Skip to content

clang-format on sparse tests #973

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
cliffburdick merged 1 commit into from
Jun 2, 2025
Merged

clang-format on sparse tests #973

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
61 changes: 41 additions & 20 deletions test/00_sparse/Basic.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,14 +20,15 @@
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
// DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
// FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
// DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
// SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
// CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
// OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
/////////////////////////////////////////////////////////////////////////////////

#include "assert.h"
Expand All @@ -38,9 +39,9 @@

using namespace matx;

template <typename T> class BasicSparseTest : public ::testing::Test { };
template <typename T> class BasicSparseTest : public ::testing::Test {};

template <typename T> class BasicSparseTestsAll : public BasicSparseTest<T> { };
template <typename T> class BasicSparseTestsAll : public BasicSparseTest<T> {};

TYPED_TEST_SUITE(BasicSparseTestsAll, MatXAllTypesAllExecs);

Expand Down Expand Up @@ -70,8 +71,12 @@ TYPED_TEST(BasicSparseTestsAll, MakeCOO) {
vals(0) = static_cast<TestType>(10);
vals(1) = static_cast<TestType>(20);
vals(2) = static_cast<TestType>(30);
idxi(0) = 0; idxi(1) = 0; idxi(2) = 3;
idxj(0) = 3; idxj(1) = 6; idxj(2) = 7;
idxi(0) = 0;
idxi(1) = 0;
idxi(2) = 3;
idxj(0) = 3;
idxj(1) = 6;
idxj(2) = 7;
auto A = experimental::make_tensor_coo(vals, idxi, idxj, {4, 8});
ASSERT_EQ(A.Rank(), 2);
ASSERT_EQ(A.Size(0), 4);
Expand All @@ -92,7 +97,8 @@ TYPED_TEST(BasicSparseTestsAll, MakeCOO) {
TYPED_TEST(BasicSparseTestsAll, MakeZeroCSR) {
MATX_ENTER_HANDLER();
using TestType = cuda::std::tuple_element_t<0, TypeParam>;
auto A = experimental::make_zero_tensor_csr<TestType, index_t, index_t>({17, 33});
auto A =
experimental::make_zero_tensor_csr<TestType, index_t, index_t>({17, 33});
ASSERT_EQ(A.Rank(), 2);
ASSERT_EQ(A.Size(0), 17);
ASSERT_EQ(A.Size(1), 33);
Expand All @@ -115,8 +121,14 @@ TYPED_TEST(BasicSparseTestsAll, MakeCSR) {
vals(0) = static_cast<TestType>(10);
vals(1) = static_cast<TestType>(20);
vals(2) = static_cast<TestType>(30);
rowp(0) = 0; rowp(1) = 2; rowp(2) = 2; rowp(3) = 2; rowp(4) = 3;
col(0) = 3; col(1) = 6; col(2) = 7;
rowp(0) = 0;
rowp(1) = 2;
rowp(2) = 2;
rowp(3) = 2;
rowp(4) = 3;
col(0) = 3;
col(1) = 6;
col(2) = 7;
auto A = experimental::make_tensor_csr(vals, rowp, col, {4, 8});
ASSERT_EQ(A.Rank(), 2);
ASSERT_EQ(A.Size(0), 4);
Expand All @@ -137,7 +149,8 @@ TYPED_TEST(BasicSparseTestsAll, MakeCSR) {
TYPED_TEST(BasicSparseTestsAll, MakeZeroCSC) {
MATX_ENTER_HANDLER();
using TestType = cuda::std::tuple_element_t<0, TypeParam>;
auto A = experimental::make_zero_tensor_csc<TestType, index_t, index_t>({17, 33});
auto A =
experimental::make_zero_tensor_csc<TestType, index_t, index_t>({17, 33});
ASSERT_EQ(A.Rank(), 2);
ASSERT_EQ(A.Size(0), 17);
ASSERT_EQ(A.Size(1), 33);
Expand All @@ -160,10 +173,18 @@ TYPED_TEST(BasicSparseTestsAll, MakeCSC) {
vals(0) = static_cast<TestType>(10);
vals(1) = static_cast<TestType>(20);
vals(2) = static_cast<TestType>(30);
colp(0) = 0; colp(1) = 0; colp(2) = 0;
colp(3) = 0; colp(4) = 1; colp(5) = 1;
colp(6) = 1; colp(7) = 2; colp(8) = 3;
row(0) = 0; row(1) = 0; row(2) = 3;
colp(0) = 0;
colp(1) = 0;
colp(2) = 0;
colp(3) = 0;
colp(4) = 1;
colp(5) = 1;
colp(6) = 1;
colp(7) = 2;
colp(8) = 3;
row(0) = 0;
row(1) = 0;
row(2) = 3;
auto A = experimental::make_tensor_csc(vals, colp, row, {4, 8});
ASSERT_EQ(A.Rank(), 2);
ASSERT_EQ(A.Size(0), 4);
Expand Down
36 changes: 19 additions & 17 deletions test/00_sparse/Convert.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,14 +20,15 @@
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
// DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
// FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
// DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
// SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
// CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
// OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
/////////////////////////////////////////////////////////////////////////////////

