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-rw-r--r--unsupported/test/cxx11_tensor_reduction.cpp88
1 files changed, 56 insertions, 32 deletions
diff --git a/unsupported/test/cxx11_tensor_reduction.cpp b/unsupported/test/cxx11_tensor_reduction.cpp
index 1490ec3da..c46c4c91d 100644
--- a/unsupported/test/cxx11_tensor_reduction.cpp
+++ b/unsupported/test/cxx11_tensor_reduction.cpp
@@ -53,20 +53,22 @@ static void test_trivial_reductions() {
}
}
-template <int DataLayout>
+template <typename Scalar,int DataLayout>
static void test_simple_reductions() {
- Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+ Tensor<Scalar, 4, DataLayout> tensor(2, 3, 5, 7);
tensor.setRandom();
+ // Add a little offset so that the product reductions won't be close to zero.
+ tensor += tensor.constant(Scalar(0.5f));
array<ptrdiff_t, 2> reduction_axis2;
reduction_axis2[0] = 1;
reduction_axis2[1] = 3;
- Tensor<float, 2, DataLayout> result = tensor.sum(reduction_axis2);
+ Tensor<Scalar, 2, DataLayout> result = tensor.sum(reduction_axis2);
VERIFY_IS_EQUAL(result.dimension(0), 2);
VERIFY_IS_EQUAL(result.dimension(1), 5);
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 5; ++j) {
- float sum = 0.0f;
+ Scalar sum = Scalar(0.0f);
for (int k = 0; k < 3; ++k) {
for (int l = 0; l < 7; ++l) {
sum += tensor(i, k, j, l);
@@ -77,7 +79,7 @@ static void test_simple_reductions() {
}
{
- Tensor<float, 0, DataLayout> sum1 = tensor.sum();
+ Tensor<Scalar, 0, DataLayout> sum1 = tensor.sum();
VERIFY_IS_EQUAL(sum1.rank(), 0);
array<ptrdiff_t, 4> reduction_axis4;
@@ -85,7 +87,7 @@ static void test_simple_reductions() {
reduction_axis4[1] = 1;
reduction_axis4[2] = 2;
reduction_axis4[3] = 3;
- Tensor<float, 0, DataLayout> sum2 = tensor.sum(reduction_axis4);
+ Tensor<Scalar, 0, DataLayout> sum2 = tensor.sum(reduction_axis4);
VERIFY_IS_EQUAL(sum2.rank(), 0);
VERIFY_IS_APPROX(sum1(), sum2());
@@ -98,7 +100,7 @@ static void test_simple_reductions() {
VERIFY_IS_EQUAL(result.dimension(1), 7);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 7; ++j) {
- float prod = 1.0f;
+ Scalar prod = Scalar(1.0f);
for (int k = 0; k < 2; ++k) {
for (int l = 0; l < 5; ++l) {
prod *= tensor(k, i, l, j);
@@ -109,7 +111,7 @@ static void test_simple_reductions() {
}
{
- Tensor<float, 0, DataLayout> prod1 = tensor.prod();
+ Tensor<Scalar, 0, DataLayout> prod1 = tensor.prod();
VERIFY_IS_EQUAL(prod1.rank(), 0);
array<ptrdiff_t, 4> reduction_axis4;
@@ -117,7 +119,7 @@ static void test_simple_reductions() {
reduction_axis4[1] = 1;
reduction_axis4[2] = 2;
reduction_axis4[3] = 3;
- Tensor<float, 0, DataLayout> prod2 = tensor.prod(reduction_axis4);
+ Tensor<Scalar, 0, DataLayout> prod2 = tensor.prod(reduction_axis4);
VERIFY_IS_EQUAL(prod2.rank(), 0);
VERIFY_IS_APPROX(prod1(), prod2());
@@ -130,7 +132,7 @@ static void test_simple_reductions() {
VERIFY_IS_EQUAL(result.dimension(1), 7);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 7; ++j) {
