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Clang-format tests, examples, libraries, benchmarks, etc.

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This commit is contained in:
Antonio Sánchez
2023-12-05 21:22:55 +00:00
committed by Rasmus Munk Larsen
parent 3252ecc7a4
commit 46e9cdb7fe
876 changed files with 33453 additions and 37795 deletions
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71
unsupported/test/cxx11_tensor_broadcasting.cpp
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@@ -14,9 +14,8 @@
using Eigen::Tensor;
template <int DataLayout>
static void test_simple_broadcasting()
{
Tensor<float, 4, DataLayout> tensor(2,3,5,7);
static void test_simple_broadcasting() {
Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
tensor.setRandom();
array<ptrdiff_t, 4> broadcasts;
broadcasts[0] = 1;
@@ -36,7 +35,7 @@ static void test_simple_broadcasting()
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 7; ++l) {
VERIFY_IS_EQUAL(tensor(i,j,k,l), no_broadcast(i,j,k,l));
VERIFY_IS_EQUAL(tensor(i, j, k, l), no_broadcast(i, j, k, l));
}
}
}
@@ -58,18 +57,16 @@ static void test_simple_broadcasting()
for (int j = 0; j < 9; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 28; ++l) {
VERIFY_IS_EQUAL(tensor(i%2,j%3,k%5,l%7), broadcast(i,j,k,l));
VERIFY_IS_EQUAL(tensor(i % 2, j % 3, k % 5, l % 7), broadcast(i, j, k, l));
}
}
}
}
}
template <int DataLayout>
static void test_vectorized_broadcasting()
{
Tensor<float, 3, DataLayout> tensor(8,3,5);
static void test_vectorized_broadcasting() {
Tensor<float, 3, DataLayout> tensor(8, 3, 5);
tensor.setRandom();
array<ptrdiff_t, 3> broadcasts;
broadcasts[0] = 2;
@@ -86,12 +83,12 @@ static void test_vectorized_broadcasting()
for (int i = 0; i < 16; ++i) {
for (int j = 0; j < 9; ++j) {
for (int k = 0; k < 20; ++k) {
VERIFY_IS_EQUAL(tensor(i%8,j%3,k%5), broadcast(i,j,k));
VERIFY_IS_EQUAL(tensor(i % 8, j % 3, k % 5), broadcast(i, j, k));
}
}
}
tensor.resize(11,3,5);
tensor.resize(11, 3, 5);
tensor.setRandom();
broadcast = tensor.broadcast(broadcasts);
@@ -103,17 +100,15 @@ static void test_vectorized_broadcasting()
for (int i = 0; i < 22; ++i) {
for (int j = 0; j < 9; ++j) {
for (int k = 0; k < 20; ++k) {
VERIFY_IS_EQUAL(tensor(i%11,j%3,k%5), broadcast(i,j,k));
VERIFY_IS_EQUAL(tensor(i % 11, j % 3, k % 5), broadcast(i, j, k));
}
}
}
}
template <int DataLayout>
static void test_static_broadcasting()
{
Tensor<float, 3, DataLayout> tensor(8,3,5);
static void test_static_broadcasting() {
Tensor<float, 3, DataLayout> tensor(8, 3, 5);
tensor.setRandom();
Eigen::IndexList<Eigen::type2index<2>, Eigen::type2index<3>, Eigen::type2index<4>> broadcasts;
@@ -127,12 +122,12 @@ static void test_static_broadcasting()
for (int i = 0; i < 16; ++i) {
for (int j = 0; j < 9; ++j) {
for (int k = 0; k < 20; ++k) {
VERIFY_IS_EQUAL(tensor(i%8,j%3,k%5), broadcast(i,j,k));
VERIFY_IS_EQUAL(tensor(i % 8, j % 3, k % 5), broadcast(i, j, k));
}
}
}
tensor.resize(11,3,5);
tensor.resize(11, 3, 5);
tensor.setRandom();
broadcast = tensor.broadcast(broadcasts);
@@ -144,16 +139,14 @@ static void test_static_broadcasting()
for (int i = 0; i < 22; ++i) {
for (int j = 0; j < 9; ++j) {
for (int k = 0; k < 20; ++k) {
VERIFY_IS_EQUAL(tensor(i%11,j%3,k%5), broadcast(i,j,k));
VERIFY_IS_EQUAL(tensor(i % 11, j % 3, k % 5), broadcast(i, j, k));
}
}
}
}
template <int DataLayout>