#include "assert.h"
Expand Down Expand Up @@ -59,12 +60,11 @@ template <typename T> class ConvertSparseTest : public ::testing::Test {
protected:
using GTestType = cuda::std::tuple_element_t<0, T>;
using GExecType = cuda::std::tuple_element_t<1, T>;
void SetUp() override {
CheckTestTypeSupport<GTestType>();
}
void SetUp() override { CheckTestTypeSupport<GTestType>(); }
};

template <typename T> class ConvertSparseTestsAll : public ConvertSparseTest<T> { };
template <typename T>
class ConvertSparseTestsAll : public ConvertSparseTest<T> {};

TYPED_TEST_SUITE(ConvertSparseTestsAll, MatXFloatNonComplexTypesCUDAExec);

Expand Down Expand Up @@ -102,7 +102,7 @@ TYPED_TEST(ConvertSparseTestsAll, ConvertCOO) {
// Convert sparse S back to dense D.
auto O = make_tensor<TestType>({m, n});
(O = sparse2dense(S)).run(exec);

// Back to cheap random-access getters only.
exec.sync();
for (index_t i = 0; i < m; i++) {
Expand Down Expand Up @@ -142,7 +142,8 @@ TYPED_TEST(ConvertSparseTestsAll, ConvertCSR) {
const auto n = D.Size(1);

// Convert dense D to sparse S.
auto S = experimental::make_zero_tensor_csr<TestType, index_t, index_t>({m, n});
auto S =
experimental::make_zero_tensor_csr<TestType, index_t, index_t>({m, n});
(S = dense2sparse(D)).run(exec);
ASSERT_EQ(S.Rank(), 2);
ASSERT_EQ(S.Size(0), m);
Expand All @@ -164,7 +165,7 @@ TYPED_TEST(ConvertSparseTestsAll, ConvertCSR) {
// Convert sparse S back to dense D.
auto O = make_tensor<TestType>({m, n});
(O = sparse2dense(S)).run(exec);

// Back to cheap random-access getters only.
exec.sync();
for (index_t i = 0; i < m; i++) {
Expand Down Expand Up @@ -199,7 +200,8 @@ TYPED_TEST(ConvertSparseTestsAll, ConvertCSC) {
const auto n = D.Size(1);

