_02 i_00 / tensor_2 + tensor_0 )
+/// lat( i_01 i_00 / tensor_1 + tensor_0 )
+/// lat( i_02 / tensor_2 )
+/// lat( i_01 / tensor_1 )
+/// lat( i_00 / tensor_0 )
+/// }
+#define IMPL_MERGER_TEST_DISJ_DISJ(DISJ1, DISJ2) \
+ TEST_F(MergerTest4T1L, Vector_##DISJ1##_##DISJ2) { \
+ auto em = DISJ1##Expr(t0, t1); \
+ auto e = DISJ2##Expr(em, t2); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto p2 = tensorPattern(t2); \
+ auto s = merger.buildLattices(e, l0); \
+ \
+ expectNumLatPoints(s, 7); \
+ expectLatPoint(s, lat(0), DISJ2##Pattern(DISJ1##Pattern(p0, p1), p2), \
+ loopsToBits({{l0, t0}, {l0, t1}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, DISJ2##Pattern(p1, p2), \
+ loopsToBits({{l0, t1}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, DISJ2##Pattern(p0, p2), \
+ loopsToBits({{l0, t0}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, DISJ1##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 6, p2, loopsToBits({{l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, p1, loopsToBits({{l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 6, p0, loopsToBits({{l0, t0}})); \
+ \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 7); \
+ expectLatPoint(s, lat(0), DISJ2##Pattern(DISJ1##Pattern(p0, p1), p2), \
+ loopsToBits({{l0, t0}, {l0, t1}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, DISJ2##Pattern(p1, p2), \
+ loopsToBits({{l0, t1}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, DISJ2##Pattern(p0, p2), \
+ loopsToBits({{l0, t0}, {l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, DISJ1##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 6, p2, loopsToBits({{l0, t2}})); \
+ expectLatPointWithinRange(s, lat(1), 6, p1, loopsToBits({{l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 6, p0, loopsToBits({{l0, t0}})); \
+ }
+
+FOREVERY_PAIR_OF_COMMON_DISJ_DISJ_BINOP(IMPL_MERGER_TEST_DISJ_DISJ)
+
+#undef IMPL_MERGER_TEST_DISJ_DISJ
+
+/// Vector multiplication (conjunction) then multiplication (conjunction), i.e.;
+/// a(i) = b(i) * c(i) * d(i);
+/// which should form
+/// {
+/// lat( i_00 i_01 i_02 / tensor_0 * tensor_1 * tensor_2 )
+/// }
+#define IMPL_MERGER_TEST_CONJ_CONJ(CONJ1, CONJ2) \
+ TEST_F(MergerTest4T1L, vector_##CONJ1##_##CONJ2) { \
+ auto em = CONJ1##Expr(t0, t1); \
+ auto e = CONJ2##Expr(em, t2); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto p2 = tensorPattern(t2); \
+ auto s = merger.buildLattices(e, l0); \
+ expectNumLatPoints(s, 1); \
+ expectLatPoint(s, lat(0), CONJ2##Pattern(CONJ1##Pattern(p0, p1), p2), \
+ loopsToBits({{l0, t0}, {l0, t1}, {l0, t2}})); \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 1); \
+ expectLatPoint(s, lat(0), CONJ2##Pattern(CONJ1##Pattern(p0, p1), p2), \
+ loopsToBits({{l0, t0}, {l0, t1}, {l0, t2}}), true); \
+ }
+
+FOREVERY_PAIR_OF_COMMON_CONJ_CONJ_BINOP(IMPL_MERGER_TEST_CONJ_CONJ)
+
+#undef IMPL_MERGER_TEST_CONJ_CONJ
+
+/// Vector addition (disjunction) of 2 vectors, i.e.;
+/// a(i) = b(i) + c(i)
+/// which should form the 3 lattice points
+/// {
+/// lat( i_00 i_01 / (sparse_tensor_0 + dense_tensor_1) )
+/// lat( i_00 / sparse_tensor_0 )
+/// lat( i_01 / dense_tensor_1 )
+/// }
+/// which should be optimized to
+/// {
+/// lat( i_00 i_01 / (sparse_tensor_0 + dense_tensor_1) ) (not singleton)
+/// lat( i_01 / dense_tensor_0 ) (no sparse dimension)
+/// }
+///
+/// lat( i_00 / sparse_tensor_0 ) should be opted out as it only has dense
diff
+/// with lat( i_00 i_01 / (sparse_tensor_0 + dense_tensor_1) ).
+#define IMPL_MERGER_TEST_OPTIMIZED_DISJ(OP) \
+ TEST_F(MergerTest3T1LD, vector_opted_##OP) { \
+ auto e = OP##Expr(tensor(t0), tensor(t1)); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto s = merger.buildLattices(e, l0); \
+ \
+ expectNumLatPoints(s, 3); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ expectLatPointWithinRange(s, lat(1), 2, p0, loopsToBits({{l0, t0}})); \
+ expectLatPointWithinRange(s, lat(1), 2, p1, loopsToBits({{l0, t1}})); \
+ \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 2); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}}), true); \
+ expectLatPoint(s, lat(1), p1, loopsToBits({{l0, t1}}), true); \
+ }
+
+FOREVERY_COMMON_DISJ_BINOP(IMPL_MERGER_TEST_OPTIMIZED_DISJ)
+
+#undef IMPL_MERGER_TEST_OPTIMIZED_CONJ
+
+/// Vector multiplication (conjunction) of 2 vectors, i.e.:
+/// a(i) = b(i) * c(i)
+/// which should form the single lattice point
+/// {
+/// lat( i_00 i_01 / (sparse_tensor_0 * dense_tensor_1) )
+/// }
+/// it should be optimized to
+/// {
+/// lat( i_00 / (sparse_tensor_0 * dense_tensor_1) )
+/// }
+/// since i_01 is a dense dimension.
+#define IMPL_MERGER_TEST_OPTIMIZED_CONJ(OP) \
+ TEST_F(MergerTest3T1LD, vector_opted_##OP) { \
+ auto e = OP##Expr(t0, t1); \
+ auto p0 = tensorPattern(t0); \
+ auto p1 = tensorPattern(t1); \
+ auto s = merger.buildLattices(e, l0); \
+ \
+ expectNumLatPoints(s, 1); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), \
+ loopsToBits({{l0, t0}, {l0, t1}})); \
+ \
+ s = merger.optimizeSet(s); \
+ expectNumLatPoints(s, 1); \
+ expectLatPoint(s, lat(0), OP##Pattern(p0, p1), loopsToBits({{l0, t0}}), \
+ true); \
+ }
+
+FOREVERY_COMMON_CONJ_BINOP(IMPL_MERGER_TEST_OPTIMIZED_CONJ)
+
+#undef IMPL_MERGER_TEST_OPTIMIZED_CONJ
+
+// TODO: mult-dim tests
+
+// restore warning status
+#if defined(_MSC_VER) && !defined(__clang__)
+#pragma warning(pop)
+#endif
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