static void test_fixed_size_broadcasting()
{
static void test_fixed_size_broadcasting() {
// Need to add a [] operator to the Size class for this to work
#if 0
Tensor<float, 1, DataLayout> t1(10);
@@ -175,9 +168,8 @@ static void test_fixed_size_broadcasting()
}
template <int DataLayout>
static void test_simple_broadcasting_one_by_n()
{
Tensor<float, 4, DataLayout> tensor(1,13,5,7);
static void test_simple_broadcasting_one_by_n() {
Tensor<float, 4, DataLayout> tensor(1, 13, 5, 7);
tensor.setRandom();
array<ptrdiff_t, 4> broadcasts;
broadcasts[0] = 9;
@@ -196,7 +188,7 @@ static void test_simple_broadcasting_one_by_n()
for (int j = 0; j < 13; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 7; ++l) {
VERIFY_IS_EQUAL(tensor(i%1,j%13,k%5,l%7), broadcast(i,j,k,l));
VERIFY_IS_EQUAL(tensor(i % 1, j % 13, k % 5, l % 7), broadcast(i, j, k, l));
}
}
}
@@ -204,9 +196,8 @@ static void test_simple_broadcasting_one_by_n()
}
template <int DataLayout>
static void test_simple_broadcasting_n_by_one()
{
Tensor<float, 4, DataLayout> tensor(7,3,5,1);
static void test_simple_broadcasting_n_by_one() {
Tensor<float, 4, DataLayout> tensor(7, 3, 5, 1);
tensor.setRandom();
array<ptrdiff_t, 4> broadcasts;
broadcasts[0] = 1;
@@ -225,7 +216,7 @@ static void test_simple_broadcasting_n_by_one()
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 5; ++k) {
for (int l = 0; l < 19; ++l) {
VERIFY_IS_EQUAL(tensor(i%7,j%3,k%5,l%1), broadcast(i,j,k,l));
VERIFY_IS_EQUAL(tensor(i % 7, j % 3, k % 5, l % 1), broadcast(i, j, k, l));
}
}
}
@@ -233,8 +224,7 @@ static void test_simple_broadcasting_n_by_one()
}
template <int DataLayout>
static void test_size_one_broadcasting()
{
static void test_size_one_broadcasting() {
Tensor<float, 1, DataLayout> tensor(1);
tensor.setRandom();
array<ptrdiff_t, 1> broadcasts = {64};
@@ -249,9 +239,8 @@ static void test_size_one_broadcasting()
}
template <int DataLayout>
static void test_simple_broadcasting_one_by_n_by_one_1d()
{
Tensor<float, 3, DataLayout> tensor(1,7,1);
static void test_simple_broadcasting_one_by_n_by_one_1d() {
Tensor<float, 3, DataLayout> tensor(1, 7, 1);
tensor.setRandom();
array<ptrdiff_t, 3> broadcasts;
broadcasts[0] = 5;
@@ -267,16 +256,15 @@ static void test_simple_broadcasting_one_by_n_by_one_1d()
for (int i = 0; i < 5; ++i) {
for (int j = 0; j < 7; ++j) {
for (int k = 0; k < 13; ++k) {
VERIFY_IS_EQUAL(tensor(0,j%7,0), broadcasted(i,j,k));
VERIFY_IS_EQUAL(tensor(0, j % 7, 0), broadcasted(i, j, k));
}
}
}
}
template <int DataLayout>
static void test_simple_broadcasting_one_by_n_by_one_2d()
{
Tensor<float, 4, DataLayout> tensor(1,7,13,1);
static void test_simple_broadcasting_one_by_n_by_one_2d() {
Tensor<float, 4, DataLayout> tensor(1, 7, 13, 1);
tensor.setRandom();
array<ptrdiff_t, 4> broadcasts;
broadcasts[0] = 5;
@@ -295,15 +283,14 @@ static void test_simple_broadcasting_one_by_n_by_one_2d()
for (int j = 0; j < 7; ++j) {
for (int k = 0; k < 13; ++k) {
for (int l = 0; l < 19; ++l) {
VERIFY_IS_EQUAL(tensor(0,j%7,k%13,0), broadcast(i,j,k,l));
VERIFY_IS_EQUAL(tensor(0, j % 7, k % 13, 0), broadcast(i, j, k, l));
}
}
}
}
}
EIGEN_DECLARE_TEST(cxx11_tensor_broadcasting)
{
EIGEN_DECLARE_TEST(cxx11_tensor_broadcasting) {
CALL_SUBTEST(test_simple_broadcasting<ColMajor>());
CALL_SUBTEST(test_simple_broadcasting<RowMajor>());
CALL_SUBTEST(test_vectorized_broadcasting<ColMajor>());