- float max_val = std::numeric_limits<float>::lowest();
+ Scalar max_val = std::numeric_limits<Scalar>::lowest();
for (int k = 0; k < 2; ++k) {
for (int l = 0; l < 5; ++l) {
max_val = (std::max)(max_val, tensor(k, i, l, j));
@@ -141,7 +143,7 @@ static void test_simple_reductions() {
}
{
- Tensor<float, 0, DataLayout> max1 = tensor.maximum();
+ Tensor<Scalar, 0, DataLayout> max1 = tensor.maximum();
VERIFY_IS_EQUAL(max1.rank(), 0);
array<ptrdiff_t, 4> reduction_axis4;
@@ -149,7 +151,7 @@ static void test_simple_reductions() {
reduction_axis4[1] = 1;
reduction_axis4[2] = 2;
reduction_axis4[3] = 3;
- Tensor<float, 0, DataLayout> max2 = tensor.maximum(reduction_axis4);
+ Tensor<Scalar, 0, DataLayout> max2 = tensor.maximum(reduction_axis4);
VERIFY_IS_EQUAL(max2.rank(), 0);
VERIFY_IS_APPROX(max1(), max2());
@@ -162,7 +164,7 @@ static void test_simple_reductions() {
VERIFY_IS_EQUAL(result.dimension(1), 7);
for (int i = 0; i < 5; ++i) {
for (int j = 0; j < 7; ++j) {
- float min_val = (std::numeric_limits<float>::max)();
+ Scalar min_val = (std::numeric_limits<Scalar>::max)();
for (int k = 0; k < 2; ++k) {
for (int l = 0; l < 3; ++l) {
min_val = (std::min)(min_val, tensor(k, l, i, j));
@@ -173,7 +175,7 @@ static void test_simple_reductions() {
}
{
- Tensor<float, 0, DataLayout> min1 = tensor.minimum();
+ Tensor<Scalar, 0, DataLayout> min1 = tensor.minimum();
VERIFY_IS_EQUAL(min1.rank(), 0);
array<ptrdiff_t, 4> reduction_axis4;
@@ -181,7 +183,7 @@ static void test_simple_reductions() {
reduction_axis4[1] = 1;
reduction_axis4[2] = 2;
reduction_axis4[3] = 3;
- Tensor<float, 0, DataLayout> min2 = tensor.minimum(reduction_axis4);
+ Tensor<Scalar, 0, DataLayout> min2 = tensor.minimum(reduction_axis4);
VERIFY_IS_EQUAL(min2.rank(), 0);
VERIFY_IS_APPROX(min1(), min2());
@@ -194,7 +196,7 @@ static void test_simple_reductions() {
VERIFY_IS_EQUAL(result.dimension(1), 7);
for (int i = 0; i < 5; ++i) {
for (int j = 0; j < 7; ++j) {
- float sum = 0.0f;
+ Scalar sum = Scalar(0.0f);
int count = 0;
for (int k = 0; k < 2; ++k) {
for (int l = 0; l < 3; ++l) {
@@ -202,12 +204,12 @@ static void test_simple_reductions() {
++count;
}
}
- VERIFY_IS_APPROX(result(i, j), sum / count);
+ VERIFY_IS_APPROX(result(i, j), sum / Scalar(count));
}
}
{
- Tensor<float, 0, DataLayout> mean1 = tensor.mean();
+ Tensor<Scalar, 0, DataLayout> mean1 = tensor.mean();
VERIFY_IS_EQUAL(mean1.rank(), 0);
array<ptrdiff_t, 4> reduction_axis4;
@@ -215,7 +217,7 @@ static void test_simple_reductions() {
reduction_axis4[1] = 1;
reduction_axis4[2] = 2;
reduction_axis4[3] = 3;
- Tensor<float, 0, DataLayout> mean2 = tensor.mean(reduction_axis4);
+ Tensor<Scalar, 0, DataLayout> mean2 = tensor.mean(reduction_axis4);
VERIFY_IS_EQUAL(mean2.rank(), 0);
VERIFY_IS_APPROX(mean1(), mean2());
@@ -225,11 +227,11 @@ static void test_simple_reductions() {
Tensor<int, 1> ints(10);
std::iota(ints.data(), ints.data() + ints.dimension(0), 0);
- TensorFixedSize<bool, Sizes<> > all;
