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#include "tensorflow/core/lib/random/philox_random.h"
#include <math.h>
#include <algorithm>
#include <functional>
#include <unordered_map>
#include <vector>
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/lib/random/philox_random_test_utils.h"
#include "tensorflow/core/lib/random/random.h"
#include "tensorflow/core/lib/random/random_distributions.h"
#include <gtest/gtest.h>
namespace tensorflow {
namespace random {
namespace {
// A trivial distribution that just returns the PhiloxRandom as a distribution
class TrivialPhiloxDistribution {
public:
// The number of elements that will be returned.
static constexpr int kResultElementCount = PhiloxRandom::kResultElementCount;
typedef PhiloxRandom::ResultType ResultType;
typedef PhiloxRandom::ResultElementType ResultElementType;
PHILOX_DEVICE_INLINE
ResultType operator()(PhiloxRandom* gen) { return (*gen)(); }
};
// This test checks that skipping certain number of samples, is equivalent to
// generate the same number of samples without skipping.
TEST(PhiloxRandomTest, SkipMatchTest) {
constexpr int count = 1024;
constexpr int skip_count = 2048;
uint64 test_seed = GetTestSeed();
std::vector<uint32> v1(count);
{
PhiloxRandom gen(test_seed);
gen.Skip(skip_count / 4);
FillRandoms<TrivialPhiloxDistribution>(gen, &v1[0], v1.size());
}
std::vector<uint32> v2(count + skip_count);
{
PhiloxRandom gen(test_seed);
FillRandoms<TrivialPhiloxDistribution>(gen, &v2[0], v2.size());
}
for (int i = 0; i < count; ++i) {
ASSERT_EQ(v1[i], v2[i + skip_count]);
}
}
} // namespace
} // namespace random
} // namespace tensorflow
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