// Convert dense D to sparse S.
auto S = experimental::make_zero_tensor_csc<TestType, index_t, index_t>({m, n});
auto S =
experimental::make_zero_tensor_csc<TestType, index_t, index_t>({m, n});
(S = dense2sparse(D)).run(exec);
ASSERT_EQ(S.Rank(), 2);
ASSERT_EQ(S.Size(0), m);
Expand All @@ -221,7 +223,7 @@ TYPED_TEST(ConvertSparseTestsAll, ConvertCSC) {
// Convert sparse S back to dense D.
auto O = make_tensor<TestType>({m, n});
(O = sparse2dense(S)).run(exec);

// Back to cheap random-access getters only.
exec.sync();
for (index_t i = 0; i < m; i++) {
Expand Down
74 changes: 41 additions & 33 deletions test/00_sparse/Matmul.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -70,39 +70,50 @@ template <typename T> static auto makeB() {
const index_t m = 8;
const index_t n = 2;
tensor_t<T, 2> B = make_tensor<T>({m, n});
B(0, 0) = static_cast<T>(1); B(0, 1) = static_cast<T>(2);
B(1, 0) = static_cast<T>(3); B(1, 1) = static_cast<T>(4);
B(2, 0) = static_cast<T>(5); B(2, 1) = static_cast<T>(6);
B(3, 0) = static_cast<T>(7); B(3, 1) = static_cast<T>(8);
B(4, 0) = static_cast<T>(9); B(4, 1) = static_cast<T>(10);
B(5, 0) = static_cast<T>(11); B(5, 1) = static_cast<T>(12);
B(6, 0) = static_cast<T>(13); B(6, 1) = static_cast<T>(14);
B(7, 0) = static_cast<T>(15); B(7, 1) = static_cast<T>(16);
B(0, 0) = static_cast<T>(1);
B(0, 1) = static_cast<T>(2);
B(1, 0) = static_cast<T>(3);
B(1, 1) = static_cast<T>(4);
B(2, 0) = static_cast<T>(5);
B(2, 1) = static_cast<T>(6);
B(3, 0) = static_cast<T>(7);
B(3, 1) = static_cast<T>(8);
B(4, 0) = static_cast<T>(9);
B(4, 1) = static_cast<T>(10);
B(5, 0) = static_cast<T>(11);
B(5, 1) = static_cast<T>(12);
B(6, 0) = static_cast<T>(13);
B(6, 1) = static_cast<T>(14);
B(7, 0) = static_cast<T>(15);
B(7, 1) = static_cast<T>(16);
return B;
}

template <typename T> static auto makeE() {
const index_t m = 4;
const index_t n = 2;
tensor_t<T, 2> E = make_tensor<T>({m, n});
E(0, 0) = static_cast<T>(7); E(0, 1) = static_cast<T>(10);
E(1, 0) = static_cast<T>(45); E(1, 1) = static_cast<T>(48);
E(2, 0) = static_cast<T>(52); E(2, 1) = static_cast<T>(56);
E(3, 0) = static_cast<T>(144); E(3, 1) = static_cast<T>(162);
E(0, 0) = static_cast<T>(7);
E(0, 1) = static_cast<T>(10);
E(1, 0) = static_cast<T>(45);
E(1, 1) = static_cast<T>(48);
E(2, 0) = static_cast<T>(52);
E(2, 1) = static_cast<T>(56);
E(3, 0) = static_cast<T>(144);
E(3, 1) = static_cast<T>(162);
return E;
}

template <typename T> class MatmulSparseTest : public ::testing::Test {
protected:
using GTestType = cuda::std::tuple_element_t<0, T>;
using GExecType = cuda::std::tuple_element_t<1, T>;
void SetUp() override {
CheckTestTypeSupport<GTestType>();
}
void SetUp() override { CheckTestTypeSupport<GTestType>(); }
float thresh = 0.001f;
};

template <typename T> class MatmulSparseTestsAll : public MatmulSparseTest<T> { };
template <typename T>
class MatmulSparseTestsAll : public MatmulSparseTest<T> {};

TYPED_TEST_SUITE(MatmulSparseTestsAll, MatXFloatNonComplexHalfTypesCUDAExec);