- all = ints.all();
- VERIFY(!all());
- all = (ints >= ints.constant(0)).all();
- VERIFY(all());
+ TensorFixedSize<bool, Sizes<> > all_;
+ all_ = ints.all();
+ VERIFY(!all_());
+ all_ = (ints >= ints.constant(0)).all();
+ VERIFY(all_());
TensorFixedSize<bool, Sizes<> > any;
any = (ints > ints.constant(10)).any();
@@ -368,7 +370,7 @@ static void test_static_dims() {
Tensor<float, 2, DataLayout> out(72, 97);
in.setRandom();
-#if !EIGEN_HAS_CONSTEXPR
+#if !EIGEN_HAS_CONSTEXPR
array<int, 2> reduction_axis;
reduction_axis[0] = 1;
reduction_axis[1] = 3;
@@ -386,7 +388,7 @@ static void test_static_dims() {
expected = (std::max)(expected, in(i, k, j, l));
}
}
- VERIFY_IS_APPROX(out(i, j), expected);
+ VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
@@ -417,7 +419,7 @@ static void test_innermost_last_dims() {
expected = (std::max)(expected, in(l, k, i, j));
}
}
- VERIFY_IS_APPROX(out(i, j), expected);
+ VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
@@ -448,7 +450,7 @@ static void test_innermost_first_dims() {
expected = (std::max)(expected, in(i, j, k, l));
}
}
- VERIFY_IS_APPROX(out(i, j), expected);
+ VERIFY_IS_EQUAL(out(i, j), expected);
}
}
}
@@ -479,16 +481,37 @@ static void test_reduce_middle_dims() {
expected = (std::max)(expected, in(i, k, l, j));
}
}
- VERIFY_IS_APPROX(out(i, j), expected);
+ VERIFY_IS_EQUAL(out(i, j), expected);
+ }
+ }
+}
+
+static void test_sum_accuracy() {
+ Tensor<float, 3> tensor(101, 101, 101);
+ for (float prescribed_mean : {1.0f, 10.0f, 100.0f, 1000.0f, 10000.0f}) {
+ tensor.setRandom();
+ tensor += tensor.constant(prescribed_mean);
+
+ Tensor<float, 0> sum = tensor.sum();
+ double expected_sum = 0.0;
+ for (int i = 0; i < 101; ++i) {
+ for (int j = 0; j < 101; ++j) {
+ for (int k = 0; k < 101; ++k) {
+ expected_sum += static_cast<double>(tensor(i, j, k));
+ }
+ }
}
+ VERIFY_IS_APPROX(sum(), static_cast<float>(expected_sum));
}
}
-void test_cxx11_tensor_reduction() {
+EIGEN_DECLARE_TEST(cxx11_tensor_reduction) {
CALL_SUBTEST(test_trivial_reductions<ColMajor>());
CALL_SUBTEST(test_trivial_reductions<RowMajor>());
- CALL_SUBTEST(test_simple_reductions<ColMajor>());
- CALL_SUBTEST(test_simple_reductions<RowMajor>());
+ CALL_SUBTEST(( test_simple_reductions<float,ColMajor>() ));
+ CALL_SUBTEST(( test_simple_reductions<float,RowMajor>() ));
+ CALL_SUBTEST(( test_simple_reductions<Eigen::half,ColMajor>() ));
+ CALL_SUBTEST(( test_simple_reductions<Eigen::bfloat16,ColMajor>() ));
CALL_SUBTEST(test_reductions_in_expr<ColMajor>());
CALL_SUBTEST(test_reductions_in_expr<RowMajor>());
CALL_SUBTEST(test_full_reductions<ColMajor>());
@@ -505,4 +528,5 @@ void test_cxx11_tensor_reduction() {
CALL_SUBTEST(test_innermost_first_dims<RowMajor>());
CALL_SUBTEST(test_reduce_middle_dims<ColMajor>());
CALL_SUBTEST(test_reduce_middle_dims<RowMajor>());
+ CALL_SUBTEST(test_sum_accuracy());
}
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-20 07:41:13 +0000