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-rw-r--r--absl/random/gaussian_distribution_test.cc10
1 files changed, 8 insertions, 2 deletions
diff --git a/absl/random/gaussian_distribution_test.cc b/absl/random/gaussian_distribution_test.cc
index 49c07513..02ac578a 100644
--- a/absl/random/gaussian_distribution_test.cc
+++ b/absl/random/gaussian_distribution_test.cc
@@ -130,12 +130,15 @@ TYPED_TEST(GaussianDistributionInterfaceTest, SerializeTest) {
ss >> after;
#if defined(__powerpc64__) || defined(__PPC64__) || defined(__powerpc__) || \
- defined(__ppc__) || defined(__PPC__)
+ defined(__ppc__) || defined(__PPC__) || defined(__EMSCRIPTEN__)
if (std::is_same<TypeParam, long double>::value) {
// Roundtripping floating point values requires sufficient precision
// to reconstruct the exact value. It turns out that long double
// has some errors doing this on ppc, particularly for values
// near {1.0 +/- epsilon}.
+ //
+ // Emscripten is even worse, implementing long double as a 128-bit
+ // type, but shipping with a strtold() that doesn't support that.
if (mean <= std::numeric_limits<double>::max() &&
mean >= std::numeric_limits<double>::lowest()) {
EXPECT_EQ(static_cast<double>(before.mean()),
@@ -213,7 +216,10 @@ class GaussianDistributionTests : public testing::TestWithParam<Param>,
template <typename D>
double SingleChiSquaredTest();
- absl::InsecureBitGen rng_;
+ // We use a fixed bit generator for distribution accuracy tests. This allows
+ // these tests to be deterministic, while still testing the qualify of the
+ // implementation.
+ absl::random_internal::pcg64_2018_engine rng_{0x2B7E151628AED2A6};
};
template <typename D>