Expand Down Expand Up @@ -136,9 +147,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCOO) {
for (index_t j = 0; j < n; j++) {
if constexpr (is_complex_v<TestType>) {
ASSERT_NEAR(O(i, j).real(), E(i, j).real(), this->thresh);
ASSERT_NEAR(O(i, j).imag(), E(i,j ).imag(), this->thresh);
}
else {
ASSERT_NEAR(O(i, j).imag(), E(i, j).imag(), this->thresh);
} else {
ASSERT_NEAR(O(i, j), E(i, j), this->thresh);
}
}
Expand All @@ -154,9 +164,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCOO) {
for (index_t j = 0; j < n; j++) {
if constexpr (is_complex_v<TestType>) {
ASSERT_NEAR(TO(j, i).real(), E(i, j).real(), this->thresh);
ASSERT_NEAR(TO(j, i).imag(), E(i,j ).imag(), this->thresh);
}
else {
ASSERT_NEAR(TO(j, i).imag(), E(i, j).imag(), this->thresh);
} else {
ASSERT_NEAR(TO(j, i), E(i, j), this->thresh);
}
}
Expand All @@ -180,7 +189,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCSR) {
const auto n = B.Size(1);

// Convert dense A to sparse S.
auto S = experimental::make_zero_tensor_csr<TestType, index_t, index_t>({m, k});
auto S =
experimental::make_zero_tensor_csr<TestType, index_t, index_t>({m, k});
(S = dense2sparse(A)).run(exec);
ASSERT_EQ(S.Nse(), 7);
ASSERT_EQ(S.posSize(1), m + 1);
Expand All @@ -195,9 +205,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCSR) {
for (index_t j = 0; j < n; j++) {
if constexpr (is_complex_v<TestType>) {
ASSERT_NEAR(O(i, j).real(), E(i, j).real(), this->thresh);
ASSERT_NEAR(O(i, j).imag(), E(i,j ).imag(), this->thresh);
}
else {
ASSERT_NEAR(O(i, j).imag(), E(i, j).imag(), this->thresh);
} else {
ASSERT_NEAR(O(i, j), E(i, j), this->thresh);
}
}
Expand All @@ -221,7 +230,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCSC) {
const auto n = B.Size(1);

// Convert dense A to sparse S.
auto S = experimental::make_zero_tensor_csc<TestType, index_t, index_t>({m, k});
auto S =
experimental::make_zero_tensor_csc<TestType, index_t, index_t>({m, k});
(S = dense2sparse(A)).run(exec);
ASSERT_EQ(S.Nse(), 7);
ASSERT_EQ(S.posSize(1), k + 1);
Expand All @@ -236,9 +246,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCSC) {
for (index_t j = 0; j < n; j++) {
if constexpr (is_complex_v<TestType>) {
ASSERT_NEAR(O(i, j).real(), E(i, j).real(), this->thresh);
ASSERT_NEAR(O(i, j).imag(), E(i,j ).imag(), this->thresh);
}
else {
ASSERT_NEAR(O(i, j).imag(), E(i, j).imag(), this->thresh);
} else {
ASSERT_NEAR(O(i, j), E(i, j), this->thresh);
}
}
Expand All @@ -256,9 +265,8 @@ TYPED_TEST(MatmulSparseTestsAll, MatmulCSC) {
for (index_t j = 0; j < n; j++) {
if constexpr (is_complex_v<TestType>) {
ASSERT_NEAR((O(i, j) - C5).real(), E(i, j).real(), this->thresh);
ASSERT_NEAR((O(i, j) - C5).imag(), E(i,j ).imag(), this->thresh);
}
else {
ASSERT_NEAR((O(i, j) - C5).imag(), E(i, j).imag(), this->thresh);
} else {
ASSERT_NEAR(O(i, j) - C5, E(i, j), this->thresh);
}
}
Expand Down
Loading