1 files changed, 120 insertions, 0 deletions
diff --git a/tensorflow/core/lib/random/simple_philox_test.cc b/tensorflow/core/lib/random/simple_philox_test.cc
new file mode 100644
index 0000000000..4246b8b4dd
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+++ b/tensorflow/core/lib/random/simple_philox_test.cc
@@ -0,0 +1,120 @@
+#include "tensorflow/core/lib/random/simple_philox.h"
+
+#include <set>
+#include <string>
+
+#include "tensorflow/core/platform/logging.h"
+#include "tensorflow/core/platform/port.h"
+#include <gtest/gtest.h>
+
+namespace tensorflow {
+namespace random {
+namespace {
+
+TEST(SimplePhiloxTest, FloatTest) {
+  PhiloxRandom philox(7, 7);
+  SimplePhilox gen(&philox);
+  static const int kIters = 1000000;
+  for (int i = 0; i < kIters; ++i) {
+    float f = gen.RandFloat();
+    EXPECT_LE(0.0f, f);
+    EXPECT_GT(1.0f, f);
+  }
+  for (int i = 0; i < kIters; ++i) {
+    double d = gen.RandDouble();
+    EXPECT_LE(0.0, d);
+    EXPECT_GT(1.0, d);
+  }
+}
+
+static void DifferenceTest(const char *names, SimplePhilox *gen1,
+                           SimplePhilox *gen2) {
+  static const int kIters = 100;
+  bool different = false;
+  for (int i = 0; i < kIters; ++i) {
+    if (gen1->Rand32() != gen2->Rand32()) {
+      different = true;
+      break;
+    }
+  }
+  CHECK(different) << "different seeds but same output!";
+}
+
+TEST(SimplePhiloxTest, DifferenceTest) {
+  PhiloxRandom philox1(1, 1), philox2(17, 17);
+  SimplePhilox gen1(&philox1), gen2(&philox2);
+
+  DifferenceTest("SimplePhilox: different seeds", &gen1, &gen2);
+}
+
+TEST(SimplePhiloxTest, DifferenceTestCloseSeeds) {
+  PhiloxRandom philox1(1, 1), philox2(2, 1);
+  SimplePhilox gen1(&philox1), gen2(&philox2);
+
+  DifferenceTest("SimplePhilox: close seeds", &gen1, &gen2);
+}
+
+TEST(SimplePhiloxTest, Regression_CloseSeedsAreDifferent) {
+  const int kCount = 1000;
+
+  // Two seeds differ only by the last bit.
+  PhiloxRandom philox1(0, 1), philox2(1, 1);
+  SimplePhilox gen1(&philox1), gen2(&philox2);
+
+  std::set<uint32> first;
+  std::set<uint32> all;
+  for (int i = 0; i < kCount; ++i) {
+    uint32 v = gen1.Rand32();
+    first.insert(v);
+    all.insert(v);
+    all.insert(gen2.Rand32());
+  }
+
+  // Broken array initialization implementation (before 2009-08-18) using the
+  // above seeds return <1000, 1007>, generating output that is >99% similar.
+  // The fix returns <1000, 2000> for completely disjoint sets.
+  EXPECT_EQ(kCount, first.size());
+  EXPECT_EQ(2 * kCount, all.size());
+}
+
+TEST(SimplePhiloxTest, TestUniform) {
+  PhiloxRandom philox(17, 17);
+  SimplePhilox gen(&philox);
+
+  uint32 range = 3 * (1L << 29);
+  uint32 threshold = 1L << 30;
+
+  size_t count = 0;
+  static const int kTrials = 100000;
+  for (int i = 0; i < kTrials; ++i) {
+    uint32 rnd = gen.Uniform(range);
+    if (rnd < threshold) {
+      ++count;
+    }
+  }
+
+  EXPECT_LT(fabs((threshold + 0.0) / range - (count + 0.0) / kTrials), 0.005);
+}
+
+TEST(SimplePhiloxTest, TestUniform64) {
+  PhiloxRandom philox(17, 17);
+  SimplePhilox gen(&philox);
+
+  uint64 range = 3 * (1LL << 59);
+  uint64 threshold = 1LL << 60;
+
+  size_t count = 0;
+  static const int kTrials = 100000;
+  for (int i = 0; i < kTrials; ++i) {
+    uint64 rnd = gen.Uniform64(range);
+    if (rnd < threshold) {
+      ++count;
+    }
+  }
+
+  EXPECT_LT(fabs((threshold + 0.0) / range - (count + 0.0) / kTrials), 0.005);
+}
+
+}  // namespace
+}  // namespace random
+}  // namespace tensorflow