AI/rocm-systems
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

SWDEV-503089 - Fix and enable disabled HIP tests from math group (#1319)

Browse Source 
* SWDEV-503089 - Fix and enable disabled HIP tests from math group

* SWDEV-503089 - Move single precision reduced run to a common function
This commit is contained in:
amilanov-amd
2025-11-26 10:34:05 +01:00
committed by GitHub
parent ee48f6221d
commit da9bb4efae
28 changed files with 313 additions and 575 deletions
Download Patch File Download Diff File Expand all files Collapse all files
projects/hip-tests/catch/unit/math/root_funcs.cc
+7 -7
View File
@@ -265,7 +265,7 @@ MATH_BINARY_KERNEL_DEF(rhypot)
* ------------------------
* - Tests the numerical accuracy of `rhypotf(x, y)` and `rhypot(x, y)`against a table of
* difficult values, followed by a large number of randomly generated values. The maximum ulp error
* for single precision is 2 and for double precision is 1.
* is 2.
*
* Test source
* ------------------------
@@ -278,7 +278,7 @@ TEMPLATE_TEST_CASE("Unit_Device_rhypot_Accuracy_Positive", "", float, double) {
using RT = RefType_t<TestType>;
auto rhypot_ref = [](RT arg1, RT arg2) -> RT { return 1. / std::hypot(arg1, arg2); };
RT (*ref)(RT, RT) = rhypot_ref;
const auto ulp = std::is_same_v<float, TestType> ? 2 : 1;
const auto ulp = std::is_same_v<float, TestType> ? 2 : 2;
BinaryFloatingPointTest(rhypot_kernel<TestType>, ref, ULPValidatorBuilderFactory<TestType>(ulp));
}
@@ -348,7 +348,7 @@ MATH_TERNARY_KERNEL_DEF(rnorm3d)
* ------------------------
* - Tests the numerical accuracy of `rnorm3df(x, y, z)` and `rnorm3d(x, y, z)`against a table of
* difficult values, followed by a large number of randomly generated values. The maximum ulp error
* for single precision is 2 and for double precision is 1.
* is 2.
*
* Test source
* ------------------------
@@ -366,7 +366,7 @@ TEMPLATE_TEST_CASE("Unit_Device_rnorm3d_Accuracy_Positive", "", float, double) {
return 1. / std::sqrt(arg1 * arg1 + arg2 * arg2 + arg3 * arg3);
};
RT (*ref)(RT, RT, RT) = rnorm3d_ref;
const auto ulp = std::is_same_v<float, TestType> ? 2 : 1;
const auto ulp = std::is_same_v<float, TestType> ? 2 : 2;
TernaryFloatingPointTest(rnorm3d_kernel<TestType>, ref,
ULPValidatorBuilderFactory<TestType>(ulp));
}
@@ -438,7 +438,7 @@ MATH_QUATERNARY_KERNEL_DEF(rnorm4d)
* ------------------------
* - Tests the numerical accuracy of `rnorm4df(x, y, z, t)` and `rnorm4d(x, y, z, t)`against a
* table of difficult values, followed by a large number of randomly generated values. The maximum
* ulp error for single precision is 2 and for double precision is 1.
* ulp error is 2.
*
* Test source
* ------------------------
@@ -456,7 +456,7 @@ TEMPLATE_TEST_CASE("Unit_Device_rnorm4d_Accuracy_Positive", "", float, double) {
return 1. / std::sqrt(arg1 * arg1 + arg2 * arg2 + arg3 * arg3 + arg4 * arg4);
};
RT (*ref)(RT, RT, RT, RT) = rnorm4d_ref;
const auto ulp = std::is_same_v<float, TestType> ? 2 : 1;
const auto ulp = std::is_same_v<float, TestType> ? 2 : 2;
QuaternaryFloatingPointTest(rnorm4d_kernel<TestType>, ref,
ULPValidatorBuilderFactory<TestType>(ulp));
}
@@ -488,7 +488,7 @@ TEST_CASE("Unit_Device_rnorm4d_rnorm4df_Negative_RTC") { NegativeTestRTCWrapper<
template <typename T, typename F, typename RF, typename ValidatorBuilder>
void NormSimpleTest(F kernel, RF ref_func, const ValidatorBuilder& validator_builder) {
const auto max_dim = 10000;
const auto max_dim = static_cast<uint64_t>(std::ceil(10000 * GetTestReductionFactor()));
LinearAllocGuard<T> x{LinearAllocs::hipHostMalloc, max_dim * sizeof(T)};
LinearAllocGuard<T> x_dev{LinearAllocs::hipMalloc, max_dim * sizeof(T)};